Prognostic impact of albumin-bilirubin score in predicting the long-term survival of distal cholangiocarcinoma after radical surgery
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Abstract Background The Albumin-Bilirubin Score (ALBI) serves as an indicator of nutritional status and is a widely recognized prognostic biomarker in cancer patients. The purpose of this research is to evaluate the association between ALBI and survival outcomes in patients with distal cholangiocarcinoma (dCCA) after radical surgery, and develop a nomogram model based on the ALBI to predict individual survival. Methods A total of 177 individuals with dCCA receiving surgery from Jan 2011 to Jan 2022 were enrolled in the research. The association between ALBI and clinicopathologic factors was investigated. The impact of ALBI on recurrence-free survival (RFS) and overall survival (OS) was evaluated by Kaplan-Meier curves and Cox proportional hazards models. Nomograms based on ALBI and other prognostic variables screened by multivariate analysis were produced in predicting RFS and OS of dCCA patients following radical surgery, and the nomograms were evaluated by the consistency index (C-index), calibration curve and decision curve analysis (DCA) curve. Results The optimal cut-off value for ALBI was − 1.67, and the area under the ROC curve (AUC) was 0.71. The High-ALBI group had a considerably shorter RFS and OS (P < 0.001). Multivariate analysis revealed that the ALBI, degree of differentiation, portal vein invasion, and lymph node invasion were significant prognostic factors for RFS, and that the ALBI, CA19-9, degree of differentiation, lymph node invasion, and portal vein invasion were significant prognostic factors for OS. The nomograms were constructed based on these significant prognostic factors. The calibration curves displayed good consistency between actual and predicted probability. Nomograms based on these variables have better discriminant ability in predicting RFS and OS compared with the American Joint Committee on Cancer (AJCC) TNM stage. Moreover, the scores predicted by the nomogram enabled patient stratification into low-points and high-points groups. Kaplan-Meier curves demonstrated that patients in the high-points group had considerably better prognoses than those in the low-points group (p < 0.001). Conclusion ALBI was an independent prognostic factor in predicting RFS and OS of dCCA patients after radical surgery. The nomograms based on ALBI can provide reliable, personalized survival prediction for dCCA.
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Prognostic impact of albumin-bilirubin score in predicting the long-term survival of distal cholangiocarcinoma after radical surgery | 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 Prognostic impact of albumin-bilirubin score in predicting the long-term survival of distal cholangiocarcinoma after radical surgery Jin-Can Huang, You-Wei Ma, Han-Xuan Wang, Ren Lang, Tao Jiang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5958306/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Apr, 2025 Read the published version in World Journal of Surgical Oncology → Version 1 posted 6 You are reading this latest preprint version Abstract Background The Albumin-Bilirubin Score (ALBI) serves as an indicator of nutritional status and is a widely recognized prognostic biomarker in cancer patients. The purpose of this research is to evaluate the association between ALBI and survival outcomes in patients with distal cholangiocarcinoma (dCCA) after radical surgery, and develop a nomogram model based on the ALBI to predict individual survival. Methods A total of 177 individuals with dCCA receiving surgery from Jan 2011 to Jan 2022 were enrolled in the research. The association between ALBI and clinicopathologic factors was investigated. The impact of ALBI on recurrence-free survival (RFS) and overall survival (OS) was evaluated by Kaplan-Meier