Perioperative NSAID use and survival after upfront cytoreductive surgery for ovarian cancer: Nationwide cohort study

Perioperative NSAID use and survival after upfront cytoreductive surgery for ovarian cancer: Nationwide cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Perioperative NSAID use and survival after upfront cytoreductive surgery for ovarian cancer: Nationwide cohort study Seongyun Lim, Joon-Young Hong, Jun-Hyeong Seo, Young Eun Chung, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9233171/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Background Inflammation influences the progression and treatment resistance of epithelial ovarian cancer, and nonsteroidal anti-inflammatory drugs (NSAIDs) have shown anticancer effects in other malignancies; however, their impact on ovarian cancer survival, particularly in Asian populations, remains unclear. Using the Korean Nationwide Cancer Public Library Database, we identified 14,736 women newly diagnosed with ovarian or fallopian tube cancer between 2012 and 2019. NSAID use was classified as Only POST (within 6 months after diagnosis only) or PRE & POST (both before and after diagnosis), and NSAID frequency was categorized as low (< 1 day/week), intermediate (1–3 days/week), or high (≥ 4 days/week). The primary outcome was all-cause mortality, analyzed with Cox proportional hazards models adjusting for demographic, clinical, and treatment-related factors, with subgroup analyses performed by primary treatment strategy (upfront surgery vs. neoadjuvant chemotherapy). Results During a median follow-up of 2.91 years, 4,108 deaths (27.9%) occurred. In the fully adjusted model, NSAID timing (PRE & POST: HR 0.94, 95% CI 0.88–1.01) and post-diagnosis frequency (high: HR 0.92, 95% CI 0.82–1.04) were not significantly associated with mortality in the overall cohort. However, in the upfront subgroup, PRE & POST users (HR 0.89, 95% CI 0.82–0.97) and high-frequency users (HR 0.84, 95% CI 0.73–0.98) had significantly lower mortality compared with their counterparts. No associations were found in the neoadjuvant chemotherapy subgroup. Conclusions NSAID use was not associated with survival overall but was linked to reduced mortality after upfront surgery, suggesting potential benefit when combined with cytoreductive surgery. ovarian cancer nonsteroidal anti-inflammatory drugs (NSAIDs) upfront surgery tumor microenvironments nationwide cohort Figures Figure 1 Figure 2 Background Ovarian cancer remains an aggressive malignancy with poorer survival rates compared to cervical or endometrial cancer, despite the overall global decline in incidence and mortality ( 1 ). According to the Surveillance, Epidemiology, and End Results (SEER) database, the 5-year survival rate for localized disease is 91.7%; however, only 20% of patients are diagnosed at this stage. In contrast, 55% of cases are identified with distant metastasis, for which the 5-year survival rate drops markedly to 31.8% ( 2 ) This is largely due to the lack of effective early detection and screening strategies. Most patients present with nonspecific symptoms, such as abdominal distension or gastrointestinal discomfort, which typically occur after the development of ascites and peritoneal dissemination at stage III or higher ( 3 ). The occurrence of peritoneal dissemination and ascites is accompanied by elevated levels of inflammatory and growth factors, such as IL-8, TNF-α and VEGF, as well as various cytokines and chemokines in the ascitic fluid. These inflammation-related changes in the tumor microenvironment contribute to cancer cell growth and invasion and play a critical role in peritoneal metastasis ( 3 – 5 ). Thus, inflammation influences the progression, metastasis, and chemo-resistance of epithelial ovarian cancer. A prospective study also demonstrated that elevated serum C-reactive protein (CRP) levels are associated with an increased risk of invasive epithelial ovarian cancer ( 6 ). This raises the question of whether modulation of inflammation could improve survival outcomes in epithelial ovarian cancer. In other malignancies such as breast cancer ( 7 ), colorectal cancer ( 8 – 10 ), and head and neck squamous cell carcinoma (HNSCC) ( 11 ), numerous studies have addressed this issue. In ovarian cancer, in vivo and murine studies have shown that interleukin-6 neutralization enhanced the efficacy of paclitaxel in epithelial ovarian cancer models ( 12 ). However, a clinical trial evaluating the addition of celecoxib to first-line chemotherapy in ovarian cancer failed to demonstrate a benefit ( 13 ). Among anti-inflammatory agents, nonsteroidal anti-inflammatory drugs (NSAIDs) are among the most widely accessible and commonly used, available over the counter for indications ranging from minor viral illnesses to autoimmune diseases. NSAIDs inhibit the cyclooxygenase (COX) pathway, thereby reducing prostaglandin E₂ (PGE₂) ( 14 ). PGE₂ is not only involved in regulating inflammation but also promotes immunosuppression, angiogenesis, and tumor growth. Consequently, NSAID-mediated inhibition of PGE₂ may provide both anti-inflammatory and antitumor effects ( 15 ). Numerous studies have investigated the relationship between aspirin use and reduced incidence and mortality in colorectal cancer ( 9 , 16 ). In contrast, a nationwide Norwegian cohort study reported that aspirin and non-aspirin NSAID use was associated with increased mortality in endometrial cancer ( 17 ). Regarding ovarian cancer, prospective cohort studies from the United States and Australia reported that NSAID use was associated with reduced mortality risk ( 18 , 19 ). Conversely, a Danish nationwide cohort study found that low-dose aspirin or non-aspirin NSAID use did not decrease mortality among ovarian cancer patients ( 20 , 21 ). To date, no such studies have been conducted in Asian populations. Given that ovarian cancer biology may vary by race and ethnicity ( 22 – 24 ), there is a clear need to investigate the impact of NSAID use on survival outcomes in Asian populations. Therefore, this study aimed to evaluate the association between NSAID use and mortality risk in ovarian cancer patients using a large, nationwide retrospective cohort in Korea. Specifically, we focused on whether this survival impact is modulated by the primary treatment strategy (upfront surgery vs. neoadjuvant chemotherapy). Methods Data source and study population This study utilized the Cancer Public Library Database (CPLD) established through the Korean Clinical Data Utilization Network for Research Excellence (K-Cure). The CPLD integrates four major national databases: The Korea National Cancer Incidence Database (KNCI DB) maintained by the Korea Central Cancer Registry (KCCR), mortality records from Statistics Korea, healthcare utilization data from the National Health Insurance Service (NHIS) National Health Information Database (NHID), and the National Health Insurance Research Database (NHIRD) managed by the Health Insurance Review & Assessment Service (HIRA). The NHIS provides universal health coverage for all residents in Korea and maintains comprehensive records of diagnoses, prescriptions, and procedures. The patient selection process is summarized in Fig. 1 . The study population included women newly diagnosed with ovarian cancer (International Classification of Diseases, 10th Revision [ICD-10] code C56) or fallopian tube cancer (C57) between January 1, 2012, and December 31, 2019. Of 20,563 registered patients, exclusions were applied as follows (Fig. 1 , flowchart): non-epithelial tumors (defined by a prescription record of etoposide within 6 months before or after diagnosis), age younger than 20 or older than 80 years at diagnosis, missing SEER (Surveillance, Epidemiology, and End Results) stage, unmatched eligibility with the NHIS, lack of ovarian cancer–related surgery or carboplatin administration, no NSAID prescription claims within 6 months after diagnosis, and application of a 6-month lag period to account for potential immortal time bias in NSAID exposure. The final cohort included 14,736 patients. This study was approved by the Institutional Review Board of Samsung Medical Center (IRB No. 2025-06-106) and conducted in accordance with the Declaration of Helsinki and relevant institutional guideline. As de-identified secondary data were used, informed consent was waived. Assessment of NSAID exposure NSAID exposure was defined based on prescription claims data from the NHIS. NSAIDs included all injectable and oral agents available in Korea, encompassing non-selective NSAIDs, selective COX-2 inhibitors, acetaminophen, and aspirin (Supplementary Table 1). Patients were categorized into two groups according to NSAID prescription timing relative to cancer diagnosis: Only POST: patients prescribed NSAIDs within 6 months after diagnosis only. PRE & POST: patients prescribed NSAIDs both within 6 months before and after diagnosis. By selecting the Only POST group (users initiating NSAIDs after diagnosis) as the comparator, we aimed to isolate the additive survival benefit of a sustained anti-inflammatory milieu (PRE & POST) established prior to diagnosis. To evaluate dose–response relationships, the frequency of NSAID use after diagnosis was calculated as the average number of prescription days per week during the first 6 months. Patients were classified into three groups: <1 day/week (low frequency), 1–3 days/week (intermediate frequency), and ≥ 4 days/week (high frequency). For interaction analyses, pre-diagnosis NSAID use was classified similarly. Covariates and outcomes Covariates were extracted from the NHIS and KCCR databases. Sociodemographic variables included age at diagnosis, income level (tertiles), and residential area (urban vs. rural). Clinicopathologic variables included cancer type (ovarian vs. fallopian tube), SEER stage (localized, regional, distant), and year of diagnosis (before vs. after July 1, 2016, the midpoint of the study period). Patients were categorized according to the primary treatment strategy: upfront surgery (primary debulking surgery, PDS) or neoadjuvant chemotherapy (NAC). Upfront surgery was defined as the first surgical intervention at diagnosis, encompassing staging procedures for localized/regional disease and primary debulking surgery for advanced disease. The NAC group included patients who received systemic chemotherapy prior to surgery, whereas those who received chemotherapy alone without subsequent surgery were excluded. Oher treatment-related variables included carboplatin use and cycles, bevacizumab use, ultra-extended procedures, and intensive care unit (ICU) admission within 1 month postoperatively. Ultra-extended procedures were defined as resections involving extra-gynecologic organs (e.g., bowel, liver, diaphragm, or spleen) within 6 months before or after the cancer diagnosis. ICU admission was defined as any intensive care unit stay occurring within 1 month after the index surgery (including the day of surgery). Comorbidities, such as hypertension, type 2 diabetes, dyslipidemia, chronic obstructive pulmonary disease (COPD), ischemic heart disease, ischemic stroke, were identified using ICD-10 diagnosis codes combined with relevant prescription records prior to cancer diagnosis. Specifically, type 2 diabetes was defined as E11–E14 with antidiabetic medications, hypertension as I10–I13 or I15 with antihypertensive medications, and dyslipidemia as E78 with anti-hyperlipidemic medications. COPD, ischemic heart disease, and ischemic stroke were defined using ICD-10 codes J41–J44, I20–I25, and I63–I64, respectively. Overall comorbidity burden was quantified using the Charlson Comorbidity Index (CCI) based on ICD-10 codes according to the Quan adaptation. The primary outcome was all-cause mortality, identified through death certificate data provided by Statistics Korea. Follow-up was defined from the date of diagnosis until the date of death or December 31, 2020, whichever came first. Statistical analysis Baseline characteristics were summarized as mean ± standard deviation (SD) for continuous variables and as frequencies with percentages for categorical variables. Group differences were assessed using Student’s t-tests or chi-square tests. Comparisons among three frequency groups were performed using analysis of variance (ANOVA) or chi-square tests as appropriate. Hazard ratios (HRs) with 95% confidence intervals (CIs) for all-cause mortality were estimated using Cox proportional hazards models. A series of models with progressive adjustment for potential confounders was constructed. The fully adjusted model (Model 7) included age at diagnosis, SEER stage, income, residence, year of diagnosis, primary treatment strategy (NAC vs. PDS), standard surgery and chemotherapy, chemotherapy cycles, bevacizumab use, ultra-extended procedures, ICU admission, aspirin and acetaminophen use, comorbidities (diabetes, hypertension, dyslipidemia, COPD, ischemic heart disease, stroke), and cancer type. Analyses were conducted to compare ( 1 ) Only POST vs. PRE & POST NSAID users, and ( 2 ) post-diagnosis NSAID frequency groups. Subgroup analyses were performed according to clinical factors considered to reflect tumor burden, including SEER stage, primary treatment strategy (NAC vs. PDS), presence of ultra-extended procedures, and ICU admission within 1 month. Because the proportion of NAC cases would be low in the localized stage, analyses stratified by SEER stage were restricted to regional and/or distant stages to allow a more appropriate comparison between NAC and PDS. Additional subgroup analyses were performed to compare post-diagnosis NSAID frequency groups between the NAC and PDS subgroups, and to evaluate NSAID frequency pre- and post-diagnosis within the PDS subgroup. Interaction terms were included to assess effect modification. All statistical analyses were conducted using SAS software, version 9.4 (SAS Institute, Cary, NC, USA). Result Baseline characteristics A total of 14,736 women were included in the study. Baseline characteristics are summarized in Table 1 . The mean age at diagnosis was 54.1 ± 11.7 years, and the majority of patients were diagnosed with ovarian cancer (95.1%). More than half of the cohort (51.6%) presented with distant-stage disease at diagnosis. Table 1 Baseline Characteristics of Patients with Ovarian or Fallopian Tube Cancer, Stratified by Nonsteroid Anti-Inflammatory Drug (NSAID) Use Timing and Frequency . Values are presented as mean with standard deviation (SD) for follow-up duration and number (percentage) for categorical variables. P-values were calculated using Student’s t-test or analysis of variance (ANOVA) for continuous variables and chi-square tests for categorical variables, as appropriate Total (n = 14736) NSAID use NSAID frequency c after diagnosis Only POST a (n = 5104) PRE & POST b (n = 9632) P value Low (n = 10168) Intermediate (n = 3170) High (n = 1398) P value NSAID frequency – no (%) < 0.001 Low (< 1 day/week) 10168 (69) 3930 (77) 6238 (64.76) Intermediate (1–3 day/week) 3170 (21.5) 936 (18.34) 2234 (23.19) High (≥ 4 day/week) 1398 (9.5) 238 (4.66) 1160 (12.04) Cancer type – no (%) < 0.001 0.161 Ovary 14021 (95.2) 4917 (96.34) 9104 (94.52) 9684 (95.24) 2998 (94.57) 1339 (95.78) Fallopian tube 715 (4.9) 187 (3.66) 528 (5.48) 484 (4.76) 172 (5.43) 59 (4.22) SEER stage – no (%) < 0.001 < 0.001 Localized 3963 (26.9) 1566 (30.68) 2397 (24.89) 3011 (29.61) 721 (22.74) 231 (16.52) Regional 3167 (21.5) 1109 (21.73) 2058 (21.37) 2272 (22.34) 641 (20.22) 254 (18.17) Distant 7606 (51.6) 2429 (47.59) 5177 (53.75) 4885 (48.04) 1808 (57.03) 913 (65.31) Age Mean ± SD – year 54.1 ± 11.7 51.64 ± 11.36 55.44 ± 11.6 < 0.001 52.93 ± 11.5 55.18 ± 11.52 60.45 ± 10.88 < 0.001 20–49 – no (%) 5051 (34.3) 2140 (41.93) 2911 (30.22) 3842 (37.79) 980 (30.91) 229 (16.38) < 0.001 50–69 – no (%) 8008 (54.3) 2614 (51.21) 5394 (56) 5420 (53.3) 1761 (55.55) 827 (59.16) 70–79 – no (%) 1677 (11.34) 350 (6.86) 1327 (13.78) 906 (8.91) 429 (13.53) 342 (24.46) Diagnosed date – no (%) 0.002 < 0.001 2012-01 ~ 2016-07 7420 (50.4) 2658 (52.08) 4762 (49.44) 5059 (49.75) 1688 (53.25) 673 (48.14) 2016-07 ~ 2019-12 7316 (49.7) 2446 (47.92) 4870 (50.56) 5109 (50.25) 1482 (46.75) 725 (51.86) Surgery – no (%) < 0.001 0.022 Not done 2178 (14.8) 701 (13.73) 1477 (15.33) 1436 (14.12) 514 (16.21) 228 (16.31) Done before diagnosis 169 (1.2) 4 (0.08) 165 (1.71) 118 (1.16) 34 (1.07) 17 (1.22) Done after diagnosis 12389 (84.1) 4399 (86.19) 7990 (82.95) 8614 (84.72) 2622 (82.71) 1153 (82.47) Chemotherapy – no (%) < 0.001 < 0.001 Not done 2048 (13.9) 818 (16.03) 1230 (12.77) 1595 (15.69) 334 (10.54) 119 (8.51) Done 12688 (86.1) 4286 (83.97) 8402 (87.23) 8573 (84.31) 2836 (89.46) 1279 (91.49) Primary treatment – no (%) < 0.001 < 0.001 Neoadjuvant chemotherapy (NAC) 3934 (26.7) 1220 (23.9) 2714 (28.18) 2472 (24.31) 952 (30.03) 510 (36.48) Upfront surgery (PDS) 10802 (73.3) 3884 (76.1) 6918 (71.82) 7696 (75.69) 2218 (69.97) 888 (63.52) Total Carboplatin cycle Mean ± SD 4.85 ± 2.3 4.69 ± 2.38 4.93 ± 2.25 < 0.001 4.74 ± 2.37 4.97 ± 2.13 5.34 ± 2.02 < 0.001 0–3 – no (%) 3239 (21.98) 1226 (24.02) 2013 (20.9) < 0.001 2418 (23.78) 622 (19.62) 199 (14.23) < 0.001 4–6 – no (%) 9734 (66.06) 3312 (64.89) 6422 (66.67) 6640 (65.3) 2147 (67.73) 947 (67.74) 7 – no (%) 1763 (11.96) 566 (11.09) 1197 (12.43) 1110 (10.92) 401 (12.65) 252 (18.03) Bevacizumab use – no (%) 1093(7.42) 343 (6.72) 750 (7.79) 0.019 696 (6.85) 251 (7.92) 146 (10.44) < 0.001 Ultra-extended procedure – no (%) 3157 (21.42) 1035 (20.28) 2122 (22.03) 0.014 1960 (19.28) 779 (24.57) 418 (29.9) < 0.001 Intensive care unit (ICU) admission – no (%) 3512 (23.83) 1163 (22.79) 2349 (24.39) 0.030 1961 (19.29) 965 (30.44) 586 (41.92) < 0.001 Socioeconomic status – no (%) Low income level 2985 (20.26) 943 (18.48) 2042 (21.2) < 0.001 2012 (19.79) 695 (21.92) 278 (19.89) 0.031 Urban 7108 (48.24) 2570 (50.35) 4538 (47.11) < 0.001 4922 (48.41) 1531 (48.3) 655 (46.85) 0.550 Medical aid – no (%) < 0.001 0.055 