Baseline serum albumin level as a predictive factor for the efficacy of trifluridine/tipiracil plus bevacizumab in metastatic colorectal cancer: A retrospective cohort study

Baseline serum albumin level as a predictive factor for the efficacy of trifluridine/tipiracil plus bevacizumab in metastatic colorectal cancer: A retrospective cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Baseline serum albumin level as a predictive factor for the efficacy of trifluridine/tipiracil plus bevacizumab in metastatic colorectal cancer: A retrospective cohort study Masatoshi Maki, Ryo Takada, Haruka Sumii, Miki Fujiwara, Hisashi Tagashira, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7790891/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Dec, 2025 Read the published version in Journal of Pharmaceutical Health Care and Sciences → Version 1 posted You are reading this latest preprint version Abstract Background Trifluridine/tipiracil (FTD/TPI) combined with bevacizumab (BEV) has become a standard later-line therapy for metastatic colorectal cancer (mCRC). However, predictive biomarkers of treatment efficacy remain limited. Serum albumin (Alb)—reflecting nutritional and inflammatory status—has been reported as a prognostic factor in various malignancies, but its predictive value in patients receiving FTD/TPI plus BEV is unclear. This study examined whether baseline Alb levels are linked to treatment outcomes in patients with metastatic CRC receiving FTD/TPI plus BEV, aiming to clarify if Alb could serve as a predictive marker of therapeutic efficacy. Methods We retrospectively analyzed patients with unresectable or recurrent mCRC treated with FTD/TPI plus BEV at Fukuyama Medical Center between December 2017 and March 2024. Patients were divided into High- or Low-Alb groups based on an optimal cutoff derived from receiver operating characteristic (ROC) analysis for progression-free survival (PFS). The primary endpoint was PFS, and the secondary endpoint was overall survival (OS). Survival outcomes were assessed using the Kaplan–Meier method and Cox proportional hazards models. Results Sixty-nine patients were included (median age, 69 years). ROC analysis identified an Alb cutoff of 3.7 g/dL (area under the curve: 0.740). Using this cutoff, 39 patients (56.5%) were included in the High-Alb group. Patients in the High-Alb group had significantly lower lactate dehydrogenase (LDH) and C-reactive protein levels than those in the Low-Alb group. The median PFS (5.2 vs. 3.0 months; p < 0.01) and OS (15.6 vs. 6.0 months; p < 0.01) were significantly longer in the High-Alb group than in the Low-Alb group. In the multivariate analysis, Alb ≥ 3.7 g/dL was independently associated with improved PFS (hazard ratio [HR]: 0.40, 95% confidence interval [CI]: 0.22–0.73, p = 0.003), whereas LDH ≥ 338 U/L was associated with shorter PFS (HR: 2.31, 95% CI: 1.28–4.32, p = 0.009). Conclusions Baseline serum albumin levels were associated with survival outcomes in patients with mCRC treated with FTD/TPI + BEV. Thus, Alb may represent a simple and clinically accessible marker with potential predictive value. Initiating FTD/TPI plus BEV before a substantial decline in nutritional or inflammatory status may help achieve more favorable outcomes. Albumin Colorectal cancer Trifluridine/tipiracil Bevacizumab predictive marker Figures Figure 1 Figure 2 Background Colorectal cancer (CRC) is one of the most prevalent malignancies worldwide and is associated with high incidence and mortality rates ( 1 , 2 ). For patients with advanced, recurrent, or unresectable disease, systemic chemotherapy remains the cornerstone of treatment. In recent years, trifluridine/tipiracil (FTD/TPI) has demonstrated a survival benefit in the later-line setting ( 3 ). Moreover, the addition of bevacizumab (BEV) to FTD/TPI has been demonstrated to further improve both progression-free survival (PFS) and overall survival (OS) ( 4 , 5 ). Based on these findings, FTD/TPI plus BEV has become widely adopted as a standard later-line therapy for advanced or recurrent CRC ( 6 , 7 ). Despite this progress, the clinical efficacy of FTD/TPI plus BEV varies considerably among patients, and reliable biomarkers to predict treatment outcomes have not yet been fully established. Routine blood tests provide valuable insights into both the general condition of patients and tumor biology ( 8 – 10 ). Among these, serum albumin (Alb) is a simple and practical marker that reflects nutritional and inflammatory status as well as overall prognosis, and it has been reported as a prognostic factor in various malignancies ( 11 , 12 ). Low Alb levels are often accompanied by elevated C-reactive protein (CRP) or lactate dehydrogenase (LDH) levels, suggesting systemic inflammation or increased tumor activity. CRP has been associated with cancer-related inflammation and poor outcomes ( 13 ), while LDH reflects tumor metabolism and burden ( 14 , 15 ), with an elevated LDH level recognized as an unfavorable prognostic factor for CRC ( 16 , 17 ). In addition, inflammatory indices such as the neutrophil-to-lymphocyte ratio and lymphocyte-to-monocyte ratio have been proposed as potential prognostic markers in patients treated with FTD/TPI or FTD/TPI plus BEV ( 18 , 19 ). Similarly, Alb—as an inflammation-based indicator—has been linked to shorter OS and PFS in CRC ( 20 ). Nevertheless, its predictive value in the specific context of FTD/TPI plus BEV therapy remains unclear. Therefore, this study aimed to retrospectively investigate the association between baseline Alb levels and treatment outcomes in patients with metastatic CRC receiving FTD/TPI plus BEV, with the aim of determining whether Alb may serve as a predictive factor for its therapeutic efficacy. Methods Study design and patient population This single-center, retrospective cohort study evaluated the association between baseline serum Alb levels and the efficacy of FTD/TPI plus BEV in patients with metastatic mCRC. Data were collected at Fukuyama Medical Center, Hiroshima, Japan, from December 1, 2017, to March 31, 2024. The study protocol is illustrated in Fig. 1 . Patients with unresectable or recurrent mCRC who had received first-, second-, or third-line chemotherapy and subsequently experienced disease progression were treated with FTD/TPI plus BEV. FTD/TPI was administered orally at a dose of 35 mg/m² twice daily according to one of the two schedules: days 1–5 and 8–12 or days 1–5 and 15–19 of a 28-day cycle. Bevacizumab was administered intravenously at 5 mg/kg on days 1 and 15 of each cycle. Patients were categorized into High-Alb and Low-Alb groups based on baseline serum Alb levels. The cutoff value for Alb was determined by receiver operating characteristic (ROC) curve analysis using PFS as the reference, with the median PFS of the study population as the anchor point. Patients with Alb levels equal to or above this cutoff were assigned to the High-Alb group and those below the cutoff were assigned to the Low-Alb group. Data collection The following data were extracted from the medical records of patients: age, sex, Eastern Cooperative Oncology Group performance status (ECOG-PS), body mass index, mutation status, metastatic sites, primary tumor location, history of primary tumor resection, prior treatments, treatment line, initial FTD/TPI dose reduction, baseline laboratory values, tumor markers, PFS, and OS. Clinical endpoints The primary endpoint was PFS, and the secondary endpoint was OS. Treatment response was assessed by the attending physicians using computed tomography (CT) scans, clinical symptoms, and tumor marker trends. Definitions of PFS and OS PFS was defined as the time from the first administration of FTD/TPI plus BEV to documented disease progression or death from any cause. OS was defined as the time from the first administration to death from any cause. Statistical analysis Continuous variables are expressed as medians with interquartile ranges (IQRs), and categorical variables are expressed as frequencies and percentages. Comparisons between the High-Alb and Low-Alb groups were made using the Mann–Whitney U test or Fisher’s exact test. The median PFS and OS were estimated using the Kaplan–Meier method, and survival curves were compared using the log-rank test. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using the Cox proportional hazards model to assess the influence of multiple covariates. Based on previous reports, established prognostic factors for CRC (age, primary tumor site, metastatic sites, and LDH) ( 16 , 21 , 22 ) were included as explanatory variables. Continuous variables were dichotomized according to cutoff values determined by ROC analysis with reference to the median PFS. A two-sided p-value of < 0.05 was considered statistically significant. Statistical analyses were performed using EZR (version 1.68; Saitama Medical Center, Jichi Medical University, Saitama, Japan). Ethical considerations This study was conducted in compliance with the “Ethical Guidelines for Medical Research Involving Human Subjects” and the “Appropriate Handling of Personal Information by Medical and Nursing Care Providers” guidelines. Ethical approval was obtained from the Ethics Review Committee of Fukuyama Medical Center (approval number: ERBP2024005). Results ROC analysis of Alb levels for PFS The median PFS of the study cohort was 3.7 months (IQR: 2.3–8.2 months). ROC curve analysis of baseline Alb levels for predicting PFS ≥ median identified an optimal cutoff of 3.7 g/dL, with an area under the curve (AUC) value of 0.740 (95% CI: 0.618–0.862), a sensitivity of 0.806, and a specificity of 0.697. Baseline clinical characteristics of participants A total of 69 patients were included (Fig. 1 ). The median age was 69 years (IQR: 60–74 years), and 35 patients (48.4%) were female. Notably, 67 patients (96.8%) had a performance status of 0 or 1 (Table 1 ). Right-sided tumors were observed in 26 patients (37.3%), and 51 patients (73.9%) had undergone primary resection. Prior therapies included BEV in 67 patients (97.1%), RAM in 30 (43.5%), and anti-epidermal growth factor receptor antibodies in 24 (34.8%). FTD/TPI plus BEV was administered as second- or third-line therapy in 38 patients (55.1%). Based on the Alb cutoff value, 39 patients were classified into the High-Alb group. Table 1 Baseline characteristics of the study cohort Characteristic Overall (N = 69) High-Alb group (n = 39) Low-Alb group (n = 30) p-value Age, years 69 (60–74) 66 (57–73) 70 (67–74) 0.046 Sex, female; number (%) 35 (48.4%) 22 (56.4%) 13 (43.3%) 0.366 ECOG-PS (0–1); number (%) 67 (96.8%) 39 (100.0%) 28 (93.3%) 0.185 BMI (kg/m 2 ) 22.7 (19.8–23.9) 22.7 (19.7–24.1) 22.9 (20.4–23.8) 0.904 KRAS mutation. number (%) 43 (59.7%) 26 (66.7%) 17 (56.7%) 0.457 BRAF status; number (%) Mutant 1 (1.4%) 0 (0.0%) 1 (3.3%) — Wild-type 60 (87.0%) 34 (87.2%) 26 (86.7%) Missing or Unknown 8 (11.6%) 5 (12.8%) 3 (10.0%) MSI status; number (%) High-MSI 1 (1.4%) 1 (2.6%) 0 (0.0%) — Stable or low MSI 63 (91.3%) 36 (92.3%) 27 (90.0%) Missing or Unknown 5 (7.2%) 2 (5.1%) 3 (10.0%) Liver metastasis; number (%) 47 (68.1%) 27 (69.2%) 20 (66.7%) 1.000 Lung metastasis; number (%) 38 (55.1%) 24 (61.5%) 14 (46.7%) 0.234 Peritoneal dissemination; number (%) 22 (31.9%) 13 (33.3%) 9 (30.0%) 0.800 Tumor location: Rectum (vs. colon); number (%) 17 (24.6%) 11 (28.2%) 6 (20.0%) 0.575 Tumor location: Right-sided (vs. left-sided); number (%) 26 (37.7%) 12 (30.8%) 14 (46.7%) 0.215 History of primary tumor resection; number (%) 51 (73.9%) 32 (82.1%) 19 (63.3%) 0.101 Prior bevacizumab treatment; number (%) 67 (97.1%) 37 (94.9%) 30 (100.0%) 0.501 Prior ramucirumab treatment; number (%) 30 (43.5%) 17 (43.6%) 13 (43.3%) 1.000 Prior anti-EGFR antibody treatment; number (%) 24 (34.8%) 12 (30.8%) 12 (40.0%) 0.455 Treatment line: 2nd or 3rd line (vs. ≥4th line); number (%) 38 (55.1%) 23 (59.0%) 15 (50.0%) 0.476 Initial dose reduction of FTD/TPI; number (%) 28 (40.6%) 12 (30.8%) 16 (53.3%) 0.084 Laboratory data White blood cell count, /µL 5,400 (4,200–7,500) 5,000 (4,200-6,300) 7,000 (4,100-8,800) 0.078 Lymphocyte count, /µL; 1,350 (970-1,625) 1,267 (1,005–1,600) 1,422 (912–1,762) 0.650 Hemoglobin, g/dL 11.8 (10.5–12.6) 12.0 (11.3–15.5) 11.1 (10.3–12.4) 0.017 Platelet, ×10 4 /µL 19.7 (13.8–24.3) 19.7 (15.5–23.5) 18.9 (12.5–27.8) 0.932 AST, U/L 29 ( 20 – 43 ) 24 ( 20 – 33 ) 34 (25–61) 0.003 ALT, U/L 21 ( 13 – 30 ) 19 ( 12 – 25 ) 25 ( 15 – 37 ) 0.045 Total bilirubin, mg/dL 0.6 (0.4–0.8) 0.6 (0.5–0.7) 0.6 (0.4–0.9) 0.937 LDH, U/L 255 (201–423) 237 (195–299) 372 (224–651) 0.016 Creatinine, mg/dL 0.74 (0.60–0.87) 0.7 2(0.60–0.82) 0.78 (0.68–0.88) 0.260 CRP, mg/dL 0.28 (0.12–1.27) 0.15 (0.10–0.79) 0.67 (0.20–2.26) 0.002 CEA, ng/mL 81.10 (21.15–427.04) 61.61 (9.24–269.85) 125.57 (32.21-724.86) 0.163 CA19-9, U/mL 251.97 (13.24–1,830.61) 210.30 (14.74–825.55) 382.31 (15.42–6,945.99) 0.268 Data are presented as medians (interquartile range [IQR], 25th–75th percentile) or as numbers (percentages). * p < 0.05 was considered statistically significant. Abbreviations: ECOG-PS, Eastern Cooperative Oncology Group performance status scale; BMI, body mass index; MSI, microsatellite instability; AST, aspartate aminotransaminase; ALT, alanine aminotransferase; LDH, lactate dehydrogenase; CRP, C-reactive protein; CEA, arcinoembryonic antigen; CA19-9, cancer antigen 19 − 9. Comparison of clinical characteristics between the groups Patients in the High-Alb group were significantly younger (66 [IQR: 57–73] years vs. 70 [IQR: 67–74] years, p = 0.046) and had higher hemoglobin levels (12.0 [IQR: 11.3–15.5] g/dL vs. 11.1 [IQR: 10.3–12.4] g/dL, p = 0.017) than those in the Low-Alb group. By contrast, LDH levels (237 [IQR: 195–299] U/L vs. 372 [IQR: 224–651] U/L, p = 0.016) and CRP levels (0.15 [IQR: 0.10–0.79] mg/dL vs. 0.67 [IQR: 0.20–2.26] mg/dL, p = 0.002) were significantly lower in the High-Alb group than in the Low-Alb group (all p < 0.05; Table 1 ). Association between Alb levels and survival Patients in the High-Alb group had significantly longer PFS (median: 5.2 vs. 3.0 months; Fig. 2 A) and OS (median: 15.6 vs. 6.0 months; Fig. 2 B) than those in the Low-Alb group. ROC analysis of LDH and CRP levels for predicting treatment efficacy ROC analysis of serum LDH and CRP levels for predicting PFS ≥ median identified optimal cutoff values of 338 U/L and 1.3 mg/dL, respectively. For LDH, the AUC was 0.605 (95% CI: 0.467–0.742), with a sensitivity of 80.6% and specificity of 45.5%. For CRP, the AUC was 0.652 (95% CI: 0.522–0.782), with a sensitivity of 88.9% and specificity of 36.4%. Exploratory analysis of predictors of PFS To identify the predictors of PFS, two Cox proportional hazards models were constructed (Table 2 ). In Model 1—adjusted for age and primary tumor site ( 20 , 23 )—Alb ≥ 3.7 g/dL was the only significant factor and was associated with prolonged PFS (HR: 0.35, 95% CI: 0.19–0.63, p < 0.001). In Model 2—adjusted for peritoneal dissemination and LDH ≥ 338 U/L ( 21 , 22 )—both Alb ≥ 3.7 g/dL (HR: 0.40, 95% CI: 0.22–0.73, p = 0.003) and LDH ≥ 338 U/L (HR: 2.31, 95% CI: 1.28–4.32, p = 0.009) were independently associated with PFS. Table 2 Univariate model Multivariate model 1 Multivariate model 2 HR (95% CI) p-value HR (95% CI) p-value HR (95% CI) p-value Age (≥ 65 years), yes 1.217 0.70–2.12 0.489 1.57 0.87–2.83 0.133 - - - Treatment line: 2nd or 3rd (vs. ≥4th), yes 0.747 0.44–1.27 0.283 - - - - - - Primary tumor location: Right-sided, yes 1.577 0.88–2.84 0.129 1.43 0.78–2.60 0.253 - - - Liver metastasis, yes 1.026 0.57–1.85 0.933 - - - - - - Lung metastasis, yes 0.841 0.49–1.44 0.527 - - - - - - Peritoneal dissemination, yes 1.11 0.62–2.00 0.729 - - - 1.40 0.76–2.56 0.281 LDH, ≥ 338 U/L 2.68 1.47–4.88 0.001 - - - 2.31 1.28–4.32 0.009 CRP, ≥ 1.3 mg/dL 2.10 1.12–3.93 0.020 - - - - - - Alubmin, ≥ 3.7 g/dL 0.36 0.20–0.64 < 0.001 0.347 0.19–0.63 < 0.001 0.40 0.22–0.73 0.003 p < 0.05 was considered statistically significant. Abbreviations: LDH, lactate dehydrogenase; CRP, C-reactive protein; CEA; HR, hazard ratio; CI, confidence interval Discussion In this study, we found that baseline serum Alb levels at the initiation of FTD/TPI plus BEV therapy were significantly associated with PFS and OS. Furthermore, patients with pretreatment Alb levels of ≥ 3.7 g/dL tended to experience more favorable outcomes with FTD/TPI plus BEV therapy. These findings suggest that Alb may serve as a simple and potentially useful marker for predicting the treatment response of FTD/TPI plus BEV in clinical practice. The median PFS in our study cohort was 3.7 months, which was somewhat shorter than the 5.6 months reported in a previous trial ( 5 ). In that study, the median age of patients was 62 years, and 92% received third-line therapy; however, the median age of patients in the present study was 69 years, and 45% received fourth-line or later therapy. These differences suggest that our study population was older and more heavily pretreated, potentially reflecting a clinical setting closer to real-world practice. Within this cohort, the median PFS in the High-Alb group was 5.2 months, approaching the outcome reported in a previous study ( 5 ). By contrast, patients in the Low-Alb group experienced more limited PFS benefit. Several factors may account for these findings. First, reduced Alb levels often reflect cancer progression and systemic inflammation, which may be associated with diminished treatment responsiveness. Previous studies have shown that the CRP-to-Alb ratio is correlated with poor PFS and OS in patients with CRC ( 24 ), and serum Alb has been reported as an independent prognostic factor for CRC ( 25 – 27 ). Cancer-associated inflammation reduces hepatic Alb synthesis via cytokines such as interleukin-6, and persistent hypoalbuminemia may contribute to cancer progression and mortality ( 28 – 30 ). Although Alb levels can be influenced by factors other than cancer ( 31 ), our findings indicate that baseline Alb levels can provide clinically useful insights into treatment response to FTD/TPI plus BEV. In Cox proportional hazards models, Alb levels ≥ 3.7 g/dL were significantly associated with prolonged PFS, and the association remained significant in multiple models. Although the reference range for adult serum Alb typically ranges from 3.5 to 5.0 g/dL—with levels below 3.5 g/dL generally considered hypoalbuminemia ( 32 , 33 )—institutional ranges vary. At our institution, the normal range for serum Alb is 4.1–5.1 g/dL; therefore, the cutoff value of 3.7 g/dL identified