Dynamic increase in FIB-4 during treatment is associated with worse overall survival in metastatic colorectal cancer

Dynamic increase in FIB-4 during treatment is associated with worse overall survival in metastatic colorectal cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Dynamic increase in FIB-4 during treatment is associated with worse overall survival in metastatic colorectal cancer Harun Avcuoglu, Sabin Goktas Aydın, Ahmet Aydın, Oguzhan Selvi, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9093822/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background: Non-invasive liver fibrosis markers have been increasingly investigated as prognostic indicators in oncology. However, the clinical relevance of dynamic changes in the fibrosis-4 (FIB-4) index during systemic therapy in metastatic colorectal cancer (mCRC) remains unclear. Methods: This retrospective multicenter study included patients with mCRC treated with at least two lines of systemic therapy between 2020 and 2025. FIB-4 scores were calculated at baseline, 6 months, and 12 months. Associations with progression-free survival (PFS) and overall survival (OS) were evaluated using Kaplan–Meier and Cox regression analyses. Results: A total of 152 patients were analyzed. Median FIB-4 increased significantly over time (1.11 at baseline, 1.69 at 6 months, and 1.87 at 12 months; p<0.001) (Table 1). Baseline FIB-4 categories were associated with PFS (median 16.8, 16.1, and 6.5 months in low-, intermediate-, and high-risk groups; p=0.01) (Table 2) and OS (median 35.6, 38.1, and 22.0 months, respectively) (Table 3). Twelve-month FIB-4 was significantly associated with OS (p=0.009) (Table 3). In multivariate analysis, 12-month FIB-4 remained an independent predictor of mortality (HR 2.35 for intermediate risk and HR 6.76 for high risk; p=0.004) (Table 4). Conclusion: FIB-4 scores increase during systemic therapy in mCRC, and both baseline and 12-month FIB-4 values are associated with overall survival. Longitudinal monitoring of FIB-4 may provide a simple prognostic biomarker in metastatic colorectal cancer. metastatic colorectal cancer FIB-4 liver fibrosis prognosis systemic therapy Figures Figure 1 Figure 2 INTRODUCTION Colorectal cancer (CRC) remains one of the most prevalent malignancies worldwide and continues to represent a major contributor to cancer-related mortality. Despite improvements in screening programs and therapeutic strategies, a considerable proportion of patients are diagnosed with metastatic disease or develop distant metastases during the course of the illness. Outcomes for metastatic colorectal cancer (mCRC) remain unsatisfactory, with reported five-year survival rates generally below 25%, underscoring the need for reliable prognostic biomarkers and improved risk stratification strategies ( 1 – 3 ). The liver is the most frequent site of metastatic spread in CRC, largely due to its unique vascular anatomy and portal circulation. Approximately half of CRC patients develop liver metastases either at presentation or later in the disease course. The interaction between tumor cells and the hepatic microenvironment plays a central role in this process. According to the classical “seed and soil” hypothesis, metastatic dissemination depends not only on tumor characteristics but also on the biological environment of the target organ. Recent research has further expanded this concept through the description of a “pre-metastatic niche,” in which systemic tumor-derived signals modify distant organs to facilitate metastatic colonization ( 4 , 5 ). Beyond tumor-specific factors, host-related characteristics increasingly appear to influence outcomes in CRC. Several clinical and laboratory indicators reflecting systemic inflammation, nutritional status, or organ function have been investigated as potential prognostic markers. In this context, simple and accessible laboratory-based indices have attracted particular attention, as they may provide clinically useful prognostic information without requiring complex testing ( 6 ). Among these markers, indices reflecting hepatic injury and fibrosis have gained interest. The fibrosis-4 (FIB-4) index, which combines patient age, aminotransferase levels, and platelet count, was originally developed as a non-invasive method to estimate liver fibrosis in chronic liver disease. Because the components of this score are routinely measured in clinical practice, FIB-4 has become widely used for fibrosis assessment in different clinical settings ( 7 ). More recently, FIB-4 has been investigated as a prognostic biomarker in several malignancies. Elevated FIB-4 levels have been associated with poorer survival outcomes in cancers such as gastric cancer and cholangiocarcinoma, suggesting that liver injury and fibrosis may influence tumor progression through changes in systemic inflammation and the hepatic microenvironment ( 8 , 9 ). In metastatic colorectal cancer, only limited evidence exists regarding the prognostic value of fibrosis-related indices. Previous studies evaluating treatment-naïve mCRC populations have reported an association between higher FIB-4 scores and inferior overall survival, indicating that liver-related laboratory markers may reflect both hepatic involvement and overall disease burden ( 10 ). Furthermore, systemic therapies commonly used in CRC may contribute to hepatic injury. Oxaliplatin-based chemotherapy, a cornerstone of treatment in mCRC, is known to induce sinusoidal injury and other forms of hepatotoxicity that may alter liver function and potentially influence clinical outcomes ( 11 ). However, most previous studies have focused primarily on baseline fibrosis indices, while the potential prognostic significance of dynamic changes in fibrosis markers during treatment has received limited attention. Given the central role of the liver in metastatic CRC and the potential impact of treatment-related hepatic injury, longitudinal evaluation of fibrosis-related markers may provide additional insight into disease progression and patient outcomes. Therefore, the present study aimed to investigate the prognostic significance of the fibrosis-4 (FIB-4) index in patients with metastatic colorectal cancer undergoing systemic therapy. In particular, we evaluated the longitudinal evolution of FIB-4 during treatment and its association with survival outcomes, with the hypothesis that dynamic changes in liver fibrosis markers may serve as an accessible prognostic indicator in this patient population MATERIAL METHOD This was a retrospective multicenter study of patients diagnosed with metastatic colorectal cancer who were treated with at least two lines of systemic therapy from January 2020 to December 2025. Eligible patients had complete clinical, laboratory, and radiological data at baseline and during follow-up to calculate the FIB-4 score at three time points, six months apart. These included patients with histologically confirmed colorectal adenocarcinoma and radiologically confirmed metastatic disease. The exclusion criteria included the presence of another concurrent malignancy, incomplete data for FIB-4 calculations, ongoing viral hepatitis or other chronic liver diseases that were not related to malignancy, consumption of alcohol (exceeding 14 units per week), and previous liver transplantation. Additionally, patients who had undergone local liver-directed therapies with no systemic treatment were excluded. In total, 205 patients met the inclusion criteria and were enrolled in the analysis. The FIB-4 score was calculated using the formula: FIB-4 = (Age × AST) / (Platelet count × √ALT). FIB-4 scores were stratified into three categories: low risk ( 2.67), in accordance with previously established thresholds. Chemotherapy regimens Treatment selection was dictated by RAS and BRAF mutation status. Patients were enrolled in either FOLFOX or FOLFIRI regimens in the first-line setting. FOLFOX consisted of oxaliplatin 85 mg/m² and leucovorin 400 mg/m² intravenously on Day 1, followed by a 5-fluorouracil (5-FU) bolus of 400 mg/m² and a 46-hour continuous infusion of 2400 mg/m². FOLFIRI treatment included irinotecan 180 mg/m², leucovorin 400 mg/m² IV on Day 1; 5-FU bolus of 400 mg/m²; and 46-hour continuous infusion of 2400 mg/m². Cetuximab was added at a once-every-two-weeks dose of 500 mg/m² in patients with RAS/BRAF wild-type tumors. Patients with RAS-mutant tumors received bevacizumab 5 mg/kg biweekly in addition to chemotherapy. In a second-line setting, an alternate regimen, FOLFIRI or FOLFOX, was chosen with the prescribed biologic agent, based on first-line treatment and molecular profile. Patients with PFS > 12 months in third-line therapy were rechallenged with FOLFOX and a biologic, while others received regorafenib, 160 mg daily for 21 days of each 28-day cycle. Patients on other chemotherapy regimens were excluded. Doses were tailored to performance status, hematologic parameters, and organ function, following institutional guidelines. STATISTICAL ANALYSIS Statistical analysis was conducted in SPSS version 24. The normality of continuous variables was tested with the Kolmogorov–Smirnov test. Descriptive statistics were reported as median (interquartile