Impact of time from diagnosis to chemotherapy on prognosis in advanced pancreatic cancer

Impact of time from diagnosis to chemotherapy on prognosis in advanced pancreatic 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 Impact of time from diagnosis to chemotherapy on prognosis in advanced pancreatic cancer Tsutomu Nishida, Aya Sugimoto, Kana Hosokawa, Haruka Masuda, Satoru Okabe, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3689606/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Feb, 2024 Read the published version in Japanese Journal of Clinical Oncology → Version 1 posted You are reading this latest preprint version Abstract Purpose Due to the aggressive nature and poor prognosis of advanced pancreatic cancer (PC), prompt initiation of treatment is critical. We investigated the effect of the survival time interval between cancer diagnosis and initiation of chemotherapy in patients with advanced PC. Methods In this retrospective, single-center study, consecutive patients with advanced PC between April 2013 and March 2022 were analyzed. Data were extracted from the electronic medical records of patients who received chemotherapy for metastatic, locally advanced, or resectable PC or who received chemotherapy due to either being intolerant of or declining surgery. Chemotherapy followed clinical practice guidelines. We compared overall survival between two groups: the early waiting time (WT) group (WT ≤ 30 days from diagnosis to chemotherapy initiation) and the elective WT group (WT ≥ 31 days). Prognostic factors, including biliary drainage, were considered. The impact of WT on survival was assessed by univariate and multivariate analyses with Cox proportional hazard models. A 1:1 propensity score matching (PSM) approach balanced bias, accounting for significant poor prognosis factors, age and sex. Results The study involved 137 patients. Overall survival exhibited no statistically significant difference between the early and elective WT groups (207 and 261 days, P = 0.2518). Univariate and multivariate analyses identified poor performance status and metastasis presence as predictors of worse prognosis. This finding persisted post PSM (275 and 222 days, P = 0. 8223). Conclusions Our study revealed that initiating chemotherapy within 30 days of diagnosis, as opposed to more than 30 days later, does not significantly affect treatment efficacy. pancreatic cancer waiting time survival prognosis chemotherapy biliary drainage Figures Figure 1 Figure 2 Figure 3 Introduction Timely initiation of treatment is critical for patients with advanced cancer, particularly those with potentially curable malignancies. Prompt disease assessment and appropriate treatment while considering psychological needs are crucial in such cases. However, unresectable advanced cancers exhibit considerable variability in disease status at diagnosis, with the primary treatment goals being symptom palliation and prolongation of life. Thus, in addition to patient psychological considerations, the pathophysiology and treatment objectives differ significantly from those of resectable advanced cancers. Pancreatic cancer (PC) is a particularly challenging disease owing to its aggressive nature and poor prognosis. Timely initiation of treatment is critical for patients with advanced PC. Some studies have suggested that delaying the start of chemotherapy after diagnosis may not significantly affect subsequent prognosis [ 1 ] [ 2 ]. However, despite a growing body of research, conclusive evidence remains elusive. While the impact of treatment timing has been studied in other cancers, the evidence to date has been inconclusive. Our recent study, which focused on advanced gastric cancer in Japanese patients, found that the time between diagnosis and the initiation of chemotherapy did not significantly affect subsequent outcomes. Initiating treatment after assessment, including biomarker confirmation, may be a reasonable approach if the disease is stable [ 3 ]. However, differences in the nature of the cancers and specific issues such as obstructive jaundice, cholangitis, and gastrointestinal transit obstruction in PC prevent direct extrapolation of findings. Moreover, the clinical course of unresectable advanced PC exhibits high variability, which is influenced by the tumor size, extent of spread, and associated complications. Additionally, patients are often older, and this diversity needs to be evaluated. Therefore, the significance of treatment timing may be obscured, making it imperative to study the direct effects of early chemotherapy initiation on prognosis, particularly for this specific cancer type. Therefore, this study was designed to explore the subclinical impact of the time between cancer diagnosis and the start of chemotherapy, including biliary drainage procedures, on the prognosis of advanced PC. By elucidating the relationship between treatment timing and patient outcomes, we aspire to provide valuable insights that will inform clinical decision making and enhance the management of this challenging disease. Materials and methods This was a single-center retrospective study. We studied consecutive patients with advanced PC who visited the Toyonaka Municipal Hospital between April 2013 and March 2022. Patients were diagnosed with advanced PC using computed tomography, magnetic resonance imaging, and tumor markers. The patients had a pathology confirmed as adenocarcinoma by endoscopic ultrasound-guided fine-needle aspiration. They were selected from the database, and data were collected from the electronic medical records of our hospital (MegaOak online imaging system, NEC, Japan). Of those selected, we enrolled consecutive patients who were diagnosed and treated for metastatic, locally advanced, or resectable PC and who were intolerant of or refused surgery. Chemotherapy recommendations were based on the Pancreatic Cancer Clinical Practice Guidelines of the Japan Pancreas Society, including gemcitabine and nab-paclitaxel (GnP), nanoliposomal-irinotecan + 5-FU/LV (5-fluorouracil/leucovorin), modified FOLFIRINOX (5-fluorouracil, leucovorin, irinotecan, and oxaliplatin), S1 alone, or gemcitabine (GEM) alone. Data collection The following data were collected from the medical records at the time of PC diagnosis. Patient-related factors included sex, age, body mass index (BMI), body weight loss, Eastern Cooperative Oncology Group (ECOG) score, performance status, and geriatric assessment tools, including the Geriatric (G)8, Vulnerable Elders Survey (VES)-13, age-adjusted Charlson Comorbidity Index (ACCI), neutrophil-to-lymphocyte ratio (NLR), and modified Glasgow Prognostic Score (mGPS). Body weight loss was considered significant if the patient had lost more than 5% of their body weight over the past six months or more than 2% of their body weight with a body mass index (BMI) of less than 20 kg/m 2 at the time of PC diagnosis, established using the diagnostic criteria proposed by Fearon et al. [ 4 ]. Factors related to PC were resectability or the presence of distant metastasis, biliary drainage, and tumor markers (serum carcinoembryonic antigen (CEA) and carbohydrate antigen (CA)) 19 − 9). Outcomes and definition Waiting time (WT) was defined as the interval between the diagnosis on imaging and the initiation of chemotherapy. The date of diagnosis was defined as the date of the first detection of PC using computed tomography or magnetic resonance imaging. The primary endpoint was the effect of WT on overall survival. The secondary endpoint was the prognostic impact of clinical factors, including biliary drainage. The last day of observation was July 15, 2023. Ethical considerations This study was conducted in accordance with the tenets of the Declaration of Helsinki and approved by the Institutional Review Board of Toyonaka Municipal Hospital (No. 2023-08-07). The requirement for informed consent was waived using the opt-out method on our hospital website. Statistical analysis The median and interquartile range (IQR) were reported for continuous variables. We used a matrix imputation method to impute missing continuous variables. Wilcoxon signed-rank tests were used to assess differences in continuous variables. Categorical variables are summarized as frequencies (percentages). Fisher's exact test was used to assess differences in categorical variables. Overall survival was estimated using the Kaplan–‒Meier method and compared using the log-rank test and Wilcoxon tests. To evaluate the influence of WT on survival, we used univariate and multivariate analyses with Cox proportional hazards models to assess whether the factors affected prognosis, providing hazard ratios (HRs) with 95% confidence intervals (CIs). Statistical sample size calculations were not performed due to a lack of evidence on which to base them and the retrospective study design. We set each assessment parameter to the following cutoff values according to previous reports. The cutoff values for the VES-13 and NLR were three [ 5 ] and four [ 6 ], respectively. We divided the ECOG PS into PS0-1 and PS ≥ 2. The total G8 score ranges from 0 to 17, with higher scores indicating a better health status. A G8 score > 14 was considered normal [ 7 ]. In the present study, we classified ACCI as low-risk (ACCI score of 0–1), moderate-risk (ACCI score of 2–3), and high-risk (ACCI score of 4 or more). The cutoff value of the mGPS was 1 [ 8 ]. We set the cutoff value of CA19-9 to 1000 IU/ml. We then calculated propensity scores for prognosis with these significant factors and created 1:1 matched study groups with a caliper width of 0.05 to minimize the effect of potential selection bias. Similarly, the early WT group was compared with the elective WT group. All calculated P values were two-tailed, and a P value < 0.05 was considered to indicate statistical significance. Statistical analysis was performed using JMP statistical software (ver. 16, SAS Institute Inc., Cary, NC, USA). Results Patient characteristics Between April 2013 and March 2022, 504 patients diagnosed with PC were admitted to our department. A total of 119 patients underwent surgery; 83 patients received the best supportive care following evaluation; 33 patients began treatment in other hospitals and were subsequently transferred to our hospital; 27 patients were referred to other hospitals after the initial evaluation in our department; four patients received chemoradiotherapy; 59 patients did not have available data on body weight information; and 42 patients were lost to follow-up. Therefore, 367 patients were excluded, and 137 patients who received chemotherapy were enrolled (Fig. 1). The baseline characteristics of the enrolled patients are shown in Table 1 . At the time of the initial evaluation for PC, the median age of the patients was 72 years (IQR: 67–77 years), and 55.5% of the patients were men. The ECOG PS performance status was 0 in 111 patients (81.0%), 1 in 23 patients (16.8%), and 2 in 3 patients (2.2%). The median BMI was 21.4 kg/m 2 (19.2, 23.4), and weight loss at diagnosis was 46.7% (64/137). The median psoas muscle mass and PMI were 930 cm 2 (728, 1301) and 3.8 cm 2 /m 2 (3.0, 4.8), respectively. Forty-five patients had diabetes, and 61 patients had chronic kidney disease. Table 1 Clinical characteristics of patients with pancreatic cancer Characteristics, n (%) Patient, n 137 Patient related factors Age, median (years) 72 (67, 77) Male sex, n (%) 76 (55.5) ECOG PS 0, 1, 2, n (%) 111 (81.0), 23 (16.8), 3 (2.2) BMI (kg/m 2 ), median (IQR) 21.4 (19.2, 23.4) Body weight loss, yes, n (%) 64 (46.7) Psoas muscle mass (cm 2 ), median (IQR) 930 (728, 1301) PMI (cm 2 /m 2 ), median (IQR) 3.8 (3.0, 4.8) Comorbidity Diabetes mellitus, yes, n (%) 45 (32.8) Chronic kidney disease, yes, n (%) 61 (44.5) Screening tool for health problems G8, median (IQR) 9.4 (9.4. 