in this study was deemed clinically reasonable. Moreover, Alb may act as an integrative marker reflecting the nutritional status, inflammatory activity, treatment responsiveness, and overall condition of the patient. This interpretation is supported by the significantly lower CRP and LDH levels observed in the High-Alb group. As CRP reflects systemic inflammation and LDH reflects tumor burden and metabolic activity ( 13 – 15 ), lower values of these markers suggest that patients in the High-Alb group may have relatively attenuated inflammation and tumor progression. Accordingly, higher Alb levels may not only indicate a better nutritional status but also reflect a background of attenuated inflammatory activity and tumor burden, which could contribute to more favorable treatment outcomes. A second possible explanation is that hypoalbuminemia or elevated LDH levels may have affected the pharmacokinetics and pharmacodynamics of BEV. In this study, PFS in the High-Alb group (5.2 months) was comparable to that reported for the BEV combination group in the SUNLIGHT trial (5.6 months) ( 5 ), despite differing patient backgrounds. Conversely, the Low-Alb group achieved a PFS of 3.0 months, closer to that of the FTD/TPI monotherapy group (2.4 months) in the same trial. This raises the possibility that low Alb levels may alter BEV pharmacokinetics, thereby attenuating its efficacy. Prior studies have suggested that even mild proteinuria—defined as a urinary protein-to-creatinine ratio of ≤ 1 g/dL—may lower BEV concentrations and reduce its therapeutic effect ( 34 ). Although urinary protein levels were not assessed in the present study, patients in the Low-Alb group may have had chronic, low-grade protein loss, potentially contributing to decreased Alb levels and reduced BEV exposure. In addition, the expression of vascular endothelial growth factor is influenced by hypoxia and inflammation, which may affect the efficacy of BEV ( 35 ). In CRC, breast cancer, and renal cell carcinoma, BEV has been reported to prolong PFS and OS, particularly in patients with low levels of systemic inflammation ( 36 – 38 ). Although evidence is more limited for non–small cell lung cancer, some reports have shown associations between BEV efficacy and inflammatory markers ( 39 , 40 ). Hoang et al. reported that hypoalbuminemia was associated with worse PFS and OS ( 39 ). In the present study, the Low-Alb group also exhibited lower hemoglobin and higher CRP and LDH levels, consistent with persistent inflammation, suggesting reduced responsiveness to BEV. Furthermore, LDH was identified as a predictive factor in multivariate analysis. A meta-analysis of LDH and BEV in CRC confirmed significant associations with both PFS and OS ( 41 ), and other studies have proposed LDH as a potential predictive biomarker for anti-angiogenic therapy ( 42 , 43 ). Moreover, in the HORIZON I trial, Bar et al. reported that elevated LDH levels were significantly associated with shorter PFS ( 44 ). Our results are broadly consistent with these prior findings. Taken together, these observations suggest that serum Alb may be an important factor influencing the treatment outcomes of FTD/TPI plus BEV therapy through mechanisms involving systemic inflammation, tumor activity, and pharmacokinetics. This study has some limitations. First, it was a single-center, retrospective study with a limited sample size, and large-scale prospective studies are needed to validate these findings. Second, response rates were not evaluated, preventing the direct assessment of treatment efficacy. Third, other prognostic factors—such as histological subtype and molecular alterations (e.g., BRAF V600E)—were not fully investigated; therefore, the possibility remains that the Low-Alb group included patients with a more aggressive disease. Conclusions The findings of this study suggest that serum Alb may serve as a potential predictive factor for the efficacy of FTD/TPI plus BEV therapy in patients with mCRC. Initiating FTD/TPI plus BEV therapy before substantial deterioration of nutritional or inflammatory status associated with disease progression may help achieve more favorable clinical outcomes. Abbreviations Alb albumin AUC area under the curve BEV bevacizumab BMI body mass index CI confidence interval CRC colorectal cancer CRP C-reactive protein FTD/TPI trifluridine/tipiracil HR hazard ratio IQR interquartile range LDH lactate dehydrogenase mCRC metastatic colorectal cancer OS overall survival PFS progression-free survival ROC receiver operating characteristic. Declarations Ethics approval and consent to participate This study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics review board of the Fukuyama Medical Center (Approval number: ERBP2024005). Informed consent was obtained via opt-out through the website. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors' contributions MM and RT contributed to the study conception and design. MM, RT, HS and MF performed material preparation, data collection, and analysis. HT and YO critically revised the manuscript. All authors have read and approved the final manuscript. Acknowledgements We would like to thank Editage (www.editage.jp) for English language editing. References Siegel RL, Miller KD, Goding Sauer A, Fedewa SA, Butterly LF, Anderson JC, Cercek A, Smith RA, Jemal A. Colorectal cancer statistics, 2020. CA Cancer J Clin. 2020 May; 70(3):145–64. 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Baseline nutritional status is predictive of response to treatment and survival in patients treated by definitive chemoradiotherapy for a locally advanced esophageal cancer. Am J Gastroenterol. 2007 Nov; 102(11):2557–63. Available from: https://journals.lww.com/ajg/abstract/2007/11000/baseline_nutritional_status_is_predictive_of.32.aspx doi:10.1111/j.1572-0241.2007.01437.x Masuda, T., Funakoshi, T., Horimatsu, T, Yamamoto S, Matsubara T, Masui S, et al. Low serum concentrations of bevacizumab and nivolumab owing to excessive urinary loss in patients with proteinuria: A case series. Cancer Chemother Pharmacol. 2024 Oct; 94(4):615–622. Available from: https://link.springer.com/article/10.1007/s00280-024-04659-3 doi:10.1007/s00280-024-04659-3 Martino, E., Misso, G., Pastina, P, Costantini S, Vanni F, Gandolfo C, et al. Immune-modulating effects of bevacizumab in metastatic non-small-cell lung cancer patients. Cell Death Discov. 2016 Oct 3; 2:16025. Available from: https://www.nature.com/articles/cddiscovery201625 doi:10.1038/cddiscovery.2016.25 Artaç M, Uysal M, Karaağaç M, Korkmaz L, Er Z, Güler T, et al. Prognostic impact of neutrophil/lymphocyte ratio, platelet count, CRP, and albumin levels in metastatic colorectal cancer patients treated with FOLFIRI-bevacizumab. J Gastrointest Cancer. 2017 Jun; 48(2):176–80. Available from: https://link.springer.com/article/10.1007/s12029-016-9879-4 doi:10.1007/s12029-016-9879-4 Miyagawa Y, Yanai A, Yanagawa T, Inatome J, Egawa C, Nishimukai A, et al. Baseline neutrophil-to-lymphocyte ratio and c-reactive protein predict efficacy of treatment with bevacizumab plus paclitaxel for locally advanced or metastatic breast cancer. Oncotarget. 2020 Jan 7; 11(1):86–98. Available from: https://www.oncotarget.com/article/27423/text/ doi:10.18632/oncotarget.27423 Heng DY, Xie W, Regan MM, Warren MA, Golshayan AR, Sahi C, et al. Prognostic factors for overall survival in patients with metastatic renal cell carcinoma treated with vascular endothelial growth factor-targeted agents: Results from a large, multicenter study. J Clin Oncol. 2009 Dec 1; 27(34):5794–9. Available from: https://ascopubs.org/doi/10.1200/JCO.2008.21.4809 doi:10.1200/JCO.2008.21.4809 Hoang T, Dahlberg SE, Sandler AB, Brahmer JR, Schiller JH, Johnson DH. Prognostic models to predict survival in non-small-cell lung cancer patients treated with first-line paclitaxel and carboplatin with or without bevacizumab. J Thorac Oncol. 2012 Sep; 7(9):1361–8. Available from: https://www.jto.org/article/S1556-0864(15)32936-1/fulltext doi:10.1097/JTO.0b013e318260e106 Botta C, Barbieri V, Ciliberto D, Rossi A, Rocco D, Addeo R, et al. Systemic inflammatory status at baseline predicts bevacizumab benefit in advanced non-small cell lung cancer patients. Cancer Biol Ther. 2013 Jun; 14(6):469–75. Available from: http://tandfonline.com/doi/full/10.4161/cbt.24425 doi:10.4161/cbt.24425 Feng W, Wang Y, Zhu X. Baseline serum lactate dehydrogenase level predicts survival benefit in patients with metastatic colorectal cancer receiving bevacizumab as first-line chemotherapy: A systematic review and meta-analysis of 7 studies and 1,219 patients. Ann Transl Med. 2019 Apr; 7(7):133. Available from: https://atm.amegroups.org/article/view/24641/23455 doi:10.21037/atm.2019.02.45 Bertaut A, Truntzer C, Madkouri R, Kaderbhai CG, Derangère V, Vincent J, et al. Blood baseline neutrophil count predicts bevacizumab efficacy in glioblastoma. Oncotarget. 2016 Oct 25; 7(43):70948–58. Available from: https://www.oncotarget.com/article/10898/text/ doi:10.18632/oncotarget.10898 Farolfi A, Petrone M, Scarpi E, Gallà V, Greco F, Casanova C, et al. Inflammatory indexes as prognostic and predictive factors in ovarian cancer treated with chemotherapy alone or together with bevacizumab. A multicenter, retrospective analysis by the MITO Group (MITO 24). Target Oncol. 