1–3 tier 4039 (27.41) 1305 (25.57) 2734 (28.38) 2736 (26.91) 928 (29.27) 375 (26.82) 4–7 tier 4974 (33.75) 1728 (33.86) 3246 (33.7) 3483 (34.25) 1036 (32.68) 455 (32.55) 8–10 tier 5723 (38.84) 2071 (40.58) 3652 (37.92) 3949 (38.84) 1206 (38.04) 568 (40.63) Comorbidity – no (%) Type 2 Diabetes 1805 (12.25) 425 (8.33) 1380 (14.33) < 0.001 1022 (10.05) 441 (13.91) 342 (24.46) < 0.001 Hypertension 4523 (30.69) 1077 (21.1) 3446 (35.78) < 0.001 2609 (25.66) 1078 (34.01) 836 (59.8) < 0.001 Dyslipidemia 3204 (21.74) 715 (14.01) 2489 (25.84) < 0.001 1806 (17.76) 767 (24.2) 631 (45.14) < 0.001 COPD d 1923 (13.05) 508 (9.95) 1415 (14.69) < 0.001 1211 (11.91) 455 (14.35) 257 (18.38) < 0.001 Ischemic heart disease 1372 (9.31) 309 (6.05) 1063 (11.04) < 0.001 710 (6.98) 337 (10.63) 325 (23.25) < 0.001 Ischemic stroke 365 (2.48) 79 (1.55) 286 (2.97) < 0.001 154 (1.51) 98 (3.09) 113 (8.08) < 0.001 Mean CCI e score ± SD 7.42 ± 3.67 6.72 ± 3.53 7.8 ± 3.69 < 0.001 7 ± 3.63 8.1 ± 3.6 9.01 ± 3.46 < 0.001 Aspirin use – no (%) 1427 (9.68) 119 (2.33) 1308 (13.58) < 0.001 304 (2.99) 385 (12.15) 738 (52.79) < 0.001 Pre-diagnosis of ovarian/tubal cancer 1031 ( 7 ) 0 (0) 1031 (10.7) < 0.001 229 (2.25) 243 (7.67) 559 (39.99) < 0.001 Post-diagnosis of ovarian/tubal cancer 1128 (7.65) 119 (2.33) 1009 (10.48) < 0.001 108 (1.06) 302 (9.53) 718 (51.36) < 0.001 Acetaminophen use – no (%) 10703 (72.63) 3175 (62.21) 7528 (78.16) < 0.001 7332 (72.11) 2385 (75.24) 986 (70.53) < 0.001 Pre-diagnosis of ovarian/tubal cancer 5659 (38.4) 1034 (20.26) 4625 (48.02) < 0.001 3663 (36.02) 1377 (43.44) 619 (44.28) < 0.001 Post-diagnosis of ovarian/tubal cancer 8857 (60.1) 2787 (54.6) 6070 (63.02) < 0.001 6158 (60.56) 1945 (61.36) 754 (53.93) < 0.001 a Only POST group was defined as patients prescribed NSAIDs within 6 months after diagnosis. b PRE & POST group was defined as patients prescribed NSAIDs both within 6 months before and after diagnosis. c NSAID frequency was categorized as low (< 1 day/week), intermediate (1–3 days/week), or high (≥ 4 days/week). d COPD, chronic obstructive pulmonary disease; e CCI, Charlson Comorbidity Index [Table 1 near here] Compared with the Only POST group (n = 5,104), patients in the PRE & POST group (n = 9,632) were older (55.4 vs. 51.6 years, P < 0.001) and more frequently diagnosed at the distant stage (53.8% vs. 47.6%, P < 0.001). The PRE & POST group also had a higher prevalence of comorbidities, including diabetes (14.3% vs. 8.3%), hypertension (35.8% vs. 21.1%), and dyslipidemia (25.8% vs. 14.0%), and a higher mean Charlson Comorbidity Index (CCI) score (7.8 vs. 6.7, all P < 0.001). They were more likely to receive NAC (28.2% vs. 23.9%, P < 0.001) and to undergo ultra-extended procedures (22.0% vs. 20.3%, P = 0.014). When stratified by post-diagnosis NSAID frequency, patients in the high-frequency group (n = 1,398) were older (60.5 vs. 55.2 vs. 52.9 years, P < 0.001), more frequently diagnosed at the distant stage (65.3% vs. 57.0% vs. 48.0%, P < 0.001), and had higher mean CCI scores (9.01 vs. 8.1 vs. 7.0, P < 0.001) compared with the intermediate- and low-frequency groups (n = 3,170 and n = 10,168, respectively). Association between NSAID use and all-cause mortality During a median follow-up of 2.91 years (interquartile range, 1.51–5.03), 4,108 deaths (27.9%) were recorded. Results of the Cox proportional hazards models are presented in Table 2 . In unadjusted analyses (Model 1), the PRE & POST group and the high-frequency post-diagnosis group showed higher mortality risks compared with the Only POST and low-frequency groups, respectively. Table 2 Hazard ratios for all-cause mortality according to NSAID use timing and frequency . Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models Death Duration d Rate e Model 1 f Model 2 g Model 3 h Model 4 i Model 5 j Model 6 k Model 7 l Group Only POST a (n = 5104) 1367 18055 75.7 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) PRE & POST b (n = 9632) 2741 31779 86.3 1.12 (1.05–1.20) 0.99 (0.93–1.06) 0.95 (0.89–1.02) 0.96 (0.90–1.03) 0.94 (0.88–1.01) 0.94 (0.88–1.01) 0.94 (0.88–1.01) NSAID frequency c Low (n = 10168) 2632 34880 75.5 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) Intermediate (n = 3170) 1006 10661 94.4 1.25 (1.17–1.35) 1.15 (1.07–1.24) 1.08 (1.01–1.16) 1.08 (1.00-1.16) 1.05 (0.97–1.13) 1.05 (0.97–1.13) 1.04 (0.97–1.12) High (n = 1398) 470 4292 109.5 1.43 (1.29–1.58) 1.08 (0.98–1.191) 0.98 (0.89–1.09) 1.01 (0.91–1.11) 0.93 (0.83–1.04) 0.93 (0.83–1.04) 0.92 (0.82–1.04) a Only POST group was defined as patients prescribed NSAIDs within 6 months after diagnosis. b PRE & POST group was defined as patients prescribed NSAIDs both within 6 months before and after diagnosis. c NSAID frequency was categorized as low (< 1 day/week), intermediate (1–3 days/week), or high (≥ 4 days/week). d Duration: Total follow-up time for the entire group (Unit: Person-Time). e Rate: Mortality rate per 1,000 person-time f Model 1 is the unadjusted crude model. g Model 2 was adjusted for age at diagnosis. h Model 3 was additionally adjusted for variables in Model 2 plus Surveillance, Epidemiology, and End Results (SEER) stage, low income level, and place of residence (urban or rural). i Model 4 was additionally adjusted for variables in Model 3 plus diagnosis date, receipt of standard treatment, use and cycles of carboplatin, and use of bevacizumab. j Model 5 was additionally adjusted for variables in Model 4 plus receipt of ultra-extended procedure, intensive care unit admission within 1 month, and use of acetaminophen and aspirin. k Model 6 was additionally adjusted for variables in Model 5 plus comorbidities (diabetes mellitus, hypertension, dyslipidemia, chronic obstructive pulmonary disease, ischemic heart disease, and stroke). l Model 7 was the fully adjusted model, additionally including all variables in Model 6 plus cancer type. [Table 2 near here] However, in the fully adjusted model (Model 7), there was no statistically difference in all-cause mortality between the PRE & POST and Only POST groups (adjusted HR, 0.94; 95% CI, 0.88–1.01). Similarly, post-diagnosis NSAID frequency was not associated with mortality after full adjustment: compared with the low-frequency group, the adjusted HRs were 1.04 (95% CI, 0.97–1.12) for the intermediate-frequency group and 0.92 (95% CI, 0.82–1.04) for the high-frequency group. Thus, NSAID timing and frequency were not independently associated with mortality in the overall cohort. Subgroup analysis To evaluate whether the association between NSAID use and mortality varied by tumor burden, subgroup analyses were performed according to SEER stage, primary treatment (NAC vs. PDS), ultra-extended procedures, and ICU admission within 1 month (Table 3 , Supplementary Table 2). Table 3 Subgroup analyses of the association between NSAID use and all-cause mortality according to primary treatment and Surveillance, Epidemiology, and End Results (SEER) stage. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models. P values for interaction were calculated by including cross-product terms in the multivariable models Group Death Duration d Rate e Model 1 f Model 2 g Model 3 h Model 4 i Model 5 j Model 6 k Model 7 l All SEER stage NAC m Only Post a (n = 1220) 466 4059 114.8 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) PRE & POST b (n = 2714) 1144 8033 142.4 1.23 (1.10–1.37) 1.11 (0.99–1.23) 1.06 (0.95–1.18) 1.07 (0.96–1.19) 1.04 (0.93–1.16) 1.04 (0.93–1.16) 1.04 (0.93–1.16) PDS n Only Post (n = 3884) 901 13996 64.4 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) PRE & POST (n = 6918) 1597 23746 67.3 1.03 (0.95–1.12) 0.92 (0.85-1.00) 0.89 (0.82–0.96) 0.91 (0.83–0.98) 0.89 (0.82–0.97) 0.89 (0.82–0.97) 0.89 (0.82–0.97) P for interaction 0.012 0.007 0.012 0.018 0.021 0.022 0.021 Regional and Distant SEER stage NAC Only Post (n = 1018) 449 3096 145.0 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) PRE & POST (n = 2370) 1113 6530 170.4 1.17 (1.05–1.31) 1.08 (0.97–1.20) 1.06 (0.95–1.18) 1.07 (0.95–1.19) 1.04 (0.93–1.17) 1.04 (0.93–1.17) 1.05 (0.94–1.17) PDS Only Post (n = 2520) 805 8442 95.4 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) PRE & POST (n = 4865) 1455 15537 93.6 0.97 (0.89–1.06) 0.90 (0.83–0.98) 0.89 (0.82–0.97) 0.91 (0.84–0.99) 0.90 (0.82–0.98) 0.90 (0.82–0.98) 0.90 (0.82–0.98) P for interaction 0.010 0.012 0.017 0.028 0.032 0.033 0.032 Distant SEER stage NAC Only Post (n = 816) 399 2328 171.4 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) PRE & POST (n = 2000) 1012 5187 195.1 1.14 (1.01–1.28) 1.07 (0.95–1.20) 1.06 (0.95–1.19) 1.07 (0.95–1.20) 1.05 (0.94–1.18) 1.05 (0.94–1.19) 1.06 (0.94–1.19) PDS Only Post (n = 1613) 653 4982 131.1 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) PRE & POST (n = 3177) 1184 9599 123.3 0.93 (0.85–1.03) 0.88 (0.80–0.97) 0.88 (0.80–0.97) 0.91 (0.82-1.00) 0.89 (0.81–0.99) 0.89 (0.81–0.99) 0.89 (0.81–0.98) P for interaction 0.010 0.011 0.013 0.030 0.033 0.031 0.029 NAC vs. PDS by post-diagnosis NSAID frequency c NAC Low (n = 2472) 961 7851 122.4 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) Intermediate (n = 952) 410 2865 143.1 1.17 (1.04–1.32) 1.12 (1.00-1.26) 1.03 (0.92–1.15) 1.03 (0.91–1.15) 1.00 (0.89–1.12) 0.99 (0.88–1.11) 0.98 (0.88–1.11) High (n = 510) 239 1376 173.7 1.39 (1.21–1.60) 1.14 (0.99–1.32) 1.01 (0.87–1.16) 1.03 (0.89–1.19) 0.95 (0.82–1.11) 0.96 (0.82–1.11) 0.95 (0.82–1.11) PDS Low (n = 7696) 1671 27029 61.8 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) Intermediate (n = 2218) 596 7797 76.4 1.24 (1.13–1.36) 1.14 (1.04–1.26) 1.10 (1.00-1.20) 1.10 (1.00-1.21) 1.07 (0.97–1.17) 1.07 (0.97–1.17) 1.07 (0.97–1.17) High (n = 888) 231 2916 79.2 1.27 (1.10–1.45) 0.96 (0.83–1.10) 0.92 (0.80–1.06) 0.94 (0.82–1.08) 0.85 (0.73–0.99) 0.85 (0.73–0.99) 0.84 (0.73–0.98) P for interaction 0.413 0.181 0.383 0.359 0.263 0.197 0.203 a Only POST group was defined as patients prescribed NSAIDs within 6 months after diagnosis. b PRE & POST group was defined as patients prescribed NSAIDs both within 6 months before and after diagnosis. c NSAID frequency was categorized as low (< 1 day/week), intermediate (1–3 days/week), or high (≥ 4 days/week). d Duration: Total follow-up time for the entire group (Unit: Person-Time). e Rate: Mortality rate per 1,000 person-time f Model 1 is the unadjusted crude model. g Model 2 was adjusted for age at diagnosis. h Model 3 was additionally adjusted for variables in Model 2 plus SEER stage, low income level, and place of residence (urban or rural). i Model 4 was additionally adjusted for variables in Model 3 plus diagnosis date, receipt of standard treatment, use and cycles of carboplatin, and use of bevacizumab. j Model 5 was additionally adjusted for variables in Model 4 plus receipt of ultra-extended procedure, intensive care unit admission within 1 month, and use of acetaminophen and aspirin. k Model 6 was additionally adjusted for variables in Model 5 plus comorbidities (diabetes mellitus, hypertension, dyslipidemia, chronic obstructive pulmonary disease, ischemic heart disease, and stroke). l Model 7 was the fully adjusted model, additionally including all variables in Model 6 plus cancer type. m NAC, neoadjuvant chemotherapy; n PDS, upfront surgery [Table 3 near here] A statistically significant interaction was observed between NSAID exposure and primary treatment (NAC vs. PDS) (p for interaction = 0.021), indicating that the association differed by treatment type. In the PDS group, the PRE & POST group had a significantly lower mortality risk compared with the Only POST group (adjusted HR = 0.89; 95% CI, 0.82–0.97). In addition, high-frequency NSAID users in the PDS group also showed a reduced mortality risk compared with low-frequency users (adjusted HR = 0.84; 95% CI, 0.73–0.98). When stratified by SEER stage, the protective association of PRE & POST NSAID use in the PDS subgroup remained consistent in both the local/regional stage and the distant stage, whereas no significant benefit was observed in the NAC subgroup. These findings are summarized in the forest plot (Fig. 2 ). In the NAC group, no association was found between NSAID exposure timing and mortality (adjusted HR = 1.04; 95% CI, 0.93–1.16). Similarly, the association between NSAID use frequency and mortality did not reach statistical significance (adjusted HR = 0.96; 95% CI, 0.82–1.11). The interaction between post-diagnosis NSAID frequency and primary treatment type was not statistically ( P for interaction = 0.203). No interaction was observed for SEER stage, ultra-extended procedures, or ICU admission within 1 month (Supplementary Table 2). Based on these findings, further interaction analyses were conducted within the PDS subgroup according to pre- and post-diagnosis NSAID frequency (Table 4 ). Among patients who did not use NSAIDs preoperatively, mortality did not differ across post-diagnosis frequency groups. In contrast, among PRE & POST users, those with intermediate/high pre-diagnosis NSAID use who either increased to or maintained high-frequency use after surgery showed lower mortality compared with those who decreased to low-frequency use (adjusted HR, 0.66; 95% CI, 0.44–0.98 and adjusted HR, 0.68; 95% CI, 0.50–0.92, respectively). Table 4 Subgroup analyses of NSAID frequency before and after diagnosis in the Upfront surgery (PDS) subgroup. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models. P values for interaction were obtained by including cross-product terms in the multivariable models Group NSAID frequency c Death Duration d Rate e Model 1 f Model 2 g Model 3 h Model 4 i Model 5 j Model 6 k Model 7 l Pre-diagnosis frequency Post-diagnosis frequency Only POST a None (n = 3884) Low (n = 3068) 669 11073 60.4 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) Intermediate (n = 668) 193 2443 79.0 1.32 (1.12–1.55) 1.29 (1.10–1.51) 1.15 (0.98–1.35) 1.17 (1.00-1.37) 1.13 (0.97–1.33) 1.13 (0.96–1.33) 1.14 (0.97–1.34) High (n = 148) 39 480 81.3 1.32 (0.96–1.83) 1.22 (0.89–1.69) 1.02 (0.74–1.41) 1.07 (0.78–1.48) 0.98 (0.71–1.37) 1.01 (0.73–1.40) 1.01 (0.73–1.40) PRE & POST b Low (n = 4997) Low (n = 3772) 751 13310 56.4 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) Intermediate (n = 1016) 237 3562 66.5 1.18 (1.02–1.37) 1.15 (0.99–1.33) 1.11 (0.96–1.28) 1.10 (0.95–1.27) 1.07 (0.93–1.24) 1.08 (0.94–1.26) 1.08 (0.94–1.25) High (n = 209) 43 639 67.3 1.17 (0.86–1.59) 1.08 (0.79–1.46) 0.92 (0.68–1.25) 0.97 (0.71–1.32) 0.88 (0.64–1.21) 0.90 (0.66–1.24) 0.90 (0.66–1.23) Intermediate (n = 1154) Low (n = 683) 187 2122 88.1 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) Intermediate (n = 354) 106 1179 89.9 1.03 (0.81–1.30) 0.94 (0.74–1.20) 1.01 (0.79–1.28) 1.01 (0.80–1.29) 0.99 (0.78–1.26) 0.99 (0.78–1.26) 0.99 (0.78–1.25) High (n = 117) 29 362 80.0 0.92 (0.62–1.36) 0.77 (0.52–1.14) 0.73 (0.49–1.08) 0.74 (0.50–1.09) 0.68 (0.45–1.01) 0.66 (0.44–0.98) 0.66 (0.44–0.98) High (n = 767) Low (n = 173) 64 523 122.3 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) 1 (Ref.) Intermediate (n = 180) 60 612 98.0 0.81 (0.57–1.15) 0.80 (0.56–1.14) 0.83 (0.59–1.19) 0.77 (0.54–1.10) 0.76 (0.53–1.08) 0.75 (0.52–1.06) 0.74 (0.52–1.06) High (n = 414) 120 1435 83.6 0.69 (0.51–0.93) 0.67 (0.50–0.91) 0.77 (0.57–1.04) 0.73 (0.54–0.99) 0.70 (0.51–0.95) 0.68 (0.50–0.93) 0.68 (0.50–0.92) P for interaction 0.041 0.038 0.604 0.338 0.391 0.292 0.270 a Only POST group was defined as patients prescribed NSAIDs within 6 months after diagnosis. b PRE & POST group was defined as patients prescribed NSAIDs both within 6 months before and after diagnosis. c NSAID frequency was categorized as low (< 1 day/week), intermediate (1–3 days/week), or high (≥ 4 days/week). d Duration: Total follow-up time for the entire group (Unit: Person-Time). e Rate: Mortality rate per 1,000 person-time. f Model 1 is the unadjusted crude model. g Model 2 was adjusted for age at diagnosis. h Model 3 was additionally adjusted for variables in Model 2 plus SEER stage, low income level, and place of residence (urban or rural). i Model 4 was additionally adjusted for variables in Model 3 plus diagnosis date, receipt of standard treatment, use and cycles of carboplatin, and use of bevacizumab. j Model 5 was additionally adjusted for variables in Model 4 plus receipt of ultra-extended procedure, intensive care unit admission within 1 month, and use of acetaminophen and aspirin. k Model 6 was additionally adjusted for variables in Model 5 plus comorbidities (diabetes mellitus, hypertension, dyslipidemia, chronic obstructive pulmonary disease, ischemic heart disease, and stroke). l Model 7 was the fully adjusted model, additionally including all variables in Model 6 plus cancer type. [Table 4 near here] Discussion In this nationwide cohort study, peri-diagnostic NSAID use and frequency were not associated with reduced mortality in the overall population of patients with epithelial ovarian cancer. Clinically, long-term or frequent NSAID users are likely to have adverse prognostic factors such as chronic pain or advanced disease. After adjusting for these clinical variables, NSAID use was not found to be an independent predictor of mortality in most settings. The most notable finding of this study was that sustained NSAID use was associated with reduced mortality among patients who underwent upfront surgery. In this subgroup, patients who used NSAIDs both before and after diagnosis (PRE & POST) had an approximately 11% lower mortality risk compared with those who used NSAIDs only after diagnosis (Only POST). Moreover, high-frequency users had a 16% lower mortality risk compared with low-frequency users. Detailed analyses further indicated that reducing NSAID use after upfront surgery was associated with increased mortality, whereas maintaining or escalating high-frequency use conferred a survival benefit. This effect may be explained by immunologic changes in the tumor microenvironment induced by upfront surgery. Cytoreductive surgery reduces tumor burden, leading to decreased circulating regulatory T cells and improved CD8⁺ T-cell function, thereby reversing immunosuppression ( 25 ). Surgical cytoreduction also reduces myeloid-derived suppressor cells (MDSCs) ( 26 , 27 ), fostering a more immunologically “hot” environment. PGE₂ promotes an immunosuppressive microenvironment, dampening tumor-infiltrating lymphocytes (TILs) and T-cell activation, thus reinforcing a “cold” tumor phenotype ( 28 , 29 ). NSAIDs inhibit the COX-2/PGE₂ pathway, potentially alleviating immunosuppression and enhancing T-cell infiltration and activation within the tumor microenvironment ( 30 ). This effect may be amplified in the more favorable immune milieu created by PDS. In contrast, patients receiving NAC typically harbor a high tumor burden, a state characterized by T-cell exhaustion, increased MDSCs, and accumulation of regulatory T cells ( 16 ). Residual tumors surviving chemotherapy are more likely to represent chemo-resistant, immunologically “cold” phenotypes ( 31 , 32 ), limiting the remodeling effect of NSAIDs even after interval debulking surgery (IDS). Another explanation for the benefit of continuous NSAID use in the upfront subgroup may relate to the acute inflammatory response induced by surgery. Surgery can trigger an inflammatory storm and platelet-mediated dissemination ( 33 ), which may facilitate tumor growth and micro-metastasis. Preoperative NSAID use could attenuate this inflammatory surge and platelet-driven metastasis, thereby improving survival outcomes. Previous prospective studies, including the Australian Ovarian Cancer Prognosis and Lifestyle (OPAL) study ( 19 ) and a U.S. cohort study ( 18 ), demonstrated a survival benefit from NSAID use in ovarian cancer. Differences between our results and these studies may reflect variations in study design (prospective vs. retrospective), racial/ethnic differences (Asian vs. Western populations), biological heterogeneity of ovarian cancer, and methods of measuring NSAID use (prescription claims vs. self-reported surveys). Clear cell histology, more prevalent in Asian populations ( 23 ), has been reported to exhibit distinct TMEs ( 34 ), which could contribute to the limited immunomodulatory effects of NSAIDs in our population. This study has several limitations. First, as a prescription-based retrospective cohort, it did not account for over-the-counter NSAID use. Second, the observed increase in mortality among patients who discontinued NSAID use postoperatively may have been due to clinical deterioration (e.g., postoperative complications, renal failure) rather than NSAID discontinuation itself, introducing potential selection bias. Also, potential residual confounding (e.g., indication bias for NSAID use such as chronic pain, cardiovascular disease) cannot be fully excluded. Furthermore, the reliance on claims data precluded assessment of oncologic outcomes such as recurrence, progression-free survival (PFS), and cancer-specific survival, as well as cause-specific mortality. Finally, detailed molecular and pathological data (e.g., cell type, genetic mutations) were not available. Conclusions In conclusion, while NSAID use was not associated with improved survival in the overall ovarian cancer cohort, continuous NSAID use was associated with reduced mortality among patients undergoing upfront surgery. Our findings highlight the potential of NSAIDs as a precision adjuvant strategy, effective specifically in patients undergoing upfront surgery where the immune milieu is conducive to immunomodulation. Although no randomized clinical trials have yet demonstrated a survival advantage with NSAID use in ovarian cancer ( 13 , 35 ), our findings highlight a potential benefit in selected patient groups. Future prospective studies in carefully stratified populations are warranted to validate these findings and further elucidate the role of NSAIDs as adjunctive therapy in ovarian cancer. Abbreviations ANOVA Analysis of variance CCI Charlson Comorbidity Index CI Confidence interval COPD Chronic obstructive pulmonary disease COX Cyclooxygenase COX-2 Cyclooxygenase-2 CPLD Cancer Public Library Database CRP C-reactive protein HIRA Health Insurance Review & Assessment Service HR Hazard ratio HNSCC Head and neck squamous cell carcinoma ICD-10 International Classification of Diseases, 10th Revision ICU Intensive care unit IDS Interval debulking surgery IL-8 Interleukin-8 KCCR Korea Central Cancer Registry K-Cure Korean Clinical Data Utilization Network for Research Excellence KNCI DB Korea National Cancer Incidence Database MDSC Myeloid-derived suppressor cell NAC Neoadjuvant chemotherapy NHID National Health Information Database NHIRD National Health Insurance Research Database NHIS National Health Insurance Service NSAID Nonsteroidal anti-inflammatory drug OPAL Australian Ovarian Cancer Prognosis and Lifestyle PDS Primary debulking surgery PFS Progression-free survival PGE₂ Prostaglandin E₂ SD Standard deviation SEER Surveillance, Epidemiology, and End Results TIL Tumor-infiltrating lymphocyte TME Tumor microenvironment TNF-α Tumor necrosis factor-alpha VEGF Vascular endothelial growth factor Declarations Human Ethics and Consent to Participate declarations: The study was conducted in accordance with the Declaration of Helsinki and was approved by the Institutional Review Board (IRB) of Samsung Medical Center (IRB No. 2025-06-106). As de-identified secondary data were used, informed consent was waived. Clinical trial number : not applicable. Consent for publication: Not applicable Availability of data and materials : This study used data from the Korean Clinical Data Utilization Network for Research Excellence (K-CURE). These data are not publicly available due to data use agreements and national privacy regulations. Qualified researchers may request access through the K-CURE data access committee with appropriate institutional and ethical approvals. Declaration of competing interests : The authors declare that they have no conflicts of interest. Funding sources: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors’ contributions: KH and YYL conceptualized the study. SYK and KH were responsible for data curation. SL, JYH and JHS performed the formal analysis and developed the methodology. JYH, JHS and YEC conducted the investigation. 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List of non-selective NSAIDs 1, selective COX-22 inhibitors, and non-NSAID analgesics included in the analysis Table S2. Subgroup analyses of the association between NSAID exposure and all-cause mortality according to SEER stage, ultra-extended procedure, and intensive care unit (ICU) admission Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 19 May, 2026 Reviewers agreed at journal 04 May, 2026 Reviewers invited by journal 08 Apr, 2026 Editor assigned by journal 30 Mar, 2026 Submission checks completed at journal 30 Mar, 2026 First submitted to journal 26 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9233171","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":620180255,"identity":"e58722c3-d4e6-4614-af64-af19d3550fde","order_by":0,"name":"Seongyun Lim","email":"","orcid":"","institution":"Samsung Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Seongyun","middleName":"","lastName":"Lim","suffix":""},{"id":620180256,"identity":"0767a5e9-8410-4bfd-9829-b2c8cde3fa53","order_by":1,"name":"Joon-Young Hong","email":"","orcid":"","institution":"Samsung Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Joon-Young","middleName":"","lastName":"Hong","suffix":""},{"id":620180257,"identity":"7e76266d-3bf5-46ab-9c83-275328649bc9","order_by":2,"name":"Jun-Hyeong Seo","email":"","orcid":"","institution":"Samsung Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Jun-Hyeong","middleName":"","lastName":"Seo","suffix":""},{"id":620180258,"identity":"a6d15f64-5331-426f-b1cf-ee20cb071eb8","order_by":3,"name":"Young Eun Chung","email":"","orcid":"","institution":"Samsung Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Young","middleName":"Eun","lastName":"Chung","suffix":""},{"id":620180259,"identity":"ec19b55e-49f1-469d-bdaa-2c08644d402c","order_by":4,"name":"Se Yun Kim","email":"","orcid":"","institution":"Sungkyunkwan University","correspondingAuthor":false,"prefix":"","firstName":"Se","middleName":"Yun","lastName":"Kim","suffix":""},{"id":620180260,"identity":"9cdbcbd6-7f00-400c-b3dd-b57bb5b256ca","order_by":5,"name":"Kyungdo Han","email":"","orcid":"","institution":"Soongsil University","correspondingAuthor":false,"prefix":"","firstName":"Kyungdo","middleName":"","lastName":"Han","suffix":""},{"id":620180261,"identity":"1ff189bd-9a5e-478a-84d7-5704ecbd05c4","order_by":6,"name":"Yoo-Young Lee","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYFADdiD+QJoWZgYGxhkka2HmIUahwfHmYxIf2+7YNTAzH3xs88cuWn5G7uEXDDU20Ti1nDmWJjmz7VlyAzNbsnFuW3Luhht5aRYMx9JyG3BpuZFjJs3bdjgZ6Coz6dwG5twNEjlmBowNh4nRwv/9t8Wf+tz5M4jUYge0hY2ZgQ2o8kaO8QN8WiTPHEu2nHHucAIbM5uxZG/b8dwNZ96YMSTg8Qvf8eaDNz6UHbbnZ29++OHHn+rc+e05xh8+1Njg1KJwgIFFAkgntiEJskkk4FAOAvINDMygZGKPLMhMYsIZBaNgFIyCYQ4AdEpazFXtse8AAAAASUVORK5CYII=","orcid":"","institution":"Samsung Medical Center","correspondingAuthor":true,"prefix":"","firstName":"Yoo-Young","middleName":"","lastName":"Lee","suffix":""}],"badges":[],"createdAt":"2026-03-26 10:55:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9233171/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9233171/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107243470,"identity":"08016227-c6e8-4e5a-9df9-d9b230bb2c00","added_by":"auto","created_at":"2026-04-19 07:51:40","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":103488,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlowchart of patient selection.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e*Non-epithelial ovarian cancer was defined by a prescription record of etoposide within 6 months before or after diagnosis. Abbreviations: NSAID, nonsteroidal anti-inflammatory drug; SEER, Surveillance, Epidemiology, and End Results.\u003c/p\u003e","description":"","filename":"figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9233171/v1/a5a87c4ea3cbbc3246464936.jpg"},{"id":107243471,"identity":"a47101d1-354c-4054-b9d4-c5cebb862658","added_by":"auto","created_at":"2026-04-19 07:51:40","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":955354,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferential association between perioperative NSAID use and survival according to primary treatment strategy\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eForest plot showing the association between perioperative NSAID use (PRE \u0026amp; POST vs. Only POST) and all-cause mortality, stratified by primary treatment strategy (primary debulking surgery [PDS] vs. neoadjuvant chemotherapy [NAC]) and SEER stage. Only POST refers to patients prescribed NSAIDs within 6 months after diagnosis only. PRE \u0026amp; POST refers to patients prescribed NSAIDs both within 6 months before and after diagnosis . Hazard ratios (HRs) and 95% confidence intervals (CIs) are shown for multivariable-adjusted models.\u003c/p\u003e","description":"","filename":"figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9233171/v1/3740de410aab4c5eacddd10e.jpg"},{"id":107482282,"identity":"f876970c-7ab3-42e7-9234-5ebade997d34","added_by":"auto","created_at":"2026-04-22 02:22:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2356428,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9233171/v1/973a5a75-db0e-44ea-ab62-0128c164291b.pdf"},{"id":107243469,"identity":"d23169bf-97e1-43ac-bb63-a7f3767ed37d","added_by":"auto","created_at":"2026-04-19 07:51:40","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":29094,"visible":true,"origin":"","legend":"\u003cp\u003eFile name: Additional file 1\u003c/p\u003e\n\u003cp\u003eFile format: docx (Microsoft Word Document)\u003c/p\u003e\n\u003cp\u003eTitle of data: Supplementary tables\u003c/p\u003e\n\u003cp\u003eDescription of data: This file contains supplementary tables that support the primary findings of the study.\u003c/p\u003e\n\u003cp\u003eTable S1. List of non-selective NSAIDs 1, selective COX-22 inhibitors, and non-NSAID analgesics included in the analysis\u003c/p\u003e\n\u003cp\u003eTable S2. Subgroup analyses of the association between NSAID exposure and all-cause mortality according to SEER stage, ultra-extended procedure, and intensive care unit (ICU) admission\u003c/p\u003e","description":"","filename":"Supplementarytablessubmit.docx","url":"https://assets-eu.researchsquare.com/files/rs-9233171/v1/1915d93a03025598be1ab03e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Perioperative NSAID use and survival after upfront cytoreductive surgery for ovarian cancer: Nationwide cohort study","fulltext":[{"header":"Background","content":"\u003cp\u003eOvarian cancer remains an aggressive malignancy with poorer survival rates compared to cervical or endometrial cancer, despite the overall global decline in incidence and mortality (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). According to the Surveillance, Epidemiology, and End Results (SEER) database, the 5-year survival rate for localized disease is 91.7%; however, only 20% of patients are diagnosed at this stage. In contrast, 55% of cases are identified with distant metastasis, for which the 5-year survival rate drops markedly to 31.8% (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) This is largely due to the lack of effective early detection and screening strategies. Most patients present with nonspecific symptoms, such as abdominal distension or gastrointestinal discomfort, which typically occur after the development of ascites and peritoneal dissemination at stage III or higher (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe occurrence of peritoneal dissemination and ascites is accompanied by elevated levels of inflammatory and growth factors, such as IL-8, TNF-α and VEGF, as well as various cytokines and chemokines in the ascitic fluid. These inflammation-related changes in the tumor microenvironment contribute to cancer cell growth and invasion and play a critical role in peritoneal metastasis (\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Thus, inflammation influences the progression, metastasis, and chemo-resistance of epithelial ovarian cancer. A prospective study also demonstrated that elevated serum C-reactive protein (CRP) levels are associated with an increased risk of invasive epithelial ovarian cancer (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis raises the question of whether modulation of inflammation could improve survival outcomes in epithelial ovarian cancer. In other malignancies such as breast cancer (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), colorectal cancer (\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), and head and neck squamous cell carcinoma (HNSCC) (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), numerous studies have addressed this issue. In ovarian cancer, in vivo and murine studies have shown that interleukin-6 neutralization enhanced the efficacy of paclitaxel in epithelial ovarian cancer models (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). However, a clinical trial evaluating the addition of celecoxib to first-line chemotherapy in ovarian cancer failed to demonstrate a benefit (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong anti-inflammatory agents, nonsteroidal anti-inflammatory drugs (NSAIDs) are among the most widely accessible and commonly used, available over the counter for indications ranging from minor viral illnesses to autoimmune diseases. NSAIDs inhibit the cyclooxygenase (COX) pathway, thereby reducing prostaglandin E₂ (PGE₂) (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). PGE₂ is not only involved in regulating inflammation but also promotes immunosuppression, angiogenesis, and tumor growth. Consequently, NSAID-mediated inhibition of PGE₂ may provide both anti-inflammatory and antitumor effects (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Numerous studies have investigated the relationship between aspirin use and reduced incidence and mortality in colorectal cancer (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). In contrast, a nationwide Norwegian cohort study reported that aspirin and non-aspirin NSAID use was associated with increased mortality in endometrial cancer (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegarding ovarian cancer, prospective cohort studies from the United States and Australia reported that NSAID use was associated with reduced mortality risk (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Conversely, a Danish nationwide cohort study found that low-dose aspirin or non-aspirin NSAID use did not decrease mortality among ovarian cancer patients (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). To date, no such studies have been conducted in Asian populations. Given that ovarian cancer biology may vary by race and ethnicity (\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), there is a clear need to investigate the impact of NSAID use on survival outcomes in Asian populations. Therefore, this study aimed to evaluate the association between NSAID use and mortality risk in ovarian cancer patients using a large, nationwide retrospective cohort in Korea. Specifically, we focused on whether this survival impact is modulated by the primary treatment strategy (upfront surgery vs. neoadjuvant chemotherapy).\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData source and study population\u003c/h2\u003e \u003cp\u003eThis study utilized the Cancer Public Library Database (CPLD) established through the Korean Clinical Data Utilization Network for Research Excellence (K-Cure). The CPLD integrates four major national databases: The Korea National Cancer Incidence Database (KNCI DB) maintained by the Korea Central Cancer Registry (KCCR), mortality records from Statistics Korea, healthcare utilization data from the National Health Insurance Service (NHIS) National Health Information Database (NHID), and the National Health Insurance Research Database (NHIRD) managed by the Health Insurance Review \u0026amp; Assessment Service (HIRA). The NHIS provides universal health coverage for all residents in Korea and maintains comprehensive records of diagnoses, prescriptions, and procedures.\u003c/p\u003e \u003cp\u003eThe patient selection process is summarized in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The study population included women newly diagnosed with ovarian cancer (International Classification of Diseases, 10th Revision [ICD-10] code C56) or fallopian tube cancer (C57) between January 1, 2012, and December 31, 2019. Of 20,563 registered patients, exclusions were applied as follows (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, flowchart): non-epithelial tumors (defined by a prescription record of etoposide within 6 months before or after diagnosis), age younger than 20 or older than 80 years at diagnosis, missing SEER (Surveillance, Epidemiology, and End Results) stage, unmatched eligibility with the NHIS, lack of ovarian cancer\u0026ndash;related surgery or carboplatin administration, no NSAID prescription claims within 6 months after diagnosis, and application of a 6-month lag period to account for potential immortal time bias in NSAID exposure. The final cohort included 14,736 patients.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThis study was approved by the Institutional Review Board of Samsung Medical Center (IRB No. 2025-06-106) and conducted in accordance with the Declaration of Helsinki and relevant institutional guideline. As de-identified secondary data were used, informed consent was waived.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAssessment of NSAID exposure\u003c/h3\u003e\n\u003cp\u003eNSAID exposure was defined based on prescription claims data from the NHIS. NSAIDs included all injectable and oral agents available in Korea, encompassing non-selective NSAIDs, selective COX-2 inhibitors, acetaminophen, and aspirin (Supplementary Table\u0026nbsp;1). Patients were categorized into two groups according to NSAID prescription timing relative to cancer diagnosis:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eOnly POST: patients prescribed NSAIDs within 6 months after diagnosis only.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePRE \u0026amp; POST: patients prescribed NSAIDs both within 6 months before and after diagnosis.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eBy selecting the Only POST group (users initiating NSAIDs after diagnosis) as the comparator, we aimed to isolate the additive survival benefit of a sustained anti-inflammatory milieu (PRE \u0026amp; POST) established prior to diagnosis.\u003c/p\u003e \u003cp\u003eTo evaluate dose\u0026ndash;response relationships, the frequency of NSAID use after diagnosis was calculated as the average number of prescription days per week during the first 6 months. Patients were classified into three groups: \u0026lt;1 day/week (low frequency), 1\u0026ndash;3 days/week (intermediate frequency), and \u0026ge;\u0026thinsp;4 days/week (high frequency). For interaction analyses, pre-diagnosis NSAID use was classified similarly.\u003c/p\u003e\n\u003ch3\u003eCovariates and outcomes\u003c/h3\u003e\n\u003cp\u003eCovariates were extracted from the NHIS and KCCR databases. Sociodemographic variables included age at diagnosis, income level (tertiles), and residential area (urban vs. rural). Clinicopathologic variables included cancer type (ovarian vs. fallopian tube), SEER stage (localized, regional, distant), and year of diagnosis (before vs. after July 1, 2016, the midpoint of the study period).\u003c/p\u003e \u003cp\u003ePatients were categorized according to the primary treatment strategy: upfront surgery (primary debulking surgery, PDS) or neoadjuvant chemotherapy (NAC). Upfront surgery was defined as the first surgical intervention at diagnosis, encompassing staging procedures for localized/regional disease and primary debulking surgery for advanced disease. The NAC group included patients who received systemic chemotherapy prior to surgery, whereas those who received chemotherapy alone without subsequent surgery were excluded. Oher treatment-related variables included carboplatin use and cycles, bevacizumab use, ultra-extended procedures, and intensive care unit (ICU) admission within 1 month postoperatively. Ultra-extended procedures were defined as resections involving extra-gynecologic organs (e.g., bowel, liver, diaphragm, or spleen) within 6 months before or after the cancer diagnosis. ICU admission was defined as any intensive care unit stay occurring within 1 month after the index surgery (including the day of surgery).\u003c/p\u003e \u003cp\u003eComorbidities, such as hypertension, type 2 diabetes, dyslipidemia, chronic obstructive pulmonary disease (COPD), ischemic heart disease, ischemic stroke, were identified using ICD-10 diagnosis codes combined with relevant prescription records prior to cancer diagnosis. Specifically, type 2 diabetes was defined as E11\u0026ndash;E14 with antidiabetic medications, hypertension as I10\u0026ndash;I13 or I15 with antihypertensive medications, and dyslipidemia as E78 with anti-hyperlipidemic medications. COPD, ischemic heart disease, and ischemic stroke were defined using ICD-10 codes J41\u0026ndash;J44, I20\u0026ndash;I25, and I63\u0026ndash;I64, respectively. Overall comorbidity burden was quantified using the Charlson Comorbidity Index (CCI) based on ICD-10 codes according to the Quan adaptation.\u003c/p\u003e \u003cp\u003eThe primary outcome was all-cause mortality, identified through death certificate data provided by Statistics Korea. Follow-up was defined from the date of diagnosis until the date of death or December 31, 2020, whichever came first.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eBaseline characteristics were summarized as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) for continuous variables and as frequencies with percentages for categorical variables. Group differences were assessed using Student\u0026rsquo;s t-tests or chi-square tests. Comparisons among three frequency groups were performed using analysis of variance (ANOVA) or chi-square tests as appropriate.\u003c/p\u003e \u003cp\u003eHazard ratios (HRs) with 95% confidence intervals (CIs) for all-cause mortality were estimated using Cox proportional hazards models. A series of models with progressive adjustment for potential confounders was constructed. The fully adjusted model (Model 7) included age at diagnosis, SEER stage, income, residence, year of diagnosis, primary treatment strategy (NAC vs. PDS), standard surgery and chemotherapy, chemotherapy cycles, bevacizumab use, ultra-extended procedures, ICU admission, aspirin and acetaminophen use, comorbidities (diabetes, hypertension, dyslipidemia, COPD, ischemic heart disease, stroke), and cancer type.\u003c/p\u003e \u003cp\u003eAnalyses were conducted to compare (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Only POST vs. PRE \u0026amp; POST NSAID users, and (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) post-diagnosis NSAID frequency groups. Subgroup analyses were performed according to clinical factors considered to reflect tumor burden, including SEER stage, primary treatment strategy (NAC vs. PDS), presence of ultra-extended procedures, and ICU admission within 1 month. Because the proportion of NAC cases would be low in the localized stage, analyses stratified by SEER stage were restricted to regional and/or distant stages to allow a more appropriate comparison between NAC and PDS. Additional subgroup analyses were performed to compare post-diagnosis NSAID frequency groups between the NAC and PDS subgroups, and to evaluate NSAID frequency pre- and post-diagnosis within the PDS subgroup. Interaction terms were included to assess effect modification. All statistical analyses were conducted using SAS software, version 9.4 (SAS Institute, Cary, NC, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"Result","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics\u003c/h2\u003e \u003cp\u003eA total of 14,736 women were included in the study. Baseline characteristics are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The mean age at diagnosis was 54.1\u0026thinsp;\u0026plusmn;\u0026thinsp;11.7 years, and the majority of patients were diagnosed with ovarian cancer (95.1%). More than half of the cohort (51.6%) presented with distant-stage disease at diagnosis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eBaseline Characteristics of Patients with Ovarian or Fallopian Tube Cancer, Stratified by Nonsteroid Anti-Inflammatory Drug (NSAID) Use Timing and Frequency\u003c/b\u003e. Values are presented as mean with standard deviation (SD) for follow-up duration and number (percentage) for categorical variables. P-values were calculated using Student\u0026rsquo;s t-test or analysis of variance (ANOVA) for continuous variables and chi-square tests for categorical variables, as appropriate\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;14736)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eNSAID use\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eNSAID frequency\u003csup\u003ec\u003c/sup\u003e after diagnosis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOnly POST\u003csup\u003ea\u003c/sup\u003e (n\u0026thinsp;=\u0026thinsp;5104)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePRE \u0026amp; POST\u003csup\u003eb\u003c/sup\u003e (n\u0026thinsp;=\u0026thinsp;9632)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLow (n\u0026thinsp;=\u0026thinsp;10168)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate (n\u0026thinsp;=\u0026thinsp;3170)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHigh (n\u0026thinsp;=\u0026thinsp;1398)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNSAID frequency \u0026ndash; no (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow (\u0026lt;\u0026thinsp;1 day/week)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10168 (69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3930 (77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6238 (64.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediate (1\u0026ndash;3 day/week)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3170 (21.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e936 (18.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2234 (23.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh (\u0026ge;\u0026thinsp;4 day/week)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1398 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e238 (4.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1160 (12.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCancer type \u0026ndash; no (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOvary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14021 (95.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4917 (96.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9104 (94.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9684 (95.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2998 (94.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1339 (95.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFallopian tube\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e715 (4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e187 (3.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e528 (5.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e484 (4.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e172 (5.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e59 (4.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEER stage \u0026ndash; no (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocalized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3963 (26.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1566 (30.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2397 (24.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3011 (29.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e721 (22.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e231 (16.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3167 (21.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1109 (21.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2058 (21.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2272 (22.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e641 (20.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e254 (18.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7606 (51.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2429 (47.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5177 (53.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4885 (48.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1808 (57.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e913 (65.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD \u0026ndash; year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.1\u0026thinsp;\u0026plusmn;\u0026thinsp;11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.64\u0026thinsp;\u0026plusmn;\u0026thinsp;11.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.44\u0026thinsp;\u0026plusmn;\u0026thinsp;11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e52.93\u0026thinsp;\u0026plusmn;\u0026thinsp;11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e55.18\u0026thinsp;\u0026plusmn;\u0026thinsp;11.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e60.45\u0026thinsp;\u0026plusmn;\u0026thinsp;10.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;49 \u0026ndash; no (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5051 (34.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2140 (41.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2911 (30.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3842 (37.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e980 (30.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e229 (16.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;69 \u0026ndash; no (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8008 (54.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2614 (51.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5394 (56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5420 (53.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1761 (55.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e827 (59.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u0026ndash;79 \u0026ndash; no (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1677 (11.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e350 (6.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1327 (13.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e906 (8.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e429 (13.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e342 (24.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiagnosed date \u0026ndash; no (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2012-01\u0026thinsp;~\u0026thinsp;2016-07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7420 (50.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2658 (52.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4762 (49.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5059 (49.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1688 (53.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e673 (48.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2016-07\u0026thinsp;~\u0026thinsp;2019-12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7316 (49.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2446 (47.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4870 (50.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5109 (50.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1482 (46.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e725 (51.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSurgery \u0026ndash; no (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot done\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2178 (14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e701 (13.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1477 (15.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1436 (14.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e514 (16.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e228 (16.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDone before diagnosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e169 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (0.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e165 (1.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e118 (1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e34 (1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e17 (1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDone after diagnosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12389 (84.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4399 (86.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7990 (82.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8614 (84.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2622 (82.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1153 (82.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChemotherapy \u0026ndash; no (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot done\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2048 (13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e818 (16.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1230 (12.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1595 (15.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e334 (10.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e119 (8.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12688 (86.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4286 (83.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8402 (87.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8573 (84.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2836 (89.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1279 (91.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrimary treatment \u0026ndash; no (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeoadjuvant chemotherapy (NAC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3934 (26.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1220 (23.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2714 (28.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2472 (24.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e952 (30.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e510 (36.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpfront surgery (PDS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10802 (73.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3884 (76.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6918 (71.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7696 (75.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2218 (69.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e888 (63.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal Carboplatin cycle\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.85\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.69\u0026thinsp;\u0026plusmn;\u0026thinsp;2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.93\u0026thinsp;\u0026plusmn;\u0026thinsp;2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.74\u0026thinsp;\u0026plusmn;\u0026thinsp;2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.97\u0026thinsp;\u0026plusmn;\u0026thinsp;2.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5.34\u0026thinsp;\u0026plusmn;\u0026thinsp;2.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;3 \u0026ndash; no (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3239 (21.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1226 (24.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2013 (20.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2418 (23.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e622 (19.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e199 (14.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u0026ndash;6 \u0026ndash; no (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9734 (66.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3312 (64.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6422 (66.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6640 (65.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2147 (67.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e947 (67.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7 \u0026ndash; no (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1763 (11.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e566 (11.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1197 (12.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1110 (10.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e401 (12.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e252 (18.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBevacizumab use \u0026ndash; no (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1093(7.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e343 (6.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e750 (7.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e696 (6.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e251 (7.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e146 (10.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUltra-extended procedure \u0026ndash; no (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3157 (21.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1035 (20.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2122 (22.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1960 (19.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e779 (24.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e418 (29.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIntensive care unit (ICU) admission \u0026ndash; no (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3512 (23.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1163 (22.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2349 (24.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1961 (19.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e965 (30.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e586 (41.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocioeconomic status \u0026ndash; no (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow income level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2985 (20.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e943 (18.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2042 (21.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2012 (19.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e695 (21.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e278 (19.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7108 (48.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2570 (50.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4538 (47.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4922 (48.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1531 (48.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e655 (46.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.550\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedical aid \u0026ndash; no (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;3 tier\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4039 (27.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1305 (25.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2734 (28.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2736 (26.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e928 (29.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e375 (26.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u0026ndash;7 tier\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4974 (33.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1728 (33.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3246 (33.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3483 (34.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1036 (32.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e455 (32.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u0026ndash;10 tier\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5723 (38.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2071 (40.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3652 (37.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3949 (38.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1206 (38.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e568 (40.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidity \u0026ndash; no (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType 2 Diabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1805 (12.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e425 (8.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1380 (14.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1022 (10.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e441 (13.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e342 (24.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4523 (30.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1077 (21.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3446 (35.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2609 (25.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1078 (34.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e836 (59.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3204 (21.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e715 (14.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2489 (25.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1806 (17.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e767 (24.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e631 (45.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1923 (13.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e508 (9.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1415 (14.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1211 (11.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e455 (14.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e257 (18.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1372 (9.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e309 (6.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1063 (11.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e710 (6.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e337 (10.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e325 (23.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic stroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e365 (2.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79 (1.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e286 (2.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e154 (1.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e98 (3.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e113 (8.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean CCI\u003csup\u003ee\u003c/sup\u003e score\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.42\u0026thinsp;\u0026plusmn;\u0026thinsp;3.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.72\u0026thinsp;\u0026plusmn;\u0026thinsp;3.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e9.01\u0026thinsp;\u0026plusmn;\u0026thinsp;3.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAspirin use \u0026ndash; no (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1427 (9.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119 (2.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1308 (13.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e304 (2.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e385 (12.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e738 (52.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-diagnosis of ovarian/tubal cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1031 (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1031 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e229 (2.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e243 (7.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e559 (39.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-diagnosis of ovarian/tubal cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1128 (7.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119 (2.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1009 (10.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e108 (1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e302 (9.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e718 (51.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAcetaminophen use \u0026ndash; no (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10703 (72.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3175 (62.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7528 (78.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7332 (72.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2385 (75.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e986 (70.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-diagnosis of ovarian/tubal cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5659 (38.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1034 (20.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4625 (48.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3663 (36.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1377 (43.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e619 (44.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-diagnosis of ovarian/tubal cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8857 (60.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2787 (54.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6070 (63.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6158 (60.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1945 (61.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e754 (53.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ea\u003c/sup\u003e Only POST group was defined as patients prescribed NSAIDs within 6 months after diagnosis. \u003csup\u003eb\u003c/sup\u003e PRE \u0026amp; POST group was defined as patients prescribed NSAIDs both within 6 months before and after diagnosis. \u003csup\u003ec\u003c/sup\u003e NSAID frequency was categorized as low (\u0026lt;\u0026thinsp;1 day/week), intermediate (1\u0026ndash;3 days/week), or high (\u0026ge;\u0026thinsp;4 days/week). \u003csup\u003ed\u003c/sup\u003e COPD, chronic obstructive pulmonary disease; \u003csup\u003ee\u003c/sup\u003e CCI, Charlson Comorbidity Index\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e near here]\u003c/p\u003e \u003cp\u003eCompared with the Only POST group (n\u0026thinsp;=\u0026thinsp;5,104), patients in the PRE \u0026amp; POST group (n\u0026thinsp;=\u0026thinsp;9,632) were older (55.4 vs. 51.6 years, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and more frequently diagnosed at the distant stage (53.8% vs. 47.6%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The PRE \u0026amp; POST group also had a higher prevalence of comorbidities, including diabetes (14.3% vs. 8.3%), hypertension (35.8% vs. 21.1%), and dyslipidemia (25.8% vs. 14.0%), and a higher mean Charlson Comorbidity Index (CCI) score (7.8 vs. 6.7, all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). They were more likely to receive NAC (28.2% vs. 23.9%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and to undergo ultra-extended procedures (22.0% vs. 20.3%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.014).\u003c/p\u003e \u003cp\u003eWhen stratified by post-diagnosis NSAID frequency, patients in the high-frequency group (n\u0026thinsp;=\u0026thinsp;1,398) were older (60.5 vs. 55.2 vs. 52.9 years, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), more frequently diagnosed at the distant stage (65.3% vs. 57.0% vs. 48.0%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and had higher mean CCI scores (9.01 vs. 8.1 vs. 7.0, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared with the intermediate- and low-frequency groups (n\u0026thinsp;=\u0026thinsp;3,170 and n\u0026thinsp;=\u0026thinsp;10,168, respectively).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAssociation between NSAID use and all-cause mortality\u003c/h3\u003e\n\u003cp\u003eDuring a median follow-up of 2.91 years (interquartile range, 1.51\u0026ndash;5.03), 4,108 deaths (27.9%) were recorded. Results of the Cox proportional hazards models are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In unadjusted analyses (Model 1), the PRE \u0026amp; POST group and the high-frequency post-diagnosis group showed higher mortality risks compared with the Only POST and low-frequency groups, respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eHazard ratios for all-cause mortality according to NSAID use timing and frequency\u003c/b\u003e. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDeath\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDuration\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRate\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModel 1\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModel 2\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eModel 3\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eModel 4\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModel 5\u003csup\u003ej\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eModel 6\u003csup\u003ek\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003eModel 7\u003csup\u003el\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c12\" namest=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnly POST\u003csup\u003ea\u003c/sup\u003e (n\u0026thinsp;=\u0026thinsp;5104)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePRE \u0026amp; POST\u003csup\u003eb\u003c/sup\u003e (n\u0026thinsp;=\u0026thinsp;9632)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31779\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003cp\u003e(1.05\u0026ndash;1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003cp\u003e(0.93\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003cp\u003e(0.89\u0026ndash;1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003cp\u003e(0.90\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003cp\u003e(0.88\u0026ndash;1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003cp\u003e(0.88\u0026ndash;1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003cp\u003e(0.88\u0026ndash;1.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNSAID frequency\u003c/b\u003e\u003csup\u003e\u003cb\u003ec\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c12\" namest=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow (n\u0026thinsp;=\u0026thinsp;10168)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e1.00 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediate (n\u0026thinsp;=\u0026thinsp;3170)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10661\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003cp\u003e(1.17\u0026ndash;1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003cp\u003e(1.07\u0026ndash;1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003cp\u003e(1.01\u0026ndash;1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003cp\u003e(1.00-1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003cp\u003e(0.97\u0026ndash;1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003cp\u003e(0.97\u0026ndash;1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003cp\u003e(0.97\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh (n\u0026thinsp;=\u0026thinsp;1398)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e109.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003cp\u003e(1.29\u0026ndash;1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003cp\u003e(0.98\u0026ndash;1.191)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003cp\u003e(0.89\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003cp\u003e(0.91\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003cp\u003e(0.83\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003cp\u003e(0.83\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003cp\u003e(0.82\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003e\u003csup\u003ea\u003c/sup\u003e Only POST group was defined as patients prescribed NSAIDs within 6 months after diagnosis. \u003csup\u003eb\u003c/sup\u003e PRE \u0026amp; POST group was defined as patients prescribed NSAIDs both within 6 months before and after diagnosis. \u003csup\u003ec\u003c/sup\u003e NSAID frequency was categorized as low (\u0026lt;\u0026thinsp;1 day/week), intermediate (1\u0026ndash;3 days/week), or high (\u0026ge;\u0026thinsp;4 days/week). \u003csup\u003ed\u003c/sup\u003e Duration: Total follow-up time for the entire group (Unit: Person-Time). \u003csup\u003ee\u003c/sup\u003e Rate: Mortality rate per 1,000 person-time\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003e\u003csup\u003ef\u003c/sup\u003e Model 1 is the unadjusted crude model. \u003csup\u003eg\u003c/sup\u003e Model 2 was adjusted for age at diagnosis. \u003csup\u003eh\u003c/sup\u003e Model 3 was additionally adjusted for variables in Model 2 plus Surveillance, Epidemiology, and End Results (SEER) stage, low income level, and place of residence (urban or rural). \u003csup\u003ei\u003c/sup\u003e Model 4 was additionally adjusted for variables in Model 3 plus diagnosis date, receipt of standard treatment, use and cycles of carboplatin, and use of bevacizumab. \u003csup\u003ej\u003c/sup\u003e Model 5 was additionally adjusted for variables in Model 4 plus receipt of ultra-extended procedure, intensive care unit admission within 1 month, and use of acetaminophen and aspirin. \u003csup\u003ek\u003c/sup\u003e Model 6 was additionally adjusted for variables in Model 5 plus comorbidities (diabetes mellitus, hypertension, dyslipidemia, chronic obstructive pulmonary disease, ischemic heart disease, and stroke). \u003csup\u003el\u003c/sup\u003e Model 7 was the fully adjusted model, additionally including all variables in Model 6 plus cancer type.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e near here]\u003c/p\u003e \u003cp\u003eHowever, in the fully adjusted model (Model 7), there was no statistically difference in all-cause mortality between the PRE \u0026amp; POST and Only POST groups (adjusted HR, 0.94; 95% CI, 0.88\u0026ndash;1.01). Similarly, post-diagnosis NSAID frequency was not associated with mortality after full adjustment: compared with the low-frequency group, the adjusted HRs were 1.04 (95% CI, 0.97\u0026ndash;1.12) for the intermediate-frequency group and 0.92 (95% CI, 0.82\u0026ndash;1.04) for the high-frequency group. Thus, NSAID timing and frequency were not independently associated with mortality in the overall cohort.\u003c/p\u003e\n\u003ch3\u003eSubgroup analysis\u003c/h3\u003e\n\u003cp\u003eTo evaluate whether the association between NSAID use and mortality varied by tumor burden, subgroup analyses were performed according to SEER stage, primary treatment (NAC vs. PDS), ultra-extended procedures, and ICU admission within 1 month (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Supplementary Table\u0026nbsp;2).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eSubgroup analyses of the association between NSAID use and all-cause mortality according to primary treatment and Surveillance, Epidemiology, and End Results (SEER) stage.\u003c/b\u003e Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models. \u003cem\u003eP\u003c/em\u003e values for interaction were calculated by including cross-product terms in the multivariable models\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDeath\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDuration\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRate\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModel 1\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eModel 2\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eModel 3\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModel 4\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eModel 5\u003csup\u003ej\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eModel 6\u003csup\u003ek\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eModel 7\u003csup\u003el\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003eAll SEER stage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNAC\u003csup\u003em\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOnly Post\u003csup\u003ea\u003c/sup\u003e (n\u0026thinsp;=\u0026thinsp;1220)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e466\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e114.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePRE \u0026amp; POST\u003csup\u003eb\u003c/sup\u003e (n\u0026thinsp;=\u0026thinsp;2714)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e142.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003cp\u003e(1.10\u0026ndash;1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003cp\u003e(0.99\u0026ndash;1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003cp\u003e(0.95\u0026ndash;1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003cp\u003e(0.96\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003cp\u003e(0.93\u0026ndash;1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003cp\u003e(0.93\u0026ndash;1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003cp\u003e(0.93\u0026ndash;1.16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePDS\u003csup\u003en\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOnly Post (n\u0026thinsp;=\u0026thinsp;3884)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePRE \u0026amp; POST (n\u0026thinsp;=\u0026thinsp;6918)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1597\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23746\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003cp\u003e(0.95\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003cp\u003e(0.85-1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003cp\u003e(0.82\u0026ndash;0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003cp\u003e(0.83\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003cp\u003e(0.82\u0026ndash;0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003cp\u003e(0.82\u0026ndash;0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.89\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(0.82\u0026ndash;0.97)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for interaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegional and Distant SEER stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOnly Post (n\u0026thinsp;=\u0026thinsp;1018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e145.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePRE \u0026amp; POST (n\u0026thinsp;=\u0026thinsp;2370)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e170.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003cp\u003e(1.05\u0026ndash;1.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003cp\u003e(0.97\u0026ndash;1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003cp\u003e(0.95\u0026ndash;1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003cp\u003e(0.95\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003cp\u003e(0.93\u0026ndash;1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003cp\u003e(0.93\u0026ndash;1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003cp\u003e(0.94\u0026ndash;1.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOnly Post (n\u0026thinsp;=\u0026thinsp;2520)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePRE \u0026amp; POST (n\u0026thinsp;=\u0026thinsp;4865)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003cp\u003e(0.89\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003cp\u003e(0.83\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003cp\u003e(0.82\u0026ndash;0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003cp\u003e(0.84\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003cp\u003e(0.82\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003cp\u003e(0.82\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.90\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(0.82\u0026ndash;0.98)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for interaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.032\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDistant SEER stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOnly Post (n\u0026thinsp;=\u0026thinsp;816)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e171.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePRE \u0026amp; POST (n\u0026thinsp;=\u0026thinsp;2000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e195.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003cp\u003e(1.01\u0026ndash;1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003cp\u003e(0.95\u0026ndash;1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003cp\u003e(0.95\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003cp\u003e(0.95\u0026ndash;1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003cp\u003e(0.94\u0026ndash;1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003cp\u003e(0.94\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003cp\u003e(0.94\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOnly Post (n\u0026thinsp;=\u0026thinsp;1613)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e131.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePRE \u0026amp; POST (n\u0026thinsp;=\u0026thinsp;3177)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9599\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e123.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003cp\u003e(0.85\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003cp\u003e(0.80\u0026ndash;0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003cp\u003e(0.80\u0026ndash;0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003cp\u003e(0.82-1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003cp\u003e(0.81\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003cp\u003e(0.81\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.89\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(0.81\u0026ndash;0.98)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for interaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.029\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNAC vs. PDS by post-diagnosis NSAID frequency\u003c/b\u003e\u003csup\u003e\u003cb\u003ec\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eNAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow (n\u0026thinsp;=\u0026thinsp;2472)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e961\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e122.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIntermediate (n\u0026thinsp;=\u0026thinsp;952)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e143.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003cp\u003e(1.04\u0026ndash;1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003cp\u003e(1.00-1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003cp\u003e(0.92\u0026ndash;1.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003cp\u003e(0.91\u0026ndash;1.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e(0.89\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003cp\u003e(0.88\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003cp\u003e(0.88\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh (n\u0026thinsp;=\u0026thinsp;510)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e173.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003cp\u003e(1.21\u0026ndash;1.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003cp\u003e(0.99\u0026ndash;1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003cp\u003e(0.87\u0026ndash;1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003cp\u003e(0.89\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003cp\u003e(0.82\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003cp\u003e(0.82\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003cp\u003e(0.82\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow (n\u0026thinsp;=\u0026thinsp;7696)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1671\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIntermediate (n\u0026thinsp;=\u0026thinsp;2218)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.24\u003c/p\u003e \u003cp\u003e(1.13\u0026ndash;1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003cp\u003e(1.04\u0026ndash;1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003cp\u003e(1.00-1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003cp\u003e(1.00-1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003cp\u003e(0.97\u0026ndash;1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003cp\u003e(0.97\u0026ndash;1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003cp\u003e(0.97\u0026ndash;1.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh (n\u0026thinsp;=\u0026thinsp;888)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2916\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.27\u003c/p\u003e \u003cp\u003e(1.10\u0026ndash;1.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003cp\u003e(0.83\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003cp\u003e(0.80\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003cp\u003e(0.82\u0026ndash;1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003cp\u003e(0.73\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003cp\u003e(0.73\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.84\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(0.73\u0026ndash;0.98)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for interaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003e\u003csup\u003ea\u003c/sup\u003e Only POST group was defined as patients prescribed NSAIDs within 6 months after diagnosis. \u003csup\u003eb\u003c/sup\u003e PRE \u0026amp; POST group was defined as patients prescribed NSAIDs both within 6 months before and after diagnosis. \u003csup\u003ec\u003c/sup\u003e NSAID frequency was categorized as low (\u0026lt;\u0026thinsp;1 day/week), intermediate (1\u0026ndash;3 days/week), or high (\u0026ge;\u0026thinsp;4 days/week). \u003csup\u003ed\u003c/sup\u003e Duration: Total follow-up time for the entire group (Unit: Person-Time). \u003csup\u003ee\u003c/sup\u003e Rate: Mortality rate per 1,000 person-time\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003e\u003csup\u003ef\u003c/sup\u003e Model 1 is the unadjusted crude model. \u003csup\u003eg\u003c/sup\u003e Model 2 was adjusted for age at diagnosis. \u003csup\u003eh\u003c/sup\u003e Model 3 was additionally adjusted for variables in Model 2 plus SEER stage, low income level, and place of residence (urban or rural). \u003csup\u003ei\u003c/sup\u003e Model 4 was additionally adjusted for variables in Model 3 plus diagnosis date, receipt of standard treatment, use and cycles of carboplatin, and use of bevacizumab. \u003csup\u003ej\u003c/sup\u003e Model 5 was additionally adjusted for variables in Model 4 plus receipt of ultra-extended procedure, intensive care unit admission within 1 month, and use of acetaminophen and aspirin. \u003csup\u003ek\u003c/sup\u003e Model 6 was additionally adjusted for variables in Model 5 plus comorbidities (diabetes mellitus, hypertension, dyslipidemia, chronic obstructive pulmonary disease, ischemic heart disease, and stroke). \u003csup\u003el\u003c/sup\u003e Model 7 was the fully adjusted model, additionally including all variables in Model 6 plus cancer type.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003e\u003csup\u003em\u003c/sup\u003e NAC, neoadjuvant chemotherapy; \u003csup\u003en\u003c/sup\u003e PDS, upfront surgery\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e near here]\u003c/p\u003e \u003cp\u003eA statistically significant interaction was observed between NSAID exposure and primary treatment (NAC vs. PDS) (p for interaction\u0026thinsp;=\u0026thinsp;0.021), indicating that the association differed by treatment type. In the PDS group, the PRE \u0026amp; POST group had a significantly lower mortality risk compared with the Only POST group (adjusted HR\u0026thinsp;=\u0026thinsp;0.89; 95% CI, 0.82\u0026ndash;0.97). In addition, high-frequency NSAID users in the PDS group also showed a reduced mortality risk compared with low-frequency users (adjusted HR\u0026thinsp;=\u0026thinsp;0.84; 95% CI, 0.73\u0026ndash;0.98). When stratified by SEER stage, the protective association of PRE \u0026amp; POST NSAID use in the PDS subgroup remained consistent in both the local/regional stage and the distant stage, whereas no significant benefit was observed in the NAC subgroup. These findings are summarized in the forest plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the NAC group, no association was found between NSAID exposure timing and mortality (adjusted HR\u0026thinsp;=\u0026thinsp;1.04; 95% CI, 0.93\u0026ndash;1.16). Similarly, the association between NSAID use frequency and mortality did not reach statistical significance (adjusted HR\u0026thinsp;=\u0026thinsp;0.96; 95% CI, 0.82\u0026ndash;1.11). The interaction between post-diagnosis NSAID frequency and primary treatment type was not statistically (\u003cem\u003eP\u003c/em\u003e for interaction\u0026thinsp;=\u0026thinsp;0.203). No interaction was observed for SEER stage, ultra-extended procedures, or ICU admission within 1 month (Supplementary Table\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eBased on these findings, further interaction analyses were conducted within the PDS subgroup according to pre- and post-diagnosis NSAID frequency (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Among patients who did not use NSAIDs preoperatively, mortality did not differ across post-diagnosis frequency groups. In contrast, among PRE \u0026amp; POST users, those with intermediate/high pre-diagnosis NSAID use who either increased to or maintained high-frequency use after surgery showed lower mortality compared with those who decreased to low-frequency use (adjusted HR, 0.66; 95% CI, 0.44\u0026ndash;0.98 and adjusted HR, 0.68; 95% CI, 0.50\u0026ndash;0.92, respectively).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eSubgroup analyses of NSAID frequency before and after diagnosis in the Upfront surgery (PDS) subgroup.\u003c/b\u003e Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models. \u003cem\u003eP\u003c/em\u003e values for interaction were obtained by including cross-product terms in the multivariable models\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNSAID frequency\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDeath\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDuration\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRate\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eModel 1\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eModel 2\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eModel 3\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eModel 4\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eModel 5\u003csup\u003ej\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eModel 6\u003csup\u003ek\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eModel 7\u003csup\u003el\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-diagnosis frequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePost-diagnosis frequency\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eOnly POST\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;3884)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow (n\u0026thinsp;=\u0026thinsp;3068)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e669\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntermediate (n\u0026thinsp;=\u0026thinsp;668)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e79.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003cp\u003e(1.12\u0026ndash;1.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.29\u003c/p\u003e \u003cp\u003e(1.10\u0026ndash;1.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003cp\u003e(0.98\u0026ndash;1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003cp\u003e(1.00-1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003cp\u003e(0.97\u0026ndash;1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003cp\u003e(0.96\u0026ndash;1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003cp\u003e(0.97\u0026ndash;1.34)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh (n\u0026thinsp;=\u0026thinsp;148)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e81.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003cp\u003e(0.96\u0026ndash;1.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003cp\u003e(0.89\u0026ndash;1.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003cp\u003e(0.74\u0026ndash;1.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003cp\u003e(0.78\u0026ndash;1.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003cp\u003e(0.71\u0026ndash;1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003cp\u003e(0.73\u0026ndash;1.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003cp\u003e(0.73\u0026ndash;1.40)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003e\u003cb\u003ePRE \u0026amp; POST\u003c/b\u003e\u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;4997)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow (n\u0026thinsp;=\u0026thinsp;3772)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e56.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntermediate (n\u0026thinsp;=\u0026thinsp;1016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e66.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003cp\u003e(1.02\u0026ndash;1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003cp\u003e(0.99\u0026ndash;1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003cp\u003e(0.96\u0026ndash;1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003cp\u003e(0.95\u0026ndash;1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003cp\u003e(0.93\u0026ndash;1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003cp\u003e(0.94\u0026ndash;1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003cp\u003e(0.94\u0026ndash;1.25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh (n\u0026thinsp;=\u0026thinsp;209)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e639\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e67.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003cp\u003e(0.86\u0026ndash;1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003cp\u003e(0.79\u0026ndash;1.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003cp\u003e(0.68\u0026ndash;1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003cp\u003e(0.71\u0026ndash;1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003cp\u003e(0.64\u0026ndash;1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003cp\u003e(0.66\u0026ndash;1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003cp\u003e(0.66\u0026ndash;1.23)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1154)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow (n\u0026thinsp;=\u0026thinsp;683)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e88.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntermediate (n\u0026thinsp;=\u0026thinsp;354)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e89.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003cp\u003e(0.81\u0026ndash;1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003cp\u003e(0.74\u0026ndash;1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003cp\u003e(0.79\u0026ndash;1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003cp\u003e(0.80\u0026ndash;1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003cp\u003e(0.78\u0026ndash;1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003cp\u003e(0.78\u0026ndash;1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003cp\u003e(0.78\u0026ndash;1.25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh (n\u0026thinsp;=\u0026thinsp;117)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e80.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003cp\u003e(0.62\u0026ndash;1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003cp\u003e(0.52\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003cp\u003e(0.49\u0026ndash;1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003cp\u003e(0.50\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003cp\u003e(0.45\u0026ndash;1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003cp\u003e(0.44\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e0.66\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(0.44\u0026ndash;0.98)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;767)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow (n\u0026thinsp;=\u0026thinsp;173)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e122.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1 (Ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntermediate (n\u0026thinsp;=\u0026thinsp;180)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e98.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003cp\u003e(0.57\u0026ndash;1.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003cp\u003e(0.56\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003cp\u003e(0.59\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003cp\u003e(0.54\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003cp\u003e(0.53\u0026ndash;1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003cp\u003e(0.52\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003cp\u003e(0.52\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh (n\u0026thinsp;=\u0026thinsp;414)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003cp\u003e(0.51\u0026ndash;0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003cp\u003e(0.50\u0026ndash;0.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003cp\u003e(0.57\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003cp\u003e(0.54\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003cp\u003e(0.51\u0026ndash;0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003cp\u003e(0.50\u0026ndash;0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e0.68\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(0.50\u0026ndash;0.92)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for interaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.604\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.270\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e\u003csup\u003ea\u003c/sup\u003e Only POST group was defined as patients prescribed NSAIDs within 6 months after diagnosis. \u003csup\u003eb\u003c/sup\u003e PRE \u0026amp; POST group was defined as patients prescribed NSAIDs both within 6 months before and after diagnosis. \u003csup\u003ec\u003c/sup\u003e NSAID frequency was categorized as low (\u0026lt;\u0026thinsp;1 day/week), intermediate (1\u0026ndash;3 days/week), or high (\u0026ge;\u0026thinsp;4 days/week). \u003csup\u003ed\u003c/sup\u003e Duration: Total follow-up time for the entire group (Unit: Person-Time). \u003csup\u003ee\u003c/sup\u003e Rate: Mortality rate per 1,000 person-time.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e\u003csup\u003ef\u003c/sup\u003e Model 1 is the unadjusted crude model. \u003csup\u003eg\u003c/sup\u003e Model 2 was adjusted for age at diagnosis. \u003csup\u003eh\u003c/sup\u003e Model 3 was additionally adjusted for variables in Model 2 plus SEER stage, low income level, and place of residence (urban or rural). \u003csup\u003ei\u003c/sup\u003e Model 4 was additionally adjusted for variables in Model 3 plus diagnosis date, receipt of standard treatment, use and cycles of carboplatin, and use of bevacizumab. \u003csup\u003ej\u003c/sup\u003e Model 5 was additionally adjusted for variables in Model 4 plus receipt of ultra-extended procedure, intensive care unit admission within 1 month, and use of acetaminophen and aspirin. \u003csup\u003ek\u003c/sup\u003e Model 6 was additionally adjusted for variables in Model 5 plus comorbidities (diabetes mellitus, hypertension, dyslipidemia, chronic obstructive pulmonary disease, ischemic heart disease, and stroke). \u003csup\u003el\u003c/sup\u003e Model 7 was the fully adjusted model, additionally including all variables in Model 6 plus cancer type.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e near here]\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this nationwide cohort study, peri-diagnostic NSAID use and frequency were not associated with reduced mortality in the overall population of patients with epithelial ovarian cancer. Clinically, long-term or frequent NSAID users are likely to have adverse prognostic factors such as chronic pain or advanced disease. After adjusting for these clinical variables, NSAID use was not found to be an independent predictor of mortality in most settings.\u003c/p\u003e \u003cp\u003eThe most notable finding of this study was that sustained NSAID use was associated with reduced mortality among patients who underwent upfront surgery. In this subgroup, patients who used NSAIDs both before and after diagnosis (PRE \u0026amp; POST) had an approximately 11% lower mortality risk compared with those who used NSAIDs only after diagnosis (Only POST). Moreover, high-frequency users had a 16% lower mortality risk compared with low-frequency users. Detailed analyses further indicated that reducing NSAID use after upfront surgery was associated with increased mortality, whereas maintaining or escalating high-frequency use conferred a survival benefit.\u003c/p\u003e \u003cp\u003eThis effect may be explained by immunologic changes in the tumor microenvironment induced by upfront surgery. Cytoreductive surgery reduces tumor burden, leading to decreased circulating regulatory T cells and improved CD8⁺ T-cell function, thereby reversing immunosuppression (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Surgical cytoreduction also reduces myeloid-derived suppressor cells (MDSCs) (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), fostering a more immunologically \u0026ldquo;hot\u0026rdquo; environment.\u003c/p\u003e \u003cp\u003ePGE₂ promotes an immunosuppressive microenvironment, dampening tumor-infiltrating lymphocytes (TILs) and T-cell activation, thus reinforcing a \u0026ldquo;cold\u0026rdquo; tumor phenotype (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). NSAIDs inhibit the COX-2/PGE₂ pathway, potentially alleviating immunosuppression and enhancing T-cell infiltration and activation within the tumor microenvironment (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). This effect may be amplified in the more favorable immune milieu created by PDS.\u003c/p\u003e \u003cp\u003eIn contrast, patients receiving NAC typically harbor a high tumor burden, a state characterized by T-cell exhaustion, increased MDSCs, and accumulation of regulatory T cells (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Residual tumors surviving chemotherapy are more likely to represent chemo-resistant, immunologically \u0026ldquo;cold\u0026rdquo; phenotypes (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), limiting the remodeling effect of NSAIDs even after interval debulking surgery (IDS).\u003c/p\u003e \u003cp\u003eAnother explanation for the benefit of continuous NSAID use in the upfront subgroup may relate to the acute inflammatory response induced by surgery. Surgery can trigger an inflammatory storm and platelet-mediated dissemination (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e), which may facilitate tumor growth and micro-metastasis. Preoperative NSAID use could attenuate this inflammatory surge and platelet-driven metastasis, thereby improving survival outcomes.\u003c/p\u003e \u003cp\u003ePrevious prospective studies, including the Australian Ovarian Cancer Prognosis and Lifestyle (OPAL) study (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) and a U.S. cohort study (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), demonstrated a survival benefit from NSAID use in ovarian cancer. Differences between our results and these studies may reflect variations in study design (prospective vs. retrospective), racial/ethnic differences (Asian vs. Western populations), biological heterogeneity of ovarian cancer, and methods of measuring NSAID use (prescription claims vs. self-reported surveys). Clear cell histology, more prevalent in Asian populations (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), has been reported to exhibit distinct TMEs (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), which could contribute to the limited immunomodulatory effects of NSAIDs in our population.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, as a prescription-based retrospective cohort, it did not account for over-the-counter NSAID use. Second, the observed increase in mortality among patients who discontinued NSAID use postoperatively may have been due to clinical deterioration (e.g., postoperative complications, renal failure) rather than NSAID discontinuation itself, introducing potential selection bias. Also, potential residual confounding (e.g., indication bias for NSAID use such as chronic pain, cardiovascular disease) cannot be fully excluded. Furthermore, the reliance on claims data precluded assessment of oncologic outcomes such as recurrence, progression-free survival (PFS), and cancer-specific survival, as well as cause-specific mortality. Finally, detailed molecular and pathological data (e.g., cell type, genetic mutations) were not available.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, while NSAID use was not associated with improved survival in the overall ovarian cancer cohort, continuous NSAID use was associated with reduced mortality among patients undergoing upfront surgery. Our findings highlight the potential of NSAIDs as a precision adjuvant strategy, effective specifically in patients undergoing upfront surgery where the immune milieu is conducive to immunomodulation. Although no randomized clinical trials have yet demonstrated a survival advantage with NSAID use in ovarian cancer (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), our findings highlight a potential benefit in selected patient groups. Future prospective studies in carefully stratified populations are warranted to validate these findings and further elucidate the role of NSAIDs as adjunctive therapy in ovarian cancer.