range) for continuous variables and as frequencies and percentages for categorical variables. Changes in FIB-4 scores (baseline, 6 months, and 12 months) were assessed using the related-samples Wilcoxon signed-rank test. Progression-free survival (PFS) and overall survival (OS) were estimated on the basis of the Kaplan–Meier method, and log-rank tests were used to investigate differences between survival curves. Variables that, in univariate analysis, are likely to affect survival (p < 0.05) enter a multivariate Cox proportional hazards model to identify independent prognostic factors. A two-sided p-value of < 0.05 is considered statistically significant. RESULTS In our cohort, 152 patients with metastatic colorectal cancer who received at least two lines of systemic therapy were included. The median age was 61.5 years (range, 33–87), with 84 (55.3%) male. Tumor localization was most often in the left colon (68 patients, 44.7%), followed by the rectum (48 patients, 31.6%) and right colon (36 patients, 23.7%). Visceral metastasis was present in 98 patients (64.5%). RAS mutation was detected in 81 of 151 evaluable patients (53.6%), while 70 (46.4%) had wild-type tumors (Table 1). The median baseline FIB-4 score was 1.11 (range, 0.26–5.30). According to predefined cut-off values, 90 patients (59.2%) were classified as low risk, 57 (37.5%) as intermediate risk, and 5 (3.3%) as high risk at baseline. At six months, the median FIB-4 score increased to 1.69 (range, 0.37–11.09), with 45 patients (29.8%) in the low-risk group, 67 (44.4%) in the intermediate-risk group, and 39 (25.8%) in the high-risk group. At twelve months, the median FIB-4 score was 1.87 (range, 0.55–10.77), and 47 patients (31.1%), 78 (51.7%), and 26 (17.2%) were categorized as low, intermediate, and high risk, respectively (Table 1). At a median follow-up of 19.7 months (5.6–73.9), disease progression was observed in 126 (82.9%) patients, and 109 patients (71.7%) had died. The longitudinal comparison of FIB-4 measurements showed a significant increase over time. The median FIB-4 score increased from 1.11 (range, 0.26–5.30) at baseline to 1.69 (range, 0.37–11.09) at six months and to 1.87 (range, 0.55–10.77) at twelve months (Table 1). Pairwise comparisons revealed statistically significant differences between baseline and six months (p < 0.001), between baseline and twelve months (p < 0.001), and between six and twelve months (p = 0.004). Table 1. Baseline Clinicopathological Characteristics of the Patients (N=152) Characteristic n (%) or Median (Range) Age, years 61.5 (33–87) Sex Male 84 (55.3%) Female 68 (44.7%) Tumor location Right colon 36 (23.7%) Left colon 68 (44.7%) Rectum 48 (31.6%) Visceral metastasis Absent 54 (35.5%) Present 98 (64.5%) RAS status (n=152) Wild-type 70 (46.1%) Mutant 82 (53.9%) Baseline FIB-4 score 1.11 (0.26–5.30) Baseline FIB-4 category Low risk (2.67) 5 (3.3%) 6-month FIB-4 score 1.69 (0.37–11.09) 6-month FIB-4 category Low risk (2.67) 39 (25.8%) 12-month FIB-4 score 1.87 (0.55–10.77) 12-month FIB-4 category Low risk (2.67) 26 (17.1%) In univariate Kaplan–Meier analyses, baseline FIB-4 categories were significantly associated with PFS (log-rank p=0.01). Median PFS was 16.8 months in the low-risk group, 16.1 months in the intermediate-risk group, and 6.5 months in the high-risk group, with corresponding 12-month PFS rates of 67.7% and 67.2% for the low- and intermediate-risk groups, respectively; the 12-month estimate for the high-risk group was not reliable due to the small sample size. By contrast, 6-month FIB-4 categories were not associated with PFS (log-rank p=0.74). Median PFS was 14.5, 15.6, and 20.0 months in the low-, intermediate-, and high-risk groups, respectively; 12-month PFS rates were 75.5% in the low-risk and 86.3% in the intermediate-risk groups, whereas the estimate for the high-risk group was unreliable. (Table 2) Gender was not associated with PFS (median PFS: 15.6 vs 17.6 months for males vs females; 12-month PFS: 89.1% vs 85.1%; p=0.46). Median PFS was 19.2 months in patients without liver metastasis and 14.1 months in those with liver metastasis, with 12-month PFS rates of 81.0% and 90.7%, respectively. RAS status was not associated with PFS (median PFS: 15.6 vs 19.2 months for wild-type vs mutant; 12-month PFS: 88.4% vs 87.5%; p=0.81). Tumor location showed no significant link to PFS (p=0.56), with median PFS of 16.1 months in the right colon, 15.6 months in the left colon, and 19.1 months in the rectum. The 12-month PFS rates were 63.3%, 69.0%, and 70.0%, respectively (Table 2). Table 2. Univariate analysis for Progression Free Survival Variable Category Median PFS (months) 12-month PFS (%) Log-rank p Baseline FIB-4 Low (2.67) 6.5 —* 6-month FIB-4 Low 14.5 75.5% 0.74 Intermediate 15.6 86.3% High 20.0 —* Gender Male 15.6 89.1% 0.46 Female 17.6 85.1% Liver metastasis Absent 19.2 81.0% 0.04 Present 14.1 90.7% RAS status Wild-type 15.6 88.4% 0,81 Mutant 19.2 87.5% Tumor location Right colon 16.1 63.3% 0.56 Left colon 15.6 69.0% Rectum 19.1 70.0% *12-month estimate not reliable due to very small sample size Baseline FIB-4 categories were significantly associated with OS. The 24-month OS rates were 79.5%, 74.5%, and 53.3% in the low-, intermediate-, and high-risk groups, respectively. Median OS was 35.6 months (95% CI: 25.3–45.9), 38.1 months (95% CI: 17.1–59.1), and 22.0 months (95% CI: 16.6–27.4), respectively. Six-month FIB-4 categories were not associated with OS (p=0.848). Twelve-month FIB-4 showed a significant association with OS (p=0.009). Median OS was 41.7, 43.3, and 24.3 months in the low-, intermediate-, and high-risk groups, with 24-month OS rates of 85.1%, 77.7%, and 71.0%, respectively. Gender was not significantly associated with OS (p=0.07), although females had longer median OS than males (43.2 vs 30.8 months). Liver metastasis was significantly associated with OS (p=0.007). Patients without liver metastasis had a median OS of 57.0 months and a 24-month OS rate of 82.2%, compared with 31.6 months and 74.9% in those with liver metastasis. RAS status (p=0.9) and tumor location (p=0.7) were not associated with OS (Table 3). Because few variables showed significance in univariate analyses and effect sizes were modest, a multivariate Cox regression for PFS was not built to prevent overfitting and unstable estimates. Table 3: Univariate analysis for Overall Survival Variable Category 24-Month OS (%) Median OS months Median OS 95% CI Log-rank p Baseline FIB-4 Low (2.67) 53.3% 22.0 16.6–27.4 6-month FIB-4 Low (2.67) 71.0% 30.2 25.0–35.4 12-month FIB-4 Low (2.67) 71.0% 24.3 17.8–30.8 Gender Male 68.6% 30.8 27.1-34.4 0.07 Female 85.8% 43.2 32.3-54.2 Liver metastasis Absent 82.2% 57.0 42.1–71.8 0.007 Present 74.9% 31.6 28.5–34.8 RAS status Wild-type 73.0% — — 0.9 Mutant 74.7% — — Tumor location Right colon 80.4% 33.3 17.8-48.7 0.7 Left colon 70.6% 31.6 25.7-37.4 Rectum 80.3% 45.8 26.5-44.6 In multivariate Cox regression analysis, 12-month FIB-4 remained independently associated with OS (overall p=0.004). Compared with the low-risk group, the intermediate-risk group had a 2.35-fold increased risk of mortality (HR 2.35, 95% CI 1.07–5.14; p=0.033), while the high-risk group had a 6.76-fold increased risk (HR 6.76, 95% CI 2.16–21.14; p=0.001). Baseline FIB-4 was also independently associated with OS (overall p=0.011). The intermediate-risk group demonstrated a lower risk of death compared with the reference category (HR 0.30, 95% CI 0.14–0.66; p=0.003), whereas the high-risk group was not significantly associated with OS (HR 0.65, 95% CI 0.07–5.96; p=0.705). Gender (HR 1.71, 95% CI 0.89–3.28; p=0.108) and liver metastasis (HR 0.57, 95% CI 0.31–1.05; p=0.073) were not independently associated with OS in the adjusted model (Table 4). Table 4. Multivariate Cox regression analysis for overall survival Variable Category HR (Exp(B)) 95% CI p value 12-month FIB-4 Overall — — 0.004 Intermediate (1.3–2.67) 2.35 1.07–5.14 0.033 High (>2.67) 6.76 2.16–21.14 0.001 Gender Male vs Female 1.71 0.89–3.28 0.108 Liver metastasis Present vs Absent 0.57 0.31–1.05 0.073 Baseline FIB-4 Overall — — 0.011 Intermediate (1.3–2.67) 0.30 0.14–0.66 0.003 High (>2.67) 0.65 0.07–5.96 0.705 DISCUSSION The liver is the most common metastatic site in colorectal cancer and significantly impacts patient outcomes; liver fibrosis, driven by chronic inflammation and the activation of hepatic stellate cells, plays a crucial role in disease progression and treatment response ( 12 , 13 ). Non-invasive markers like FIB-4 index, which uses routinely measured lab parameters, have become vital for assessing liver fibrosis ( 14 ). FIB-4 is valued for its accessibility and has been incorporated into screening algorithms, also showing promise as a prognostic marker beyond chronic liver diseases ( 15 , 16 ). Loosen et al. demonstrated that elevated FIB-4 scores were associated with an increased risk of hepatocellular carcinoma development in patients with non-alcoholic fatty liver disease ( 15 ). Similarly, Kariyama et al. reported that FIB-4 was an independent prognostic factor for survival in hepatocellular carcinoma ( 16 ). In another study focusing on cholangiocarcinoma, Steffani et al. showed that