curves and Cox proportional hazards models. Nomograms based on ALBI and other prognostic variables screened by multivariate analysis were produced in predicting RFS and OS of dCCA patients following radical surgery, and the nomograms were evaluated by the consistency index (C-index), calibration curve and decision curve analysis (DCA) curve. Results The optimal cut-off value for ALBI was − 1.67, and the area under the ROC curve (AUC) was 0.71. The High-ALBI group had a considerably shorter RFS and OS (P < 0.001). Multivariate analysis revealed that the ALBI, degree of differentiation, portal vein invasion, and lymph node invasion were significant prognostic factors for RFS, and that the ALBI, CA19-9, degree of differentiation, lymph node invasion, and portal vein invasion were significant prognostic factors for OS. The nomograms were constructed based on these significant prognostic factors. The calibration curves displayed good consistency between actual and predicted probability. Nomograms based on these variables have better discriminant ability in predicting RFS and OS compared with the American Joint Committee on Cancer (AJCC) TNM stage. Moreover, the scores predicted by the nomogram enabled patient stratification into low-points and high-points groups. Kaplan-Meier curves demonstrated that patients in the high-points group had considerably better prognoses than those in the low-points group (p < 0.001). Conclusion ALBI was an independent prognostic factor in predicting RFS and OS of dCCA patients after radical surgery. The nomograms based on ALBI can provide reliable, personalized survival prediction for dCCA. Distal cholangiocarcinoma Albumin-bilirubin score Nomogram Prognosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Distal cholangiocarcinoma (dCCA) is a malignancy originating from the distal segment of the common bile duct to the ampulla of Vater, constituting 20%-40% of all cholangiocarcinoma( 1 , 2 ). Notably, the incidence of dCCA is markedly higher in Asian countries as compared with Western nations( 3 ). Pancreatoduodenectomy (PD) is the most effective and standardized method in dealing with dCCA compared with other surgical procedures. Patients suffering from dCCA following radical surgery may achieve 5-year survival rates ranging from 13–54%( 4 ), whereas those who do not have surgical resection experience a considerably lower 5-year survival rate of merely 3%( 5 ). Although comprehensive treatment regimens have shown significant effects in improving overall prognosis( 6 – 8 ), radical surgical resection remains the primary treatment option for patients with dCCA. Consequently, precise prognostic assessment of dCCA patients following radical surgery plays a pivotal role in shaping more refined and effective treatment protocols. The preoperative nutritional state has a considerable impact on the prognosis of cancer patients( 9 , 10 ). Although ALBI, a novel nutritional evaluation score, has demonstrated its prognostic impact in several types of tumors( 11 , 12 ), its relationship with the survival outcomes of dCCA remains unexplored. Albumin is the main protein synthesized by the liver, reflecting its synthetic function, while total bilirubin is a metabolic waste product of the liver, with elevated levels typically indicating liver dysfunction. These two factors are combined in the ALBI score, which provides a comprehensive assessment of liver function and can predict clinical outcomes of patients. Therefore, we believe that a higher ALBI score may reflect poorer liver function, which may affect the long-term prognosis of patients with dCCA. Physicians may apply nomograms, predictive models capable of integrating several prognostic signals, to boost the accuracy of forecasting patient survival ( 13 – 15 ). Despite the widespread use of nomograms in various prognostic assessments, few have been developed for predicting the survival outcomes of dCCA patients. Therefore, this study proposes to explore the impact of ALBI on the survival outcomes of dCCA patients following radical surgery, and to create an innovative nomogram that integrates ALBI and other clinicopathological factors for predicting RFS and OS in dCCA patients. The findings of the research are likely to inform more effective treatment strategies for physicians. 