2018 Aug; 13(4):469–79. Available from: https://link.springer.com/article/10.1007/s11523-018-0574-1#citeas doi:10.1007/s11523-018-0574-1 Bertolini F, Sukhatme VP, Bouche G. Drug repurposing in oncology--patient and health systems opportunities. 2015 Dec; 12(12):732–42. Available from: https://www.nature.com/articles/nrclinonc.2015.169 doi:10.1038/nrclinonc.2015.169 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 03 Dec, 2025 Read the published version in Journal of Pharmaceutical Health Care and Sciences → 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7790891","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":531625813,"identity":"6bb0efd5-9ca9-47c0-a421-b24495e4757a","order_by":0,"name":"Masatoshi 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19:30:35","extension":"xml","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":139398,"visible":true,"origin":"","legend":"","description":"","filename":"ce8811d83d6d42d6ba755b9be497adc51structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7790891/v1/4e4c59233f9a7d4ed797f82d.xml"},{"id":94138780,"identity":"e2ab5d9f-fba2-4e9d-a147-1338fab2a503","added_by":"auto","created_at":"2025-10-22 19:30:35","extension":"html","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":151084,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7790891/v1/4a1c558c523ff1b78f45b8a5.html"},{"id":94140205,"identity":"1a935fa0-2c25-48c7-b69e-223b14fe7793","added_by":"auto","created_at":"2025-10-22 19:38:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":38310,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of patient selection.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7790891/v1/f010a2ec6e6f4ed229976dfe.png"},{"id":94140721,"identity":"bc8796be-72a8-434d-8e9f-6782c0e2cec0","added_by":"auto","created_at":"2025-10-22 19:46:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":178302,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(A)\u003c/strong\u003eKaplan–Meier curves for progression-free survival (PFS) stratified by baseline serum albumin (Alb) levels. Patients were categorized into High-Alb (≥3.7 g/dL) and Low-Alb (\u0026lt;3.7 g/dL) groups. The High-Alb group demonstrated significantly longer PFS than the Low-Alb group (median: 5.2 vs. 3.0 months; p \u0026lt; 0.001, log-rank test).\u003cstrong\u003e (B)\u003c/strong\u003e Kaplan–Meier curves for overall survival (OS) stratified by baseline serum Alb levels. The High-Alb group showed significantly longer OS than the Low-Alb group (median: 15.6 vs. 6.0 months; p \u0026lt; 0.001, log-rank test).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7790891/v1/396fdc9d24fd8b0b9986c18d.png"},{"id":97724584,"identity":"a2c06e14-939a-4f06-973c-ff9003287a72","added_by":"auto","created_at":"2025-12-08 16:12:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1178040,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7790891/v1/9858cde2-fced-451a-8387-0e242686dae3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Baseline serum albumin level as a predictive factor for the efficacy of trifluridine/tipiracil plus bevacizumab in metastatic colorectal cancer: A retrospective cohort study","fulltext":[{"header":"Background","content":"\u003cp\u003eColorectal cancer (CRC) is one of the most prevalent malignancies worldwide and is associated with high incidence and mortality rates (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). For patients with advanced, recurrent, or unresectable disease, systemic chemotherapy remains the cornerstone of treatment. In recent years, trifluridine/tipiracil (FTD/TPI) has demonstrated a survival benefit in the later-line setting (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Moreover, the addition of bevacizumab (BEV) to FTD/TPI has been demonstrated to further improve both progression-free survival (PFS) and overall survival (OS) (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Based on these findings, FTD/TPI plus BEV has become widely adopted as a standard later-line therapy for advanced or recurrent CRC (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite this progress, the clinical efficacy of FTD/TPI plus BEV varies considerably among patients, and reliable biomarkers to predict treatment outcomes have not yet been fully established. Routine blood tests provide valuable insights into both the general condition of patients and tumor biology (\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Among these, serum albumin (Alb) is a simple and practical marker that reflects nutritional and inflammatory status as well as overall prognosis, and it has been reported as a prognostic factor in various malignancies (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Low Alb levels are often accompanied by elevated C-reactive protein (CRP) or lactate dehydrogenase (LDH) levels, suggesting systemic inflammation or increased tumor activity. CRP has been associated with cancer-related inflammation and poor outcomes (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), while LDH reflects tumor metabolism and burden (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), with an elevated LDH level recognized as an unfavorable prognostic factor for CRC (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn addition, inflammatory indices such as the neutrophil-to-lymphocyte ratio and lymphocyte-to-monocyte ratio have been proposed as potential prognostic markers in patients treated with FTD/TPI or FTD/TPI plus BEV (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Similarly, Alb\u0026mdash;as an inflammation-based indicator\u0026mdash;has been linked to shorter OS and PFS in CRC (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Nevertheless, its predictive value in the specific context of FTD/TPI plus BEV therapy remains unclear.\u003c/p\u003e\u003cp\u003eTherefore, this study aimed to retrospectively investigate the association between baseline Alb levels and treatment outcomes in patients with metastatic CRC receiving FTD/TPI plus BEV, with the aim of determining whether Alb may serve as a predictive factor for its therapeutic efficacy.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design and patient population\u003c/h2\u003e\u003cp\u003eThis single-center, retrospective cohort study evaluated the association between baseline serum Alb levels and the efficacy of FTD/TPI plus BEV in patients with metastatic mCRC. Data were collected at Fukuyama Medical Center, Hiroshima, Japan, from December 1, 2017, to March 31, 2024. The study protocol is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePatients with unresectable or recurrent mCRC who had received first-, second-, or third-line chemotherapy and subsequently experienced disease progression were treated with FTD/TPI plus BEV. FTD/TPI was administered orally at a dose of 35 mg/m\u0026sup2; twice daily according to one of the two schedules: days 1\u0026ndash;5 and 8\u0026ndash;12 or days 1\u0026ndash;5 and 15\u0026ndash;19 of a 28-day cycle. Bevacizumab was administered intravenously at 5 mg/kg on days 1 and 15 of each cycle.\u003c/p\u003e\u003cp\u003ePatients were categorized into High-Alb and Low-Alb groups based on baseline serum Alb levels. The cutoff value for Alb was determined by receiver operating characteristic (ROC) curve analysis using PFS as the reference, with the median PFS of the study population as the anchor point. Patients with Alb levels equal to or above this cutoff were assigned to the High-Alb group and those below the cutoff were assigned to the Low-Alb group.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eThe following data were extracted from the medical records of patients: age, sex, Eastern Cooperative Oncology Group performance status (ECOG-PS), body mass index, mutation status, metastatic sites, primary tumor location, history of primary tumor resection, prior treatments, treatment line, initial FTD/TPI dose reduction, baseline laboratory values, tumor markers, PFS, and OS.\u003c/p\u003e\n\u003ch3\u003eClinical endpoints\u003c/h3\u003e\n\u003cp\u003eThe primary endpoint was PFS, and the secondary endpoint was OS. Treatment response was assessed by the attending physicians using computed tomography (CT) scans, clinical symptoms, and tumor marker trends.\u003c/p\u003e\n\u003ch3\u003eDefinitions of PFS and OS\u003c/h3\u003e\n\u003cp\u003ePFS was defined as the time from the first administration of FTD/TPI plus BEV to documented disease progression or death from any cause. OS was defined as the time from the first administration to death from any cause.\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eContinuous variables are expressed as medians with interquartile ranges (IQRs), and categorical variables are expressed as frequencies and percentages. Comparisons between the High-Alb and Low-Alb groups were made using the Mann\u0026ndash;Whitney U test or Fisher\u0026rsquo;s exact test. The median PFS and OS were estimated using the Kaplan\u0026ndash;Meier method, and survival curves were compared using the log-rank test. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using the Cox proportional hazards model to assess the influence of multiple covariates. Based on previous reports, established prognostic factors for CRC (age, primary tumor site, metastatic sites, and LDH) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) were included as explanatory variables. Continuous variables were dichotomized according to cutoff values determined by ROC analysis with reference to the median PFS. A two-sided p-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant. Statistical analyses were performed using EZR (version 1.68; Saitama Medical Center, Jichi Medical University, Saitama, Japan).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eEthical considerations\u003c/h2\u003e\u003cp\u003e This study was conducted in compliance with the \u0026ldquo;Ethical Guidelines for Medical Research Involving Human Subjects\u0026rdquo; and the \u0026ldquo;Appropriate Handling of Personal Information by Medical and Nursing Care Providers\u0026rdquo; guidelines. Ethical approval was obtained from the Ethics Review Committee of Fukuyama Medical Center (approval number: ERBP2024005).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eROC analysis of Alb levels for PFS\u003c/h2\u003e\u003cp\u003eThe median PFS of the study cohort was 3.7 months (IQR: 2.3\u0026ndash;8.2 months). ROC curve analysis of baseline Alb levels for predicting PFS\u0026thinsp;\u0026ge;\u0026thinsp;median identified an optimal cutoff of 3.7 g/dL, with an area under the curve (AUC) value of 0.740 (95% CI: 0.618\u0026ndash;0.862), a sensitivity of 0.806, and a specificity of 0.697.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eBaseline clinical characteristics of participants\u003c/h2\u003e\u003cp\u003eA total of 69 patients were included (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The median age was 69 years (IQR: 60\u0026ndash;74 years), and 35 patients (48.4%) were female. Notably, 67 patients (96.8%) had a performance status of 0 or 1 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Right-sided tumors were observed in 26 patients (37.3%), and 51 patients (73.9%) had undergone primary resection. Prior therapies included BEV in 67 patients (97.1%), RAM in 30 (43.5%), and anti-epidermal growth factor receptor antibodies in 24 (34.8%). FTD/TPI plus BEV was administered as second- or third-line therapy in 38 patients (55.1%). Based on the Alb cutoff value, 39 patients were classified into the High-Alb group.\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\u003eBaseline characteristics of the study cohort\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"12\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eOverall (N\u0026thinsp;=\u0026thinsp;69)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003eHigh-Alb group (n\u0026thinsp;=\u0026thinsp;39)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e\u003cp\u003eLow-Alb group (n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\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\u003eAge, years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(60\u0026ndash;74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e(57\u0026ndash;73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e(67\u0026ndash;74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.046\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex, female; number (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(48.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e(56.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e(43.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.366\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eECOG-PS (0\u0026ndash;1); number (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(96.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e(100.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e(93.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.185\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)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(19.8\u0026ndash;23.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e22.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e(19.7\u0026ndash;24.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e22.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e(20.4\u0026ndash;23.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.904\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKRAS mutation. number (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(59.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e(66.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e(56.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.457\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBRAF status; number (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMutant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e(0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e(3.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWild-type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(87.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e(87.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e(86.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMissing or Unknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(11.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e(12.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e(10.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e\u003cp\u003eMSI status; number (%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh-MSI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e(2.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e(0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStable or low MSI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(91.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e(92.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e(90.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMissing or Unknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(7.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e(5.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e(10.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiver metastasis; number (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(68.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e(69.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e(66.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLung metastasis; number (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(55.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e(61.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e(46.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.234\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePeritoneal dissemination; number (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(31.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e(33.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e(30.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.800\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTumor location: Rectum (vs. colon); number (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(24.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e(28.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e(20.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.575\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTumor location: Right-sided (vs. left-sided); number (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(37.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e(30.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e(46.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.215\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHistory of primary tumor resection; number (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(73.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e(82.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e(63.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.101\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrior bevacizumab treatment; number (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(97.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e(94.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e(100.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.501\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrior ramucirumab treatment; number (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(43.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e(43.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e(43.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrior anti-EGFR antibody treatment; number (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(34.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e(30.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e(40.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.455\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreatment line: 2nd or 3rd line (vs. \u0026ge;4th line); number (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(55.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e(59.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e(50.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.476\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInitial dose reduction of FTD/TPI; number (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(40.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e(30.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e(53.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.084\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e\u003cp\u003eLaboratory data\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWhite blood cell count, /\u0026micro;L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5,400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(4,200\u0026ndash;7,500)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e5,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e(4,200-6,300)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e7,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e(4,100-8,800)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.078\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLymphocyte count, /\u0026micro;L;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,350\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(970-1,625)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1,267\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e(1,005\u0026ndash;1,600)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e1,422\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e(912\u0026ndash;1,762)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.650\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHemoglobin, g/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(10.5\u0026ndash;12.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e12.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e(11.3\u0026ndash;15.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e11.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e(10.3\u0026ndash;12.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePlatelet, \u0026times;10\u003csup\u003e4\u003c/sup\u003e/\u0026micro;L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(13.8\u0026ndash;24.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e19.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e(15.5\u0026ndash;23.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e18.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e(12.5\u0026ndash;27.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.932\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAST, U/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29 CR30 CR31 CR32 CR33 CR34 CR35 CR36 CR37 CR38 CR39 CR40 CR41 CR42\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29 CR30 CR31 CR32\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e(25\u0026ndash;61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALT, U/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR14 CR15 CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR13 CR14 CR15 CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29 CR30 CR31 CR32 CR33 CR34 CR35 CR36\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.045\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal bilirubin, mg/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.4\u0026ndash;0.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e(0.5\u0026ndash;0.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e(0.4\u0026ndash;0.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.937\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLDH, U/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e255\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(201\u0026ndash;423)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e237\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e(195\u0026ndash;299)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e372\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e(224\u0026ndash;651)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCreatinine, mg/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.60\u0026ndash;0.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2(0.60\u0026ndash;0.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e(0.68\u0026ndash;0.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.260\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCRP, mg/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.12\u0026ndash;1.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e(0.10\u0026ndash;0.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e(0.20\u0026ndash;2.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCEA, ng/mL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e81.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(21.15\u0026ndash;427.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e61.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e(9.24\u0026ndash;269.85)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e125.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e(32.21-724.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.163\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCA19-9, U/mL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e251.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(13.24\u0026ndash;1,830.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e210.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e(14.74\u0026ndash;825.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e382.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e(15.42\u0026ndash;6,945.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.268\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"12\"\u003eData are presented as medians (interquartile range [IQR], 25th\u0026ndash;75th percentile) or as numbers (percentages). * \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"12\"\u003eAbbreviations: ECOG-PS, Eastern Cooperative Oncology Group performance status scale; BMI, body mass index; MSI, microsatellite instability; AST, aspartate aminotransaminase; ALT, alanine aminotransferase; LDH, lactate dehydrogenase; CRP, C-reactive protein; CEA, arcinoembryonic antigen; CA19-9, cancer antigen 19\u0026thinsp;\u0026minus;\u0026thinsp;9.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eComparison of clinical characteristics between the groups\u003c/h2\u003e\u003cp\u003ePatients in the High-Alb group were significantly younger (66 [IQR: 57\u0026ndash;73] years vs. 70 [IQR: 67\u0026ndash;74] years, p\u0026thinsp;=\u0026thinsp;0.046) and had higher hemoglobin levels (12.0 [IQR: 11.3\u0026ndash;15.5] g/dL vs. 11.1 [IQR: 10.3\u0026ndash;12.4] g/dL, p\u0026thinsp;=\u0026thinsp;0.017) than those in the Low-Alb group. By contrast, LDH levels (237 [IQR: 195\u0026ndash;299] U/L vs. 372 [IQR: 224\u0026ndash;651] U/L, p\u0026thinsp;=\u0026thinsp;0.016) and CRP levels (0.15 [IQR: 0.10\u0026ndash;0.79] mg/dL vs. 0.67 [IQR: 0.20\u0026ndash;2.26] mg/dL, p\u0026thinsp;=\u0026thinsp;0.002) were significantly lower in the High-Alb group than in the Low-Alb group (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eAssociation between Alb levels and survival\u003c/h2\u003e\u003cp\u003ePatients in the High-Alb group had significantly longer PFS (median: 5.2 vs. 3.0 months; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA) and OS (median: 15.6 vs. 6.0 months; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB) than those in the Low-Alb group.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eROC analysis of LDH and CRP levels for predicting treatment efficacy\u003c/h2\u003e\u003cp\u003eROC analysis of serum LDH and CRP levels for predicting PFS\u0026thinsp;\u0026ge;\u0026thinsp;median identified optimal cutoff values of 338 U/L and 1.3 mg/dL, respectively. For LDH, the AUC was 0.605 (95% CI: 0.467\u0026ndash;0.742), with a sensitivity of 80.6% and specificity of 45.5%. For CRP, the AUC was 0.652 (95% CI: 0.522\u0026ndash;0.782), with a sensitivity of 88.9% and specificity of 36.4%.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eExploratory analysis of predictors of PFS\u003c/h2\u003e\u003cp\u003eTo identify the predictors of PFS, two Cox proportional hazards models were constructed (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In Model 1\u0026mdash;adjusted for age and primary tumor site (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e)\u0026mdash;Alb\u0026thinsp;\u0026ge;\u0026thinsp;3.7 g/dL was the only significant factor and was associated with prolonged PFS (HR: 0.35, 95% CI: 0.19\u0026ndash;0.63, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In Model 2\u0026mdash;adjusted for peritoneal dissemination and LDH\u0026thinsp;\u0026ge;\u0026thinsp;338 U/L (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e)\u0026mdash;both Alb\u0026thinsp;\u0026ge;\u0026thinsp;3.7 g/dL (HR: 0.40, 95% CI: 0.22\u0026ndash;0.73, p\u0026thinsp;=\u0026thinsp;0.003) and LDH\u0026thinsp;\u0026ge;\u0026thinsp;338 U/L (HR: 2.31, 95% CI: 1.28\u0026ndash;4.32, p\u0026thinsp;=\u0026thinsp;0.009) were independently associated with PFS.\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\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eUnivariate model\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eMultivariate model 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u003cp\u003eMultivariate model 2\u003c/p\u003e\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\u003eHR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eHR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (\u0026ge;\u0026thinsp;65 years), yes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.217\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.70\u0026ndash;2.