the presence of liver fibrosis was associated with significantly worse overall survival and higher recurrence rates following treatment ( 17 ). These observations support the concept that changes in fibrosis markers may reflect ongoing pathological processes affecting the liver. In a large community cohort, Wang et al. demonstrated that higher liver fibrosis scores were associated with increased cancer-related mortality ( 18 ). Likewise, inflammatory and metabolic pathways linked to fibrosis have been associated with increased mortality and adverse clinical outcomes in metabolic liver disease populations ( 19 ). These observations support the hypothesis that fibrosis indices may reflect systemic inflammatory and metabolic disturbances that influence cancer prognosis. In metastatic colorectal cancer specifically, the prognostic significance of fibrosis markers has been investigated only in limited studies. Yıldırım et al. recently evaluated several non-invasive liver fibrosis indices, including FIB-4, APRI, and ALBI scores, in treatment-naïve metastatic colorectal cancer patients and demonstrated that higher FIB-4 values were associated with poorer overall survival. However, most previous investigations have focused primarily on baseline fibrosis markers, and little information is available regarding temporal changes in fibrosis indices during systemic therapy. For instance, Wang et al. demonstrated that post-treatment changes in FIB-4 scores were associated with the subsequent development of hepatocellular carcinoma in patients with chronic hepatitis C infection ( 21 ). Likewise, longitudinal studies in population-based cohorts have shown that increasing fibrosis scores are associated with higher risks of liver-related complications and mortality ( 22 ). These findings support the concept that temporal changes in fibrosis markers may reflect ongoing pathological processes affecting hepatic function. In the present study, we evaluated both baseline FIB-4 values and their longitudinal evolution during treatment in patients with metastatic colorectal cancer. Similar to the literature knowledge, our findings demonstrated a significant increase in FIB-4 scores over time, with median values rising from 1.11 at baseline to 1.69 at six months and 1.87 at twelve months. Baseline FIB-4 values were significantly associated with both progression-free survival and overall survival in our cohort. Patients with higher baseline FIB-4 scores experienced shorter survival compared with those in the low-risk group. A particularly notable finding of our study was the prognostic significance of longitudinal FIB-4 measurements. While six-month FIB-4 categories were not associated with survival outcomes, twelve-month FIB-4 values demonstrated a significant association with overall survival and remained an independent prognostic factor in multivariate analysis. Patients in the intermediate- and high-risk groups at twelve months showed substantially increased mortality risk compared with those in the low-risk category. Several mechanisms may explain the increase in FIB-4 scores observed during systemic therapy in our cohort. One potential explanation is chemotherapy-related hepatotoxicity . Oxaliplatin-based chemotherapy, a cornerstone of colorectal cancer treatment, has been associated with sinusoidal obstruction syndrome and other forms of hepatic injury. Histopathological studies have shown that oxaliplatin can induce sinusoidal dilatation, hepatic congestion, and perisinusoidal fibrosis ( 23 ). In patients undergoing hepatic resection for colorectal liver metastases, prior exposure to oxaliplatin has been linked to sinusoidal injury and impaired liver function ( 24 ). Another possible explanation involves the interaction between metastatic tumor burden and the hepatic microenvironment. In our cohort, liver metastasis was significantly associated with overall survival in univariate analysis but did not remain an independent predictor in multivariate models. This observation may indicate that fibrosis-related indices such as FIB-4 capture broader aspects of hepatic dysfunction that are not solely explained by the presence of metastatic disease Several limitations should be considered when interpreting the results of this study. First, the retrospective design introduces the potential for selection bias and limits causal inference. Second, the relatively small number of patients in the high-risk FIB-4 group may have affected the stability of subgroup analyses. Third, FIB-4 represents an indirect marker of fibrosis and may be influenced by factors such as systemic inflammation, chemotherapy-induced hepatotoxicity, or thrombocytopenia. These factors may contribute to variability in FIB-4 values independent of structural fibrosis. Despite these limitations, our study provides novel insights into the potential prognostic role of fibrosis-related biomarkers in metastatic colorectal cancer. To our knowledge, few studies have examined longitudinal changes in FIB-4 during systemic therapy and their association with survival outcomes. Our findings suggest that monitoring dynamic changes in FIB-4 may provide clinically relevant prognostic information and help identify patients at increased risk of adverse outcomes. CONCLUSION FIB-4 scores increased progressively during systemic therapy in patients with metastatic colorectal cancer, and both baseline and twelve-month FIB-4 values were associated with overall survival. These findings indicate that longitudinal monitoring of fibrosis markers may offer a simple and accessible approach for prognostic assessment in this patient population. Further prospective studies are warranted to validate these observations and to clarify the mechanisms linking hepatic fibrosis markers with cancer progression and treatment-related liver injury. Abbreviations FIB-4 Fibrosis-4 index mCRC Metastatic colorectal cancer PFS Progression-free survival OS Overall survival CRC Colorectal cancer AST Aspartate aminotransferase ALT Alanine aminotransferase 5-FU 5-fluorouracil HR Hazard ratio CI Confidence interval IV Intravenous Declarations Ethics approval and consent to participate This study was conducted in accordance with the ethical principles of the Declaration of Helsinki. Ethical approval was obtained from the Institutional Ethics Committee of Istanbul Medipol University (Approval number: E-10840098-202.3.02-1501, February 2026). Written informed consent was obtained from all participants. Consent for publication Not applicable. Availability of data and materials The data that support the findings of this study are not publicly available due to their sensitive nature but are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests. Funding The authors received no financial support for the research, authorship, and/or publication of this article. Authors’ contributions All authors contributed to the conception of the study. S.G.A. and H.A. designed the study and drafted the manuscript. All authors contributed to the interpretation of the data. S.G.A., H.A., and E.S. critically revised the manuscript for important intellectual content. All authors approved the submitted version. All authors agree to be personally accountable for their own contributions and to ensure that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Acknowledgements Not applicable. Author details 1 Department of General Surgery, Kanuni Sultan Suleyman Training and Research Hospital, Istanbul, Turkey 2 Department of Internal Medicine, Istanbul Medipol University, Istanbul, Turkey 3 Department of Medical Oncology, Kanuni Sultan Suleyman Training and Research Hospital, Istanbul, Turkey 4 Bezmialem Vakif University Faculty of Medicine, Medical oncology clinic, Istanbul, Turkey References Zhang Y et al. Emerging strategies in colorectal cancer immunotherapy. Front Immunol. 2025. DOI: 10.3389/fimmu.2025.1616414 Steup C et al. Current and emerging concepts for systemic treatment of metastatic colorectal cancer. Gut. 2025. DOI: 10.1136/gutjnl-2025-335412 Ohta R et al. Exercise and survival in metastatic colorectal cancer. Cureus. 2025. DOI: 10.7759/cureus.97682 Li Y et al. Understanding pre-metastatic niche formation in colorectal liver metastasis. J Transl Med. 2025. DOI: 10.1186/s12967-025-06328-2 Kaplan RN et al. Pre-metastatic niches. Nature. 2005. 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J Clin Oncol. 