2. Materials and Methods 2.1. Patient Selection We conducted a retrospective assessment of clinical data and follow-up information from 177 patients based on specific inclusion and exclusion criteria. Inclusion criteria included: ( 1 ) patients who underwent surgery in the Department of Hepatobiliary Surgery at Beijing Chaoyang Hospital from January 2011 to January 2022; ( 2 ) preoperative imaging confirming dCCA; ( 3 ) patients who underwent radical PD or PD with allogeneic venous replacement; ( 4 ) postoperative pathology confirmed bile duct adenocarcinoma. Exclusion criteria included: ( 1 ) survival of less than one month; ( 2 ) presence of distant metastases; ( 3 ) absence of surgery; ( 4 ) multiple primary malignancies. 2.2. Data collection and follow-up All dCCA patients received blood routine and liver function testing 3–7 days before surgery. The ALBI score was computed using the formula: ALBI = (log10 total bilirubin [µmol/L]×0.66)+(albumin [g/L]×−0.0852)( 16 ). According to the optimal cut-off value for the ALBI score, all patients were categorized into two groups: ≤ − 1.67 as Low-ALBI group and >–1.67 as High-ALBI group. Demographic data, preoperative medical records, and pathology findings were obtained. Preoperative biliary drainage was performed in selected dCCA patients based on specific clinical indications( 17 ). All patients received adjuvant chemotherapy postoperatively in accordance with the guidelines established by the National Comprehensive Cancer Network( 18 ). Postoperative follow-ups included regular radiological scans and blood testing. Any new lesion suggesting a recurrence of the initial dCCA was categorized as postoperative recurrence and diagnosed using clinical assessment, which included computed tomography, magnetic resonance imaging, and bone scintigraphy, or by pathology as appropriate. RFS was defined as the period from the original operation to the first reported recurrence and all death. Postoperative OS was calculated from the operation date to the date of death from any cause. 2.3. Ethics and informed consent The Ethics Committee of Beijing Chao-Yang Hospital approved the study protocol (Approval No. 2020-D-301) and waived the requirement for informed consent for the use of anonymized patient data. This study conforms to the provisions of the Declaration of Helsinki. All information was collected after obtaining written informed consent from the participants. 2.4. Statistical analysis Continuous variables were summarized employing either the mean and standard deviation (SD) or the median and interquartile range (IQR), while categorical variables were tested using Chi-square tests or Fisher’s exact tests. Kaplan-Meier curves were applied to examine survival outcomes with log-rank testing. The Cox proportional hazards model was utilized for both univariate and multivariate studies to uncover independent prognostic variables. A significance level of P < 0.05 was employed. We built nomograms utilizing the independent prognostic variables. The consistency index (C-index), calibration curves, and DCA curves were applied to assess the nomogram's accuracy. Statistical analysis was performed using SPSS (IBM 22.0) and R 4.3.1 software. 