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.489\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.87\u0026ndash;2.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.133\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreatment line: 2nd or 3rd (vs. \u0026ge;4th), yes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.747\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.44\u0026ndash;1.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary tumor location: Right-sided, yes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.577\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.88\u0026ndash;2.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.129\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.78\u0026ndash;2.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.253\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiver metastasis, yes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.57\u0026ndash;1.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.933\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLung metastasis, yes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.841\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.49\u0026ndash;1.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.527\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePeritoneal dissemination, yes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.62\u0026ndash;2.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.729\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.76\u0026ndash;2.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.281\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLDH, \u0026ge;\u0026thinsp;338 U/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.47\u0026ndash;4.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.28\u0026ndash;4.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCRP, \u0026ge;\u0026thinsp;1.3 mg/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.12\u0026ndash;3.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlubmin, \u0026ge;\u0026thinsp;3.7 g/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.20\u0026ndash;0.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.347\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.19\u0026ndash;0.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.22\u0026ndash;0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"10\"\u003eAbbreviations: LDH, lactate dehydrogenase; CRP, C-reactive protein; CEA; HR, hazard ratio; CI, confidence interval\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\u003eIn this study, we found that baseline serum Alb levels at the initiation of FTD/TPI plus BEV therapy were significantly associated with PFS and OS. Furthermore, patients with pretreatment Alb levels of \u0026ge;\u0026thinsp;3.7 g/dL tended to experience more favorable outcomes with FTD/TPI plus BEV therapy. These findings suggest that Alb may serve as a simple and potentially useful marker for predicting the treatment response of FTD/TPI plus BEV in clinical practice.\u003c/p\u003e\u003cp\u003eThe median PFS in our study cohort was 3.7 months, which was somewhat shorter than the 5.6 months reported in a previous trial (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). In that study, the median age of patients was 62 years, and 92% received third-line therapy; however, the median age of patients in the present study was 69 years, and 45% received fourth-line or later therapy. These differences suggest that our study population was older and more heavily pretreated, potentially reflecting a clinical setting closer to real-world practice. Within this cohort, the median PFS in the High-Alb group was 5.2 months, approaching the outcome reported in a previous study (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). By contrast, patients in the Low-Alb group experienced more limited PFS benefit.\u003c/p\u003e\u003cp\u003eSeveral factors may account for these findings. First, reduced Alb levels often reflect cancer progression and systemic inflammation, which may be associated with diminished treatment responsiveness. Previous studies have shown that the CRP-to-Alb ratio is correlated with poor PFS and OS in patients with CRC (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), and serum Alb has been reported as an independent prognostic factor for CRC (\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Cancer-associated inflammation reduces hepatic Alb synthesis via cytokines such as interleukin-6, and persistent hypoalbuminemia may contribute to cancer progression and mortality (\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Although Alb levels can be influenced by factors other than cancer (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), our findings indicate that baseline Alb levels can provide clinically useful insights into treatment response to FTD/TPI plus BEV. In Cox proportional hazards models, Alb levels\u0026thinsp;\u0026ge;\u0026thinsp;3.7 g/dL were significantly associated with prolonged PFS, and the association remained significant in multiple models. Although the reference range for adult serum Alb typically ranges from 3.5 to 5.0 g/dL\u0026mdash;with levels below 3.5 g/dL generally considered hypoalbuminemia (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e)\u0026mdash;institutional ranges vary. At our institution, the normal range for serum Alb is 4.1\u0026ndash;5.1 g/dL; therefore, the cutoff value of 3.7 g/dL identified in this study was deemed clinically reasonable. Moreover, Alb may act as an integrative marker reflecting the nutritional status, inflammatory activity, treatment responsiveness, and overall condition of the patient. This interpretation is supported by the significantly lower CRP and LDH levels observed in the High-Alb group. As CRP reflects systemic inflammation and LDH reflects tumor burden and metabolic activity (\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), lower values of these markers suggest that patients in the High-Alb group may have relatively attenuated inflammation and tumor progression. Accordingly, higher Alb levels may not only indicate a better nutritional status but also reflect a background of attenuated inflammatory activity and tumor burden, which could contribute to more favorable treatment outcomes.\u003c/p\u003e\u003cp\u003eA second possible explanation is that hypoalbuminemia or elevated LDH levels may have affected the pharmacokinetics and pharmacodynamics of BEV. In this study, PFS in the High-Alb group (5.2 months) was comparable to that reported for the BEV combination group in the SUNLIGHT trial (5.6 months) (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), despite differing patient backgrounds. Conversely, the Low-Alb group achieved a PFS of 3.0 months, closer to that of the FTD/TPI monotherapy group (2.4 months) in the same trial. This raises the possibility that low Alb levels may alter BEV pharmacokinetics, thereby attenuating its efficacy. Prior studies have suggested that even mild proteinuria\u0026mdash;defined as a urinary protein-to-creatinine ratio of \u0026le;\u0026thinsp;1 g/dL\u0026mdash;may lower BEV concentrations and reduce its therapeutic effect (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Although urinary protein levels were not assessed in the present study, patients in the Low-Alb group may have had chronic, low-grade protein loss, potentially contributing to decreased Alb levels and reduced BEV exposure.\u003c/p\u003e\u003cp\u003eIn addition, the expression of vascular endothelial growth factor is influenced by hypoxia and inflammation, which may affect the efficacy of BEV (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). In CRC, breast cancer, and renal cell carcinoma, BEV has been reported to prolong PFS and OS, particularly in patients with low levels of systemic inflammation (\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Although evidence is more limited for non\u0026ndash;small cell lung cancer, some reports have shown associations between BEV efficacy and inflammatory markers (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Hoang et al. reported that hypoalbuminemia was associated with worse PFS and OS (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). In the present study, the Low-Alb group also exhibited lower hemoglobin and higher CRP and LDH levels, consistent with persistent inflammation, suggesting reduced responsiveness to BEV. Furthermore, LDH was identified as a predictive factor in multivariate analysis. A meta-analysis of LDH and BEV in CRC confirmed significant associations with both PFS and OS (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e), and other studies have proposed LDH as a potential predictive biomarker for anti-angiogenic therapy (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). Moreover, in the HORIZON I trial, Bar et al. reported that elevated LDH levels were significantly associated with shorter PFS (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). Our results are broadly consistent with these prior findings.\u003c/p\u003e\u003cp\u003eTaken together, these observations suggest that serum Alb may be an important factor influencing the treatment outcomes of FTD/TPI plus BEV therapy through mechanisms involving systemic inflammation, tumor activity, and pharmacokinetics.\u003c/p\u003e\u003cp\u003eThis study has some limitations. First, it was a single-center, retrospective study with a limited sample size, and large-scale prospective studies are needed to validate these findings. Second, response rates were not evaluated, preventing the direct assessment of treatment efficacy. Third, other prognostic factors\u0026mdash;such as histological subtype and molecular alterations (e.g., BRAF V600E)\u0026mdash;were not fully investigated; therefore, the possibility remains that the Low-Alb group included patients with a more aggressive disease.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe findings of this study suggest that serum Alb may serve as a potential predictive factor for the efficacy of FTD/TPI plus BEV therapy in patients with mCRC. Initiating FTD/TPI plus BEV therapy before substantial deterioration of nutritional or inflammatory status associated with disease progression may help achieve more favorable clinical outcomes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAlb\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ealbumin\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAUC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003earea under the curve\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBEV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ebevacizumab\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ebody mass index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003econfidence interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCRC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ecolorectal cancer\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCRP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eC-reactive protein\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eFTD/TPI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003etrifluridine/tipiracil\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ehazard ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003einterquartile range\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLDH\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003elactate dehydrogenase\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003emCRC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003emetastatic colorectal cancer\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eOS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eoverall survival\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePFS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eprogression-free survival\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ereceiver operating characteristic.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics review board of the Fukuyama Medical Center (Approval number: ERBP2024005). Informed consent was obtained via opt-out through the website.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMM and RT contributed to the study conception and design. MM, RT, HS and MF performed material preparation, data collection, and analysis. HT and YO critically revised the manuscript. All authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Editage (www.editage.jp) for English language editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSiegel RL, Miller KD, Goding Sauer A, Fedewa SA, Butterly LF, Anderson JC, Cercek A, Smith RA, Jemal A. Colorectal cancer statistics, 2020. CA Cancer J Clin. 2020 May; 70(3):145\u0026ndash;64. Available from: https://acsjournals.onlinelibrary.wiley.com/doi/full/10.3322/caac.21601 doi:10.3322/caac.21601\u003c/li\u003e\n\u003cli\u003eMiyashita Y, Kawazoe A, Yoshino T. [Chemotherapy for unresectable advanced, metastatic or recurrent colorectal cancer]. Gan To Kagaku Ryoho. 2024 Mar; 51(3):245\u0026ndash;9. in Japanese\u003c/li\u003e\n\u003cli\u003eMayer RJ, Van Cutsem E, Falcone A, Yoshino T, Garcia-Carbonero R, Mizunuma N, et al. Randomized trial of TAS-102 for refractory metastatic colorectal cancer. N Engl J Med. 2015 May 14; 372(20):1909\u0026ndash;19. Available from: https://www.nejm.org/doi/full/10.1056/NEJMoa1414325 doi:10.1056/NEJMoa1414325\u003c/li\u003e\n\u003cli\u003ePfeiffer P, Yilmaz M, M\u0026ouml;ller S, Zitnjak D, Krogh M, Petersen LN, et al. TAS-102 with or without bevacizumab in patients with chemorefractory metastatic colorectal cancer: An investigator-initiated, open-label, randomised, phase 2 trial. Lancet Oncol. 2020 Mar; 21(3):412\u0026ndash;20. Available from: https://www.thelancet.com/journals/lanonc/article/PIIS1470-2045(19)30827-7/abstract doi:10.1016/S1470-2045(19)30827-7.\u003c/li\u003e\n\u003cli\u003ePrager GW, Taieb J, Fakih M, Ciardiello F, Van Cutsem E, Elez E, et al. 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Available from: https://www.nature.com/articles/nrclinonc.2015.169 doi:10.1038/nrclinonc.2015.169\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"Albumin, Colorectal cancer, Trifluridine/tipiracil, Bevacizumab, predictive marker","lastPublishedDoi":"10.21203/rs.3.rs-7790891/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7790891/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eTrifluridine/tipiracil (FTD/TPI) combined with bevacizumab (BEV) has become a standard later-line therapy for metastatic colorectal cancer (mCRC). However, predictive biomarkers of treatment efficacy remain limited. Serum albumin (Alb)\u0026mdash;reflecting nutritional and inflammatory status\u0026mdash;has been reported as a prognostic factor in various malignancies, but its predictive value in patients receiving FTD/TPI plus BEV is unclear. This study examined whether baseline Alb levels are linked to treatment outcomes in patients with metastatic CRC receiving FTD/TPI plus BEV, aiming to clarify if Alb could serve as a predictive marker of therapeutic efficacy.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe retrospectively analyzed patients with unresectable or recurrent mCRC treated with FTD/TPI plus BEV at Fukuyama Medical Center between December 2017 and March 2024. Patients were divided into High- or Low-Alb groups based on an optimal cutoff derived from receiver operating characteristic (ROC) analysis for progression-free survival (PFS). The primary endpoint was PFS, and the secondary endpoint was overall survival (OS). Survival outcomes were assessed using the Kaplan\u0026ndash;Meier method and Cox proportional hazards models.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eSixty-nine patients were included (median age, 69 years). ROC analysis identified an Alb cutoff of 3.7 g/dL (area under the curve: 0.740). Using this cutoff, 39 patients (56.5%) were included in the High-Alb group. Patients in the High-Alb group had significantly lower lactate dehydrogenase (LDH) and C-reactive protein levels than those in the Low-Alb group. The median PFS (5.2 vs. 3.0 months; p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and OS (15.6 vs. 6.0 months; p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) were significantly longer in the High-Alb group than in the Low-Alb group. In the multivariate analysis, Alb\u0026thinsp;\u0026ge;\u0026thinsp;3.7 g/dL was independently associated with improved PFS (hazard ratio [HR]: 0.40, 95% confidence interval [CI]: 0.22\u0026ndash;0.73, p\u0026thinsp;=\u0026thinsp;0.003), whereas LDH\u0026thinsp;\u0026ge;\u0026thinsp;338 U/L was associated with shorter PFS (HR: 2.31, 95% CI: 1.28\u0026ndash;4.32, p\u0026thinsp;=\u0026thinsp;0.009).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eBaseline serum albumin levels were associated with survival outcomes in patients with mCRC treated with FTD/TPI\u0026thinsp;+\u0026thinsp;BEV. Thus, Alb may represent a simple and clinically accessible marker with potential predictive value. Initiating FTD/TPI plus BEV before a substantial decline in nutritional or inflammatory status may help achieve more favorable outcomes.\u003c/p\u003e","manuscriptTitle":"Baseline serum albumin level as a predictive factor for the efficacy of trifluridine/tipiracil plus bevacizumab in metastatic colorectal cancer: A retrospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-22 19:30:30","doi":"10.21203/rs.3.rs-7790891/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":"32a92f53-688b-4b45-93c3-03bfebcd8f48","owner":[],"postedDate":"October 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-08T16:09:05+00:00","versionOfRecord":{"articleIdentity":"rs-7790891","link":"https://doi.org/10.1186/s40780-025-00518-2","journal":{"identity":"journal-of-pharmaceutical-health-care-and-sciences","isVorOnly":false,"title":"Journal of Pharmaceutical Health Care and Sciences"},"publishedOn":"2025-12-03 15:57:52","publishedOnDateReadable":"December 3rd, 2025"},"versionCreatedAt":"2025-10-22 19:30:30","video":"","vorDoi":"10.1186/s40780-025-00518-2","vorDoiUrl":"https://doi.org/10.1186/s40780-025-00518-2","workflowStages":[]},"version":"v1","identity":"rs-7790891","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7790891","identity":"rs-7790891","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}