2006. DOI: 10.1200/JCO.2006.06.0032 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 09 May, 2026 Reviewers agreed at journal 29 Apr, 2026 Reviewers invited by journal 24 Apr, 2026 Editor assigned by journal 23 Apr, 2026 Editor invited by journal 02 Apr, 2026 Submission checks completed at journal 01 Apr, 2026 First submitted to journal 01 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-9093822","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":633933201,"identity":"4d6a33d8-d841-4ddc-bd39-c0a8a74ae46f","order_by":0,"name":"Harun Avcuoglu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8klEQVRIiWNgGAWjYBACAyQ24wGGCiDFzNxAtBaGAwxnQFoYSdHC2Aa2Db8Wc/azz6QLag7LGxxvv3CYd15tNH87UMuPim04tVj2pJtJzzh22HDDmTMFh3m3Hc+dcZixgbHnzG3cDjuQxibNw5aWYHAjJwGo5VhuA1ALM2MbHi3nnwG1/INpmXMsdz5BLTeAtvC22QC1pB84zNtQk7uBsJZnzNa8fTaGM8+cYTg459iB3I1ALQfx+uV8GuNtnm8S8nzH2x8+eFNTlzvv/OGDD35U4NaCBHhAcXQYzDxAjHogYH8AJOqIVDwKRsEoGAUjCQAAOphfAbwPbZUAAAAASUVORK5CYII=","orcid":"","institution":"İstanbul Kanuni Sultan Süleyman Eğitim ve Araştırma Hastanesi","correspondingAuthor":true,"prefix":"","firstName":"Harun","middleName":"","lastName":"Avcuoglu","suffix":""},{"id":633933203,"identity":"9c1a5809-926e-4356-b2da-fe1673e27130","order_by":1,"name":"Sabin Goktas Aydın","email":"","orcid":"","institution":"İstanbul Kanuni Sultan Süleyman Eğitim ve Araştırma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Sabin","middleName":"Goktas","lastName":"Aydın","suffix":""},{"id":633933204,"identity":"d24da0b1-9dbe-4d89-8748-a14604624949","order_by":2,"name":"Ahmet Aydın","email":"","orcid":"","institution":"Istanbul Medipol University","correspondingAuthor":false,"prefix":"","firstName":"Ahmet","middleName":"","lastName":"Aydın","suffix":""},{"id":633933205,"identity":"26948f6f-068e-4da7-9681-8826b30732c7","order_by":3,"name":"Oguzhan Selvi","email":"","orcid":"","institution":"Bezmialem Foundation University Medical Faculty Hospital","correspondingAuthor":false,"prefix":"","firstName":"Oguzhan","middleName":"","lastName":"Selvi","suffix":""},{"id":633933208,"identity":"eab16e87-ac7e-4303-baf6-e3e73f0b3476","order_by":4,"name":"Murtaza Furkan Eskici","email":"","orcid":"","institution":"İstanbul Kanuni Sultan Süleyman Eğitim ve Araştırma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Murtaza","middleName":"Furkan","lastName":"Eskici","suffix":""},{"id":633933209,"identity":"fa4854ee-073c-4d70-ab42-338b84681150","order_by":5,"name":"Hatice Telci","email":"","orcid":"","institution":"İstanbul Kanuni Sultan Süleyman Eğitim ve Araştırma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Hatice","middleName":"","lastName":"Telci","suffix":""},{"id":633933212,"identity":"e5f4922c-6380-43b0-b79b-f67834875b42","order_by":6,"name":"Ozgur Gangal","email":"","orcid":"","institution":"İstanbul Kanuni Sultan Süleyman Eğitim ve Araştırma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Ozgur","middleName":"","lastName":"Gangal","suffix":""},{"id":633933213,"identity":"56278b61-5611-43b2-b404-9ffb85ef505b","order_by":7,"name":"Emre Bozdag","email":"","orcid":"","institution":"İstanbul Kanuni Sultan Süleyman Eğitim ve Araştırma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Emre","middleName":"","lastName":"Bozdag","suffix":""},{"id":633933214,"identity":"187a13bc-fa92-4d41-a620-a2cd1ff0c072","order_by":8,"name":"Erkan Somuncu","email":"","orcid":"","institution":"İstanbul Kanuni Sultan Süleyman Eğitim ve Araştırma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Erkan","middleName":"","lastName":"Somuncu","suffix":""}],"badges":[],"createdAt":"2026-03-11 12:20:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9093822/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9093822/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108820191,"identity":"c60065fa-8730-4f70-9749-d15ef17c8187","added_by":"auto","created_at":"2026-05-08 16:40:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":62260,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe relationship between baseline FIB-4 score and Overall Survival\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKaplan–Meier survival curves demonstrate the differences in overall survival among the FIB-4 groups. Patients with a higher baseline FIB-4 score (\u0026gt;2.67) showed lower overall survival compared with those with lower FIB-4 scores. (Figure 1)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9093822/v1/8e996df339799cf2da2a5813.png"},{"id":108821383,"identity":"6ca39623-a3ec-4c17-9c3f-866db8030ae6","added_by":"auto","created_at":"2026-05-08 16:45:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":58950,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe relationship between 12. month FIB-4 score and Overall Survival\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKaplan–Meier survival curves demonstrating overall survival according to 12-month FIB-4 score categories. Patients with higher 12-month FIB-4 scores (\u0026gt;2.67) showed lower overall survival compared with those with lower FIB-4 scores. (Figure 2)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9093822/v1/705bc55a5e9ed01f787abaed.png"},{"id":108822981,"identity":"c7f44c4a-7849-485e-8e65-c4cf7851e13a","added_by":"auto","created_at":"2026-05-08 16:51:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":453326,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9093822/v1/4a27cd0c-b8d2-4305-a895-f3de127b696b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Dynamic increase in FIB-4 during treatment is associated with worse overall survival in metastatic colorectal cancer","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eColorectal cancer (CRC) remains one of the most prevalent malignancies worldwide and continues to represent a major contributor to cancer-related mortality. Despite improvements in screening programs and therapeutic strategies, a considerable proportion of patients are diagnosed with metastatic disease or develop distant metastases during the course of the illness. Outcomes for metastatic colorectal cancer (mCRC) remain unsatisfactory, with reported five-year survival rates generally below 25%, underscoring the need for reliable prognostic biomarkers and improved risk stratification strategies (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe liver is the most frequent site of metastatic spread in CRC, largely due to its unique vascular anatomy and portal circulation. Approximately half of CRC patients develop liver metastases either at presentation or later in the disease course. The interaction between tumor cells and the hepatic microenvironment plays a central role in this process. According to the classical \u0026ldquo;seed and soil\u0026rdquo; hypothesis, metastatic dissemination depends not only on tumor characteristics but also on the biological environment of the target organ. Recent research has further expanded this concept through the description of a \u0026ldquo;pre-metastatic niche,\u0026rdquo; in which systemic tumor-derived signals modify distant organs to facilitate metastatic colonization (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBeyond tumor-specific factors, host-related characteristics increasingly appear to influence outcomes in CRC. Several clinical and laboratory indicators reflecting systemic inflammation, nutritional status, or organ function have been investigated as potential prognostic markers. In this context, simple and accessible laboratory-based indices have attracted particular attention, as they may provide clinically useful prognostic information without requiring complex testing (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong these markers, indices reflecting hepatic injury and fibrosis have gained interest. The fibrosis-4 (FIB-4) index, which combines patient age, aminotransferase levels, and platelet count, was originally developed as a non-invasive method to estimate liver fibrosis in chronic liver disease. Because the components of this score are routinely measured in clinical practice, FIB-4 has become widely used for fibrosis assessment in different clinical settings (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMore recently, FIB-4 has been investigated as a prognostic biomarker in several malignancies. Elevated FIB-4 levels have been associated with poorer survival outcomes in cancers such as gastric cancer and cholangiocarcinoma, suggesting that liver injury and fibrosis may influence tumor progression through changes in systemic inflammation and the hepatic microenvironment (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn metastatic colorectal cancer, only limited evidence exists regarding the prognostic value of fibrosis-related indices. Previous studies evaluating treatment-na\u0026iuml;ve mCRC populations have reported an association between higher FIB-4 scores and inferior overall survival, indicating that liver-related laboratory markers may reflect both hepatic involvement and overall disease burden (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFurthermore, systemic therapies commonly used in CRC may contribute to hepatic injury. Oxaliplatin-based chemotherapy, a cornerstone of treatment in mCRC, is known to induce sinusoidal injury and other forms of hepatotoxicity that may alter liver function and potentially influence clinical outcomes (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, most previous studies have focused primarily on baseline fibrosis indices, while the potential prognostic significance of dynamic changes in fibrosis markers during treatment has received limited attention. Given the central role of the liver in metastatic CRC and the potential impact of treatment-related hepatic injury, longitudinal evaluation of fibrosis-related markers may provide additional insight into disease progression and patient outcomes. Therefore, the present study aimed to investigate the prognostic significance of the fibrosis-4 (FIB-4) index in patients with metastatic colorectal cancer undergoing systemic therapy. In particular, we evaluated the longitudinal evolution of FIB-4 during treatment and its association with survival outcomes, with the hypothesis that dynamic changes in liver fibrosis markers may serve as an accessible prognostic indicator in this patient population\u003c/p\u003e"},{"header":"MATERIAL METHOD","content":"\u003cp\u003eThis was a retrospective multicenter study of patients diagnosed with metastatic colorectal cancer who were treated with at least two lines of systemic therapy from January 2020 to December 2025. Eligible patients had complete clinical, laboratory, and radiological data at baseline and during follow-up to calculate the FIB-4 score at three time points, six months apart. These included patients with histologically confirmed colorectal adenocarcinoma and radiologically confirmed metastatic disease. The exclusion criteria included the presence of another concurrent malignancy, incomplete data for FIB-4 calculations, ongoing viral hepatitis or other chronic liver diseases that were not related to malignancy, consumption of alcohol (exceeding 14 units per week), and previous liver transplantation. Additionally, patients who had undergone local liver-directed therapies with no systemic treatment were excluded. In total, 205 patients met the inclusion criteria and were enrolled in the analysis.