3. Results 3.1. Associations between clinicopathological factors and the ALBI score The study included 177 dCCA patients who experienced aggressive surgery, comprising 105 males and 72 females with an average age of 66 years. A total of 51 patients (28.8%) experienced postoperative complications. Among these complications, biochemical fistula occurred in 19 cases (10.7%), clinically relevant pancreatic fistula was observed in 13 cases (7.3%), and hemorrhage was noted in 7 cases (4.0%). Additionally, abdominal infection was present in 6 cases (3.4%), and disturbance of gastric emptying was found in 6 cases (3.4%). Patients were classified into two groups based on the best cut-off value of the ROC curve using preoperative ALBI and the 1-year overall survival rate: the Low-ALBI group (ALBI≤–1.67, n = 93) and the High-ALBI group (ALBI>-1.67, n = 84). The area under the ROC curve for ALBI was 0.71, indicating a sensitivity of 60.3% and a specificity of 77.0% (Fig. 1 ). As demonstrated in Table 1 , the preoperative albumin level was significantly greater in the Low-ALBI group, and the total bilirubin and ALBI score were significantly lower compared with the High-ALBI group. There were no significant differences between the two groups in other clinicopathological characteristics. Table 1 Demographics and clinicopathological characteristics of dCCA patients Variables Total (n = 177) Low-ALBI (n = 93) High-ALBI (n = 84) P Age, median (IQR), y 66(60,72.5) 64 (60,70.5) 67.5(60,73) 0.094 Gender, n(%) 0.799 Male 105(59.3) 56(60.2) 49(58.3) Female 72(40.7) 37(39.8) 35(41.7) BMI, mean (SD), kg/m2 23.78(3.42) 23.77(3.34) 23.78(3.52) 0.99 ALT, median (IQR), U/L 68(35.5,146.5) 66(29.5,163) 77.5(44.25,144) 0.608 TB, median (IQR), µmol /L 105.5(41.85,203.35) 49(20.55,115.55) 193.15(110.4,260.78) < 0.001 Albumin, mean (SD), g/L 35.51(5.88) 39.52(3.81) 31.08(4.39) < 0.001 ALBI score, mean (SD) -1.75(0.67) -2.27(0.41) -1.18(0.37) < 0.001 CA19-9, median (IQR), U/mL 68(26,245.85) 59.2(23.65,205.1) 75.5(28.6,381.83) 0.146 CEA, median (IQR), U/mL 2(1.2,3.15) 1.8(1.2,3.2) 2.15(1.23,3.15) 0.542 Biliary drainage, n(%) 0.732 Yes 84(47.5) 43(46.2) 41(48.8) No 93(52.5) 50(53.8) 43(51.2) Biliary drainage duration, mean (SD), days 7.82(0.83) 7.85(1.23) 7.80(1.11) 0.849 Degree of differentiation, n(%) 0.682 Poor 60(33.9) 30(32.3) 30(35.7) Moderate-Well 117(66.1) 63(67.7) 54(64.3) Tumor size, median (IQR), cm 2(1.5,2.5) 2(1.5,2.5) 2(1.5,2.5) 0.693 Resection margin, n(%) 0.883 R0 169(95.5) 89(95.7) 80(95.2) R1 8(4.5) 4(4.3) 4(4.8) Portal vein invasion, n(%) 0.167 Yes 23( 13 ) 9(9.7) 14(16.7) No 154(87) 84(90.3) 70(83.3) Lymph node invasion, n(%) 0.128 Yes 80(45.2) 37(39.8) 43(51.2) No 97 (54.8) 56(60.2) 41(48.8) Postoperative chemotherapy, n(%) 0.705 Yes 53(29.9) 29(31.2) 24(28.6) No 124(70.1) 64(68.8) 60(71.4) 3.2. Correlation between the ALBI grade and survival outcomes Among the patients included in this study, the median RFS duration was 22 months, with corresponding RFS rates of 65.6%, 38.9%, and 32.0% at 1, 3, and 5 years, respectively. The median OS duration was 26 months, with OS rates at 1, 3, and 5 years following radical surgery of 80.0%, 35.83%, and 27.5%, respectively. In the Kaplan-Meier analysis of RFS and OS based on the ALBI score, the High-ALBI group displayed significantly improved RFS and OS (P < 0.001) compared to the Low-ALBI group. The median RFS for patients in the High-ALBI and Low-ALBI groups was 14 and 50 months, with corresponding 1-, 3-, and 5-year RFS rates of 55.8%, 23.5%, 11.7%, and 74.2%, 52.1%, 48.4%, respectively (Fig. 2 A). The median OS in the two groups was 18 and 38 months, with 1-, 3-, and 5-year OS rates of 68.6%, 20.3%, 10.1%, and 90.2%, 50.1%, 43.1%, respectively (Fig. 2 B). 