9.4) VES-13, median (IQR) 3.1 (3.1, 3.1) ACCI, median (IQR) 4 (4, 5) NLR, median (IQR) 3.3 (2.4, 4.6) mGPS, 0/1/2 92 (67.1), 32 (23.4), 13 (9.5) Cancer related factors Main tumor location Head, body, body/tail, tail 48 (35.0), 44 (32.1), 4 (2.9), 41 (29.9) Resectability, R/UR-LA/UR-M 3 (2.2), 41 (29.9), 93 (67.9) Biliary drainage, yes, n (%) 47 (34.3) Duodenal stenosis prior to 1st line chemotherapy, n (%) 4 (2.9) Gastroduodenal stenting prior to chemotherapy, n (%) 3 (2.2) Bypass operation prior to chemotherapy, n (%) 1 (0.7) CEA, (U/mL) median (IQR) 6.8 (3.4, 25.1) CA19-9, (U/mL) median (IQR) 1311 (77.5, 11710) Waiting time, days, median (IQR) 26 (17.5, 37) Observation period, days, median (IQR) 226 (137, 367) All death during observation period, n (%) 129 (94.2) Chemotherapy regimen S1, n (%) 7 (5.1) GEM, n (%) 37 (27.0) GnP, n (%) 82 (59.9) mFOLFIRINOX, n (%) 11 (8.0) Secondary chemotherapy transition rate 58 (42.3) S1, n (%) 25 (43.1) GEM, n (%) 14 (24.1) GnP, n (%) 5 (8.6) mFOLFIRINOX, n (%) 3 (5.2) nal-IRI + 5FU/LV, n (%) 11 (19.0) ECOG: Eastern Cooperative Oncology Group, PS: performance status , BMI: body mass index, PMI: psoas muscle index, R: resectable, UR: unresectable, LA: locally advanced, M: metastasis, G8: Geriatric 8, VES-13: vulnerable elders survey, ACCI: age-adjusted Charlson Comorbidity Index, NLR: neutrophil-to-lymphocyte ratio, mGPS: modified Glasgow Prognostic Score, GEM: gemcitabine , GnP: gemcitabine and nab-paclitaxel, nal-IRI + 5FU/LV: nanoliposomal-irinotecan + 5-fluorouracil/leucovorin, FOLFIRINOX:5-fluorouracil, leucovorin, irinotecan, and oxaliplatin Regarding screening tools for health problems, the median (IQR) was 9.4 for G8, 3.1 for VES-13, 4 for ACCI, and 3.3 for NLR. The mGPS 0/1/2 was 92 (67.1%)/32 (23.4%)/13 (9.5%). Regarding cancer-related profiles, the most dominant tumor location was the pancreatic head in 48 patients (35.0%), followed by the pancreatic body in 44 patients (32.1%). Resectability was classified as resectable in three patients, unresectable locally advanced disease in 41, and unresectable metastatic disease in 93. Biliary drainage was needed in 47 patients (34.3%), and four patients (2.9%) needed gastroduodenal stent placement or bypass surgery for duodenal obstruction due to PC during the initial evaluation. The median CEA and CA19-9 levels were 6.8 U/mL (3. 4, 25.1) and 1311 U/mL (77.5, 11710), respectively. The median waiting time was 26 (17.5, 37) days. Therefore, we grouped the patients into early WT and elective WT groups using a 30-day cutoff. The observation period from clinical diagnosis to the last visit ranged from 29 to 1611 days (median, 226 days; IQR, 137–367 days). Of these, 129 (94.2%) died during follow-up. Of the 137 patients who received chemotherapy, 82 received GnP, 11 received mFOLFIRINOX, 7 received S1, and 37 received GEM as initial chemotherapy. The secondary chemotherapy transition rate was 42.3%. (Table 1 ). Table 2 compares the characteristics of the patients in the early WT and elective WT groups. The early WT group included 85 patients, and the elective WT group included 52 patients. There were no significant differences in age, sex, ECOG-PS, BMI, psoas muscle mass, PMI, body weight loss, diabetes, or chronic kidney disease. Regarding screening tools for health problems, the G8, VES-13, ACCI, and NLR did not differ between the groups, but the mGPS was significantly lower in the elective WT group. Regarding cancer-related factors, the presence of metastasis was significantly higher in the early WT group, and the CA19-9 level was significantly lower in the elective WT group than in the early WT group. (Table 2 ). There were no significant differences in the first-line chemotherapy regimen or secondary chemotherapy transition rates between the groups. Table 2 Comparison of characteristics of patients in the early waiting time and elective waiting time groups Characteristics, n (%) Early waiting time Elective waiting time P value Patient, n (%) 85 (62.0) 52 (38.0) Patient related factors Age, median (years) 72 (67.5, 77) 73 (67, 76.8) 0.7967 Male sex, n (%) 44 (51.8) 32 (61.5) 0.2917 ECOG PS 0, 1, 2, n (%) 67 (78.8)/15 (17.7)/3 (3.5) 44 (84.6)/8 (15.4)/0 (3.5) 0.3557 BMI (kg/m 2 ), median (IQR) 20.7 (18.4, 23.5) 21.8 (19.7, 23.4) 0.2811 Body weight loss, yes, n (%) 41 (48.2) 23 (44.2) 0.7251 Psoas muscle mass (cm 2 ), median (IQR) 885 (686, 1257) 1010(736, 1349) 0.1211 PMI (cm 2 /m 2 ), median (IQR) 3.6 (2.8, 4.6) 3.9 (3.1, 4.9) 0.1243 Comorbidity Diabetes mellitus, yes, n (%) 28 (29.4) 20 (38.5) 0.3488 Chronic kidney disease, yes, n (%) 38 (44.7) 23 (44.2) 0.9567 Screening tool for health problems G8, median (IQR) 9.4 (9.4,9.4) 9.4 (9.4,9.4) 0.4430 VES-13, median (IQR) 3.1 (2.5,3.1) 3.1 (3.1, 3.1) 0.4301 ACCI, median (IQR) 4 (3, 5) 4 (4, 5) 0.2116 NLR, median (IQR) 3.5 (2.6, 4.7) 3.1 (2.4, 4.5) 0.5419 mGPS, 0/1/2 50 (58.8), 26 (30.6), 9 (10.6) 42 (80.8), 6 (11.5), 4 (7.7) 0.0222 Cancer related factors Main tumor location Head, body, body/tail, tail 24 (28.2). 31 (36.5), 3 (3.5), 27 (31.8) 24 (46.2), 13 (25.0), 1 (1.9), 14 (26.9) 0.1858 Resectability, R/UR-LA/UR-M 0 (0)/23 (27.1)/62 (72.9) 3 (5.8)/18 (34.6)/62 (59.6) 0.0415 Biliary drainage, yes, n (%) 25 (29.4) 22 (42.3) 0.1404 Duodenal stenosis prior to 1st line chemotherapy, n (%) 1(1.2) 3 (5.8) 0.1530 CEA, (U/mL) median (IQR) 6.9 (3.5, 37.6) 6.3 (3.3, 23.3) 0.3108 CA19-9, (U/mL) median (IQR) 2156 (2001, 24413) 737 (9, 6348) 0.0016 Treatment and outcomes Waiting time, days, median (IQR) 20 (14, 23) 45 (35, 57) < 0.0001 Observation period, days, median (IQR) 207 (101, 362) 261 (172, 426) 0.0379 All death during observation period, n (%) 77 (90.6) 52 (100) 0.0241 Chemotherapy regimen 0.2692 S1, n (%) 3 (2.4) 5 (9.6) GEM, n (%) 23 (27.1) 14 (26.9) GnP, n (%) 52 (61.2) 30 (57.7) mFOLFIRINOX, n (%) 8 (9.4) 3 (5.8) Secondary chemotherapy transition rate 38 (44.7) 20 (38.5) 0.5932 S1, n (%) 15 (39.5) 10 (50.0) GEM, n (%) 9 (23.7) 5 (25.0) GnP, n (%) 3 (7.9) 2 (10.0) mFOLFIRINOX, n (%) 2 (5.3) 1 (5.0) nal-IRI + 5FU/LV, n (%) 9 (23.7) 2 (10.0) ECOG: Eastern Cooperative Oncology Group, PS: performance status , BMI: body mass index, PMI: psoas muscle index, R: resectable, UR: unresectable, LA: locally advanced, M: metastasis, G8: Geriatric 8, VES-13: vulnerable elders survey, ACCI: age-adjusted Charlson Comorbidity Index, NLR: neutrophil-to-lymphocyte ratio, mGPS: modified Glasgow Prognostic Score, GEM: gemcitabine, GnP: gemcitabine and nab-paclitaxel, nal-IRI + 5FU/LV: nanoliposomal-irinotecan + 5-fluorouracil/leucovorin, FOLFIRINOX:5-fluorouracil, leucovorin, irinotecan, and oxaliplatin Overall survival curves of patients in the early WT and elective WT groups The overall survival (OS) times of patients in the early WT and elective WT groups are shown in Fig. 2 . The median OS times (MST) were 207 and 261 days in the early and elective WT groups, respectively. There was no significant difference in OS between the two groups according to the log-rank test (P = 0.2518); however, there was a trend toward longer OS in the elective WT group according to the Wilcoxon test (P = 0.0646). Univariate and multivariate analyses with Cox proportional hazards models for predicting prognosis in patients with advanced pancreatic cancer. We evaluated the clinical factors that predicted PC prognosis. Univariate analysis showed that PS > 2, presence of metastasis, NLR > 3, mGPS 1/2, and higher CA19-9 levels were significantly associated with poor prognosis. However, longer waiting times, including the treatment of biliary drainage or duodenal obstruction, were not associated with a poor prognosis (Table 3 ). The results of the multivariate analysis adjusted for age and sex, including the five significant variables plus waiting time, biliary drainage, and duodenal obstruction, indicated that poor PS and the presence of metastasis were significantly associated with poor prognosis (Table 3 ). Table 3 Univariate and multivariate analyses with Cox proportional hazards models for clinical factors predicting pancreatic cancer prognosis Univariate Multivariate § Factors Reference HR 95% CI P value HR 95% CI P value Sex, Female Men 1.08 0.75–1.55 0.6962 Age ≥ 75 years < 75 years 1.05 0.72–1.53 0.7979 Waiting time Early 0.75 0.52–1.08 0.1249 0.96 0.63–1.46 0.8537 PS 0–1 8.4 2.5–28.2 0.0005 9.28 2.59–33.2 0.0006 Body weight loss, yes no 1.19 0.83–1.70 0.3484 Diabetes mellitus, yes no 0.99 0.68–1.44 0.9615 Chronic kidney disease*, yes no 1.25 0.87–1.79 0.2364 Biliary drainage, yes no 1.01 0.70–1.46 0.9520 0.95 0.63–1.43 0.7955 Duodenal obstruction, yes no 1.02 0.32–3.23 0.9676 1.34 0.40–4.6 0.6351 Meatastasis†, yes no 2.09 1.38–3.19 0.0006 1.91 1.23-3.00 0.0042 NLR ≥ 3 < 3 1.68 1.14–2.47 0.0090 1.26 0.82–1.94 0.2903 mGPS, 1–2 0 1.92 1.30–2.83 0.0011 1.46 0.92–2.31 0.1051 CA19-9, ≥ 1000 U/mL 14 0.43 0.06–3.08 0.3972 VES-13 ≥ 3 < 3 1.25 0.77–2.02 0.3732 ACCI, high risk Low to medium risk 0.96 0.63–1.47 0.8618 PMI, Low Normal 1.05 0.68–1.62 0.8162 *Chronic kidney disease is defined as an eGFR of less than 60 mL/min. †Among the three groups according to resectability, metastasis was a significantly poor prognostic factor, but there was no difference between locally advanced and resectable patients (resectable/locally advanced; HR 1.30, P = 0.4548). Therefore, we compared the two groups: patients with metastases and patients with resectable/locally advanced disease. §Age and sex adjusted UR: unresectable, M: metastasis, NLR: neutrophil-to-lymphocyte ratio, mGPS: modified Glasgow Prognostic Score, G8: Geriatric 8, VES-13: vulnerable elders survey, ACCI: age-adjusted Charlson Comorbidity Index, PMI: psoas muscle index Propensity score matching analysis Multivariate logistic analysis showed that poor PS and the presence of metastasis were significant independent risk factors for poor prognosis. We performed a 1:1 propensity score matching analysis to evaluate the impact of waiting time on predicting poor prognosis using the above two factors adjusted by age and sex by multivariate analysis. We obtained 27 matched patients in the early and elective WT groups. Table 4 shows the results of the propensity score matching. After propensity score matching, there were no significant differences between the groups. OS was evaluated in propensity score-matched patients in both groups. There was no significant difference in OS between the two groups, with median OS times of 275 and 222 days, respectively (log-rank P = 0.8223, Wilcoxon test P = 0.9098) (Fig. 3). Table 4 Comparison of characteristics of patients between early waiting time and elective waiting time groups after propensity score matching Propensity- matched cohort Early waiting time Elective waiting time P value Patient, n (%) 27 27 Patient related factors Age, median (years) 72 (68, 76) 73 (67, 76) 0.9171 Male sex, n (%) 15 (55.6) 17 (63.0) 0.7822 ECOG PS 0, 1, n (%) 27 (100), 0(0) 25 (92.6), 2 (7.4) 0.4906 BMI (kg/m 2 ), median (IQR) 21.9 (18.7, 23.4) 21.8 (20.3, 24.4) 0.6528 Body weight loss, yes, n (%) 17 (63.0) 14 (51.9) 0.5826 Psoas muscle mass (cm 2 ), median (IQR) 853 (784, 1287) 1025 (568, 1381) 0.5448 PMI (cm 2 /m 2 ), median (IQR) 3.5 (3.1, 4.7) 3.9 (2.9, 5.33) 0.6159 Comorbidity Diabetes mellitus, yes, n (%) 8 (29.6) 10 (37.0) 0.7734 Chronic kidney disease, yes, n (%) 14 (51.9) 11 (40.7) 0.5857 Screening tool for health problems G8, median (IQR) 9.4 (9.4, 9.4) 9.4 (9.4, 9.4) 0.6782 VES-13, median (IQR) 3.1 (3.1, 3.1) 3.1 (3.1, 3.1) 0.1487 ACCI, median (IQR) 4 (4, 5) 4 (4, 5) 0.8683 NLR, median (IQR) 3.2 (1.9, 4.1) 3.3 (2.9, 4.6) mGPS, 0/1/2 16 (59.3)/8 (29.6)/3 (11.1) 21 (77.8)/4 (14.8)/2 (7.4) 0.3314 Meatastasis†, yes 16 (59.3) 15 (55.6) 1.000 Biliary drainage, yes, n (%) 8 (29.6) 12 (44.4) 0.3983 Duodenal stenosis, n (%) 1 (3.7) 2 (7.4) 1.000 CEA, (U/mL) median (IQR) 6.2 (3.5, 23.8) 6.8 (4, 15.7) 0.6158 CA19-9, (U/mL) median (IQR) 1428 (149, 22136) 717 (4, 4588) 0.0717 