\u003c/p\u003e \u003cp\u003eThe FIB-4 score was calculated using the formula: FIB-4 = (Age \u0026times; AST) / (Platelet count \u0026times; \u0026radic;ALT). FIB-4 scores were stratified into three categories: low risk (\u0026lt;\u0026thinsp;1.3), intermediate risk (1.3\u0026ndash;2.67), and high risk (\u0026gt;\u0026thinsp;2.67), in accordance with previously established thresholds.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eChemotherapy regimens\u003c/h2\u003e \u003cp\u003eTreatment selection was dictated by RAS and BRAF mutation status. Patients were enrolled in either FOLFOX or FOLFIRI regimens in the first-line setting. FOLFOX consisted of oxaliplatin 85 mg/m\u0026sup2; and leucovorin 400 mg/m\u0026sup2; intravenously on Day 1, followed by a 5-fluorouracil (5-FU) bolus of 400 mg/m\u0026sup2; and a 46-hour continuous infusion of 2400 mg/m\u0026sup2;. FOLFIRI treatment included irinotecan 180 mg/m\u0026sup2;, leucovorin 400 mg/m\u0026sup2; IV on Day 1; 5-FU bolus of 400 mg/m\u0026sup2;; and 46-hour continuous infusion of 2400 mg/m\u0026sup2;. Cetuximab was added at a once-every-two-weeks dose of 500 mg/m\u0026sup2; in patients with RAS/BRAF wild-type tumors. Patients with RAS-mutant tumors received bevacizumab 5 mg/kg biweekly in addition to chemotherapy. In a second-line setting, an alternate regimen, FOLFIRI or FOLFOX, was chosen with the prescribed biologic agent, based on first-line treatment and molecular profile. Patients with PFS\u0026thinsp;\u0026gt;\u0026thinsp;12 months in third-line therapy were rechallenged with FOLFOX and a biologic, while others received regorafenib, 160 mg daily for 21 days of each 28-day cycle. Patients on other chemotherapy regimens were excluded. Doses were tailored to performance status, hematologic parameters, and organ function, following institutional guidelines.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSTATISTICAL ANALYSIS\u003c/h2\u003e \u003cp\u003eStatistical analysis was conducted in SPSS version 24. The normality of continuous variables was tested with the Kolmogorov\u0026ndash;Smirnov test. Descriptive statistics were reported as median (interquartile range) for continuous variables and as frequencies and percentages for categorical variables. Changes in FIB-4 scores (baseline, 6 months, and 12 months) were assessed using the related-samples Wilcoxon signed-rank test. Progression-free survival (PFS) and overall survival (OS) were estimated on the basis of the Kaplan\u0026ndash;Meier method, and log-rank tests were used to investigate differences between survival curves. Variables that, in univariate analysis, are likely to affect survival (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) enter a multivariate Cox proportional hazards model to identify independent prognostic factors. A two-sided p-value of \u0026lt;\u0026thinsp;0.05 is considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eIn our cohort, 152 patients with metastatic colorectal cancer who received at least two lines of systemic therapy were included. The median age was 61.5 years (range, 33\u0026ndash;87), with 84 (55.3%) male. Tumor localization was most often in the left colon (68 patients, 44.7%), followed by the rectum (48 patients, 31.6%) and right colon (36 patients, 23.7%). Visceral metastasis was present in 98 patients (64.5%). RAS mutation was detected in 81 of 151 evaluable patients (53.6%), while 70 (46.4%) had wild-type tumors (Table 1).\u003c/p\u003e\n\u003cp\u003eThe median baseline FIB-4 score was 1.11 (range, 0.26\u0026ndash;5.30). According to predefined cut-off values, 90 patients (59.2%) were classified as low risk, 57 (37.5%) as intermediate risk, and 5 (3.3%) as high risk at baseline. At six months, the median FIB-4 score increased to 1.69 (range, 0.37\u0026ndash;11.09), with 45 patients (29.8%) in the low-risk group, 67 (44.4%) in the intermediate-risk group, and 39 (25.8%) in the high-risk group. At twelve months, the median FIB-4 score was 1.87 (range, 0.55\u0026ndash;10.77), and 47 patients (31.1%), 78 (51.7%), and 26 (17.2%) were categorized as low, intermediate, and high risk, respectively (Table 1).\u003c/p\u003e\n\u003cp\u003eAt a median follow-up of 19.7 months (5.6\u0026ndash;73.9), disease progression was observed in 126 (82.9%) patients, and 109 patients (71.7%) had died.\u003c/p\u003e\n\u003cp\u003eThe longitudinal comparison of FIB-4 measurements showed a significant increase over time. The median FIB-4 score increased from 1.11 (range, 0.26\u0026ndash;5.30) at baseline to 1.69 (range, 0.37\u0026ndash;11.09) at six months and to 1.87 (range, 0.55\u0026ndash;10.77) at twelve months (Table 1). Pairwise comparisons revealed statistically significant differences between baseline and six months (p \u0026lt; 0.001), between baseline and twelve months (p \u0026lt; 0.001), and between six and twelve months (p = 0.004).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Baseline Clinicopathological Characteristics of the Patients (N=152)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en (%) or Median (Range)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e61.5 (33\u0026ndash;87)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e84 (55.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e68 (44.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTumor location\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eRight colon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e36 (23.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eLeft colon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e68 (44.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eRectum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e48 (31.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVisceral metastasis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eAbsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e54 (35.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003ePresent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e98 (64.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRAS status\u003c/strong\u003e (n=152)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eWild-type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e70 (46.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eMutant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e82 (53.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline FIB-4 score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e1.11 (0.26\u0026ndash;5.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline FIB-4 category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eLow risk (\u0026lt;1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e90 (59.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eIntermediate risk (1.3\u0026ndash;2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e57 (37.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eHigh risk (\u0026gt;2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e5 (3.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6-month FIB-4 score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e1.69 (0.37\u0026ndash;11.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6-month FIB-4 category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eLow risk (\u0026lt;1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e45 (29.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eIntermediate risk (1.3\u0026ndash;2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e67 (44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eHigh risk (\u0026gt;2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e39 (25.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12-month FIB-4 score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e1.87 (0.55\u0026ndash;10.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12-month FIB-4 category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eLow risk (\u0026lt;1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e47 (30.