3.3. Univariate and multivariate analysis of prognostic factors for RFS and OS In univariate Cox regression, albumin, total bilirubin, ALBI, CA19-9, degree of differentiation, lymph node invasion, and portal vein invasion were significant for RFS and OS (P < 0.05). In the multivariate Cox regression of OS, the ALBI (HR: 2.091; 95%CI: 1.294–3.377; P = 0.003), CA19-9(HR: 1.655; 95%CI: 1.067–2.569; P = 0.025), degree of differentiation(HR: 1.556; 95%CI: 1.047–2.312; P = 0.029), lymph node invasion (HR: 2.312; 95%CI: 1.562–3.421; P < 0.001), and portal vein invasion (HR: 2.182; 95%CI: 1.293–3.683; P = 0.003) were independent prognostic factors (Table 2 ).In the multivariate Cox regression of RFS, the ALBI (HR: 2.073; 95%CI: 1.261–3.408; P = 0.004), degree of differentiation(HR: 1.597; 95%CI: 1.056–2.415; P = 0.027), lymph node invasion (HR: 2.700; 95%CI: 1.791–4.070; P < 0.001), and portal vein invasion (HR: 1.800; 95%CI: 1.035–3.128; P = 0.037) were independent prognostic factors (Table 3 ). Table 2 Univariable and multivariable analysis of the prognostic factors for RFS Variable N Univariate Analysis Multivariate Analysis HR(95% CI) p Value HR(95% CI) p Value Gender Female 72 Reference 0.868 Male 105 1.033(0.702–1.521) Age (y) < 60 41 Reference 0.936 ≥ 60 136 0.982(0.613–1.528) Albumin (g/L) ≥ 40 38 Reference 0.042 Reference 0.970 26 144 1.732(1.042–2.878) 0.849(0.460–1.564) ALBI <-1.67 93 Reference < 0.001 Reference 0.004 ≥-1.67 84 2.208(1.504–3.243) 2.073(1.261–3.408) CA19-9 (U/ml) 40 111 1.145(0.773–1.697) CEA (U/ml) < 5 160 Reference 0.076 ≥ 5 17 1.666(0.948–2.926) Degree of differentiation Moderate-Well 117 Reference 0.001 Reference 0.027 Poor 60 1.934(1.307–2.862) 1.597(1.056–2.415) Tumor size (cm) < 3 142 Reference 0.138 ≥ 3 35 1.419(0.893–2.253) Resection margin R0 169 Reference 0.806 R1 8 1.119(0.456–2.750) Lymph node invasion No 97 Reference < 0.001 Reference < 0.001 Yes 80 3.258(2.190–4.828) 2.700(1.791–4.070) Portal vein invasion No 154 Reference < 0.001 Reference 0.037 Yes 23 2.753(1.605–4.720) 1.800(1.035–3.128) Postoperative chemotherapy Yes 124 Reference 0.920 No 53 0.979(0.650–1.475) Table 3 Univariable and multivariable analysis of the prognostic factors for OS Variable N Univariate Analysis Multivariate Analysis HR(95% CI) p Value HR(95% CI) p Value Gender Female 72 Reference 0.729 Male 105 1.068(0.735–1.553) Age (y) < 60 41 Reference 0.653 ≥ 60 136 1.105(0.714–1.711) Albumin (g/L) ≥ 40 38 Reference 0.005 Reference 0.542 26 144 2.104(1.256–3.525) 0.947(0.509–1.760) ALBI <-1.67 93 Reference < 0.001 Reference 0.003 ≥-1.67 84 2.532(1.741–3.683) 2.091(1.294–3.377) CA19-9 (U/ml) < 37 58 Reference 40 111 1.175(0.803–1.719) CEA (U/ml) < 5 160 Reference 0.296 ≥ 5 17 1.348(0.770–2.359) Degree of differentiation Moderate-Well 117 Reference < 0.001 Reference 0.029 Poor 60 1.961(1.348–2.852) 1.556(1.047–2.312) Tumor size (cm) < 3 142 Reference 0.070 ≥ 3 35 1.499(0.968–2.322) Resection margin R0 169 Reference 0.855 R1 8 1.087(0.444–2.665) Lymph node invasion No 97 Reference < 0.001 Reference < 0.001 Yes 80 2.792(1.914–4.072) 2.312(1.562–3.421) Portal vein invasion No 154 Reference < 0.001 Reference 0.003 Yes 23 3.214(1.927–5.359) 2.182(1.293–3.683) Postoperative chemotherapy Yes 124 Reference 0.300 No 53 1.246(0.822–1.889) 3.4. Construction of the prognostic nomogram Using a multivariable COX regression analysis, we developed nomograms for predicting 1-year, 3-year, and 5-year RFS and OS in dCCA patients (Fig. 3 A-B). The RFS nomogram has a C-index value of 0.74, while the OS nomogram's C-index value is 0.75, suggesting their accurate prognostic prediction capability. Calibration curves indicate that the predictions of the 5-year survival probability models for RFS and OS closely correspond with the actual observations (Fig. 4 A-B). Furthermore, DCA curves were built to test the prediction ability of the nomograms in comparison to the AJCC TNM stage. The results demonstrated a significantly greater benefit from our model compared to the TNM stage (Fig. 4 C-D). Each factor was assigned points based on the nomogram, and the total points were calculated by summing the assigned points for all factors. Patients were classified into low-point and high-point groups according to specified cutoff values in the RFS and OS nomograms (215.4 and 262.3, respectively). Kaplan-Meier survival curves (Fig. 5 A-B) demonstrated that patients in the high-point group exhibited markedly superior prognoses compared to those in the low-point group (p < 0.001). 