Secondary chemotherapy transition rate 13 (48.2) 9 (33.3) 0.4064 *Chronic kidney disease is defined as an eGFR of less than 60 mL/min. UR: unresectable, M: metastasis, NLR: neutrophil-to-lymphocyte ratio, mGPS: modified Glasgow Prognostic Score, G8: Geriatric 8, VES-13: vulnerable elders survey, ACCI: age-adjusted Charlson Comorbidity Index, PMI: psoas muscle index Discussion Advanced PC often causes obstructive jaundice, gastrointestinal dysfunction, pain, cachexia, and weight loss at the time of diagnosis [ 9 ]. Chemotherapy should be promptly initiated after confirmation of advanced PC without surgical indications. However, the necessity to manage these patient complications may result in delayed chemotherapy initiation. Nonetheless, there is currently insufficient evidence to determine whether such treatment initiation delays impact prognosis. In this study, we aimed to ascertain the prognostic influence of the interval between cancer diagnosis and chemotherapy initiation in Japanese patients with advanced PC. The findings revealed that initiation of chemotherapy within 30 days after diagnosis did not significantly correlate with worse prognosis compared with commencing chemotherapy more than 30 days after diagnosis. Within our cohort, the early WT group exhibited a higher proportion of patients with metastatic disease and elevated CA19-9 levels than the selective WT group. However, the early WT group included more patients with lower mGPS scores. To address these background disparities, propensity score matching was employed, which consistently reinforced our results. These results suggest that delaying chemotherapy initiation might not substantially affect the prognosis of Japanese patients with advanced PC, even after biliary drainage for obstructive jaundice or cholangitis. Additionally, the survival curves for the early WT group were divided into subgroups of ≤ 14 days and 15–30 days or less, whereas the survival curves of the ≥ 31 days were divided into three groups. These results further validated the overlapping survival curves between the ≤ 14 days and the 15-30-day WT groups, supporting the rationale behind the 30-day cutoff in this study ( Supplementary Figure ). This observation implies that the conventional emphasis on initiating chemotherapy immediately after diagnosis might not yield the anticipated benefits in terms of overall survival and disease progression. These results offer valuable insights for clinical decision-making and may guide treatment strategies for this formidable disease. Effective management of complications that might lead to timely chemotherapy initiation is of paramount importance for patients’ subsequent prognosis. The current dearth of evidence has resulted in mixed and varying conclusions. Delays in adjuvant treatment initiation or overall treatment time have been correlated with worse survival outcomes in specific malignancies, including resectable stage I to II PC [ 10 ]. Investigations focused on the timing of adjuvant chemotherapy in PC have produced mixed results. A meta-analysis concluded that commencing adjuvant therapy within 20 days after surgery was correlated with improved overall survival [ 11 ]. However, the ESPAC-3 study found no notable outcome difference when adjuvant chemotherapy was delayed by up to 12 weeks to allow for postoperative recovery [ 12 ]. Even in terms of postoperative adjuvant chemotherapy for low-volume PC, the evidence within the PC realm remains inconsistent. The need to distinguish between patients with PC who are eligible for postoperative adjuvant chemotherapy and those who are unresectable for palliative chemotherapy, given their distinct tumor volumes and underlying conditions, renders the results of this study crucial. Obstructive jaundice and cholangitis, common complications of PC, can hinder timely chemotherapy initiation. In the present study, 47 (34.3%) patients needed biliary drainage prior to chemotherapy, more in the elective WT group than in the early WT group, but this difference was not significant (n = 25 (29.4%) vs. n = 22 (42.3%), P = 0.1405). Univariate and multivariate analyses also showed no effect on prognosis. Nakata et al. reported that in 169 Japanese patients with pancreatic head cancer, obstructive jaundice and total bilirubin levels > 3 mg/dL at diagnosis predicted unfavorable survival compared with nonjaundiced patients [ 13 ]. However, in 85 unresectable cases, survival was not significantly different between the jaundice and nonjaundice groups (MST, 5.2 vs. 5.3 months, respectively). A retrospective review by Lee et al. from four hospitals reported that delaying palliative chemotherapy initiation beyond a 2-week wait did not adversely affect the survival of patients with unresectable PC [ 1 ]. Conversely, patients with a ≤ 2-week waiting period who initially presented with jaundice exhibited worse OS than those with a waiting time of > 2 weeks. Lamarca et al. found that biliary stent-related events (SREs) during chemotherapy were observed in 43% of patients with pancreatic biliary tract cancer who received a stent at the commencement of palliative chemotherapy. Among these, there was a delay or discontinuation of chemotherapy in 41% as a result [ 14 ]. Patients with mild complications and no chemotherapy delay displayed longer OS than those with severe complications resulting in chemotherapy interruption or death (OS 11.6 vs. 4.4 months, P = 0.001). Interestingly, there was a trend toward longer survival in the SRE group, encompassing cholangitis or stent obstruction, than in the no-SRE group, although the differences were not statistically significant (OS 9.8 vs. 7.6 months, P = 0.0947). These findings indicate that the prognosis for advanced pancreatic biliary tract cancer patients may not be as favorable if chemotherapy is not commenced promptly after proper procedure or if SREs occur and are not manageable. Gastric outlet obstruction (GOO) is a major concern in patients with advanced PC.[ 15 ] Once malignant GOO emerges, patients experience abdominal fullness, nausea, vomiting, and impaired oral intake. [ 16 ] This complication significantly deteriorates patients' quality of life by exacerbating symptoms. These symptoms worsen performance status and quality of life, complicate cancer treatment, and shorten patient survival.[ 17 ] In the present study, we observed only four patients (2.9%) who needed stenting or bypass surgery prior to chemotherapy. Although the number of cases was too small to fully evaluate, no obvious prognostic impact was observed. A significant discovery by Takamatsu et al. was that patients who received endoscopic duodenal stent placement prior to chemotherapy exhibited markedly extended overall survival. [ 18 ] This underscores the potential impact of relieving obstructive symptoms through less invasive interventions, such as gastrointestinal stenting, on the success of subsequent cancer treatment. The choice of a suitable stent that minimizes the risk of reocclusion or dislodgment has emerged as a pivotal consideration, often outweighing the urgency of chemotherapy initiation when gastrointestinal transit impairment is a concern. This study has several limitations. First, it was a retrospective study conducted at a single center. Second, as the decision to curtail or postpone chemotherapy depends on the attending physician, the subsequent outcomes may have been influenced by this variability. Third, the evaluation of chemotherapy initiation delay due to cancer pain was challenging in this study. Finally, owing to the retrospective nature of the study, statistical sample size calculations were not performed. Thus, the number of cases may have been insufficient to derive the present findings. Conclusion Although the imperative of promptly initiating chemotherapy has long been upheld in managing advanced PC, our study introduced a more nuanced perspective. Timing alone may not be the sole determinant of improved prognosis, warranting a comprehensive assessment of patient-specific factors and complications that may impede timely treatment. By addressing these factors, such as obstructive jaundice, cholangitis, and gastrointestinal obstruction, through appropriate interventions such as stent placement, the overall success of chemotherapy and, consequently, patient outcomes could be enhanced. The results of this study encourage a shift toward a personalized and complication-conscious approach in the treatment of advanced PC. Declarations Funding Sources : No funding was received for this study. Disclosure statement: There are no relevant financial or nonfinancial competing interests. Data availability statement: The data supporting this study's findings are available on request from the corresponding author Nishida T. The data are not publicly available due to restrictions (e.g., they contain information that could compromise the privacy of the research participants). List contribution of each author: Nishida T conceptualized and designed this study. Nishida T wrote the original draft. Nishida T and Hosokawa K performed the data curation. Nishida T performed formal analysis. All authors reviewed the manuscript draft and revised it critically on intellectual content. All authors approved the final version of the manuscript to be published. References Lee SH, Chang PH, Chen PT, Lu CH, Hung YS, Tsang NM, Hung CY, Chen JS, Hsu HC, Chen YY, Chou WC. Association of time interval between cancer diagnosis and initiation of palliative chemotherapy with overall survival in patients with unresectable pancreatic cancer. Cancer Med. 2019;8(7):3471–8. 10.1002/cam4.2254 . Jooste V, Dejardin O, Bouvier V, Arveux P, Maynadie M, Launoy G, Bouvier AM. Pancreatic cancer: Wait times from presentation to treatment and survival in a population-based study. Int J Cancer. 2016;139(5):1073–80. 10.1002/ijc.30166 . Nishida T, Sugimoto A, Tomita R, Higaki Y, Osugi N, Takahashi K, Mukai K, Matsubara T, Nakamatsu D, Hayashi S, Yamamoto M, Nakajima S, Fukui K, Inada M. Impact of time from diagnosis to chemotherapy in advanced gastric cancer: A Propensity Score Matching Study to Balance Prognostic Factors. World J Gastrointest Oncol. 2019;11(1):28–38. 10.4251/wjgo.v11.i1.28 . Fearon K, Strasser F, Anker SD, Bosaeus I, Bruera E, Fainsinger RL, Jatoi A, Loprinzi C, MacDonald N, Mantovani G, Davis M, Muscaritoli M, Ottery F, Radbruch L, Ravasco P, Walsh D, Wilcock A, Kaasa S, Baracos VE. Definition and classification of cancer cachexia: an international consensus. Lancet Oncol. 2011;12(5):489–95. 10.1016/s1470-2045(10)70218-7 . Min L, Yoon W, Mariano J, Wenger NS, Elliott MN, Kamberg C, Saliba D. The vulnerable elders-13 survey predicts 5-year functional decline and mortality outcomes in older ambulatory care patients. J Am Geriatr Soc. 2009;57(11):2070–6. 10.1111/j.1532-5415.2009.02497.x . Sugimoto A, Nishida T, Osugi N, Takahashi K, Mukai K, Nakamatsu D, Matsubara T, Hayashi S, Yamamoto M, Nakajima S, Fukui K, Inada M. Prediction of survival benefit when deciding between chemotherapy and best supportive therapy in elderly patients with advanced gastric cancer: A retrospective cohort study. Mol Clin Oncol. 2019;10(1):83–91. 10.3892/mco.2018.1772 . Takahashi M, Takahashi M, Komine K, Yamada H, Kasahara Y, Chikamatsu S, Okita A, Ito S, Ouchi K, Okada Y, Imai H, Saijo K, Shirota H, Takahashi S, Mori T, Shimodaira H, Ishioka C. The G8 screening tool enhances prognostic value to ECOG performance status in elderly cancer patients: A retrospective, single institutional study. PLoS ONE. 2017;12(6):e0179694. 10.1371/journal.pone.0179694 . Zhang H, Ren D, Jin X, Wu H. The prognostic value of modified Glasgow Prognostic Score in pancreatic cancer: a meta-analysis. Cancer Cell Int. 2020;20:462. 10.1186/s12935-020-01558-4 . Hosokawa K, Nishida T, Hayashi D, Kitazawa M, Masuda H, Tono K, Katanosaka Y, Sakamoto N, Fujii Y, Sugimoto A, Nakamatsu D, Matsumoto K, Yamamoto M, Fukui K. Impact of Initial Body Weight Loss on Prognosis in Advanced Pancreatic Cancer: Insights From a Single-Center Retrospective Study. Cancer Control. 2023;30:10732748231204719. 10.1177/10732748231204719 . Ma SJ, Oladeru OT, Miccio JA, Iovoli AJ, Hermann GM, Singh AK. Association of Timing of Adjuvant Therapy With Survival in Patients With Resected Stage I to II Pancreatic Cancer. JAMA Netw Open. 2019;2(8):e199126. 10.1001/jamanetworkopen.2019.9126 . Sugumar K, Hue JJ, De La Serna S, Rothermel LD, Ocuin LM, Hardacre JM, Ammori JB, Winter JM. The importance of time-to-adjuvant treatment on survival with pancreatic cancer: A systematic review and meta-analysis. Cancer Rep (Hoboken). 2021;4(5):e1390. 10.1002/cnr2.1390 . Valle JW, Palmer D, Jackson R, Cox T, Neoptolemos JP, Ghaneh P, Rawcliffe CL, Bassi C, Stocken DD, Cunningham D, O'Reilly D, Goldstein D, Robinson BA, Karapetis C, Scarfe A, Lacaine F, Sand J, Izbicki JR, Mayerle J, Dervenis C, Oláh A, Butturini G, Lind PA, Middleton MR, Anthoney A, Sumpter K, Carter R, Büchler MW. Optimal duration and timing of adjuvant chemotherapy after definitive surgery for ductal adenocarcinoma of the pancreas: ongoing lessons from the ESPAC-3 study. J Clin Oncol. 2014;32(6):504–12. 10.1200/jco.2013.50.7657 . Nakata B, Amano R, Kimura K, Hirakawa K. Comparison of prognosis between patients of pancreatic head cancer with and without obstructive jaundice at diagnosis. Int J Surg. 2013;11(4):344–9. 10.1016/j.ijsu.2013.02.023 . Lamarca A, Rigby C, McNamara MG, Hubner RA, Valle JW. Impact of biliary stent-related events in patients diagnosed with advanced pancreatobiliary tumours receiving palliative chemotherapy. World J Gastroenterol. 2016;22(26):6065–75. 10.3748/wjg.v22.i26.6065 . Adler DG, Baron TH. Endoscopic palliation of malignant gastric outlet obstruction using self-expanding metal stents: experience in 36 patients. Am J Gastroenterol. 2002;97(1):72–8. 10.1111/j.1572-0241.2002.05423.x . Oh SY, Edwards A, Mandelson M, Ross A, Irani S, Larsen M, Gan SI, Gluck M, Picozzi V, Helton S, Kozarek RA. Survival and clinical outcome after endoscopic duodenal stent placement for malignant gastric outlet obstruction: comparison of pancreatic cancer and nonpancreatic cancer. Gastrointest Endosc. 2015. 10.1016/j.gie.2015.01.026 . Bessoud B, de Baere T, Denys A, Kuoch V, Ducreux M, Precetti S, Roche A, Menu Y. Malignant gastroduodenal obstruction: palliation with self-expanding metallic stents. J Vasc Interv Radiol. 2005;16(2 Pt 1):247–53. 10.1097/01.Rvi.0000145227.90754.76 . Takamatsu Y, Fujimori N, Miyagahara T, Suehiro Y, Kaku T, Kawabe K, Ohno A, Matsumoto K, Murakami M, Teramatsu K, Takeno A, Oono T, Ogawa Y. The Glasgow Prognostic Score and stricture site can predict prognosis after endoscopic duodenal stent placement for malignant gastric outlet obstruction. Sci Rep. 2022;12(1):9746. 10.1038/s41598-022-13209-x . Additional Declarations No competing interests reported. Supplementary Files SupplementaryFig.tiff Cite Share Download PDF Status: Published Journal Publication published 28 Feb, 2024 Read the published version in Japanese Journal of Clinical Oncology → 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-3689606","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":255033444,"identity":"1e684539-0e94-48f7-8d4b-67d2d0e1119f","order_by":0,"name":"Tsutomu 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01:59:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3689606/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3689606/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1093/jjco/hyae027","type":"published","date":"2024-02-29T03:00:54+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":47588773,"identity":"c74c3d8b-fa24-48fc-b69e-ee6bb55ad94a","added_by":"auto","created_at":"2023-12-04 21:33:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":144616,"visible":true,"origin":"","legend":"\u003cp\u003ePatient enrollment flowchart\u003c/p\u003e","description":"","filename":"Figuer1.png","url":"https://assets-eu.researchsquare.com/files/rs-3689606/v1/a77f0ac79567e52dcf451418.png"},{"id":47587724,"identity":"e6ef3a7d-70eb-4e9f-9c53-b5027c615c16","added_by":"auto","created_at":"2023-12-04 21:25:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":137833,"visible":true,"origin":"","legend":"\u003cp\u003eOverall survival times of patients in the early waiting time and elective waiting time groups\u003c/p\u003e","description":"","filename":"Figuer2.png","url":"https://assets-eu.researchsquare.com/files/rs-3689606/v1/e162fc8b89a9c31275a0ef21.png"},{"id":47587722,"identity":"28963750-f98a-4988-af94-842866ee3057","added_by":"auto","created_at":"2023-12-04 21:25:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":124728,"visible":true,"origin":"","legend":"\u003cp\u003eOverall survival times of patients in the early waiting time and elective waiting time groups after propensity score matching\u003c/p\u003e","description":"","filename":"Figuer3.png","url":"https://assets-eu.researchsquare.com/files/rs-3689606/v1/6bad708f0f70aaa947ab3a27.png"},{"id":57556673,"identity":"4120e53c-3acd-4775-b018-e7ecd84e16bd","added_by":"auto","created_at":"2024-06-02 03:01:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1187563,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3689606/v1/67614391-55eb-442c-87f0-c6cf28ec49d6.pdf"},{"id":47587725,"identity":"f31e2542-7a8d-45c2-a706-eeb0c552778f","added_by":"auto","created_at":"2023-12-04 21:25:04","extension":"tiff","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":4521082,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFig.tiff","url":"https://assets-eu.researchsquare.com/files/rs-3689606/v1/6ea4e0b5c075146c3d0f3536.tiff"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of time from diagnosis to chemotherapy on prognosis in advanced pancreatic cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTimely initiation of treatment is critical for patients with advanced cancer, particularly those with potentially curable malignancies. Prompt disease assessment and appropriate treatment while considering psychological needs are crucial in such cases. However, unresectable advanced cancers exhibit considerable variability in disease status at diagnosis, with the primary treatment goals being symptom palliation and prolongation of life. Thus, in addition to patient psychological considerations, the pathophysiology and treatment objectives differ significantly from those of resectable advanced cancers.\u003c/p\u003e \u003cp\u003ePancreatic cancer (PC) is a particularly challenging disease owing to its aggressive nature and poor prognosis. Timely initiation of treatment is critical for patients with advanced PC. Some studies have suggested that delaying the start of chemotherapy after diagnosis may not significantly affect subsequent prognosis [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, despite a growing body of research, conclusive evidence remains elusive. While the impact of treatment timing has been studied in other cancers, the evidence to date has been inconclusive. Our recent study, which focused on advanced gastric cancer in Japanese patients, found that the time between diagnosis and the initiation of chemotherapy did not significantly affect subsequent outcomes. Initiating treatment after assessment, including biomarker confirmation, may be a reasonable approach if the disease is stable [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, differences in the nature of the cancers and specific issues such as obstructive jaundice, cholangitis, and gastrointestinal transit obstruction in PC prevent direct extrapolation of findings. Moreover, the clinical course of unresectable advanced PC exhibits high variability, which is influenced by the tumor size, extent of spread, and associated complications. Additionally, patients are often older, and this diversity needs to be evaluated. Therefore, the significance of treatment timing may be obscured, making it imperative to study the direct effects of early chemotherapy initiation on prognosis, particularly for this specific cancer type.\u003c/p\u003e \u003cp\u003eTherefore, this study was designed to explore the subclinical impact of the time between cancer diagnosis and the start of chemotherapy, including biliary drainage procedures, on the prognosis of advanced PC. By elucidating the relationship between treatment timing and patient outcomes, we aspire to provide valuable insights that will inform clinical decision making and enhance the management of this challenging disease.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eThis was a single-center retrospective study. We studied consecutive patients with advanced PC who visited the Toyonaka Municipal Hospital between April 2013 and March 2022. Patients were diagnosed with advanced PC using computed tomography, magnetic resonance imaging, and tumor markers. The patients had a pathology confirmed as adenocarcinoma by endoscopic ultrasound-guided fine-needle aspiration. They were selected from the database, and data were collected from the electronic medical records of our hospital (MegaOak online imaging system, NEC, Japan). Of those selected, we enrolled consecutive patients who were diagnosed and treated for metastatic, locally advanced, or resectable PC and who were intolerant of or refused surgery. Chemotherapy recommendations were based on the Pancreatic Cancer Clinical Practice Guidelines of the Japan Pancreas Society, including gemcitabine and nab-paclitaxel (GnP), nanoliposomal-irinotecan\u0026thinsp;+\u0026thinsp;5-FU/LV (5-fluorouracil/leucovorin), modified FOLFIRINOX (5-fluorouracil, leucovorin, irinotecan, and oxaliplatin), S1 alone, or gemcitabine (GEM) alone.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eThe following data were collected from the medical records at the time of PC diagnosis. Patient-related factors included sex, age, body mass index (BMI), body weight loss, Eastern Cooperative Oncology Group (ECOG) score, performance status, and geriatric assessment tools, including the Geriatric (G)8, Vulnerable Elders Survey (VES)-13, age-adjusted Charlson Comorbidity Index (ACCI), neutrophil-to-lymphocyte ratio (NLR), and modified Glasgow Prognostic Score (mGPS). Body weight loss was considered significant if the patient had lost more than 5% of their body weight over the past six months or more than 2% of their body weight with a body mass index (BMI) of less than 20 kg/m\u003csup\u003e2\u003c/sup\u003e at the time of PC diagnosis, established using the diagnostic criteria proposed by Fearon et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Factors related to PC were resectability or the presence of distant metastasis, biliary drainage, and tumor markers (serum carcinoembryonic antigen (CEA) and carbohydrate antigen (CA)) 19\u0026thinsp;\u0026minus;\u0026thinsp;9).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eOutcomes and definition\u003c/h2\u003e \u003cp\u003eWaiting time (WT) was defined as the interval between the diagnosis on imaging and the initiation of chemotherapy. The date of diagnosis was defined as the date of the first detection of PC using computed tomography or magnetic resonance imaging. The primary endpoint was the effect of WT on overall survival. The secondary endpoint was the prognostic impact of clinical factors, including biliary drainage. The last day of observation was July 15, 2023.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eEthical considerations\u003c/h2\u003e \u003cp\u003e This study was conducted in accordance with the tenets of the Declaration of Helsinki and approved by the Institutional Review Board of Toyonaka Municipal Hospital (No. 2023-08-07). The requirement for informed consent was waived using the opt-out method on our hospital website.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe median and interquartile range (IQR) were reported for continuous variables. We used a matrix imputation method to impute missing continuous variables. Wilcoxon signed-rank tests were used to assess differences in continuous variables. Categorical variables are summarized as frequencies (percentages). Fisher's exact test was used to assess differences in categorical variables. Overall survival was estimated using the Kaplan\u0026ndash;‒Meier method and compared using the log-rank test and Wilcoxon tests. To evaluate the influence of WT on survival, we used univariate and multivariate analyses with Cox proportional hazards models to assess whether the factors affected prognosis, providing hazard ratios (HRs) with 95% confidence intervals (CIs). Statistical sample size calculations were not performed due to a lack of evidence on which to base them and the retrospective study design. We set each assessment parameter to the following cutoff values according to previous reports. The cutoff values for the VES-13 and NLR were three [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] and four [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], respectively. We divided the ECOG PS into PS0-1 and PS\u0026thinsp;\u0026ge;\u0026thinsp;2. The total G8 score ranges from 0 to 17, with higher scores indicating a better health status. A G8 score\u0026thinsp;\u0026gt;\u0026thinsp;14 was considered normal [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In the present study, we classified ACCI as low-risk (ACCI score of 0\u0026ndash;1), moderate-risk (ACCI score of 2\u0026ndash;3), and high-risk (ACCI score of 4 or more). The cutoff value of the mGPS was 1 [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. We set the cutoff value of CA19-9 to 1000 IU/ml.\u003c/p\u003e \u003cp\u003eWe then calculated propensity scores for prognosis with these significant factors and created 1:1 matched study groups with a caliper width of 0.05 to minimize the effect of potential selection bias. Similarly, the early WT group was compared with the elective WT group.\u003c/p\u003e \u003cp\u003eAll calculated P values were two-tailed, and a P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to indicate statistical significance. Statistical analysis was performed using JMP statistical software (ver. 16, SAS Institute Inc., Cary, NC, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePatient characteristics\u003c/h2\u003e \u003cp\u003eBetween April 2013 and March 2022, 504 patients diagnosed with PC were admitted to our department. A total of 119 patients underwent surgery; 83 patients received the best supportive care following evaluation; 33 patients began treatment in other hospitals and were subsequently transferred to our hospital; 27 patients were referred to other hospitals after the initial evaluation in our department; four patients received chemoradiotherapy; 59 patients did not have available data on body weight information; and 42 patients were lost to follow-up. Therefore, 367 patients were excluded, and 137 patients who received chemotherapy were enrolled (Fig.\u0026nbsp;1).\u003c/p\u003e \u003cp\u003eThe baseline characteristics of the enrolled patients are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. At the time of the initial evaluation for PC, the median age of the patients was 72 years (IQR: 67\u0026ndash;77 years), and 55.5% of the patients were men. The ECOG PS performance status was 0 in 111 patients (81.0%), 1 in 23 patients (16.8%), and 2 in 3 patients (2.2%). The median BMI was 21.4 kg/m\u003csup\u003e2\u003c/sup\u003e (19.2, 23.4), and weight loss at diagnosis was 46.7% (64/137). The median psoas muscle mass and PMI were 930 cm\u003csup\u003e2\u003c/sup\u003e (728, 1301) and 3.8 cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e (3.0, 4.8), respectively. Forty-five patients had diabetes, and 61 patients had chronic kidney disease.\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\u003eClinical characteristics of patients with pancreatic cancer\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics, n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient, n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient related factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, median (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72 (67, 77)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76 (55.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eECOG PS 0, 1, 2, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111 (81.0), 23 (16.8), 3 (2.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.4 (19.2, 23.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody weight loss, yes, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64 (46.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsoas muscle mass (cm\u003csup\u003e2\u003c/sup\u003e), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e930 (728, 1301)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePMI (cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.8 (3.0, 4.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus, yes, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (32.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic kidney disease, yes, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 (44.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScreening tool for health problems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG8, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.4 (9.4. 9.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVES-13, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.1 (3.1, 3.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACCI, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (4, 5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.3 (2.4, 4.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emGPS, 0/1/2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92 (67.1), 32 (23.4), 13 (9.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer related factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMain tumor location\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHead, body, body/tail, tail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 (35.0), 44 (32.1), 4 (2.9), 41 (29.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResectability, R/UR-LA/UR-M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2.2), 41 (29.9), 93 (67.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiliary drainage, yes, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47 (34.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuodenal stenosis prior to 1st line chemotherapy, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (2.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastroduodenal stenting prior to chemotherapy, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBypass operation prior to chemotherapy, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCEA, (U/mL) median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.8 (3.4, 25.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA19-9, (U/mL) median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1311 (77.5, 11710)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaiting time, days, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (17.5, 37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservation period, days, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e226 (137, 367)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll death during observation period, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129 (94.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemotherapy regimen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS1, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (5.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGEM, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (27.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGnP, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82 (59.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emFOLFIRINOX, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (8.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary chemotherapy transition rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 (42.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS1, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (43.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGEM, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (24.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGnP, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (8.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emFOLFIRINOX, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (5.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003enal-IRI\u0026thinsp;+\u0026thinsp;5FU/LV, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (19.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eECOG: Eastern Cooperative Oncology Group, PS: \u003cem\u003eperformance status\u003c/em\u003e, BMI: body mass index, PMI: psoas muscle index, R: resectable, UR: unresectable, LA: locally advanced, M: metastasis, G8: Geriatric 8, VES-13: vulnerable elders survey, ACCI: age-adjusted Charlson Comorbidity Index, NLR: neutrophil-to-lymphocyte ratio, mGPS: modified Glasgow Prognostic Score, GEM: \u003cem\u003egemcitabine\u003c/em\u003e, GnP: gemcitabine and nab-paclitaxel, nal-IRI\u0026thinsp;+\u0026thinsp;5FU/LV: nanoliposomal-irinotecan\u0026thinsp;+\u0026thinsp;5-fluorouracil/leucovorin, FOLFIRINOX:5-fluorouracil, leucovorin, irinotecan, and oxaliplatin\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRegarding screening tools for health problems, the median (IQR) was 9.4 for G8, 3.1 for VES-13, 4 for ACCI, and 3.3 for NLR. The mGPS 0/1/2 was 92 (67.1%)/32 (23.4%)/13 (9.5%). Regarding cancer-related profiles, the most dominant tumor location was the pancreatic head in 48 patients (35.0%), followed by the pancreatic body in 44 patients (32.1%). Resectability was classified as resectable in three patients, unresectable locally advanced disease in 41, and unresectable metastatic disease in 93. Biliary drainage was needed in 47 patients (34.3%), and four patients (2.9%) needed gastroduodenal stent placement or bypass surgery for duodenal obstruction due to PC during the initial evaluation. The median CEA and CA19-9 levels were 6.8 U/mL (3. 4, 25.1) and 1311 U/mL (77.5, 11710), respectively.\u003c/p\u003e \u003cp\u003eThe median waiting time was 26 (17.5, 37) days. Therefore, we grouped the patients into early WT and elective WT groups using a 30-day cutoff. The observation period from clinical diagnosis to the last visit ranged from 29 to 1611 days (median, 226 days; IQR, 137\u0026ndash;367 days). Of these, 129 (94.2%) died during follow-up. Of the 137 patients who received chemotherapy, 82 received GnP, 11 received mFOLFIRINOX, 7 received S1, and 37 received GEM as initial chemotherapy. The secondary chemotherapy transition rate was 42.3%. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e compares the characteristics of the patients in the early WT and elective WT groups. The early WT group included 85 patients, and the elective WT group included 52 patients. There were no significant differences in age, sex, ECOG-PS, BMI, psoas muscle mass, PMI, body weight loss, diabetes, or chronic kidney disease. Regarding screening tools for health problems, the G8, VES-13, ACCI, and NLR did not differ between the groups, but the mGPS was significantly lower in the elective WT group. Regarding cancer-related factors, the presence of metastasis was significantly higher in the early WT group, and the CA19-9 level was significantly lower in the elective WT group than in the early WT group. (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). There were no significant differences in the first-line chemotherapy regimen or secondary chemotherapy transition rates between the groups.\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\u003eComparison of characteristics of patients in the early waiting time and elective waiting time groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics, n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEarly waiting time\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eElective waiting time\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\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\u003ePatient, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85 (62.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (38.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient related factors\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, median (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72 (67.5, 77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 (67, 76.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7967\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (51.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (61.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2917\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eECOG PS 0, 1, 2, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67 (78.8)/15 (17.7)/3 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (84.6)/8 (15.4)/0 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3557\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.7 (18.4, 23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.8 (19.7, 23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2811\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody weight loss, yes, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (48.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (44.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7251\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsoas muscle mass (cm\u003csup\u003e2\u003c/sup\u003e), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e885 (686, 1257)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1010(736, 1349)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1211\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePMI (cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.6 (2.8, 4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.9 (3.1, 4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1243\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidity\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus, yes, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (29.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (38.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3488\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic kidney disease, yes, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (44.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (44.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9567\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScreening tool for health problems\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG8, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.4 (9.4,9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.4 (9.4,9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4430\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVES-13, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.1 (2.5,3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.1 (3.1, 3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4301\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACCI, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (3, 5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (4, 5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2116\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.5 (2.6, 4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.1 (2.4, 4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5419\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emGPS, 0/1/2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 (58.8), 26 (30.6), 9 (10.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (80.8), 6 (11.5), 4 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0222\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer related factors\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMain tumor location\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHead, body, body/tail, tail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (28.2). 31 (36.5), 3 (3.5), 27 (31.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (46.2), 13 (25.0), 1 (1.9), 14 (26.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1858\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResectability, R/UR-LA/UR-M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)/23 (27.1)/62 (72.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (5.8)/18 (34.6)/62 (59.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0415\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiliary drainage, yes, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (29.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (42.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1404\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuodenal stenosis prior to 1st line chemotherapy, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1530\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCEA, (U/mL) median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.9 (3.5, 37.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.3 (3.3, 23.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA19-9, (U/mL) median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2156 (2001, 24413)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e737 (9, 6348)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment and outcomes\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaiting time, days, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (14, 23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (35, 57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservation period, days, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e207 (101, 362)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e261 (172, 426)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0379\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll death during observation period, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77 (90.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0241\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemotherapy regimen\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=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2692\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS1, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGEM, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (26.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGnP, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52 (61.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (57.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emFOLFIRINOX, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary chemotherapy transition rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (44.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (38.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5932\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS1, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (39.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGEM, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (23.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGnP, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emFOLFIRINOX, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003enal-IRI\u0026thinsp;+\u0026thinsp;5FU/LV, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (23.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eECOG: Eastern Cooperative Oncology Group, PS: \u003cem\u003eperformance status\u003c/em\u003e, BMI: body mass index, PMI: psoas muscle index, R: resectable, UR: unresectable, LA: locally advanced, M: metastasis, G8: Geriatric 8, VES-13: vulnerable elders survey, ACCI: age-adjusted Charlson Comorbidity Index, NLR: neutrophil-to-lymphocyte ratio, mGPS: modified Glasgow Prognostic Score, GEM: gemcitabine, GnP: gemcitabine and nab-paclitaxel, nal-IRI\u0026thinsp;+\u0026thinsp;5FU/LV: nanoliposomal-irinotecan\u0026thinsp;+\u0026thinsp;5-fluorouracil/leucovorin, FOLFIRINOX:5-fluorouracil, leucovorin, irinotecan, and oxaliplatin\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eOverall survival curves of patients in the early WT and elective WT groups\u003c/h2\u003e \u003cp\u003eThe overall survival (OS) times of patients in the early WT and elective WT groups are shown in \u003cb\u003eFig.\u0026nbsp;2\u003c/b\u003e. The median OS times (MST) were 207 and 261 days in the early and elective WT groups, respectively. There was no significant difference in OS between the two groups according to the log-rank test (P\u0026thinsp;=\u0026thinsp;0.2518); however, there was a trend toward longer OS in the elective WT group according to the Wilcoxon test (P\u0026thinsp;=\u0026thinsp;0.0646).\u003c/p\u003e \u003cp\u003e \u003cem\u003eUnivariate and multivariate analyses with\u003c/em\u003e Cox proportional hazards models \u003cem\u003efor predicting prognosis in patients with advanced pancreatic cancer.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eWe evaluated the clinical factors that predicted PC prognosis. Univariate analysis showed that PS\u0026thinsp;\u0026gt;\u0026thinsp;2, presence of metastasis, NLR\u0026thinsp;\u0026gt;\u0026thinsp;3, mGPS 1/2, and higher CA19-9 levels were significantly associated with poor prognosis. However, longer waiting times, including the treatment of biliary drainage or duodenal obstruction, were not associated with a poor prognosis (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The results of the multivariate analysis adjusted for age and sex, including the five significant variables plus waiting time, biliary drainage, and duodenal obstruction, indicated that poor PS and the presence of metastasis were significantly associated with poor prognosis (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate analyses with Cox proportional hazards models for clinical factors predicting pancreatic cancer prognosis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eMultivariate\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75\u0026ndash;1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.6962\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u0026thinsp;\u0026ge;\u0026thinsp;75 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;75 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.72\u0026ndash;1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.7979\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaiting time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEarly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.52\u0026ndash;1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.63\u0026ndash;1.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.8537\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.5\u0026ndash;28.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.59\u0026ndash;33.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody weight loss, yes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83\u0026ndash;1.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3484\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus, yes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68\u0026ndash;1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic kidney disease*, yes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.87\u0026ndash;1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiliary drainage, yes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70\u0026ndash;1.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.63\u0026ndash;1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.7955\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuodenal obstruction, yes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.32\u0026ndash;3.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9676\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.40\u0026ndash;4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.6351\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeatastasis\u0026dagger;, yes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.38\u0026ndash;3.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.23-3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0042\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR\u0026thinsp;\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14\u0026ndash;2.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.82\u0026ndash;1.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.2903\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emGPS, 1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.30\u0026ndash;2.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.92\u0026ndash;2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.1051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA19-9, \u0026ge;\u0026thinsp;1000 U/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1000 U/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.05\u0026ndash;2.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.90-2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.1503\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG8\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06\u0026ndash;3.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3972\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVES-13\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77\u0026ndash;2.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3732\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACCI, high risk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow to medium risk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.63\u0026ndash;1.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.8618\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePMI, Low\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68\u0026ndash;1.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.8162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e*Chronic kidney disease is defined as an eGFR of less than 60 mL/min.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u0026dagger;Among the three groups according to resectability, metastasis was a significantly poor prognostic factor, but there was no difference between locally advanced and resectable patients (resectable/locally advanced; HR 1.30, P\u0026thinsp;=\u0026thinsp;0.4548). Therefore, we compared the two groups: patients with metastases and patients with resectable/locally advanced disease.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u0026sect;Age and sex adjusted\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eUR: unresectable, M: metastasis, NLR: neutrophil-to-lymphocyte ratio, mGPS: modified Glasgow Prognostic Score, G8: Geriatric 8, VES-13: vulnerable elders survey, ACCI: age-adjusted Charlson Comorbidity Index, PMI: psoas muscle index\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003ePropensity score matching analysis\u003c/h2\u003e \u003cp\u003eMultivariate logistic analysis showed that poor PS and the presence of metastasis were significant independent risk factors for poor prognosis. We performed a 1:1 propensity score matching analysis to evaluate the impact of waiting time on predicting poor prognosis using the above two factors adjusted by age and sex by multivariate analysis. We obtained 27 matched patients in the early and elective WT groups. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the results of the propensity score matching. After propensity score matching, there were no significant differences between the groups. OS was evaluated in propensity score-matched patients in both groups. There was no significant difference in OS between the two groups, with median OS times of 275 and 222 days, respectively (log-rank P\u0026thinsp;=\u0026thinsp;0.8223, Wilcoxon test P\u0026thinsp;=\u0026thinsp;0.9098) (Fig.\u0026nbsp;3).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of characteristics of patients between early waiting time and elective waiting time groups after propensity score matching\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePropensity- matched cohort\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEarly waiting time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eElective waiting time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient related factors\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, median (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72 (68, 76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 (67, 76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9171\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (63.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7822\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eECOG PS 0, 1, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (100), 0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (92.6), 2 (7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4906\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.9 (18.7, 23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.8 (20.3, 24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6528\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody weight loss, yes, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (63.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (51.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5826\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsoas muscle mass (cm\u003csup\u003e2\u003c/sup\u003e), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e853 (784, 1287)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1025 (568, 1381)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5448\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePMI (cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.5 (3.1, 4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.9 (2.9, 5.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6159\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidity\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus, yes, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (37.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7734\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic kidney disease, yes, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (51.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (40.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5857\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScreening tool for health problems\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG8, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.4 (9.4, 9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.4 (9.4, 9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6782\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVES-13, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.1 (3.1, 3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.1 (3.1, 3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1487\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACCI, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (4, 5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (4, 5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8683\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.2 (1.9, 4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.3 (2.9, 4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emGPS, 0/1/2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (59.3)/8 (29.6)/3 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (77.8)/4 (14.8)/2 (7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3314\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeatastasis\u0026dagger;, yes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (59.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiliary drainage, yes, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3983\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuodenal stenosis, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCEA, (U/mL) median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.2 (3.5, 23.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.8 (4, 15.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6158\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA19-9, (U/mL) median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1428 (149, 22136)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e717 (4, 4588)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0717\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary chemotherapy transition rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (48.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4064\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*Chronic kidney disease is defined as an eGFR of less than 60 mL/min.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eUR: unresectable, M: metastasis, NLR: neutrophil-to-lymphocyte ratio, mGPS: modified Glasgow Prognostic Score, G8: Geriatric 8, VES-13: vulnerable elders survey, ACCI: age-adjusted Charlson Comorbidity Index, PMI: psoas muscle index\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eAdvanced PC often causes obstructive jaundice, gastrointestinal dysfunction, pain, cachexia, and weight loss at the time of diagnosis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Chemotherapy should be promptly initiated after confirmation of advanced PC without surgical indications. However, the necessity to manage these patient complications may result in delayed chemotherapy initiation. Nonetheless, there is currently insufficient evidence to determine whether such treatment initiation delays impact prognosis. In this study, we aimed to ascertain the prognostic influence of the interval between cancer diagnosis and chemotherapy initiation in Japanese patients with advanced PC. The findings revealed that initiation of chemotherapy within 30 days after diagnosis did not significantly correlate with worse prognosis compared with commencing chemotherapy more than 30 days after diagnosis. Within our cohort, the early WT group exhibited a higher proportion of patients with metastatic disease and elevated CA19-9 levels than the selective WT group. However, the early WT group included more patients with lower mGPS scores. To address these background disparities, propensity score matching was employed, which consistently reinforced our results. These results suggest that delaying chemotherapy initiation might not substantially affect the prognosis of Japanese patients with advanced PC, even after biliary drainage for obstructive jaundice or cholangitis.\u003c/p\u003e \u003cp\u003eAdditionally, the survival curves for the early WT group were divided into subgroups of \u0026le;\u0026thinsp;14 days and 15\u0026ndash;30 days or less, whereas the survival curves of the \u0026ge;\u0026thinsp;31 days were divided into three groups. These results further validated the overlapping survival curves between the \u0026le;\u0026thinsp;14 days and the 15-30-day WT groups, supporting the rationale behind the 30-day cutoff in this study (\u003cb\u003eSupplementary Figure\u003c/b\u003e). This observation implies that the conventional emphasis on initiating chemotherapy immediately after diagnosis might not yield the anticipated benefits in terms of overall survival and disease progression. These results offer valuable insights for clinical decision-making and may guide treatment strategies for this formidable disease.\u003c/p\u003e \u003cp\u003eEffective management of complications that might lead to timely chemotherapy initiation is of paramount importance for patients\u0026rsquo; subsequent prognosis. The current dearth of evidence has resulted in mixed and varying conclusions. Delays in adjuvant treatment initiation or overall treatment time have been correlated with worse survival outcomes in specific malignancies, including resectable stage I to II PC [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Investigations focused on the timing of adjuvant chemotherapy in PC have produced mixed results. A meta-analysis concluded that commencing adjuvant therapy within 20 days after surgery was correlated with improved overall survival [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, the ESPAC-3 study found no notable outcome difference when adjuvant chemotherapy was delayed by up to 12 weeks to allow for postoperative recovery [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Even in terms of postoperative adjuvant chemotherapy for low-volume PC, the evidence within the PC realm remains inconsistent. The need to distinguish between patients with PC who are eligible for postoperative adjuvant chemotherapy and those who are unresectable for palliative chemotherapy, given their distinct tumor volumes and underlying conditions, renders the results of this study crucial.\u003c/p\u003e \u003cp\u003eObstructive jaundice and cholangitis, common complications of PC, can hinder timely chemotherapy initiation. In the present study, 47 (34.3%) patients needed biliary drainage prior to chemotherapy, more in the elective WT group than in the early WT group, but this difference was not significant (n\u0026thinsp;=\u0026thinsp;25 (29.4%) vs. n\u0026thinsp;=\u0026thinsp;22 (42.3%), P\u0026thinsp;=\u0026thinsp;0.1405). Univariate and multivariate analyses also showed no effect on prognosis. Nakata et al. reported that in 169 Japanese patients with pancreatic head cancer, obstructive jaundice and total bilirubin levels\u0026thinsp;\u0026gt;\u0026thinsp;3 mg/dL at diagnosis predicted unfavorable survival compared with nonjaundiced patients [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, in 85 unresectable cases, survival was not significantly different between the jaundice and nonjaundice groups (MST, 5.2 vs. 5.3 months, respectively). A retrospective review by Lee et al. from four hospitals reported that delaying palliative chemotherapy initiation beyond a 2-week wait did not adversely affect the survival of patients with unresectable PC [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Conversely, patients with a\u0026thinsp;\u0026le;\u0026thinsp;2-week waiting period who initially presented with jaundice exhibited worse OS than those with a waiting time of \u0026gt;\u0026thinsp;2 weeks. Lamarca et al. found that biliary stent-related events (SREs) during chemotherapy were observed in 43% of patients with pancreatic biliary tract cancer who received a stent at the commencement of palliative chemotherapy. Among these, there was a delay or discontinuation of chemotherapy in 41% as a result [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Patients with mild complications and no chemotherapy delay displayed longer OS than those with severe complications resulting in chemotherapy interruption or death (OS 11.6 vs. 4.4 months, P\u0026thinsp;=\u0026thinsp;0.001). Interestingly, there was a trend toward longer survival in the SRE group, encompassing cholangitis or stent obstruction, than in the no-SRE group, although the differences were not statistically significant (OS 9.8 vs. 7.6 months, P\u0026thinsp;=\u0026thinsp;0.0947). These findings indicate that the prognosis for advanced pancreatic biliary tract cancer patients may not be as favorable if chemotherapy is not commenced promptly after proper procedure or if SREs occur and are not manageable.\u003c/p\u003e \u003cp\u003eGastric outlet obstruction (GOO) is a major concern in patients with advanced PC.[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] Once malignant GOO emerges, patients experience abdominal fullness, nausea, vomiting, and impaired oral intake. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] This complication significantly deteriorates patients' quality of life by exacerbating symptoms. These symptoms worsen performance status and quality of life, complicate cancer treatment, and shorten patient survival.[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] In the present study, we observed only four patients (2.9%) who needed stenting or bypass surgery prior to chemotherapy. Although the number of cases was too small to fully evaluate, no obvious prognostic impact was observed. A significant discovery by Takamatsu et al. was that patients who received endoscopic duodenal stent placement prior to chemotherapy exhibited markedly extended overall survival. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] This underscores the potential impact of relieving obstructive symptoms through less invasive interventions, such as gastrointestinal stenting, on the success of subsequent cancer treatment. The choice of a suitable stent that minimizes the risk of reocclusion or dislodgment has emerged as a pivotal consideration, often outweighing the urgency of chemotherapy initiation when gastrointestinal transit impairment is a concern.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, it was a retrospective study conducted at a single center. Second, as the decision to curtail or postpone chemotherapy depends on the attending physician, the subsequent outcomes may have been influenced by this variability. Third, the evaluation of chemotherapy initiation delay due to cancer pain was challenging in this study. Finally, owing to the retrospective nature of the study, statistical sample size calculations were not performed. Thus, the number of cases may have been insufficient to derive the present findings.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAlthough the imperative of promptly initiating chemotherapy has long been upheld in managing advanced PC, our study introduced a more nuanced perspective. Timing alone may not be the sole determinant of improved prognosis, warranting a comprehensive assessment of patient-specific factors and complications that may impede timely treatment. By addressing these factors, such as obstructive jaundice, cholangitis, and gastrointestinal obstruction, through appropriate interventions such as stent placement, the overall success of chemotherapy and, consequently, patient outcomes could be enhanced. The results of this study encourage a shift toward a personalized and complication-conscious approach in the treatment of advanced PC.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding Sources\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eNo funding was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure statement:\u0026nbsp;\u003c/strong\u003eThere are no relevant financial or\u0026nbsp;nonfinancial\u0026nbsp;competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement:\u003c/strong\u003e The data supporting this study\u0026apos;s findings are available on request from the corresponding author Nishida T. The data are not publicly available due to restrictions (e.g., they contain information that could compromise the privacy of the research participants).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eList contribution of each author:\u003c/strong\u003e Nishida T conceptualized and designed this study. Nishida T wrote the original draft. Nishida T and Hosokawa K performed the data curation. Nishida T performed formal analysis.\u0026nbsp;\u003cstrong\u003eAll authors\u003c/strong\u003e reviewed the manuscript draft and revised it critically on intellectual content.\u0026nbsp;\u003cstrong\u003eAll authors\u003c/strong\u003eapproved the final version of the manuscript to be published.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLee SH, Chang PH, Chen PT, Lu CH, Hung YS, Tsang NM, Hung CY, Chen JS, Hsu HC, Chen YY, Chou WC. 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Sci Rep. 2022;12(1):9746. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-022-13209-x\u003c/span\u003e\u003cspan address=\"10.1038/s41598-022-13209-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"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":"pancreatic cancer, waiting time, survival prognosis, chemotherapy, biliary drainage","lastPublishedDoi":"10.21203/rs.3.rs-3689606/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3689606/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eDue to the aggressive nature and poor prognosis of advanced pancreatic cancer (PC), prompt initiation of treatment is critical. We investigated the effect of the survival time interval between cancer diagnosis and initiation of chemotherapy in patients with advanced PC.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this retrospective, single-center study, consecutive patients with advanced PC between April 2013 and March 2022 were analyzed. Data were extracted from the electronic medical records of patients who received chemotherapy for metastatic, locally advanced, or resectable PC or who received chemotherapy due to either being intolerant of or declining surgery. Chemotherapy followed clinical practice guidelines. We compared overall survival between two groups: the early waiting time (WT) group (WT\u0026thinsp;\u0026le;\u0026thinsp;30 days from diagnosis to chemotherapy initiation) and the elective WT group (WT\u0026thinsp;\u0026ge;\u0026thinsp;31 days). Prognostic factors, including biliary drainage, were considered. The impact of WT on survival was assessed by univariate and multivariate analyses with Cox proportional hazard models. A 1:1 propensity score matching (PSM) approach balanced bias, accounting for significant poor prognosis factors, age and sex.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe study involved 137 patients. Overall survival exhibited no statistically significant difference between the early and elective WT groups (207 and 261 days, P\u0026thinsp;=\u0026thinsp;0.2518). Univariate and multivariate analyses identified poor performance status and metastasis presence as predictors of worse prognosis. This finding persisted post PSM (275 and 222 days, P\u0026thinsp;=\u0026thinsp;0. 8223).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eOur study revealed that initiating chemotherapy within 30 days of diagnosis, as opposed to more than 30 days later, does not significantly affect treatment efficacy.\u003c/p\u003e","manuscriptTitle":"Impact of time from diagnosis to chemotherapy on prognosis in advanced pancreatic cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-12-04 21:24:59","doi":"10.21203/rs.3.rs-3689606/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":"d082b41e-238e-4a91-97d5-5c524cddbbbb","owner":[],"postedDate":"December 4th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-06-02T03:00:54+00:00","versionOfRecord":{"articleIdentity":"rs-3689606","link":"https://doi.org/10.1093/jjco/hyae027","journal":{"identity":"japanese-journal-of-clinical-oncology","isVorOnly":true,"title":"Japanese Journal of Clinical Oncology"},"publishedOn":"2024-02-29 03:00:54","publishedOnDateReadable":"February 29th, 2024"},"versionCreatedAt":"2023-12-04 21:24:59","video":"","vorDoi":"10.1093/jjco/hyae027","vorDoiUrl":"https://doi.org/10.1093/jjco/hyae027","workflowStages":[]},"version":"v1","identity":"rs-3689606","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3689606","identity":"rs-3689606","version":["v1"]},"buildId":"ehx78VzkSd0WSzXnipQa-","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}