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eIntermediate risk (1.3\u0026ndash;2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e79 (52.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eHigh risk (\u0026gt;2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e26 (17.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eIn univariate Kaplan\u0026ndash;Meier analyses, baseline FIB-4 categories were significantly associated with PFS (log-rank p=0.01). Median PFS was 16.8 months in the low-risk group, 16.1 months in the intermediate-risk group, and 6.5 months in the high-risk group, with corresponding 12-month PFS rates of 67.7% and 67.2% for the low- and intermediate-risk groups, respectively; the 12-month estimate for the high-risk group was not reliable due to the small sample size. By contrast, 6-month FIB-4 categories were not associated with PFS (log-rank p=0.74). Median PFS was 14.5, 15.6, and 20.0 months in the low-, intermediate-, and high-risk groups, respectively; 12-month PFS rates were 75.5% in the low-risk and 86.3% in the intermediate-risk groups, whereas the estimate for the high-risk group was unreliable. (Table 2)\u003c/p\u003e\n\u003cp\u003eGender was not associated with PFS (median PFS: 15.6 vs 17.6 months for males vs females; 12-month PFS: 89.1% vs 85.1%; p=0.46). Median PFS was 19.2 months in patients without liver metastasis and 14.1 months in those with liver metastasis, with 12-month PFS rates of 81.0% and 90.7%, respectively. RAS status was not associated with PFS (median PFS: 15.6 vs 19.2 months for wild-type vs mutant; 12-month PFS: 88.4% vs 87.5%; p=0.81). Tumor location showed no significant link to PFS (p=0.56), with median PFS of 16.1 months in the right colon, 15.6 months in the left colon, and 19.1 months in the rectum. The 12-month PFS rates were 63.3%, 69.0%, and 70.0%, respectively (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Univariate analysis for Progression Free Survival\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"623\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian PFS (months)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e12-month PFS (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLog-rank p\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline FIB-4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLow (\u0026lt;1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e67.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.01\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIntermediate (1.3\u0026ndash;2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e67.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigh (\u0026gt;2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e6-month FIB-4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIntermediate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e86.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026mdash;*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e89.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e85.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLiver metastasis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAbsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e81.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.04\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePresent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e90.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRAS status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWild-type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e88.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0,81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMutant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e87.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTumor location\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRight colon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLeft colon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e69.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRectum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e70.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003e*12-month estimate not reliable due to very small sample size\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBaseline FIB-4 categories were significantly associated with OS. The 24-month OS rates were 79.5%, 74.5%, and 53.3% in the low-, intermediate-, and high-risk groups, respectively. Median OS was 35.6 months (95% CI: 25.3\u0026ndash;45.9), 38.1 months (95% CI: 17.1\u0026ndash;59.1), and 22.0 months (95% CI: 16.6\u0026ndash;27.4), respectively. Six-month FIB-4 categories were not associated with OS (p=0.848). Twelve-month FIB-4 showed a significant association with OS (p=0.009). Median OS was 41.7, 43.3, and 24.3 months in the low-, intermediate-, and high-risk groups, with 24-month OS rates of 85.1%, 77.7%, and 71.0%, respectively. Gender was not significantly associated with OS (p=0.07), although females had longer median OS than males (43.2 vs 30.8 months). Liver metastasis was significantly associated with OS (p=0.007). Patients without liver metastasis had a median OS of 57.0 months and a 24-month OS rate of 82.2%, compared with 31.6 months and 74.9% in those with liver metastasis. RAS status (p=0.9) and tumor location (p=0.7) were not associated with OS (Table 3).\u003c/p\u003e\n\u003cp\u003eBecause few variables showed significance in univariate analyses and effect sizes were modest, a multivariate Cox regression for PFS was not built to prevent overfitting and unstable estimates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Univariate analysis for Overall Survival\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"623\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e24-Month OS (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian OS months\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian OS 95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLog-rank p\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline FIB-4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eLow (\u0026lt;1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e79.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e35.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e25.3\u0026ndash;45.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eIntermediate (1.3\u0026ndash;2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e74.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e38.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e17.1\u0026ndash;59.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eHigh (\u0026gt;2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e53.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e22.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e16.6\u0026ndash;27.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6-month FIB-4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eLow (\u0026lt;1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e82.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e36.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e25.8\u0026ndash;47.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.848\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eIntermediate (1.3\u0026ndash;2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e74.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e34.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e21.3\u0026ndash;47.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eHigh (\u0026gt;2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e71.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e30.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e25.0\u0026ndash;35.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12-month FIB-4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eLow (\u0026lt;1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e85.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e41.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e29.7\u0026ndash;53.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eIntermediate (1.3\u0026ndash;2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e77.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e43.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e29.1\u0026ndash;57.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eHigh (\u0026gt;2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e71.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e24.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e17.8\u0026ndash;30.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e68.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e30.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e27.1-34.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e85.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e43.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e32.3-54.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLiver metastasis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eAbsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e82.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e57.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e42.1\u0026ndash;71.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003ePresent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e74.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e31.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e28.5\u0026ndash;34.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eRAS status\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eWild-type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e73.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eMutant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e74.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTumor location\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eRight colon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e80.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e33.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e17.8-48.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eLeft colon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e70.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e31.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e25.7-37.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eRectum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e80.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e45.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e26.5-44.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eIn multivariate Cox regression analysis, 12-month FIB-4 remained independently associated with OS (overall p=0.004). Compared with the low-risk group, the intermediate-risk group had a 2.35-fold increased risk of mortality (HR 2.35, 95% CI 1.07\u0026ndash;5.14; p=0.033), while the high-risk group had a 6.76-fold increased risk (HR 6.76, 95% CI 2.16\u0026ndash;21.14; p=0.001). Baseline FIB-4 was also independently associated with OS (overall p=0.011). The intermediate-risk group demonstrated a lower risk of death compared with the reference category (HR 0.30, 95% CI 0.14\u0026ndash;0.66; p=0.003), whereas the high-risk group was not significantly associated with OS (HR 0.65, 95% CI 0.07\u0026ndash;5.96; p=0.705). \u0026nbsp;Gender (HR 1.71, 95% CI 0.89\u0026ndash;3.28; p=0.108) and liver metastasis (HR 0.57, 95% CI 0.31\u0026ndash;1.05; p=0.073) were not independently associated with OS in the adjusted model (Table 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. Multivariate Cox regression analysis for overall survival\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR (Exp(B))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12-month FIB-4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003eOverall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003eIntermediate (1.3\u0026ndash;2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e2.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e1.07\u0026ndash;5.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003eHigh (\u0026gt;2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e6.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e2.16\u0026ndash;21.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003eMale vs Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e1.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e0.89\u0026ndash;3.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.108\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLiver metastasis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003ePresent vs Absent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e0.31\u0026ndash;1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline FIB-4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003eOverall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003eIntermediate (1.3\u0026ndash;2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e0.14\u0026ndash;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003eHigh (\u0026gt;2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e0.07\u0026ndash;5.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.705\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe liver is the most common metastatic site in colorectal cancer and significantly impacts patient outcomes; liver fibrosis, driven by chronic inflammation and the activation of hepatic stellate cells, plays a crucial role in disease progression and treatment response (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Non-invasive markers like FIB-4 index, which uses routinely measured lab parameters, have become vital for assessing liver fibrosis (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). FIB-4 is valued for its accessibility and has been incorporated into screening algorithms, also showing promise as a prognostic marker beyond chronic liver diseases (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLoosen et al. demonstrated that elevated FIB-4 scores were associated with an increased risk of hepatocellular carcinoma development in patients with non-alcoholic fatty liver disease (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Similarly, Kariyama et al. reported that FIB-4 was an independent prognostic factor for survival in hepatocellular carcinoma (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). In another study focusing on cholangiocarcinoma, Steffani et al. showed that the presence of liver fibrosis was associated with significantly worse overall survival and higher recurrence rates following treatment (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). These observations support the concept that changes in fibrosis markers may reflect ongoing pathological processes affecting the liver.\u003c/p\u003e \u003cp\u003eIn a large community cohort, Wang et al. demonstrated that higher liver fibrosis scores were associated with increased cancer-related mortality (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Likewise, inflammatory and metabolic pathways linked to fibrosis have been associated with increased mortality and adverse clinical outcomes in metabolic liver disease populations (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). These observations support the hypothesis that fibrosis indices may reflect systemic inflammatory and metabolic disturbances that influence cancer prognosis.\u003c/p\u003e \u003cp\u003eIn metastatic colorectal cancer specifically, the prognostic significance of fibrosis markers has been investigated only in limited studies. Yıldırım et al. recently evaluated several non-invasive liver fibrosis indices, including FIB-4, APRI, and ALBI scores, in treatment-na\u0026iuml;ve metastatic colorectal cancer patients and demonstrated that higher FIB-4 values were associated with poorer overall survival. However, most previous investigations have focused primarily on baseline fibrosis markers, and little information is available regarding temporal changes in fibrosis indices during systemic therapy.\u003c/p\u003e \u003cp\u003eFor instance, Wang et al. demonstrated that post-treatment changes in FIB-4 scores were associated with the subsequent development of hepatocellular carcinoma in patients with chronic hepatitis C infection (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Likewise, longitudinal studies in population-based cohorts have shown that increasing fibrosis scores are associated with higher risks of liver-related complications and mortality (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). These findings support the concept that temporal changes in fibrosis markers may reflect ongoing pathological processes affecting hepatic function.\u003c/p\u003e \u003cp\u003eIn the present study, we evaluated both baseline FIB-4 values and their longitudinal evolution during treatment in patients with metastatic colorectal cancer. Similar to the literature knowledge, our findings demonstrated a significant increase in FIB-4 scores over time, with median values rising from 1.11 at baseline to 1.69 at six months and 1.87 at twelve months. Baseline FIB-4 values were significantly associated with both progression-free survival and overall survival in our cohort. Patients with higher baseline FIB-4 scores experienced shorter survival compared with those in the low-risk group. A particularly notable finding of our study was the prognostic significance of longitudinal FIB-4 measurements. While six-month FIB-4 categories were not associated with survival outcomes, twelve-month FIB-4 values demonstrated a significant association with overall survival and remained an independent prognostic factor in multivariate analysis. Patients in the intermediate- and high-risk groups at twelve months showed substantially increased mortality risk compared with those in the low-risk category.