4. Discussion As a malignant tumor emerging from the epithelium distal to the insertion of the cystic duct, dCCA may rapidly infiltrate the biliary tree in a short period, and it’s crucial to treat with dCCA in an early stage( 19 ). With the advancement of chemotherapy and radiology, radical surgery remains the foundation of curative therapy for dCCA. The surgical excision of dCCA typically involves a pancreaticoduodenectomy and lymphadenectomy of nodes surrounding the common bile duct and porta hepatis( 20 ). In a large cohort of cholangiocarcinoma patients who had surgical resection, 78% of those with dCCA achieved R0 resection( 21 ). In addition to surgical details, the preoperative nutritional status and pathological findings significantly impact postoperative complications and the survival outcomes of patients with dCCA after surgery( 22 ). Due to the anatomical location of the primary tumor, the majority of advanced-stage dCCA patients present at the hospital with obstructive jaundice in a malnourished state. Furthermore, surgery causes an inflammatory response corresponding with the level of surgical trauma, prompting a metabolic stress response. Preoperative nutritional assessment plays a vital role in advising physicians to establish appropriate treatment regimens. While some research has explored some nutritional evaluation tools in dCCA( 23 – 25 ), the effect of ALBI in dCCA still needs more evaluation. ALBI, a novel nutritional status scoring system, is derived from the values of albumin and total bilirubin. ALBI has a great effect on the prognosis of some malignant tumors( 26 – 28 ). The result above with in consistent with our study, low-ALBI was an independent prognostic factor in predicting the OS of dCCA patients. Additionally, we observed that patients in Low-ALBI group have a much longer RFS. As a part of ALBI, albumin was usually defined as a simple yet efficient indication for reflecting the body’s nutritional state, which plays a key role in cancer cell immunological responses. Previous studies have consistently identified serum albumin as a significant prognostic factor in a wide range of malignancies( 29 , 30 ). Furthermore, hypoalbuminemia impairs the systemic immune system while boosting tumor cell growth. Research has demonstrated that reduced serum albumin levels may be induced by pro-inflammatory cytokines, which affect albumin synthesis by hepatocytes( 31 , 32 ). Numerous studies have indicated that low preoperative serum albumin levels are linked to poor OS in patients with intrahepatic and perihilar cholangiocarcinoma( 33 , 34 ). The univariate analysis of albumin in our study also indicates the potential predictive ability of OS and RFS in dCCA. Hyperbilirubinemia was associated with dysfunction of the liver, kidneys, and immune system, and heightened gut mucosa permeability( 35 ). Recent studies have indicated a significant correlation between low serum bilirubin levels following biliary drainage and reduced mortality rates( 36 , 37 ). However, despite performing preoperative biliary drainage to reduce total bilirubin levels, full liver function recovery may take 4–6 weeks. From the univariate analysis of our study, a high level of total bilirubin may have a negative effect on the prognosis of dCCA. A retrospective study analyzing 115 perihilar cholangiocarcinoma patients arrived at a similar conclusion. Patients with low preoperative bilirubin levels exhibited significantly superior OS and RFS rates compared to patients with high preoperative bilirubin levels( 38 ). Apart from the ALBI reflecting the nutritional status of dCCA patients, CA19-9 and tumor differentiation represent tumor malignancy from some perspective. Some previous studies have found a relationship between CA19-9 and the survival of dCCA( 39 , 40 ). Patients who had poor differentiation tend to have poor overall survival and early recurrence( 41 – 43 ). Besides, the invasion of the portal vein and lymph