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eANOVA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAnalysis of variance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCharlson Comorbidity Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOPD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChronic obstructive pulmonary disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOX\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCyclooxygenase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOX-2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCyclooxygenase-2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCPLD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCancer Public Library Database\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eC-reactive protein\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHIRA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHealth Insurance Review \u0026amp; Assessment Service\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHazard ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHNSCC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHead and neck squamous cell carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICD-10\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational Classification of Diseases, 10th Revision\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntensive care unit\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIDS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterval debulking surgery\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIL-8\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterleukin-8\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKCCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKorea Central Cancer Registry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eK-Cure\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKorean Clinical Data Utilization Network for Research Excellence\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKNCI DB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKorea National Cancer Incidence Database\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMDSC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMyeloid-derived suppressor cell\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNAC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNeoadjuvant chemotherapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNHID\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Health Information Database\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNHIRD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Health Insurance Research Database\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNHIS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Health Insurance Service\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNSAID\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNonsteroidal anti-inflammatory drug\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOPAL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAustralian Ovarian Cancer Prognosis and Lifestyle\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePDS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePrimary debulking surgery\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePFS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProgression-free survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePGE₂\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProstaglandin E₂\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSEER\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSurveillance, Epidemiology, and End Results\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTIL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTumor-infiltrating lymphocyte\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTME\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTumor microenvironment\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTNF-α\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTumor necrosis factor-alpha\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVEGF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVascular endothelial growth factor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eHuman Ethics and Consent to Participate declarations:\u0026nbsp;\u003c/strong\u003eThe study was conducted in accordance with the Declaration of Helsinki and was approved by the Institutional Review Board (IRB) of Samsung Medical Center (IRB No. 2025-06-106). As de-identified secondary data were used, informed consent was waived.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e: not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThis study used data from the Korean Clinical Data Utilization Network for Research Excellence (K-CURE). These data are not publicly available due to data use agreements and national privacy regulations. Qualified researchers may request access through the K-CURE data access committee with appropriate institutional and ethical approvals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003einterests\u003c/strong\u003e: The authors declare that they have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding sources:\u003c/strong\u003e This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eKH and YYL conceptualized the study. SYK and KH were responsible for data curation. SL, JYH and JHS performed the formal analysis and developed the methodology. JYH, JHS and YEC conducted the investigation. SYK was responsible for the software and validation of the data. SL and YEC were responsible for visualization. SYK, KH, and YYL provided the necessary resources for the study. KH, YYL served as the project administrator and supervised the overall research. SL and JYH were major contributors in writing the original draft. KH, YYL reviewed and edited the final manuscript. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e The authors used an artificial intelligence\u0026ndash;based language tool for limited language editing. The authors reviewed and take full responsibility for all content.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHuang J, Chan WC, Ngai CH, Lok V, Zhang L, Lucero-Prisno DE 3. rd, Worldwide Burden, Risk Factors, and Temporal Trends of Ovarian Cancer: A Global Study. Cancers (Basel). 2022;14(9).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNational Cancer Institute SEaERP. Cancer Stat Facts: Ovarian Cancer 2025 [Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://seer.cancer.gov/statfacts/html/ovary.html\u003c/span\u003e\u003cspan address=\"https://seer.cancer.gov/statfacts/html/ovary.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFu X, Wang Q, Du H, Hao H. CXCL8 and the peritoneal metastasis of ovarian and gastric cancer. Front Immunol. 2023;14:1159061.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMei S, Chen X, Wang K, Chen Y. Tumor microenvironment in ovarian cancer peritoneal metastasis. Cancer Cell Int. 2023;23(1):11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFord CE, Werner B, Hacker NF, Warton K. The untapped potential of ascites in ovarian cancer research and treatment. Br J Cancer. 2020;123(1):9\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePoole EM, Lee IM, Ridker PM, Buring JE, Hankinson SE, Tworoger SS. A prospective study of circulating C-reactive protein, interleukin-6, and tumor necrosis factor alpha receptor 2 levels and risk of ovarian cancer. Am J Epidemiol. 2013;178(8):1256\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eForget P, Bentin C, Machiels JP, Berliere M, Coulie PG, De Kock M. Intraoperative use of ketorolac or diclofenac is associated with improved disease-free survival and overall survival in conservative breast cancer surgery. Br J Anaesth. 2014;113(Suppl 1):i82\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBastiaannet E, Sampieri K, Dekkers OM, de Craen AJ, van Herk-Sukel MP, Lemmens V, et al. Use of aspirin postdiagnosis improves survival for colon cancer patients. Br J Cancer. 2012;106(9):1564\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChan AT, Ogino S, Fuchs CS. Aspirin use and survival after diagnosis of colorectal cancer. JAMA. 2009;302(6):649\u0026ndash;58.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHua X, Phipps AI, Burnett-Hartman AN, Adams SV, Hardikar S, Cohen SA, et al. Timing of Aspirin and Other Nonsteroidal Anti-Inflammatory Drug Use Among Patients With Colorectal Cancer in Relation to Tumor Markers and Survival. J Clin Oncol. 2017;35(24):2806\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHedberg ML, Peyser ND, Bauman JE, Gooding WE, Li H, Bhola NE, et al. Use of nonsteroidal anti-inflammatory drugs predicts improved patient survival for PIK3CA-altered head and neck cancer. J Exp Med. 2019;216(2):419\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStone RL, Nick AM, McNeish IA, Balkwill F, Han HD, Bottsford-Miller J, et al. Paraneoplastic thrombocytosis in ovarian cancer. N Engl J Med. 2012;366(7):610\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReyners AKL, de Munck L, Erdkamp FLG, Smit WM, Hoekman K, Lalisang RI, et al. A randomized phase II study investigating the addition of the specific COX-2 inhibitor celecoxib to docetaxel plus carboplatin as first-line chemotherapy for stage IC to IV epithelial ovarian cancer, Fallopian tube or primary peritoneal carcinomas: the DoCaCel study. Ann Oncol. 2012;23(11):2896\u0026ndash;902.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRicciotti E, FitzGerald GA. Prostaglandins and inflammation. Arterioscler Thromb Vasc Biol. 2011;31(5):986\u0026ndash;1000.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNakanishi M, Rosenberg DW. Multifaceted roles of PGE2 in inflammation and cancer. Semin Immunopathol. 2013;35(2):123\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlgra AM, Rothwell PM. Effects of regular aspirin on long-term cancer incidence and metastasis: a systematic comparison of evidence from observational studies versus randomised trials. Lancet Oncol. 2012;13(5):518\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaug AJ, Stoer N, Langseth H, Siafarikas F, Botteri E, Fortner RT, et al. Non-steroidal anti-inflammatory medication use and endometrial cancer survival: A population-based Norwegian cohort study. Int J Cancer. 2025;157(2):277\u0026ndash;87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMerritt MA, Rice MS, Barnard ME, Hankinson SE, Matulonis UA, Poole EM, et al. Pre-diagnosis and post-diagnosis use of common analgesics and ovarian cancer prognosis (NHS/NHSII): a cohort study. Lancet Oncol. 2018;19(8):1107\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMajidi A, Na R, Jordan SJ, DeFazio A, Obermair A, Friedlander M, et al. Common analgesics and ovarian cancer survival: the Ovarian cancer Prognosis And Lifestyle (OPAL) Study. J Natl Cancer Inst. 2023;115(5):570\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerdoodt F, Dehlendorff C, Friis S, Kjaer SK. Non-aspirin NSAID use and ovarian cancer mortality. Gynecol Oncol. 2018;150(2):331\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerdoodt F, Kjaer SK, Dehlendorff C, Friis S. Aspirin use and ovarian cancer mortality in a Danish nationwide cohort study. Br J Cancer. 2018;118(4):611\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArter ZL, Desmond D, Berenberg JL, Killeen JL, Bunch K, Merritt MA. Epithelial ovarian cancer survival by race and ethnicity in an equal-access healthcare population. Br J Cancer. 2024;130(1):108\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee AW, Navajas EE, Liu L. Clear differences in ovarian cancer incidence and trends by ethnicity among Asian Americans. Cancer Epidemiol. 2019;61:142\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBandera EV, Lee VS, Rodriguez-Rodriguez L, Powell CB, Kushi LH. Racial/Ethnic Disparities in Ovarian Cancer Treatment and Survival. Clin Cancer Res. 2016;22(23):5909\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNapoletano C, Bellati F, Landi R, Pauselli S, Marchetti C, Visconti V, et al. Ovarian cancer cytoreduction induces changes in T cell population subsets reducing immunosuppression. J Cell Mol Med. 2010;14(12):2748\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePredina JD, Kapoor V, Judy BF, Cheng G, Fridlender ZG, Albelda SM, et al. Cytoreduction surgery reduces systemic myeloid suppressor cell populations and restores intratumoral immunotherapy effectiveness. J Hematol Oncol. 2012;5:34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOuYang LY, Wu XJ, Ye SB, Zhang RX, Li ZL, Liao W, et al. Tumor-induced myeloid-derived suppressor cells promote tumor progression through oxidative metabolism in human colorectal cancer. J Transl Med. 2015;13:47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKalinski P. Regulation of immune responses by prostaglandin E2. J Immunol. 2012;188(1):21\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorotti M, Grimm AJ, Hope HC, Arnaud M, Desbuisson M, Rayroux N, et al. PGE(2) inhibits TIL expansion by disrupting IL-2 signalling and mitochondrial function. Nature. 2024;629(8011):426\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZelenay S, van der Veen AG, Bottcher JP, Snelgrove KJ, Rogers N, Acton SE, et al. Cyclooxygenase-Dependent Tumor Growth through Evasion of Immunity. Cell. 2015;162(6):1257\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSkourti E, Seip K, Mensali N, Jabeen S, Juell S, Oynebraten I, et al. Chemoresistant tumor cell secretome potentiates immune suppression in triple negative breast cancer. Breast Cancer Res. 2025;27(1):131.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRupp L, Dietsche I, Kiessler M, Sommer U, Muckenhuber A, Steiger K, et al. Neoadjuvant chemotherapy is associated with suppression of the B cell-centered immune landscape in pancreatic ductal adenocarcinoma. Front Immunol. 2024;15:1378190.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKwak SB, Kim SJ, Kim J, Kang YL, Ko CW, Kim I, et al. Tumor regionalization after surgery: Roles of the tumor microenvironment and neutrophil extracellular traps. Exp Mol Med. 2022;54(6):720\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang M, He Y, Sun X, Li Q, Wang W, Zhao A, et al. A high M1/M2 ratio of tumor-associated macrophages is associated with extended survival in ovarian cancer patients. J Ovarian Res. 2014;7:19.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGupta R, Cristea M, Frankel P, Ruel C, Chen C, Wang Y, et al. Randomized trial of oral cyclophosphamide versus oral cyclophosphamide with celecoxib for recurrent epithelial ovarian, fallopian tube, and primary peritoneal cancer. Cancer Treat Res Commun. 2019;21:100155.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-ovarian-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jovr","sideBox":"Learn more about [Journal of Ovarian Research](http://ovarianresearch.biomedcentral.com)","snPcode":"13048","submissionUrl":"https://submission.nature.com/new-submission/13048/3","title":"Journal of Ovarian Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"ovarian cancer, nonsteroidal anti-inflammatory drugs (NSAIDs), upfront surgery, tumor microenvironments, nationwide cohort","lastPublishedDoi":"10.21203/rs.3.rs-9233171/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9233171/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eInflammation influences the progression and treatment resistance of epithelial ovarian cancer, and nonsteroidal anti-inflammatory drugs (NSAIDs) have shown anticancer effects in other malignancies; however, their impact on ovarian cancer survival, particularly in Asian populations, remains unclear. Using the Korean Nationwide Cancer Public Library Database, we identified 14,736 women newly diagnosed with ovarian or fallopian tube cancer between 2012 and 2019. NSAID use was classified as Only POST (within 6 months after diagnosis only) or PRE \u0026amp; POST (both before and after diagnosis), and NSAID frequency was categorized as low (\u0026lt;\u0026thinsp;1 day/week), intermediate (1\u0026ndash;3 days/week), or high (\u0026ge;\u0026thinsp;4 days/week). The primary outcome was all-cause mortality, analyzed with Cox proportional hazards models adjusting for demographic, clinical, and treatment-related factors, with subgroup analyses performed by primary treatment strategy (upfront surgery vs. neoadjuvant chemotherapy).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eDuring a median follow-up of 2.91 years, 4,108 deaths (27.9%) occurred. In the fully adjusted model, NSAID timing (PRE \u0026amp; POST: HR 0.94, 95% CI 0.88\u0026ndash;1.01) and post-diagnosis frequency (high: HR 0.92, 95% CI 0.82\u0026ndash;1.04) were not significantly associated with mortality in the overall cohort. However, in the upfront subgroup, PRE \u0026amp; POST users (HR 0.89, 95% CI 0.82\u0026ndash;0.97) and high-frequency users (HR 0.84, 95% CI 0.73\u0026ndash;0.98) had significantly lower mortality compared with their counterparts. No associations were found in the neoadjuvant chemotherapy subgroup.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eNSAID use was not associated with survival overall but was linked to reduced mortality after upfront surgery, suggesting potential benefit when combined with cytoreductive surgery.\u003c/p\u003e","manuscriptTitle":"Perioperative NSAID use and survival after upfront cytoreductive surgery for ovarian cancer: Nationwide cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-19 07:51:36","doi":"10.21203/rs.3.rs-9233171/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"170081062941982273866323249862912078698","date":"2026-05-19T05:18:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"74494163655189215990345915223808098711","date":"2026-05-04T19:45:39+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-08T09:55:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-30T04:44:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-30T04:44:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Ovarian Research","date":"2026-03-26T10:49:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-ovarian-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jovr","sideBox":"Learn more about [Journal of Ovarian Research](http://ovarianresearch.biomedcentral.com)","snPcode":"13048","submissionUrl":"https://submission.nature.com/new-submission/13048/3","title":"Journal of Ovarian Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cfb8eeb2-d900-414f-a11b-baf5a2212c64","owner":[],"postedDate":"April 19th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"170081062941982273866323249862912078698","date":"2026-05-19T05:18:47+00:00","index":50,"fulltext":""},{"type":"reviewerAgreed","content":"74494163655189215990345915223808098711","date":"2026-05-04T19:45:39+00:00","index":42,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-19T07:51:36+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-19 07:51:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9233171","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9233171","identity":"rs-9233171","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}