\u003c/p\u003e \u003cp\u003eSeveral mechanisms may explain the increase in FIB-4 scores observed during systemic therapy in our cohort. One potential explanation is \u003cb\u003echemotherapy-related hepatotoxicity\u003c/b\u003e. Oxaliplatin-based chemotherapy, a cornerstone of colorectal cancer treatment, has been associated with sinusoidal obstruction syndrome and other forms of hepatic injury. Histopathological studies have shown that oxaliplatin can induce sinusoidal dilatation, hepatic congestion, and perisinusoidal fibrosis (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). In patients undergoing hepatic resection for colorectal liver metastases, prior exposure to oxaliplatin has been linked to sinusoidal injury and impaired liver function (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnother possible explanation involves the interaction between metastatic tumor burden and the hepatic microenvironment. In our cohort, liver metastasis was significantly associated with overall survival in univariate analysis but did not remain an independent predictor in multivariate models. This observation may indicate that fibrosis-related indices such as FIB-4 capture broader aspects of hepatic dysfunction that are not solely explained by the presence of metastatic disease\u003c/p\u003e \u003cp\u003eSeveral limitations should be considered when interpreting the results of this study. First, the retrospective design introduces the potential for selection bias and limits causal inference. Second, the relatively small number of patients in the high-risk FIB-4 group may have affected the stability of subgroup analyses. Third, FIB-4 represents an indirect marker of fibrosis and may be influenced by factors such as systemic inflammation, chemotherapy-induced hepatotoxicity, or thrombocytopenia. These factors may contribute to variability in FIB-4 values independent of structural fibrosis.\u003c/p\u003e \u003cp\u003eDespite these limitations, our study provides novel insights into the potential prognostic role of fibrosis-related biomarkers in metastatic colorectal cancer. To our knowledge, few studies have examined longitudinal changes in FIB-4 during systemic therapy and their association with survival outcomes. Our findings suggest that monitoring dynamic changes in FIB-4 may provide clinically relevant prognostic information and help identify patients at increased risk of adverse outcomes.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eFIB-4 scores increased progressively during systemic therapy in patients with metastatic colorectal cancer, and both baseline and twelve-month FIB-4 values were associated with overall survival. These findings indicate that longitudinal monitoring of fibrosis markers may offer a simple and accessible approach for prognostic assessment in this patient population. Further prospective studies are warranted to validate these observations and to clarify the mechanisms linking hepatic fibrosis markers with cancer progression and treatment-related liver injury.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFIB-4\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFibrosis-4 index\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\"\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\"\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\"\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\"\u003eAST\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAspartate aminotransferase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eALT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAlanine aminotransferase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e5-FU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e5-fluorouracil\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\"\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\"\u003eIV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntravenous\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 ethical principles of the Declaration of Helsinki. Ethical approval was obtained from the Institutional Ethics Committee of Istanbul Medipol University (Approval number: E-10840098-202.3.02-1501, February 2026). Written informed consent was obtained from all participants.\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Not applicable.\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The data that support the findings of this study are not publicly available due to their sensitive nature but are available from the corresponding author upon reasonable request.\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u003cstrong\u003eCompeting interests\u003cbr\u003e\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing interests.\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The authors received no financial support for the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the conception of the study.\u0026nbsp;\u003cbr\u003e\u0026nbsp;S.G.A. and H.A. designed the study and drafted the manuscript.\u0026nbsp;\u003cbr\u003e\u0026nbsp;All authors contributed to the interpretation of the data.\u0026nbsp;\u003cbr\u003e\u0026nbsp;S.G.A., H.A., and E.S. critically revised the manuscript for important intellectual content.\u0026nbsp;\u003cbr\u003e\u0026nbsp;All authors approved the submitted version.\u0026nbsp;\u003cbr\u003e\u0026nbsp;All authors agree to be personally accountable for their own contributions and to ensure that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003cbr\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u0026nbsp;\u003c/sup\u003eDepartment of General Surgery, Kanuni Sultan Suleyman Training and Research Hospital, Istanbul, Turkey\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003e Department of Internal Medicine, Istanbul Medipol University, Istanbul, Turkey\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003eDepartment of Medical Oncology, Kanuni Sultan Suleyman Training and Research Hospital, Istanbul, Turkey\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e4\u003c/sup\u003e Bezmialem Vakif University Faculty of Medicine, Medical oncology clinic, Istanbul, Turkey\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eZhang Y et al. 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DOI: 10.1200/JCO.2006.06.0032\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"metastatic colorectal cancer, FIB-4, liver fibrosis, prognosis, systemic therapy","lastPublishedDoi":"10.21203/rs.3.rs-9093822/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9093822/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eNon-invasive liver fibrosis markers have been increasingly investigated as prognostic indicators in oncology. However, the clinical relevance of dynamic changes in the fibrosis-4 (FIB-4) index during systemic therapy in metastatic colorectal cancer (mCRC) remains unclear.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThis retrospective multicenter study included patients with mCRC treated with at least two lines of systemic therapy between 2020 and 2025. FIB-4 scores were calculated at baseline, 6 months, and 12 months. Associations with progression-free survival (PFS) and overall survival (OS) were evaluated using Kaplan–Meier and Cox regression analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eA total of 152 patients were analyzed. Median FIB-4 increased significantly over time (1.11 at baseline, 1.69 at 6 months, and 1.87 at 12 months; p\u0026lt;0.001) (Table 1). Baseline FIB-4 categories were associated with PFS (median 16.8, 16.1, and 6.5 months in low-, intermediate-, and high-risk groups; p=0.01) (Table 2) and OS (median 35.6, 38.1, and 22.0 months, respectively) (Table 3). Twelve-month FIB-4 was significantly associated with OS (p=0.009) (Table 3). \u0026nbsp;In multivariate analysis, 12-month FIB-4 remained an independent predictor of mortality (HR 2.35 for intermediate risk and HR 6.76 for high risk; p=0.004) (Table 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eFIB-4 scores increase during systemic therapy in mCRC, and both baseline and 12-month FIB-4 values are associated with overall survival. Longitudinal monitoring of FIB-4 may provide a simple prognostic biomarker in metastatic colorectal cancer.\u003c/p\u003e","manuscriptTitle":"Dynamic increase in FIB-4 during treatment is associated with worse overall survival in metastatic colorectal cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-08 16:20:55","doi":"10.21203/rs.3.rs-9093822/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-09T09:55:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"110382025946615133971034012444795959918","date":"2026-04-29T07:44:58+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-24T07:25:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-23T07:31:54+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-02T06:13:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-02T03:30:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2026-04-02T03:26:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"64f77425-ea84-431c-b9e1-f35b978e0cc5","owner":[],"postedDate":"May 8th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-09T09:55:12+00:00","index":65,"fulltext":""},{"type":"reviewerAgreed","content":"110382025946615133971034012444795959918","date":"2026-04-29T07:44:58+00:00","index":47,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-08T16:21:00+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-08 16:20:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9093822","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9093822","identity":"rs-9093822","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}