node also reflects the malignancy of the tumor and results in a poor prognosis in dCCA patients ( 44 , 45 ). We must consider all these nutritional and oncological factors in predicting survival in a more accurate method. Nomograms have been developed and demonstrated superior accuracy compared to conventional staging systems in predicting prognosis for certain cancers( 46 , 47 ). Therefore, we constructed a prognostic nomogram that integrates nutritional status and oncological factors for patients with dCCA following radical surgery. The nomogram exhibited strong predictive performance for survival, which was verified by the C-index and calibration curve. Comparing the nomogram to the AJCC staging system revealed that the nomogram exhibited superior predictive accuracy and greater clinical utility. Using the scores predicted by the nomogram, patients could be categorized into two groups. The Kaplan–Meier data revealed significant differences in RFS and OS between these two groups. Given the dismal prognosis of the low-points group, patients in this category should receive heightened care. The nomogram can enable clinicians in early prognosis evaluation, guide adjuvant treatment options, and stratify patients based on the anticipated risk score. The research has several limitations that should be addressed in future research. First, the relatively small sample size from a single-center cohort may limit the generalizability and accuracy of our findings. The results might not fully reflect the broader population of dCCA patients, and larger, multi-center studies are needed to validate these conclusions. Second, due to the limited sample size, we were unable to conduct both internal and external validation of the nomograms. This step is crucial to ensure the robustness and applicability of the predictive model across diverse patient populations. In future studies, we aspire to validate the ALBI score in diverse patient cohorts and utilize these findings to guide the design of future clinical trials. 5. Conclusion In conclusion, ALBI was an independent prognostic factor in predicting RFS and OS of dCCA patients after radical surgery. The nomograms based on ALBI can provide reliable, personalized survival prediction for patients with dCCA following radical surgery. Declarations Declaration of competing interest Authors declare no conflicts of interest. Ethics Declaration This study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Ethics Committee of Beijing Chao-Yang Hospital (No. 2020-D-301) and individual consent for this retrospective analysis was waived. Data availability The data used and analyzed in this study is included in the article and is also available from the corresponding and first authors on reasonable request. Funding None. Authors’ contributions Jin-Can Huang: data analysis & collection, manuscript writing; You-Wei Ma: data analysis & collection, manuscript writing; Han-Xuan Wang: data collection; Ren Lang and Tao Jiang: project development, manuscript editing. All authors read and approved the final version of the manuscript. Jin-Can Huang, You-Wei Ma contribute equally to this manuscript and share the first authorship. Acknowledgment None. References Rizvi S, Gores GJ. Pathogenesis, diagnosis, and management of cholangiocarcinoma. 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Terasaki F, Sugiura T, Okamura Y, Ito T, Yamamoto Y, Ashida R, Ohgi K, Uesaka K. Use of preoperative controlling nutritional status (CONUT) score as a better prognostic marker for distal cholangiocarcinoma after pancreatoduodenectomy. Surg Today. 2021;51(3):358–65. 10.1007/s00595-020-02098-0 . Epub 2020/08/08. Kitasato A, Kuroki T. Significance of inflammatory and nutritional markers as prognostic predictors in patients with resected distal cholangiocarcinoma. Asian J Surg. 2021;44(12):1574–6. 10.1016/j.asjsur.2021.08.021 . Epub 2021/09/11. Zhang ZQ, Xiong L, Zhou JJ, Miao XY, Li QL, Wen Y, