Prognosis and adjuvant chemotherapy for patients with malignant peritoneal cytology in early-stage non-endometrioid endometrial cancer

Prognosis and adjuvant chemotherapy for patients with malignant peritoneal cytology in early-stage non-endometrioid endometrial cancer | 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 Prognosis and adjuvant chemotherapy for patients with malignant peritoneal cytology in early-stage non-endometrioid endometrial cancer Xinyue Tang, Na Li, Yuanjing Hu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3214955/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective To investigate the influence of malignant peritoneal cytology (MPC) on the prognosis of early-stage patients with endometrial clear cell carcinoma(CCC) and serous carcinoma(SC), and the value of chemotherapy in their treatment. Methods A retrospective observational cohort study was conducted by querying the National Cancer Institute’s Surveillance, Epidemiology, and End Results Program from 2010 to 2019. Women with early-stage CCC and SC with available peritoneal cytology results were enrolled. Propensity score matching(PSM) and propensity score inverse probability of treatment weighting (IPTW) was used to balance the measured covariates in each sub-cohort. Results A total of 3,616 eligible patients were included, and 368 patients had MPC (10.2%). Women with MPC were more likely to receive postoperative chemotherapy (OR 2.033;95%CI 1.589–2.602). In PSM model, MPC had worse overall survival(OS) and cancer-specific survival (CSS) (All,p < 0.001). The 5-year OS rates were 56.5% for women with MPC and 74.4% for those with negative peritoneal cytology, and the 5-year CSS rates were 60.8% versus 80.0%(All, p < 0.0001). In the subgroup analyses, MPC was associated with decreased OS and CSS in serous, clear cell histology group, and stage IA cases(All,p < 0.001), but not for stage IB or stage II disease. In multivariate analysis, chemotherapy improved the prognosis of patients with MPC(OS:p = 0.005; CSS:p = 0.010). Additionally, in stage IA subgroup, chemotherapy improved survival outcomes in patients with MPC(OS:P = 0.025; CSS:P = 0.038), in NPC patients, however, chemotherapy was a good prognostic factor for OS (P = 0.001) but not for CSS(P = 0.300). Conclusion MPC was a prognostic factor for decreased survival in early-stage endometrial CCC and SC, and those with MPC could further benefit from chemotherapy. Clear cell endometrial cancer Serous endometrial cancer Peritoneal cytology Survival outcomes Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Endometrial cancer (EC) is one of most common gynecological cancers, with 66,200 estimated new cases in the United States in 2023( 1 ). Traditionally, EC is classified as endometrioid and non-endometrioid cancer, and the latter account for about 20% of EC characterized by a higher rate of extra-uterine spread and worse prognosis( 2 ). Of note, clear cell cancer and serous cancer are the major non-endometrioid endometrial cancer, together accounting for about 75% of non-endometrioid cancer( 2 – 4 ). Endometrial cancer is commonly diagnosed at an early stage. The standard surgical treatment approach for patients with apparent early-stage disease is hysterectomy, salpingo-oophorectomy, and additional lymphadenectomy, which allows primary tumor removal and identification of major prognostic factors (e.g., myometrial invasion, lymph vascular space invasion) for tailoring postoperative adjuvant therapy( 5 ). The presence of tumor cells seen in the peritoneal cytologic specimen at hysterectomy, known as malignant peritoneal cytology, is another possible risk factor considered as an indication of adjuvant therapy. In the National Comprehensive Cancer Network® (NCCN®) guidelines, noninvasive stage IA CCC and SC are stratified according to peritoneal cytology results for tailored adjuvant treatment strategies( 6 ). Malignant peritoneal cytology can be seen in approximately 5% of early-stage endometrial cancer, and the incidence seems higher in the non-endometrioid histological type( 7 – 9 ). Multiple studies have suggested that malignant peritoneal cytology is an adverse prognostic factor for survival outcome in early-stage EC, but studies specifically evaluating early-stage non-endometrioid types are limited due to its rarity( 2 , 7 – 13 ). The objective of this study was to examine the association between malignant peritoneal cytology and survival in women with early-stage endometrial clear cell carcinoma and serous carcinoma, and to explore whether malignant peritoneal cytology may be used as an indication to guide the use of chemotherapy in early-stage CCC and SC. 2. Materials and methods 2.1 Data Source The Surveillance, Epidemiology, and End Results (SEER) database, a population-based cancer registry established by the National Cancer Institute (NCI), was searched for the analysis( 14 ). Patient identification, data accumulation and entry, and rigorous quality control for the database are managed by registered trained personnel( 15 ). We obtained the information of patients diagnosed between 2010 and 2019 from the SEER∗ Stat version 8.4.0.1 ( https://seer.cancer.gov/seerstat/ ). 2.2 Study Population The International Classification of Diseases for Oncology, Third Edition (ICD-O-3) morphology codes “8310/3: Clear cell adenocarcinoma, NOS; 8441/3: Serous cystadenocarcinoma, NOS; 8460/3: Papillary serous cystadenocarcinoma; 8461/3: Serous surface papillary carcinoma” was used to identify endometrial clear cell carcinoma (CCC) and serous carcinoma (SC) from patients with histologically confirmed primary endometrial cancer (ICD-O-3, C54.1). The American Joint Committee on Cancer staging classification schema was used for defining T stage. We gathered the following information: age at diagnosis, race, marital status, peritoneal cytology, tumor differentiation, stage, tumor size, hysterectomy type, para-aortic lymphadenectomy, pelvic lymphadenectomy, chemotherapy, radiotherapy, and survival data. Women with stage I-II (T1/N0/M0, T2/N0/M0) endometrial cancer with histologic confirmation who had available data on survival time and peritoneal cytology results from 2010 to 2019 were included. Exclusion criteria included non-CCC and non-SC, and no hysterectomy or unknown surgery type. 2.3 Outcome Measure Overall survival (OS) and cancer-specific survival (CSS) were assessed for outcome analysis. OS was considered as the time from diagnosis to death for any cause or to the last contact. CSS was defined as the time from diagnosis to death due to endometrial carcinoma. Women who had no survival event at the last follow-up were censored. 2.4 Statistical analyses The first step of the analysis was to identify the independent characteristics associated with malignant peritoneal cytology. Differences in the baseline characteristics were assessed with chi-square test for univariable analysis. All the significant covariates with a p-value < 0.05 on univariable analysis were entered in the binary logistic regression model, and effect size was expressed with an adjusted odds ratio (OR) and corresponding 95% confidence interval (CI). Hosmer-Lemeshow test was used to assess the goodness-of-fit in the final model, and a P > 0.05 was interpreted as a good-fit model. The second step of the analysis was to evaluate the survival effect of malignant peritoneal cytology in stage I-II endometrial CCC and SC. The propensity score was calculated based on the covariates age at diagnosis, race, marital status, tumor differentiation, stage, tumor size, hysterectomy type, para-aortic lymphadenectomy, pelvic lymphadenectomy, chemotherapy, radiotherapy to reduce the imbalance between the malignant and negative peritoneal cytology groups. Malignant peritoneal cytology cases were matched to negative peritoneal cytology group in a 1:4 ratio and a caliper width of 0.05 standard deviation (SD) was specified. Survival analysis was assessed with the Kaplan–Meier method, and the results were compared with the log-rank test. The Kaplan-Meier method was used to plot survival curves, and a Cox proportional hazard regression model was fitted to estimate hazard ratio (HR) with 95% confidence interval (CI) for malignant peritoneal cytology. Lastly, cox regression analyses were employed to identify whether adjuvant chemotherapy improved the outcome of endometrial CCC/SC patients with malignant peritoneal cytology by reporting the hazard ratios (HR) and 95% CI. In addition, we conducted multiple subgroup analyses to enhance the validity of this study. First, the effect of peritoneal cytology results on survival outcome was examined, stratified by histology (clear cell versus serous), and stage (stage IA, stage IB, stage II). Second, the effect of chemotherapy on the prognosis of women with stage IA was examined based on peritoneal cytology results (malignant versus negative). Propensity score inverse probability of treatment weighting (IPTW) was used to balance the measured covariates in each subcohort( 16 ). The Kaplan-Meier method was used to plot survival curves, and the survival analysis results were compared with the log-rank test. Statistical analyses were all performed with SPSS (version26.0, IBM Corporation, USA) and R software (version 4.2.1; http://www.R-project.org/ ). A two-sided p value < 0.05 was considered statistically significant. 3. Results 3.1 Patient population A total of 3,616 patients were eligible for incidence analysis (Fig. 1 ). Of those, malignant peritoneal cytology was reported in 368 (10.2%) women and the remaining 3,248 (89.8%) women had negative peritoneal cytology. Majority of women were 60–69 years (43.5%), white (71.1%), and married (50.3%). In terms of histopathology, most of patients were serous carcinoma (84.2%), poor differentiated or undifferentiated (67.7%), and IA stage (71.2%). Simple hysterectomy was performed in 90.7% of patients. Pelvic and para-aortic lymphadenectomy were performed in 88.9% and 55.9% cases, respectively. 47.6% of the included patients received radiotherapy, and more than half of patients received chemotherapy (60.6%). 3.2 Factors associated with malignant peritoneal cytology In the univariable and multivariable analysis (Table 1 ), race, marital status, and postoperative adjuvant chemotherapy were the factors associated with peritoneal cytology results (all p < 0.05). Blacks were more likely to have negative peritoneal cytology than whites (OR 0.565; 95%CI 0.406–0.787). Women in the malignant peritoneal cytology were more likely to receive postoperative adjuvant chemotherapy (OR 2.033; 95%CI 1.589–2.602). Table 1 Patient demographics per peritoneal cytology status (N = 3616). Characteristics Total = 3,616 (n,%) Negative ,n = 3,248 (n,%) Malignant ,n = 368 (n,%) P-value Adjusted OR (95% CI) P-value Age (year) 0.103 <50 26(0.7) 20(0.6) 6(1.6) 50–59 484(13.4) 427(13.1) 57(15.5) 60–69 1572(43.5) 1419(43.7) 153(41.6) 70–79 1146((31.7) 1038(32.0) 108(29.3) ≥ 80 388(10.7) 344(10.6) 44(12.0) Race 0.028 White 2572(71.1) 2287(70.4) 285(77.4) 1 Black 672(18.6) 625(19.2) 47(12.8) 0.565(0.406–0.787) 0.001 Asian or Pacific Islander 333(9.2) 299(9.2) 34(9.2) 0.888(0.608–1.296) 0.537 American Indian/Alaska Native 22(0.6) 21(0.6) 1(0.3) 0.417(0.055–3.142) 0.396 Unknown 17(0.5) 16(0.5) 1(0.3) 0.513(0.067–3.922) 0.520 Marital status 0.015 Married 1819(50.3) 1617(49.8) 202(54.9) 1 Divorced 404(11.2) 380(11.7) 24(6.5) 0.537(0.346–0.835) 0.006 Separated 50(1.4) 43(1.3) 7(1.9) 1.502(0.660–3.422) 0.332 Single (never married) 511(14.1) 454(14.0) 57(15.5) 1.156(0.838–1.595) 0.376 Unmarried or Domestic Partner 12(0.3) 9(0.3) 3(0.8) 2.353(0.626–8.848) 0.205 Widowed 640(17.7) 578(17.8) 62(16.8) 0.988(0.728–1.340) 0.937 Unknown 180(5.0) 167(5.1) 13(3.5) 0.661(0.368–1.188) 0.166 Histology type 0.332 Clear cell carcinoma 572(15.8) 521(16.0) 51(13.9) Serous carcinoma 3044(84.2) 2727(84.0) 317(86.1) Tumor differentiation 0.255 Well differentiated 65(1.8) 60(1.8) 5(1.4) Moderately differentiated 109(3.0) 92(2.8) 17(4.6) Poorly differentiated or undifferentiated 2448(67.7) 2200(67.7) 248(67.4) Unknown 994(27.5) 896(27.6) 98(26.6) Stage 0.122 IA 2575(71.2) 2330(71.7) 245(66.6) IB 538(14.9) 477(14.7) 61(16.6) I NOS 97(2.7) 88(2.7) 9(2.4) II 406(11.2) 353(10.9) 53(14.4) Tumor size (cm) 0.196 ≤ 2.0 899(24.9) 823(25.3) 76(20.7) 2.1−4.0 1011(28.0) 908(28.0) 103(28.0) 4.1−6.0 552(15.3) 483(14.9) 69(18.8) 6.1−8.0 166(4.6) 146(4.5) 20(5.4) >8 98(2.7) 86(2.6) 12(3.3) Unknown 890(24.6) 802(24.7) 88(23.9) Hysterectomy type 0.599 Simple 3279(90.7) 2952(90.9) 327(88.9) Supracervical 22(0.6) 20(0.6) 2(0.5) Modified/radical 181(5.0) 159(4.9) 22(6.0) NOS 134(3.7) 117(3.6) 17(4.6) Para-aortic lymphadenectomy 0.919 No 1431(39.6) 1289(39.7) 142(38.6) Yes 2022(55.9) 1813(55.8) 209(56.8) Unknown 163(4.5) 146(4.5) 17(4.6) Pelvic lymphadenectomy 0.290 No 348(9.6) 305(9.4) 43(11.7) Yes 3213(88.9) 2895(89.1) 318(86.4) Unknown 55(1.5) 48(1.5) 7(1.9) Radiotherapy 0.272 Radioactive implants (includes brachytherapy) or radioisotopes 1216(33.6) 1088(33.5) 128(34.8) Beam radiation 332(9.2) 295(9.1) 37(10.1) Combination of beam with implants or isotopes 164(4.5) 151(4.6) 13(3.5) Radiation,NOS 10(0.3) 9(0.3) 1(0.3) No 93(2.6) 90(2.8) 3(0.8) Unknown 1801(49.8) 1615(49.7) 186(50.5) Chemotherapy < 0.001 No/Unknown 1426(39.4) 1331(41.0) 95(25.8) 1 Yes 2190(60.6) 1917(59.0) 273(74.2) 2.033(1.589–2.602) < 0.001 Abbreviations: NOS, not otherwise significant. Bold values indicate significance at p < 0.05. 3.3 Survival effect of malignant peritoneal cytology All of the 12 measured covariates were well-balanced after propensity score matching (PSM) ( Table S1 ). In the PSM model, 365 women with malignant peritoneal cytology were compared with 1406 women with negative peritoneal cytology for survival outcome analysis. The cox proportional hazard regression model showed that malignant peritoneal cytology was an independent risk prognostic factor for overall survival (OS) (Univariate: HR 2.028; 95%CI 1.650–2.492; p < 0.001. Multivariate: HR 2.200; 95%CI 1.781–2.718; p < 0.001). A similar association was observed for cancer-specific survival (CSS) (Univariate: HR 2.453; 95%CI 1.945–3.094; p < 0.001. Multivariate: HR 2.704; 95%CI 2.130–3.432; p < 0.001) ( Table S2 ). The 5-year OS rates were 56.5% for women with malignant peritoneal cytology and 74.4% for those with negative peritoneal cytology (p < 0.0001) (Fig. 2 A), and the 5-year CSS rates were 60.8% versus 80.0% (p < 0.0001) (Fig. 2 B). Malignant peritoneal cytology was a prognostic risk factor observed for the sub-cohorts of patients with CCC histology(OS: P < 0.001; CSS: P < 0.001)(Fig. 3 A; 3 B), SC histology (OS:P < 0.001; CSS: P < 0.001) (Fig. 3 C; 3 D), and stage IA(OS: P < 0.001; CSS: P < 0.001) (Fig. 3 E; 3 F). In contrast, peritoneal cytology was not associated with prognosis in the stage IB (OS: P = 0.366; CSS: P = 0.131) ( Figure S1 A;B ) and stage II (OS: P = 0.215; CSS: P = 0.100) ( Figure S1 C;D ) subgroups. 3.4 Significance of adjuvant chemotherapy in patients based on peritoneal cytology results The association between adjuvant chemotherapy and survival was examined among women with malignant peritoneal cytology (Table 2 ). According the multivariate cox regression analysis, after controlling for confounding factors, adjuvant chemotherapy as an independent prognostic factor could improve the survival of patients with malignant peritoneal cytology (OS: HR 0.557, 95%CI 0.370–0.839, p = 0.005; CSS: HR 0.553, 95%CI 0.354–0.866, p = 0.010). Table 2 Univariate and Multivariate cox regression analysis of patients with malignant peritoneal cytology.(n = 368) Clinical variables OS CSS Univariate analysis Multivariate analysis Univariate analysis Multivariate analysis HR (95% CI) P-value HR (95% CI) P-value HR (95% CI) P-value HR (95% CI) P-value Age (year) <50 Ref Ref 50–59 2.337(0.311–17.564) 0.410 1.931(0.254–14.691) 0.525 60–69 2.428(0.335–17.613) 0.380 2.112(0.290−15.369) 0.460 70–79 3.633(0.500−26.383) 0.202 2.959(0.406–21.594) 0.285 ≥ 80 6.101(0.829–44.918) 0.076 5.280(0.713–39.113) 0.103 Race White Ref Ref Ref Ref Black 1.525(0.970–2.398) 0.068 1.396(0.846–2.302) 0.192 1.318(0.784–2.215) 0.195 1.247(0.706–2.201) 0.447 Asian or Pacific Islander 0.973(0.491–1.925) 0.936 1.121(0.553–2.271) 0.752 1.003(0.486–2.071) 0.448 1.153(0.542–2.452) 0.711 American Indian/Alaska Native 46.980(5.860−376.665) < 0.001 38.512(4.550−325.987) 0.001 91.188(10.163−818.194) < 0.001 78.844(8.219−756.378) < 0.001 Unknown - - - - - - - - Marital status Married Ref Ref Ref Ref Divorced 1.110(0.533–2.311) 0.781 1.069(0.495–2.309) 0.865 1.109(0.506–2.430) 0.796 1.015(0.434–2.376) 0.972 Separated 1.840(0.577–5.864) 0.303 1.464(0.446–4.804) 0.529 1.398(0.341–5.734) 0.642 1.187(0.281–5.018) 0.816 Single (never married) 1.042(0.620–1.753) 0.875 1.152(0.674–1.967) 0.605 0.938(0.524–1.680) 0.829 1.110(0.610–2.021) 0.733 Unmarried or Domestic Partner - - - - - - - - Widowed 2.334(1.538–3.542) < 0.001 1.830(1.164–2.877) 0.009 2.223(1.408–3.509) 0.001 1.836(1.118–3.014) 0.016 Unknown 0.942(0.380–2.338) 0.898 1.228(0.421–3.578) 0.707 01.087(0.436–2.710) 0.858 1.671(0.623–4.480) 0.308 Histology type Clear cell carcinoma Ref Ref Serous carcinoma 0.688(0.439–1.078) 0.102 0.751(0.454–1.243) 0.265 Tumor differentiation Well differentiated Ref Ref Moderately differentiated 1.777(0.218–14.465) 0.591 1.229(0.143–10.533) 0.851 Poorly differentiated or undifferentiated 1.432(0.200−10.279) 0.721 1.172(0.163–8.427) 0.875 Unknown 1.166(0.159–8.580) 0.880 1.018(0.138–7.522) 0.986 Stage IA Ref Ref Ref Ref IB 0.841(0.499–1.417) 0.514 0.925(0.539–1.587) 0.777 0.796(0.449–1.411) 0.435 0.934(0.514–1.698) 0.823 I NOS 2.188(0.886–5.405) 0.090 1.269(0.480–3.358) 0.631 2.002(0.730–5.486) 0.177 1.074(0.365–3.159) 0.897 II 1.994(1.313–3.029) 0.001 2.390(1.496–3.818) < 0.001 1.851(1.166–2.939) 0.009 2.283(1.371–3.801) 0.002 Tumor size (cm) ≤ 2.0 Ref Ref 2.1−4.0 0.838(0.521–1.350) 0.468 0.916(0.546–1.537) 0.739 4.1−6.0 0.869(0.505–1.496) 0.613 0.773(0.414–1.441) 0.418 6.1−8.0 1.577(0.774–3.210) 0.210 1.737(0.813–3.709) 0.154 >8 1.111(0.464–2.658) 0.813 1.132(0.434–2.948) 0.800 Unknown 0.786(0.476–1.301) 0.349 0.871(0.505−1.500) 0.618 Hysterectomy type Simple Ref Ref Ref Supracervical 0.856(0.119–6.133) 0.877 - - - - Modified/radical 0.393(0.145–1.064) 0.066 0.230(0.057–0.932) 0.040 0.240(0.055–1.051) 0.058 NOS 1.107(0.487–2.514) 0.809 1.284(0.563–2.928) 0.552 1.206(0.499–2.918) 0.677 Para-aortic lymphadenectomy No Ref Ref Ref Ref Yes 0.575(0.408–0.811) 0.002 0.796(0.525–1.207) 0.284 0.659(0.453–0.960) 0.030 0.925(0.581–1.471) 0.741 Unknown 0.569(0.178–1.819) 0.342 1.086(0.143–8.258) 0.937 0.499(0.121–2.057) 0.336 1.424(0.183–11.080) 0.736 Pelvic lymphadenectomy No Ref Ref Ref Ref Yes 0.504(0.326–0.780) 0.002 0.658(0.391–1.107) 0.115 0.482(0.303–0.769) 0.002 0.569(0.322–1.008) 0.053 Unknown 0.380(0.090–1.609) 0.189 0.323(0.023–4.564) 0.403 0.220(0.030–1.640) 0.140 0.244(0.012–4.961) 0.358 Radiotherapy Radioactive implants (includes brachytherapy) or radioisotopes Ref Ref Ref Ref Beam radiation 1.424(0.774–2.623) 0.256 1.126(0.597–2.122) 0.714 1.402(0.729–2.696) 0.312 1.080(0.544–2.146) 0.825 Combination of beam with implants or isotopes 1.887(0.735–4.845) 0.187 1.501(0.552–4.083) 0.426 1.686(0.591–4.806) 0.329 1.234(0.395–3.851) 0.718 Radiation,NOS - - - - - - - - No 2.771(0.664–11.565) 0.162 2.568(0.585–11.266) 0.211 3.123(0.744–13.107) 0.120 2.778(0.618–12.478) 0.183 Unknown 1.945(1.295–2.921) 0.001 1.502(0.950–2.376) 0.082 1.822(1.176–2.823) 0.007 1.413(0.860–2.323) 0.173 Chemotherapy No/unknown Ref Ref Ref Ref Yes 0.411(0.291–0.581) < 0.001 0.557(0.370–0.839) 0.005 0.423(0.290–0.618) < 0.001 0.553(0.354–0.866) 0.010 Abbreviations: NOS, not otherwise significant. OS,overall survival.CSS,specific cancer survival. Bold values indicate significance at p < 0.05. Additionally, in stage IA patients with malignant peritoneal cytology, adjuvant chemotherapy could improve the survival outcomes (OS: P = 0.025; CSS: P = 0.038) (Fig. 4 A; B ). Of note, in stage IA patients with negative peritoneal cytology, chemotherapy was a good prognostic factor for OS (P = 0.001) but not for CSS (P = 0.300) (Fig. 4 C; D ). 4. Discussion Our study found that malignant peritoneal cytology was significantly correlated with shorter OS and CSS in early-stage endometrial clear cell carcinoma and serous carcinoma. Moreover, the survival effect of adjuvant chemotherapy may differ depending on peritoneal cytology status for early-stage endometrial clear cell carcinoma and serous carcinoma. In our study, malignant peritoneal cytology was seen in 10.2% of stage I-II ECCC and SC, compared to 6.0–10.9% which has been reported in prior studies( 7 , 17 – 21 ). This prevalence is far higher than in early-stage endometrioid endometrial cancer, where malignant peritoneal cytology is reported to be around 5%( 8 , 10 , 11 ). One possible mechanism of malignant peritoneal cytology is the retrograde spread of tumor cells via the fallopian tubes. A study of 4489 EC patients, including 686 SC patients and 172 CCC patients, revealed that tubal ligation is associated with decreased risk of peritoneal tumor metastasis (GOG-210)( 22 ). The risk reduction is much more significant in SC group than endometroid histology (SC: OR 0.28, 95% CI 0.11–0.68; Low-grade endometroid: OR 1.27, 95% CI 0.41–3.89). In the CCC group, although no statistically significant conclusions can be drawn due to the small number of CCC patients, CCC patients with tubal ligation tend to have a lower risk of peritoneal tumor metastasis (OR 0.27, 95% CI 0.00-2.24). Non-endometrioid EC is more likely to have trans-tubal spread, which may explain the higher incidence of malignant peritoneal cytology in SC and CCC than endometrioid tumors. Based on a SEER study( 7 ), the increased risk of malignant peritoneal cytology is associated with diagnosis at an older age (> 78 years old), serous histology, and larger tumor size (4.1-6.0cm vs. <2cm) in stage I non-endometrioid EC. Our study, however, failed to find an association between the above factors and malignant peritoneal cytology, which is consistent with several studies targeted SC/CCC histology ( 21 , 23 ). Our study demonstrated that malignant peritoneal cytology was a poor prognostic factor for stage I -II ECCC and SC histology, which was in line with the results of previous studies, but our study specifically targeted SC and CCC groups and the sample size was larger( 2 , 7 , 12 , 21 , 23 ). A big-data SEER analysis reported by Matsuo K, et al. revealed that malignant peritoneal cytology was associated with a nearly two-fold increase in all-cause mortality risk compared to negative peritoneal cytology (5-year rates, 63.4% versus 80.2%, HR 2.18, 95% CI 1.78–2.66) in stage I non-endometrioid EC( 7 ). In an analysis of a large cohort of stage I SC/CCC patients with long-term follow-up, Jeans EB, et al. demonstrated any recurrence was worse for tumors of at least 3.5 cm (HR 3.8, 95%CI 1.3–11.7, p = 0.02) and patients with positive/suspicious cytology (HR 4.4, 95%CI 1.5 to 12.4, p ≤ 0.01), and multivariate modeling showed worse any recurrence with positive/suspicious cytology after adjusting for the effect of age( 2 ). A recent study of 101 patients with stage I SC and CCC showed that patients with malignant cytology had a higher likelihood of peritoneal recurrence and a shorter time to relapse (13 vs. 38 months, p = 0.022), as compared to patients with negative cytology( 21 ). A retrospective study of 148 patients diagnosed with uterine serous carcinoma reported malignant peritoneal cytology had a statistically significant effect on OS (HR: 2.09, 95% CI 1.19–3.68) and on CSS (HR: 2.02, 95% CI 1.06–3.82), but the study included stage III SC patients ( 23 ). A study enrolling patients with stage I-II uterine serous carcinoma without adjuvant therapy demonstrated malignant peritoneal cytology was significant prognosticators (DFS: HR 4.24; 95% CI 1.56–11.50; p = 0.005; OS: HR 4.96; 95% CI 1.34–18.30; p = 0.017)( 12 ). Our study explored the prognostic value of malignant peritoneal cytology in not only early-stage non-endometrioid EC patients but also in various subgroups stratified based on stage and histological type. In the subgroup analyses, malignant peritoneal cytology was associated with decreased OS and CSS in serous, clear cell histology group, and stage IA disease, but not for stage IB or stage II disease, which was consistent with the big-data results reported by Matsuo K, et al( 7 ). The previous retrospective study on 68 cases with USC without adjuvant therapy also showed that malignant peritoneal cytology had significant worse prognostic impact on OS (p = 0.0012) and DFS (p = 0.0001) in stage IA disease (n = 42), but not in stage IB (n = 7) (OS: p = 0.722; DFS: p = 0.911) and II (n = 19) (OS: p = 0.48; DFS : p = 0.85)( 12 ). Yang J, et al, however, reported that the detrimental effects of malignant cytology on survival were more prominent in patients with stage IB disease. Notably, the limited number of patients with malignant peritoneal cytology may result in a few underpowered analyses in the study reported by Yang J, et al( 21 ). Adjuvant therapy for early-stage endometrial clear cell carcinoma and serous carcinoma is highly individualized, and the role of chemotherapy remains controversial. Previous studies have shown that chemotherapy could improve the prognosis of patients with stage I SC and CCC( 19 , 21 ). These study, however, did not consider peritoneal cytology as a stratification factor to explore the role of chemotherapy. In our study, patients with malignant peritoneal cytology tended to receive adjuvant chemotherapy, and subgroup analysis found that malignant peritoneal cytology was an adverse prognostic factor in SC/CCC patients with stage IA, so we further explored whether adjuvant chemotherapy could improve the prognosis of patients with malignant peritoneal cytology in stage IA. We found that in stage IA patients with malignant peritoneal cytology, those who received chemotherapy had longer OS (p = 0.025) and CSS (p = 0.038), and for those with negative peritoneal cytology, chemotherapy improved OS (p = 0.001) but not CSS (p = 0.300). Therefore, we believed that SC and CCC patients with stage IA and malignant peritoneal cytology could be considered for chemotherapy. Our finding was in accordance with the NCCN recommendation. According to the 2023 NCCN guideline, noninvasive stage IA CCC and SC are stratified according to peritoneal cytology results for tailored adjuvant therapy strategies, and systemic therapy and vaginal brachytherapy is recommended if positive washings( 6 ). Additionally, for patients with invasive stage IA, systemic therapy could be considered regardless of peritoneal cytology( 6 ). A recent retrospective study revealed that chemotherapy did not improve RFS or OS in type II ECs (SC: n = 22, CCC: n = 12) with stage IA and malignant peritoneal cytology. Although the results were not statistically significant, it could be found that the 5-year relapse-free survival rate and 5-year overall survival rate in the chemotherapy group were higher than those in the non-chemotherapy group (RFS:85.2% vs. 66.7%, p = 0.11; OS: 91.9% vs. 77.8%, p = 0.15), so it may be better to treat them with adjuvant chemotherapy( 24 ). An observational retrospective study of 16,851 stage I-II ECs including 973 serous carcinomas and 190 clear cell carcinomas revealed that adjuvant chemotherapy was associated with increased overall survival in early-stage EC patients with malignant peritoneal cytology (HR 0.62, 95%CI 0.40–0.95, P = 0.03). However, studies have not fully discussed which histologic subtype of early-stage patients with malignant peritoneal cytology may be able to experience increased survival with adjuvant chemotherapy( 9 ). A study, involving stage I SC and CCC patients who had received adjuvant vaginal cuff brachytherapy and/or chemotherapy, reported that positive/suspicious cytology were at increased risk for relapse and worse survival, and should be considered for additional upfront adjuvant treatments, such as platinum-based chemotherapy( 2 ). However, the role of chemotherapy has not been individually investigated in stage IA patients in this analysis( 2 ). For early-stage non-endometrioid endometrial cancer with negative peritoneal cytology, Matsuo K, et al. stated that women who received chemotherapy-based postoperative therapy had higher 5-year OS rates compared to those received whole pelvic irradiation (79.6% for chemotherapy ± brachytherapy, 77.4% for chemotherapy with whole pelvic irradiation, and 56.9% for whole pelvic irradiation, P < 0.001)( 7 ). However, a study reported by Tate K, et al. revealed that patients with stage IA or IB USC showing negative peritoneal cytology might have an extremely favorable prognosis (5-year DFS rate:88.8%; 5-year OS rate:93.6%) and did not need any adjuvant therapies( 12 ). More clinical studies are needed to investigate the significance of adjuvant chemotherapy in patients with stage IA non-endometrioid endometrial cancer with negative peritoneal cytology. Strengths of the current study include: this was a population-based analysis with the large sample size for endometrial clear cell carcinoma and serous carcinoma; the long follow-up period; several subgroup analyses with stage and histologic type as stratification factors enhanced the interpretation of the study results; the analytic approach with propensity score matching and propensity score inverse probability of treatment weighting enriched the statistical rigor. Additionally, our study does have several limitations. Predominantly, it was a retrospective study with inherent unmeasured bias. For example, details of surgical-pathological factors such as lympho-vascular space invasion, and omental biopsy were not available in the SEER Program, but may be associated with the incidence of malignant peritoneal cytology as well as the oncologic outcomes. Second, the accuracy of malignant cytology results was unknown due to the lack of central pathology review in the study. Third, as this study only examined the U.S. population, whether our findings are generalizable to other study populations needs to be further examined. Fourth, per the SEER Program definition, cases with no and unknown status are grouped together in chemotherapy, and details of chemotherapy (regimen and cycle) were not available. 5. Conclusion In conclusion, the current study clearly showed that malignant peritoneal cytology was identified as an adverse prognostic factor in analyses of all early-stage endometrial clear cell carcinoma and serous carcinoma as well as in CCC histology type, SC histology type, and stage IA subgroup analyses. Based on the results of the present study, stage IA SC/CCC patients with malignant peritoneal cytology could further benefit from chemotherapy. Of note, peritoneal cytology results should not be taken in isolation to guide adjuvant therapy, and it should also be considered in combination with other risk factors for survival outcomes. Further prospective clinical trials are necessary to evaluate the efficacy of adjuvant therapy in stage IA SC/CCC groups. Declarations Ethics approval and consent to participate: Not applicable Consent for publication: Not applicable Availability of data and materials: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests: The authors declare that they have no competing interests Funding: The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Authors' contributions: Xinyue Tang: Proiect development, Data collection, Manuscript writing. Na Li: Data collection. Yuanjing Hu: Project development. All the authors have reviewed the final draft of the manuscript and approved it for publication. Acknowledgements: Not applicable Authors' information (optional)Compliance with Ethical Standards : Not Applicable References Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA: a cancer journal for clinicians. 2023;73(1):17-48. Jeans EB, Breen WG, Mullikin TC, Looker BA, Mariani A, Keeney GL, et al. Adjuvant brachytherapy for FIGO stage I serous or clear cell endometrial cancer. International journal of gynecological cancer : official journal of the International Gynecological Cancer Society. 2021;31(6):859-67. Bogani G, Ray-Coquard I, Concin N, Ngoi NYL, Morice P, Enomoto T, et al. Clear cell carcinoma of the endometrium. Gynecologic oncology. 2022;164(3):658-66. Bogani G, Ray-Coquard I, Concin N, Ngoi NYL, Morice P, Enomoto T, et al. Uterine serous carcinoma. Gynecologic oncology. 2021;162(1):226-34. Oaknin A, Bosse TJ, Creutzberg CL, Giornelli G, Harter P, Joly F, et al. Endometrial cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up. Annals of oncology : official journal of the European Society for Medical Oncology. 2022;33(9):860-77. Abu-Rustum. NR, Yashar. CM, Bradley. K, Brooks. R, Campos SM. NCCN Guidelines®Uterine Neoplasms.Version 1.2023.https://www.nccn.org/professionals/physician_gls/pdf/uterine.pdf. Matsuo K, Nusbaum DJ, Matsuzaki S, Chang EJ, Roman LD, Wright JD, et al. Malignant peritoneal cytology and increased mortality risk in stage I non-endometrioid endometrial cancer. Gynecologic oncology. 2020;159(1):43-51. Matsuo K, Yabuno A, Hom MS, Shida M, Kakuda M, Adachi S, et al. Significance of abnormal peritoneal cytology on survival of women with stage I-II endometrioid endometrial cancer. Gynecologic oncology. 2018;149(2):301-9. Seagle BL, Alexander AL, Lantsman T, Shahabi S. Prognosis and treatment of positive peritoneal cytology in early endometrial cancer: matched cohort analyses from the National Cancer Database. American journal of obstetrics and gynecology. 2018;218(3):329.e1-.e15. Takenaka M, Kamii M, Iida Y, Yanaihara N, Suzuki J, Takahashi K, et al. Re-thinking the prognostic significance of positive peritoneal cytology in endometrial cancer. Gynecologic oncology. 2021;161(1):135-42. Matsuo K, Matsuzaki S, Nusbaum DJ, Machida H, Nagase Y, Grubbs BH, et al. Malignant peritoneal cytology and decreased survival of women with stage I endometrioid endometrial cancer. European journal of cancer (Oxford, England : 1990). 2020;133:33-46. Tate K, Yoshida H, Ishikawa M, Uehara T, Ikeda SI, Hiraoka N, et al. Prognostic factors for patients with early-stage uterine serous carcinoma without adjuvant therapy. Journal of gynecologic oncology. 2018;29(3):e34. Garg G, Gao F, Wright JD, Hagemann AR, Mutch DG, Powell MA. Positive peritoneal cytology is an independent risk-factor in early stage endometrial cancer. Gynecologic oncology. 2013;128(1):77-82. Surveillance, Epidemiology, and End Results (SEER) Program (www.seer.cancer.gov) SEER*Stat Database: Incidence - SEER Research Plus Data, 17 Registries, Nov 2021 Sub (2000-2019) - Linked To County Attributes - Time Dependent (1990-2019) Income/Rurality, 1969-2020 Counties, National Cancer Institute, DCCPS, Surveillance Research Program, released April 2022, based on the November 2021 submission. National Cancer Registrars Association. http://www.ncra-usa.org/. Accessed 23 Jul 2020. Austin PC, Stuart EA. Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies. Statistics in medicine. 2015;34(28):3661-79. Mysona DP, Tran LKH, Tran PMH, Gehrig PA, Van Le L, Ghamande S, et al. Clinical calculator predictive of chemotherapy benefit in stage 1A uterine papillary serous cancers. Gynecologic oncology. 2020;156(1):77-84. Orellana TJ, Garrett AA, Soong TR, Rives T, Courtney-Brooks M, Taylor SE, et al. The role of adjuvant treatment for early-stage uterine clear cell carcinomas. Gynecologic oncology. 2023;170:77-83. Qu XM, Velker VM, Leung E, Kwon JS, Elshaikh MA, Kong I, et al. The role of adjuvant therapy in stage IA serous and clear cell uterine cancer: A multi-institutional pooled analysis. Gynecologic oncology. 2018;149(2):283-90. Ditto A, Leone Roberti Maggiore U, Lopez S, Martinelli F, Bogani G, Lo Vullo S, et al. Uterine serous carcinoma: role of surgery, risk factors and oncologic outcomes. Experience of a tertiary center. European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology. 2022;48(1):268-74. Yang J, Yang J, Cao D, Wu M, Xiang Y. Prognostic Value of Peritoneal Cytology in Stage I Serous and Clear Cell Carcinoma of the Endometrium. Journal of clinical medicine. 2023;12(4). Felix AS, Brinton LA, McMeekin DS, Creasman WT, Mutch D, Cohn DE, et al. Relationships of Tubal Ligation to Endometrial Carcinoma Stage and Mortality in the NRG Oncology/ Gynecologic Oncology Group 210 Trial. Journal of the National Cancer Institute. 2015;107(9). Corey L, Fucinari J, Elshaikh M, Schultz D, Musallam R, Zaiem F, et al. Impact of positive cytology in uterine serous carcinoma: A reassessment. Gynecologic oncology reports. 2021;37:100830. Kanno M, Yunokawa M, Nakabayashi M, Omi M, Ikki A, Mizusaki M, et al. Prognosis and adjuvant chemotherapy for patients with positive peritoneal cytology in stage IA endometrial cancer. Scientific reports. 2022;12(1):166. Additional Declarations No competing interests reported. Supplementary Files FigureS1.tif Figure S1 Based on the adjuvant chemotherapy, overall survival (A) and cancer-specific survival (B) for stage IB patients; overall survival (C) and cancer-specific survival (D) for stage II patients. TableS1andS2.docx Table S1 Patient demographics per peritoneal cytology status after PSM (N=1771). PSM, propensity score matching; NOS, not otherwise significant. Table S2 Cox proportional hazard regression model after PSM. Cite Share Download PDF Status: Posted Version 1 posted 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-3214955","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":228030162,"identity":"1cc60624-c1c1-4916-b09c-e788232ef1ef","order_by":0,"name":"Xinyue Tang","email":"","orcid":"","institution":"Tianjin Central Hospital of Obstetrics \u0026 Gynecology","correspondingAuthor":false,"prefix":"","firstName":"Xinyue","middleName":"","lastName":"Tang","suffix":""},{"id":228030163,"identity":"0c062e46-a7c4-4aff-888f-3818a899cfe3","order_by":1,"name":"Na Li","email":"","orcid":"","institution":"Tianjin Central Hospital of Obstetrics \u0026 Gynecology","correspondingAuthor":false,"prefix":"","firstName":"Na","middleName":"","lastName":"Li","suffix":""},{"id":228030164,"identity":"21ed583d-147d-481b-9f1c-0f871b4a7e69","order_by":2,"name":"Yuanjing Hu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYBACNmb+hw8kDCTk+JmZDxCnhY+dh9nAosLGWLKdLYE4LXL8PGwSFWfSEjec5zEg1mG8hw1uth02ZjjM8/HGGwY7Od0Gglr4Eh/ObDssx9jMu9lyDkOysdkBgloYjI0lgbYwM/Nuk+ZhOJC4jQgtZtJ/2w4ntjHzPCNWC4+ZhATQ+z3MPGzEamFLNpAABrIEM5ux5RwDIvwi33/4IDgq7c8ffnjjTYWdHEEtKECC2KhB1kKqjlEwCkbBKBgRAACEzzmsBo8rgAAAAABJRU5ErkJggg==","orcid":"","institution":"Tianjin Central Hospital of Obstetrics \u0026 Gynecology","correspondingAuthor":true,"prefix":"","firstName":"Yuanjing","middleName":"","lastName":"Hu","suffix":""}],"badges":[],"createdAt":"2023-07-29 06:44:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3214955/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3214955/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":42148629,"identity":"2b62f7d7-7337-4ccd-8f79-043543beb350","added_by":"auto","created_at":"2023-08-25 17:01:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":102829,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of patient selection from the Surveillance, Epidemiology, and End Results (SEER) database.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3214955/v1/8a93d17c5a9b4f9410d1658d.png"},{"id":42148630,"identity":"b2acf82e-2d8c-48fe-97da-fe02cc155a40","added_by":"auto","created_at":"2023-08-25 17:01:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":135081,"visible":true,"origin":"","legend":"\u003cp\u003eOverall survival (\u003cstrong\u003eA\u003c/strong\u003e) and cancer-specific survival (\u003cstrong\u003eB\u003c/strong\u003e) based on the peritoneal cytology results (negative or malignant) for the entire cohort.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3214955/v1/2fc8b91d2a4d5839dfb6a612.png"},{"id":42148633,"identity":"51411a28-d351-4646-a34c-de7c95826b78","added_by":"auto","created_at":"2023-08-25 17:01:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":377719,"visible":true,"origin":"","legend":"\u003cp\u003eBased on the peritoneal cytology results (negative or malignant), overall survival (\u003cstrong\u003eA\u003c/strong\u003e) and cancer-specific survival (\u003cstrong\u003eB\u003c/strong\u003e) for CCC histology; overall survival (\u003cstrong\u003eC\u003c/strong\u003e) and cancer-specific survival \u003cstrong\u003e(D\u003c/strong\u003e) for SC histology; overall survival (\u003cstrong\u003eE\u003c/strong\u003e) and cancer-specific survival (\u003cstrong\u003eF\u003c/strong\u003e) for stage IA patients.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-3214955/v1/f249c7055306ccafc348d79c.png"},{"id":42148631,"identity":"38861f0e-6271-48dd-bbf1-07a6a323182f","added_by":"auto","created_at":"2023-08-25 17:01:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":225217,"visible":true,"origin":"","legend":"\u003cp\u003eBased on the peritoneal cytology results (negative or malignant), overall survival (\u003cstrong\u003eA\u003c/strong\u003e) and cancer-specific survival (\u003cstrong\u003eB\u003c/strong\u003e) for stage IA patients with malignant peritoneal cytology; overall survival (\u003cstrong\u003eC\u003c/strong\u003e) and cancer-specific survival (\u003cstrong\u003eD\u003c/strong\u003e) for stage IA patients with negative peritoneal cytology.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-3214955/v1/7aa1103e80c9af07333d63f5.png"},{"id":43336745,"identity":"921cae6d-1ea6-4c9e-9802-aabb66734391","added_by":"auto","created_at":"2023-09-19 05:07:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1282770,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3214955/v1/1245d82b-2140-4a60-91e1-79654a607932.pdf"},{"id":42148634,"identity":"2d104178-9082-458a-b539-739af6c8fc0f","added_by":"auto","created_at":"2023-08-25 17:01:44","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3838164,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure S1\u003c/strong\u003e Based on the adjuvant chemotherapy, overall survival (\u003cstrong\u003eA\u003c/strong\u003e) and cancer-specific survival (\u003cstrong\u003eB\u003c/strong\u003e) for stage IB patients; overall survival (\u003cstrong\u003eC\u003c/strong\u003e) and cancer-specific survival (\u003cstrong\u003eD\u003c/strong\u003e) for stage II patients.\u003c/p\u003e","description":"","filename":"FigureS1.tif","url":"https://assets-eu.researchsquare.com/files/rs-3214955/v1/dc0e393893077a4291472b8e.tif"},{"id":42148632,"identity":"c25dbb54-37da-44a4-a637-b7aec5dc7cd7","added_by":"auto","created_at":"2023-08-25 17:01:43","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":17926,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable S1\u003c/strong\u003e Patient demographics per peritoneal cytology status after PSM (N=1771). PSM, propensity score matching; NOS, not otherwise significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S2 \u003c/strong\u003eCox proportional hazard regression model after PSM.\u003c/p\u003e","description":"","filename":"TableS1andS2.docx","url":"https://assets-eu.researchsquare.com/files/rs-3214955/v1/e6fe4a6af4818e6d932597ef.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prognosis and adjuvant chemotherapy for patients with malignant peritoneal cytology in early-stage non-endometrioid endometrial cancer","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eEndometrial cancer (EC) is one of most common gynecological cancers, with 66,200 estimated new cases in the United States in 2023(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Traditionally, EC is classified as endometrioid and non-endometrioid cancer, and the latter account for about 20% of EC characterized by a higher rate of extra-uterine spread and worse prognosis(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Of note, clear cell cancer and serous cancer are the major non-endometrioid endometrial cancer, together accounting for about 75% of non-endometrioid cancer(\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEndometrial cancer is commonly diagnosed at an early stage. The standard surgical treatment approach for patients with apparent early-stage disease is hysterectomy, salpingo-oophorectomy, and additional lymphadenectomy, which allows primary tumor removal and identification of major prognostic factors (e.g., myometrial invasion, lymph vascular space invasion) for tailoring postoperative adjuvant therapy(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). The presence of tumor cells seen in the peritoneal cytologic specimen at hysterectomy, known as malignant peritoneal cytology, is another possible risk factor considered as an indication of adjuvant therapy. In the National Comprehensive Cancer Network\u0026reg; (NCCN\u0026reg;) guidelines, noninvasive stage IA CCC and SC are stratified according to peritoneal cytology results for tailored adjuvant treatment strategies(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMalignant peritoneal cytology can be seen in approximately 5% of early-stage endometrial cancer, and the incidence seems higher in the non-endometrioid histological type(\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Multiple studies have suggested that malignant peritoneal cytology is an adverse prognostic factor for survival outcome in early-stage EC, but studies specifically evaluating early-stage non-endometrioid types are limited due to its rarity(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan additionalcitationids=\"CR8 CR9 CR10 CR11 CR12\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe objective of this study was to examine the association between malignant peritoneal cytology and survival in women with early-stage endometrial clear cell carcinoma and serous carcinoma, and to explore whether malignant peritoneal cytology may be used as an indication to guide the use of chemotherapy in early-stage CCC and SC.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Data Source\u003c/h2\u003e \u003cp\u003eThe Surveillance, Epidemiology, and End Results (SEER) database, a population-based cancer registry established by the National Cancer Institute (NCI), was searched for the analysis(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Patient identification, data accumulation and entry, and rigorous quality control for the database are managed by registered trained personnel(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). We obtained the information of patients diagnosed between 2010 and 2019 from the SEER\u0026lowast; Stat version 8.4.0.1 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://seer.cancer.gov/seerstat/\u003c/span\u003e\u003cspan address=\"https://seer.cancer.gov/seerstat/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Study Population\u003c/h2\u003e \u003cp\u003eThe International Classification of Diseases for Oncology, Third Edition (ICD-O-3) morphology codes \u0026ldquo;8310/3: Clear cell adenocarcinoma, NOS; 8441/3: Serous cystadenocarcinoma, NOS; 8460/3: Papillary serous cystadenocarcinoma; 8461/3: Serous surface papillary carcinoma\u0026rdquo; was used to identify endometrial clear cell carcinoma (CCC) and serous carcinoma (SC) from patients with histologically confirmed primary endometrial cancer (ICD-O-3, C54.1). The American Joint Committee on Cancer staging classification schema was used for defining T stage. We gathered the following information: age at diagnosis, race, marital status, peritoneal cytology, tumor differentiation, stage, tumor size, hysterectomy type, para-aortic lymphadenectomy, pelvic lymphadenectomy, chemotherapy, radiotherapy, and survival data.\u003c/p\u003e \u003cp\u003eWomen with stage I-II (T1/N0/M0, T2/N0/M0) endometrial cancer with histologic confirmation who had available data on survival time and peritoneal cytology results from 2010 to 2019 were included. Exclusion criteria included non-CCC and non-SC, and no hysterectomy or unknown surgery type.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Outcome Measure\u003c/h2\u003e \u003cp\u003eOverall survival (OS) and cancer-specific survival (CSS) were assessed for outcome analysis. OS was considered as the time from diagnosis to death for any cause or to the last contact. CSS was defined as the time from diagnosis to death due to endometrial carcinoma. Women who had no survival event at the last follow-up were censored.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical analyses\u003c/h2\u003e \u003cp\u003eThe first step of the analysis was to identify the independent characteristics associated with malignant peritoneal cytology. Differences in the baseline characteristics were assessed with chi-square test for univariable analysis. All the significant covariates with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 on univariable analysis were entered in the\u003c/p\u003e \u003cp\u003ebinary logistic regression model, and effect size was expressed with an adjusted odds ratio (OR) and corresponding 95% confidence interval (CI). Hosmer-Lemeshow test was used to assess the goodness-of-fit in the final model, and a P\u0026thinsp;\u0026gt;\u0026thinsp;0.05 was interpreted as a good-fit model.\u003c/p\u003e \u003cp\u003eThe second step of the analysis was to evaluate the survival effect of malignant peritoneal cytology in stage I-II endometrial CCC and SC. The propensity score was calculated based on the covariates age at diagnosis, race, marital status, tumor differentiation, stage, tumor size, hysterectomy type, para-aortic lymphadenectomy, pelvic lymphadenectomy, chemotherapy, radiotherapy to reduce the imbalance between the malignant and negative peritoneal cytology groups. Malignant peritoneal cytology cases were matched to negative peritoneal cytology group in a 1:4 ratio and a caliper width of 0.05 standard deviation (SD) was specified. Survival analysis was assessed with the Kaplan\u0026ndash;Meier method, and the results were compared with the log-rank test. The Kaplan-Meier method was used to plot survival curves, and a Cox proportional hazard regression model was fitted to estimate hazard ratio (HR) with 95% confidence interval (CI) for malignant peritoneal cytology.\u003c/p\u003e \u003cp\u003eLastly, cox regression analyses were employed to identify whether adjuvant chemotherapy improved the outcome of endometrial CCC/SC patients with malignant peritoneal cytology by reporting the hazard ratios (HR) and 95% CI.\u003c/p\u003e \u003cp\u003eIn addition, we conducted multiple subgroup analyses to enhance the validity of this study. First, the effect of peritoneal cytology results on survival outcome was examined, stratified by histology (clear cell versus serous), and stage (stage IA, stage IB, stage II). Second, the effect of chemotherapy on the prognosis of women with stage IA was examined based on peritoneal cytology results (malignant versus negative). Propensity score inverse probability of treatment weighting (IPTW) was used to balance the measured covariates in each subcohort(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). The Kaplan-Meier method was used to plot survival curves, and the survival analysis results were compared with the log-rank test.\u003c/p\u003e \u003cp\u003eStatistical analyses were all performed with SPSS (version26.0, IBM Corporation, USA) and R software (version 4.2.1; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.R-project.org/\u003c/span\u003e\u003cspan address=\"http://www.R-project.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e A two-sided p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Patient population\u003c/h2\u003e \u003cp\u003eA total of 3,616 patients were eligible for incidence analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Of those, malignant peritoneal cytology was reported in 368 (10.2%) women and the remaining 3,248 (89.8%) women had negative peritoneal cytology. Majority of women were 60\u0026ndash;69 years (43.5%), white (71.1%), and married (50.3%). In terms of histopathology, most of patients were serous carcinoma (84.2%), poor differentiated or undifferentiated (67.7%), and IA stage (71.2%). Simple hysterectomy was performed in 90.7% of patients. Pelvic and para-aortic lymphadenectomy were performed in 88.9% and 55.9% cases, respectively. 47.6% of the included patients received radiotherapy, and more than half of patients received chemotherapy (60.6%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Factors associated with malignant peritoneal cytology\u003c/h2\u003e \u003cp\u003eIn the univariable and multivariable analysis (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), race, marital status, and postoperative adjuvant chemotherapy were the factors associated with peritoneal cytology results (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Blacks were more likely to have negative peritoneal cytology than whites (OR 0.565; 95%CI 0.406\u0026ndash;0.787). Women in the malignant peritoneal cytology were more likely to receive postoperative adjuvant chemotherapy (OR 2.033; 95%CI 1.589\u0026ndash;2.602).\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\u003ePatient demographics per peritoneal cytology status (N\u0026thinsp;=\u0026thinsp;3616).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u0026thinsp;=\u0026thinsp;3,616\u003c/p\u003e \u003cp\u003e(n,%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNegative ,n\u0026thinsp;=\u0026thinsp;3,248\u003c/p\u003e \u003cp\u003e(n,%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMalignant ,n\u0026thinsp;=\u0026thinsp;368\u003c/p\u003e \u003cp\u003e(n,%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAdjusted OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP-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\u003eAge (year)\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 \u003cp\u003e0.103\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26(0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(1.6)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e484(13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e427(13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57(15.5)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1572(43.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1419(43.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e153(41.6)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1146((31.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1038(32.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e108(29.3)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e388(10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e344(10.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44(12.0)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace\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 \u003cp\u003e\u003cb\u003e0.028\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2572(71.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2287(70.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e285(77.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e672(18.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e625(19.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47(12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.565(0.406\u0026ndash;0.787)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian or Pacific Islander\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e333(9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e299(9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34(9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.888(0.608\u0026ndash;1.296)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.537\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmerican Indian/Alaska Native\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22(0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21(0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.417(0.055\u0026ndash;3.142)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.396\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17(0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16(0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.513(0.067\u0026ndash;3.922)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.520\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\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 \u003cp\u003e\u003cb\u003e0.015\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1819(50.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1617(49.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e202(54.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e404(11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e380(11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24(6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.537(0.346\u0026ndash;0.835)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeparated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50(1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43(1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7(1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.502(0.660\u0026ndash;3.422)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.332\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle (never married)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e511(14.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e454(14.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57(15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.156(0.838\u0026ndash;1.595)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.376\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnmarried or Domestic Partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12(0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3(0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.353(0.626\u0026ndash;8.848)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.205\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e640(17.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e578(17.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62(16.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.988(0.728\u0026ndash;1.340)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.937\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e180(5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e167(5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.661(0.368\u0026ndash;1.188)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.166\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistology type\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 \u003cp\u003e0.332\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClear cell carcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e572(15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e521(16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51(13.9)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerous carcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3044(84.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2727(84.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e317(86.1)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumor differentiation\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 \u003cp\u003e0.255\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWell differentiated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65(1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60(1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(1.4)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerately differentiated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e109(3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92(2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17(4.6)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorly differentiated or undifferentiated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2448(67.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2200(67.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e248(67.4)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e994(27.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e896(27.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98(26.6)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStage\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 \u003cp\u003e0.122\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2575(71.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2330(71.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e245(66.6)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e538(14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e477(14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61(16.6)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI NOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97(2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88(2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9(2.4)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e406(11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e353(10.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53(14.4)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumor size (cm)\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 \u003cp\u003e0.196\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e899(24.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e823(25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76(20.7)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.1\u0026minus;4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1011(28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e908(28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e103(28.0)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4.1\u0026minus;6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e552(15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e483(14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69(18.8)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.1\u0026minus;8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e166(4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e146(4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20(5.4)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98(2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86(2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(3.3)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e890(24.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e802(24.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88(23.9)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHysterectomy type\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 \u003cp\u003e0.599\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSimple\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3279(90.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2952(90.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e327(88.9)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSupracervical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22(0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(0.5)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModified/radical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e181(5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e159(4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22(6.0)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e134(3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117(3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17(4.6)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePara-aortic lymphadenectomy\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 \u003cp\u003e0.919\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1431(39.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1289(39.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e142(38.6)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2022(55.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1813(55.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e209(56.8)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e163(4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e146(4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17(4.6)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePelvic lymphadenectomy\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 \u003cp\u003e0.290\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e348(9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e305(9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43(11.7)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3213(88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2895(89.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e318(86.4)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55(1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48(1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7(1.9)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRadiotherapy\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 \u003cp\u003e0.272\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRadioactive implants (includes brachytherapy) or radioisotopes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1216(33.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1088(33.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e128(34.8)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeam radiation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e332(9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e295(9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37(10.1)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCombination of beam with implants or isotopes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e164(4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e151(4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(3.5)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRadiation,NOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10(0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(0.3)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93(2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90(2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3(0.8)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1801(49.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1615(49.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186(50.5)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChemotherapy\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 \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo/Unknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1426(39.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1331(41.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95(25.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2190(60.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1917(59.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e273(74.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.033(1.589\u0026ndash;2.602)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eAbbreviations: NOS, not otherwise significant. Bold values indicate significance at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Survival effect of malignant peritoneal cytology\u003c/h2\u003e \u003cp\u003eAll of the 12 measured covariates were well-balanced after propensity score matching (PSM) (\u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). In the PSM model, 365 women with malignant peritoneal cytology were compared with 1406 women with negative peritoneal cytology for survival outcome analysis. The cox proportional hazard regression model showed that malignant peritoneal cytology was an independent risk prognostic factor for overall survival (OS) (Univariate: HR 2.028; 95%CI 1.650\u0026ndash;2.492; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. Multivariate: HR 2.200; 95%CI 1.781\u0026ndash;2.718; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). A similar association was observed for cancer-specific survival (CSS) (Univariate: HR 2.453; 95%CI 1.945\u0026ndash;3.094; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. Multivariate: HR 2.704; 95%CI 2.130\u0026ndash;3.432; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (\u003cb\u003eTable \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e\u003c/b\u003e). The 5-year OS rates were 56.5% for women with malignant peritoneal cytology and 74.4% for those with negative peritoneal cytology (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), and the 5-year CSS rates were 60.8% versus 80.0% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMalignant peritoneal cytology was a prognostic risk factor observed for the sub-cohorts of patients with CCC histology(OS: P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; CSS: P\u0026thinsp;\u0026lt;\u0026thinsp;0.001)(Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB), SC histology (OS:P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; CSS: P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD), and stage IA(OS: P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; CSS: P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). In contrast, peritoneal cytology was not associated with prognosis in the stage IB (OS: P\u0026thinsp;=\u0026thinsp;0.366; CSS: P\u0026thinsp;=\u0026thinsp;0.131) (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e A;B\u003c/b\u003e) and stage II (OS: P\u0026thinsp;=\u0026thinsp;0.215; CSS: P\u0026thinsp;=\u0026thinsp;0.100) (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e C;D\u003c/b\u003e) subgroups.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Significance of adjuvant chemotherapy in patients based on peritoneal cytology results\u003c/h2\u003e \u003cp\u003eThe association between adjuvant chemotherapy and survival was examined among women with malignant peritoneal cytology (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). According the multivariate cox regression analysis, after controlling for confounding factors, adjuvant chemotherapy as an independent prognostic factor could improve the survival of patients with malignant peritoneal cytology (OS: HR 0.557, 95%CI 0.370\u0026ndash;0.839, p\u0026thinsp;=\u0026thinsp;0.005; CSS: HR 0.553, 95%CI 0.354\u0026ndash;0.866, p\u0026thinsp;=\u0026thinsp;0.010).\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\u003eUnivariate and Multivariate cox regression analysis of patients with malignant peritoneal cytology.(n\u0026thinsp;=\u0026thinsp;368)\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eOS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eCSS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eP-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\u003eAge (year)\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\u003e\u0026lt;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \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 \u003cp\u003eRef\u003c/p\u003e \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\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.337(0.311\u0026ndash;17.564)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.410\u003c/p\u003e \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 \u003cp\u003e1.931(0.254\u0026ndash;14.691)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.525\u003c/p\u003e \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\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.428(0.335\u0026ndash;17.613)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.380\u003c/p\u003e \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 \u003cp\u003e2.112(0.290\u0026minus;15.369)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.460\u003c/p\u003e \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\u003e70\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.633(0.500\u0026minus;26.383)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.202\u003c/p\u003e \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 \u003cp\u003e2.959(0.406\u0026ndash;21.594)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.285\u003c/p\u003e \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\u0026ge;\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.101(0.829\u0026ndash;44.918)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.076\u003c/p\u003e \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 \u003cp\u003e5.280(0.713\u0026ndash;39.113)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.103\u003c/p\u003e \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\u003eRace\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\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRef\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\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.525(0.970\u0026ndash;2.398)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.396(0.846\u0026ndash;2.302)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.318(0.784\u0026ndash;2.215)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.247(0.706\u0026ndash;2.201)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.447\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian or Pacific Islander\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.973(0.491\u0026ndash;1.925)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.936\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.121(0.553\u0026ndash;2.271)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.003(0.486\u0026ndash;2.071)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.153(0.542\u0026ndash;2.452)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.711\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmerican Indian/Alaska Native\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.980(5.860\u0026minus;376.665)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.512(4.550\u0026minus;325.987)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e91.188(10.163\u0026minus;818.194)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e78.844(8.219\u0026minus;756.378)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\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\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRef\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\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.110(0.533\u0026ndash;2.311)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.069(0.495\u0026ndash;2.309)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.109(0.506\u0026ndash;2.430)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.796\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.015(0.434\u0026ndash;2.376)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.972\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeparated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.840(0.577\u0026ndash;5.864)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.464(0.446\u0026ndash;4.804)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.398(0.341\u0026ndash;5.734)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.187(0.281\u0026ndash;5.018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.816\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle (never married)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.042(0.620\u0026ndash;1.753)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.152(0.674\u0026ndash;1.967)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.938(0.524\u0026ndash;1.680)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.110(0.610\u0026ndash;2.021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.733\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnmarried or Domestic Partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.334(1.538\u0026ndash;3.542)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.830(1.164\u0026ndash;2.877)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.223(1.408\u0026ndash;3.509)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.836(1.118\u0026ndash;3.014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.016\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.942(0.380\u0026ndash;2.338)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.228(0.421\u0026ndash;3.578)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e01.087(0.436\u0026ndash;2.710)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.671(0.623\u0026ndash;4.480)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.308\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistology type\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\u003eClear cell carcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \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 \u003cp\u003eRef\u003c/p\u003e \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\u003eSerous carcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.688(0.439\u0026ndash;1.078)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.102\u003c/p\u003e \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 \u003cp\u003e0.751(0.454\u0026ndash;1.243)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.265\u003c/p\u003e \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\u003eTumor differentiation\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\u003eWell differentiated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \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 \u003cp\u003eRef\u003c/p\u003e \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\u003eModerately differentiated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.777(0.218\u0026ndash;14.465)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.591\u003c/p\u003e \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 \u003cp\u003e1.229(0.143\u0026ndash;10.533)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.851\u003c/p\u003e \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\u003ePoorly differentiated or undifferentiated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.432(0.200\u0026minus;10.279)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.721\u003c/p\u003e \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 \u003cp\u003e1.172(0.163\u0026ndash;8.427)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.875\u003c/p\u003e \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\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.166(0.159\u0026ndash;8.580)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.880\u003c/p\u003e \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 \u003cp\u003e1.018(0.138\u0026ndash;7.522)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.986\u003c/p\u003e \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\u003eStage\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\u003eIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRef\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\u003eIB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.841(0.499\u0026ndash;1.417)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.925(0.539\u0026ndash;1.587)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.796(0.449\u0026ndash;1.411)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.934(0.514\u0026ndash;1.698)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.823\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI NOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.188(0.886\u0026ndash;5.405)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.269(0.480\u0026ndash;3.358)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.631\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.002(0.730\u0026ndash;5.486)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.074(0.365\u0026ndash;3.159)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.897\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.994(1.313\u0026ndash;3.029)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.390(1.496\u0026ndash;3.818)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.851(1.166\u0026ndash;2.939)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.283(1.371\u0026ndash;3.801)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumor size (cm)\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\u003e\u0026le;\u0026thinsp;2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \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 \u003cp\u003eRef\u003c/p\u003e \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\u003e2.1\u0026minus;4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.838(0.521\u0026ndash;1.350)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.468\u003c/p\u003e \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 \u003cp\u003e0.916(0.546\u0026ndash;1.537)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.739\u003c/p\u003e \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\u003e4.1\u0026minus;6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.869(0.505\u0026ndash;1.496)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.613\u003c/p\u003e \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 \u003cp\u003e0.773(0.414\u0026ndash;1.441)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.418\u003c/p\u003e \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\u003e6.1\u0026minus;8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.577(0.774\u0026ndash;3.210)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.210\u003c/p\u003e \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 \u003cp\u003e1.737(0.813\u0026ndash;3.709)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.154\u003c/p\u003e \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\u0026gt;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.111(0.464\u0026ndash;2.658)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.813\u003c/p\u003e \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 \u003cp\u003e1.132(0.434\u0026ndash;2.948)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.800\u003c/p\u003e \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\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.786(0.476\u0026ndash;1.301)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.349\u003c/p\u003e \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 \u003cp\u003e0.871(0.505\u0026minus;1.500)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.618\u003c/p\u003e \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\u003eHysterectomy type\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\u003eSimple\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \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 \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRef\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\u003eSupracervical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.856(0.119\u0026ndash;6.133)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.877\u003c/p\u003e \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 \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModified/radical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.393(0.145\u0026ndash;1.064)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.066\u003c/p\u003e \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 \u003cp\u003e0.230(0.057\u0026ndash;0.932)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.040\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.240(0.055\u0026ndash;1.051)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.107(0.487\u0026ndash;2.514)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.809\u003c/p\u003e \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 \u003cp\u003e1.284(0.563\u0026ndash;2.928)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.206(0.499\u0026ndash;2.918)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.677\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePara-aortic lymphadenectomy\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRef\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.575(0.408\u0026ndash;0.811)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.796(0.525\u0026ndash;1.207)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.659(0.453\u0026ndash;0.960)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.030\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.925(0.581\u0026ndash;1.471)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.741\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.569(0.178\u0026ndash;1.819)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.086(0.143\u0026ndash;8.258)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.937\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.499(0.121\u0026ndash;2.057)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.424(0.183\u0026ndash;11.080)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.736\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePelvic lymphadenectomy\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRef\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.504(0.326\u0026ndash;0.780)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.658(0.391\u0026ndash;1.107)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.482(0.303\u0026ndash;0.769)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.569(0.322\u0026ndash;1.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.380(0.090\u0026ndash;1.609)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.323(0.023\u0026ndash;4.564)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.220(0.030\u0026ndash;1.640)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.244(0.012\u0026ndash;4.961)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.358\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRadiotherapy\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\u003eRadioactive implants (includes brachytherapy) or radioisotopes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRef\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\u003eBeam radiation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.424(0.774\u0026ndash;2.623)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.126(0.597\u0026ndash;2.122)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.402(0.729\u0026ndash;2.696)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.080(0.544\u0026ndash;2.146)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.825\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCombination of beam with implants or isotopes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.887(0.735\u0026ndash;4.845)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.501(0.552\u0026ndash;4.083)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.686(0.591\u0026ndash;4.806)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.234(0.395\u0026ndash;3.851)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.718\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRadiation,NOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.771(0.664\u0026ndash;11.565)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.568(0.585\u0026ndash;11.266)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.123(0.744\u0026ndash;13.107)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.778(0.618\u0026ndash;12.478)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.945(1.295\u0026ndash;2.921)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.502(0.950\u0026ndash;2.376)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.822(1.176\u0026ndash;2.823)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.413(0.860\u0026ndash;2.323)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.173\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChemotherapy\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\u003eNo/unknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRef\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.411(0.291\u0026ndash;0.581)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.557(0.370\u0026ndash;0.839)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.423(0.290\u0026ndash;0.618)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.553(0.354\u0026ndash;0.866)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eAbbreviations: NOS, not otherwise significant. OS,overall survival.CSS,specific cancer survival. Bold values indicate significance at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAdditionally, in stage IA patients with malignant peritoneal cytology, adjuvant chemotherapy could improve the survival outcomes (OS: P\u0026thinsp;=\u0026thinsp;0.025; CSS: P\u0026thinsp;=\u0026thinsp;0.038) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA;\u003cb\u003eB\u003c/b\u003e). Of note, in stage IA patients with negative peritoneal cytology, chemotherapy was a good prognostic factor for OS (P\u0026thinsp;=\u0026thinsp;0.001) but not for CSS (P\u0026thinsp;=\u0026thinsp;0.300) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC;\u003cb\u003eD\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eOur study found that malignant peritoneal cytology was significantly correlated with shorter OS and CSS in early-stage endometrial clear cell carcinoma and serous carcinoma. Moreover, the survival effect of adjuvant chemotherapy may differ depending on peritoneal cytology status for early-stage endometrial clear cell carcinoma and serous carcinoma.\u003c/p\u003e \u003cp\u003eIn our study, malignant peritoneal cytology was seen in 10.2% of stage I-II ECCC and SC, compared to 6.0\u0026ndash;10.9% which has been reported in prior studies(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR18 CR19 CR20\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). This prevalence is far higher than in early-stage endometrioid endometrial cancer, where malignant peritoneal cytology is reported to be around 5%(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). One possible mechanism of malignant peritoneal cytology is the retrograde spread of tumor cells via the fallopian tubes. A study of 4489 EC patients, including 686 SC patients and 172 CCC patients, revealed that tubal ligation is associated with decreased risk of peritoneal tumor metastasis (GOG-210)(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). The risk reduction is much more significant in SC group than endometroid histology (SC: OR 0.28, 95% CI 0.11\u0026ndash;0.68; Low-grade endometroid: OR 1.27, 95% CI 0.41\u0026ndash;3.89). In the CCC group, although no statistically significant conclusions can be drawn due to the small number of CCC patients, CCC patients with tubal ligation tend to have a lower risk of peritoneal tumor metastasis (OR 0.27, 95% CI 0.00-2.24). Non-endometrioid EC is more likely to have trans-tubal spread, which may explain the higher incidence of malignant peritoneal cytology in SC and CCC than endometrioid tumors. Based on a SEER study(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), the increased risk of malignant peritoneal cytology is associated with diagnosis at an older age (\u0026gt;\u0026thinsp;78 years old), serous histology, and larger tumor size (4.1-6.0cm vs. \u0026lt;2cm) in stage I non-endometrioid EC. Our study, however, failed to find an association between the above factors and malignant peritoneal cytology, which is consistent with several studies targeted SC/CCC histology (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur study demonstrated that malignant peritoneal cytology was a poor prognostic factor for stage I -II ECCC and SC histology, which was in line with the results of previous studies, but our study specifically targeted SC and CCC groups and the sample size was larger(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). A big-data SEER analysis reported by Matsuo K, et al. revealed that malignant peritoneal cytology was associated with a nearly two-fold increase in all-cause mortality risk compared to negative peritoneal cytology (5-year rates, 63.4% versus 80.2%, HR 2.18, 95% CI 1.78\u0026ndash;2.66) in stage I non-endometrioid EC(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). In an analysis of a large cohort of stage I SC/CCC patients with long-term follow-up, Jeans EB, et al. demonstrated any recurrence was worse for tumors of at least 3.5 cm (HR 3.8, 95%CI 1.3\u0026ndash;11.7, p\u0026thinsp;=\u0026thinsp;0.02) and patients with positive/suspicious cytology (HR 4.4, 95%CI 1.5 to 12.4, p\u0026thinsp;\u0026le;\u0026thinsp;0.01), and multivariate modeling showed worse any recurrence with positive/suspicious cytology after adjusting for the effect of age(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). A recent study of 101 patients with stage I SC and CCC showed that patients with malignant cytology had a higher likelihood of peritoneal recurrence and a shorter time to relapse (13 vs. 38 months, p\u0026thinsp;=\u0026thinsp;0.022), as compared to patients with negative cytology(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). A retrospective study of 148 patients diagnosed with uterine serous carcinoma reported malignant peritoneal cytology had a statistically significant effect on OS (HR: 2.09, 95% CI 1.19\u0026ndash;3.68) and on CSS (HR: 2.02, 95% CI 1.06\u0026ndash;3.82), but the study included stage III SC patients (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). A study enrolling patients with stage I-II uterine serous carcinoma without adjuvant therapy demonstrated malignant peritoneal cytology was significant prognosticators (DFS: HR 4.24; 95% CI 1.56\u0026ndash;11.50; p\u0026thinsp;=\u0026thinsp;0.005; OS: HR 4.96; 95% CI 1.34\u0026ndash;18.30; p\u0026thinsp;=\u0026thinsp;0.017)(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur study explored the prognostic value of malignant peritoneal cytology in not only early-stage non-endometrioid EC patients but also in various subgroups stratified based on stage and histological type. In the subgroup analyses, malignant peritoneal cytology was associated with decreased OS and CSS in serous, clear cell histology group, and stage IA disease, but not for stage IB or stage II disease, which was consistent with the big-data results reported by Matsuo K, et al(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The previous retrospective study on 68 cases with USC without adjuvant therapy also showed that malignant peritoneal cytology had significant worse prognostic impact on OS (p\u0026thinsp;=\u0026thinsp;0.0012) and DFS (p\u0026thinsp;=\u0026thinsp;0.0001) in stage IA disease (n\u0026thinsp;=\u0026thinsp;42), but not in stage IB (n\u0026thinsp;=\u0026thinsp;7) (OS: p\u0026thinsp;=\u0026thinsp;0.722; DFS: p\u0026thinsp;=\u0026thinsp;0.911) and II (n\u0026thinsp;=\u0026thinsp;19) (OS: p\u0026thinsp;=\u0026thinsp;0.48; DFS : p\u0026thinsp;=\u0026thinsp;0.85)(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Yang J, et al, however, reported that the detrimental effects of malignant cytology on survival were more prominent in patients with stage IB disease. Notably, the limited number of patients with malignant peritoneal cytology may result in a few underpowered analyses in the study reported by Yang J, et al(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAdjuvant therapy for early-stage endometrial clear cell carcinoma and serous carcinoma is highly individualized, and the role of chemotherapy remains controversial. Previous studies have shown that chemotherapy could improve the prognosis of patients with stage I SC and CCC(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). These study, however, did not consider peritoneal cytology as a stratification factor to explore the role of chemotherapy. In our study, patients with malignant peritoneal cytology tended to receive adjuvant chemotherapy, and subgroup analysis found that malignant peritoneal cytology was an adverse prognostic factor in SC/CCC patients with stage IA, so we further explored whether adjuvant chemotherapy could improve the prognosis of patients with malignant peritoneal cytology in stage IA. We found that in stage IA patients with malignant peritoneal cytology, those who received chemotherapy had longer OS (p\u0026thinsp;=\u0026thinsp;0.025) and CSS (p\u0026thinsp;=\u0026thinsp;0.038), and for those with negative peritoneal cytology, chemotherapy improved OS (p\u0026thinsp;=\u0026thinsp;0.001) but not CSS (p\u0026thinsp;=\u0026thinsp;0.300). Therefore, we believed that SC and CCC patients with stage IA and malignant peritoneal cytology could be considered for chemotherapy. Our finding was in accordance with the NCCN recommendation. According to the 2023 NCCN guideline, noninvasive stage IA CCC and SC are stratified according to peritoneal cytology results for tailored adjuvant therapy strategies, and systemic therapy and vaginal brachytherapy is recommended if positive washings(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Additionally, for patients with invasive stage IA, systemic therapy could be considered regardless of peritoneal cytology(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA recent retrospective study revealed that chemotherapy did not improve RFS or OS in type II ECs (SC: n\u0026thinsp;=\u0026thinsp;22, CCC: n\u0026thinsp;=\u0026thinsp;12) with stage IA and malignant peritoneal cytology. Although the results were not statistically significant, it could be found that the 5-year relapse-free survival rate and 5-year overall survival rate in the chemotherapy group were higher than those in the non-chemotherapy group (RFS:85.2% vs. 66.7%, p\u0026thinsp;=\u0026thinsp;0.11; OS: 91.9% vs. 77.8%, p\u0026thinsp;=\u0026thinsp;0.15), so it may be better to treat them with adjuvant chemotherapy(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). An observational retrospective study of 16,851 stage I-II ECs including 973 serous carcinomas and 190 clear cell carcinomas revealed that adjuvant chemotherapy was associated with increased overall survival in early-stage EC patients with malignant peritoneal cytology (HR 0.62, 95%CI 0.40\u0026ndash;0.95, P\u0026thinsp;=\u0026thinsp;0.03). However, studies have not fully discussed which histologic subtype of early-stage patients with malignant peritoneal cytology may be able to experience increased survival with adjuvant chemotherapy(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). A study, involving stage I SC and CCC patients who had received adjuvant vaginal cuff brachytherapy and/or chemotherapy, reported that positive/suspicious cytology were at increased risk for relapse and worse survival, and should be considered for additional upfront adjuvant treatments, such as platinum-based chemotherapy(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). However, the role of chemotherapy has not been individually investigated in stage IA patients in this analysis(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). For early-stage non-endometrioid endometrial cancer with negative peritoneal cytology, Matsuo K, et al. stated that women who received chemotherapy-based postoperative therapy had higher 5-year OS rates compared to those received whole pelvic irradiation (79.6% for chemotherapy\u0026thinsp;\u0026plusmn;\u0026thinsp;brachytherapy, 77.4% for chemotherapy with whole pelvic irradiation, and 56.9% for whole pelvic irradiation, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001)(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). However, a study reported by Tate K, et al. revealed that patients with stage IA or IB USC showing negative peritoneal cytology might have an extremely favorable prognosis (5-year DFS rate:88.8%; 5-year OS rate:93.6%) and did not need any adjuvant therapies(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). More clinical studies are needed to investigate the significance of adjuvant chemotherapy in patients with stage IA non-endometrioid endometrial cancer with negative peritoneal cytology.\u003c/p\u003e \u003cp\u003eStrengths of the current study include: this was a population-based analysis with the large sample size for endometrial clear cell carcinoma and serous carcinoma; the long follow-up period; several subgroup analyses with stage and histologic type as stratification factors enhanced the interpretation of the study results; the analytic approach with propensity score matching and propensity score inverse probability of treatment weighting enriched the statistical rigor.\u003c/p\u003e \u003cp\u003eAdditionally, our study does have several limitations. Predominantly, it was a retrospective study with inherent unmeasured bias. For example, details of surgical-pathological factors such as lympho-vascular space invasion, and omental biopsy were not available in the SEER Program, but may be associated with the incidence of malignant peritoneal cytology as well as the oncologic outcomes. Second, the accuracy of malignant cytology results was unknown due to the lack of central pathology review in the study. Third, as this study only examined the U.S. population, whether our findings are generalizable to other study populations needs to be further examined. Fourth, per the SEER Program definition, cases with no and unknown status are grouped together in chemotherapy, and details of chemotherapy (regimen and cycle) were not available.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, the current study clearly showed that malignant peritoneal cytology was identified as an adverse prognostic factor in analyses of all early-stage endometrial clear cell carcinoma and serous carcinoma as well as in CCC histology type, SC histology type, and stage IA subgroup analyses. Based on the results of the present study, stage IA SC/CCC patients with malignant peritoneal cytology could further benefit from chemotherapy. Of note, peritoneal cytology results should not be taken in isolation to guide adjuvant therapy, and it should also be considered in combination with other risk factors for survival outcomes. Further prospective clinical trials are necessary to evaluate the efficacy of adjuvant therapy in stage IA SC/CCC groups.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eNot 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:\u0026nbsp;\u003c/strong\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u0026nbsp;\u003c/strong\u003eXinyue Tang: Proiect development, Data collection, Manuscript writing. Na Li: Data collection. Yuanjing Hu: Project development. All the authors have reviewed the final draft of the manuscript and approved it for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information (optional)Compliance with Ethical Standards :\u003c/strong\u003eNot Applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSiegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA: a cancer journal for clinicians. 2023;73(1):17-48.\u003c/li\u003e\n\u003cli\u003eJeans EB, Breen WG, Mullikin TC, Looker BA, Mariani A, Keeney GL, et al. Adjuvant brachytherapy for FIGO stage I serous or clear cell endometrial cancer. International journal of gynecological cancer : official journal of the International Gynecological Cancer Society. 2021;31(6):859-67.\u003c/li\u003e\n\u003cli\u003eBogani G, Ray-Coquard I, Concin N, Ngoi NYL, Morice P, Enomoto T, et al. Clear cell carcinoma of the endometrium. Gynecologic oncology. 2022;164(3):658-66.\u003c/li\u003e\n\u003cli\u003eBogani G, Ray-Coquard I, Concin N, Ngoi NYL, Morice P, Enomoto T, et al. Uterine serous carcinoma. Gynecologic oncology. 2021;162(1):226-34.\u003c/li\u003e\n\u003cli\u003eOaknin A, Bosse TJ, Creutzberg CL, Giornelli G, Harter P, Joly F, et al. Endometrial cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up. Annals of oncology : official journal of the European Society for Medical Oncology. 2022;33(9):860-77.\u003c/li\u003e\n\u003cli\u003eAbu-Rustum. NR, Yashar. CM, Bradley. K, Brooks. R, Campos SM. NCCN Guidelines\u0026reg;Uterine Neoplasms.Version 1.2023.https://www.nccn.org/professionals/physician_gls/pdf/uterine.pdf.\u003c/li\u003e\n\u003cli\u003eMatsuo K, Nusbaum DJ, Matsuzaki S, Chang EJ, Roman LD, Wright JD, et al. Malignant peritoneal cytology and increased mortality risk in stage I non-endometrioid endometrial cancer. Gynecologic oncology. 2020;159(1):43-51.\u003c/li\u003e\n\u003cli\u003eMatsuo K, Yabuno A, Hom MS, Shida M, Kakuda M, Adachi S, et al. Significance of abnormal peritoneal cytology on survival of women with stage I-II endometrioid endometrial cancer. Gynecologic oncology. 2018;149(2):301-9.\u003c/li\u003e\n\u003cli\u003eSeagle BL, Alexander AL, Lantsman T, Shahabi S. Prognosis and treatment of positive peritoneal cytology in early endometrial cancer: matched cohort analyses from the National Cancer Database. American journal of obstetrics and gynecology. 2018;218(3):329.e1-.e15.\u003c/li\u003e\n\u003cli\u003eTakenaka M, Kamii M, Iida Y, Yanaihara N, Suzuki J, Takahashi K, et al. Re-thinking the prognostic significance of positive peritoneal cytology in endometrial cancer. Gynecologic oncology. 2021;161(1):135-42.\u003c/li\u003e\n\u003cli\u003eMatsuo K, Matsuzaki S, Nusbaum DJ, Machida H, Nagase Y, Grubbs BH, et al. Malignant peritoneal cytology and decreased survival of women with stage I endometrioid endometrial cancer. European journal of cancer (Oxford, England : 1990). 2020;133:33-46.\u003c/li\u003e\n\u003cli\u003eTate K, Yoshida H, Ishikawa M, Uehara T, Ikeda SI, Hiraoka N, et al. Prognostic factors for patients with early-stage uterine serous carcinoma without adjuvant therapy. Journal of gynecologic oncology. 2018;29(3):e34.\u003c/li\u003e\n\u003cli\u003eGarg G, Gao F, Wright JD, Hagemann AR, Mutch DG, Powell MA. Positive peritoneal cytology is an independent risk-factor in early stage endometrial cancer. Gynecologic oncology. 2013;128(1):77-82.\u003c/li\u003e\n\u003cli\u003eSurveillance, Epidemiology, and End Results (SEER) Program (www.seer.cancer.gov) SEER*Stat Database: Incidence - SEER Research Plus Data, 17 Registries, Nov 2021 Sub (2000-2019) - Linked To County Attributes - Time Dependent (1990-2019) Income/Rurality, 1969-2020 Counties, National Cancer Institute, DCCPS, Surveillance Research Program, released April 2022, based on the November 2021 submission.\u003c/li\u003e\n\u003cli\u003eNational Cancer Registrars Association. http://www.ncra-usa.org/. Accessed 23 Jul 2020.\u003c/li\u003e\n\u003cli\u003eAustin PC, Stuart EA. Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies. Statistics in medicine. 2015;34(28):3661-79.\u003c/li\u003e\n\u003cli\u003eMysona DP, Tran LKH, Tran PMH, Gehrig PA, Van Le L, Ghamande S, et al. Clinical calculator predictive of chemotherapy benefit in stage 1A uterine papillary serous cancers. Gynecologic oncology. 2020;156(1):77-84.\u003c/li\u003e\n\u003cli\u003eOrellana TJ, Garrett AA, Soong TR, Rives T, Courtney-Brooks M, Taylor SE, et al. The role of adjuvant treatment for early-stage uterine clear cell carcinomas. Gynecologic oncology. 2023;170:77-83.\u003c/li\u003e\n\u003cli\u003eQu XM, Velker VM, Leung E, Kwon JS, Elshaikh MA, Kong I, et al. The role of adjuvant therapy in stage IA serous and clear cell uterine cancer: A multi-institutional pooled analysis. Gynecologic oncology. 2018;149(2):283-90.\u003c/li\u003e\n\u003cli\u003eDitto A, Leone Roberti Maggiore U, Lopez S, Martinelli F, Bogani G, Lo Vullo S, et al. Uterine serous carcinoma: role of surgery, risk factors and oncologic outcomes. Experience of a tertiary center. European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology. 2022;48(1):268-74.\u003c/li\u003e\n\u003cli\u003eYang J, Yang J, Cao D, Wu M, Xiang Y. Prognostic Value of Peritoneal Cytology in Stage I Serous and Clear Cell Carcinoma of the Endometrium. Journal of clinical medicine. 2023;12(4).\u003c/li\u003e\n\u003cli\u003eFelix AS, Brinton LA, McMeekin DS, Creasman WT, Mutch D, Cohn DE, et al. Relationships of Tubal Ligation to Endometrial Carcinoma Stage and Mortality in the NRG Oncology/ Gynecologic Oncology Group 210 Trial. Journal of the National Cancer Institute. 2015;107(9).\u003c/li\u003e\n\u003cli\u003eCorey L, Fucinari J, Elshaikh M, Schultz D, Musallam R, Zaiem F, et al. Impact of positive cytology in uterine serous carcinoma: A reassessment. Gynecologic oncology reports. 2021;37:100830.\u003c/li\u003e\n\u003cli\u003eKanno M, Yunokawa M, Nakabayashi M, Omi M, Ikki A, Mizusaki M, et al. Prognosis and adjuvant chemotherapy for patients with positive peritoneal cytology in stage IA endometrial cancer. Scientific reports. 2022;12(1):166.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Clear cell endometrial cancer, Serous endometrial cancer, Peritoneal cytology, Survival outcomes","lastPublishedDoi":"10.21203/rs.3.rs-3214955/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3214955/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo investigate the influence of malignant peritoneal cytology (MPC) on the prognosis of early-stage patients with endometrial clear cell carcinoma(CCC) and serous carcinoma(SC), and the value of chemotherapy in their treatment.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA retrospective observational cohort study was conducted by querying the National Cancer Institute\u0026rsquo;s Surveillance, Epidemiology, and End Results Program from 2010 to 2019. Women with early-stage CCC and SC with available peritoneal cytology results were enrolled. Propensity score matching(PSM) and propensity score inverse probability of treatment weighting (IPTW) was used to balance the measured covariates in each sub-cohort.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 3,616 eligible patients were included, and 368 patients had MPC (10.2%). Women with MPC were more likely to receive postoperative chemotherapy (OR 2.033;95%CI 1.589\u0026ndash;2.602). In PSM model, MPC had worse overall survival(OS) and cancer-specific survival (CSS) (All,p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The 5-year OS rates were 56.5% for women with MPC and 74.4% for those with negative peritoneal cytology, and the 5-year CSS rates were 60.8% versus 80.0%(All, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). In the subgroup analyses, MPC was associated with decreased OS and CSS in serous, clear cell histology group, and stage IA cases(All,p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but not for stage IB or stage II disease. In multivariate analysis, chemotherapy improved the prognosis of patients with MPC(OS:p\u0026thinsp;=\u0026thinsp;0.005; CSS:p\u0026thinsp;=\u0026thinsp;0.010). Additionally, in stage IA subgroup, chemotherapy improved survival outcomes in patients with MPC(OS:P\u0026thinsp;=\u0026thinsp;0.025; CSS:P\u0026thinsp;=\u0026thinsp;0.038), in NPC patients, however, chemotherapy was a good prognostic factor for OS (P\u0026thinsp;=\u0026thinsp;0.001) but not for CSS(P\u0026thinsp;=\u0026thinsp;0.300).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eMPC was a prognostic factor for decreased survival in early-stage endometrial CCC and SC, and those with MPC could further benefit from chemotherapy.\u003c/p\u003e","manuscriptTitle":"Prognosis and adjuvant chemotherapy for patients with malignant peritoneal cytology in early-stage non-endometrioid endometrial cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-08-25 17:01:38","doi":"10.21203/rs.3.rs-3214955/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"20f33f4f-ecb4-485f-9485-0644dfe4dd47","owner":[],"postedDate":"August 25th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-09-19T04:59:26+00:00","versionOfRecord":[],"versionCreatedAt":"2023-08-25 17:01:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3214955","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3214955","identity":"rs-3214955","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}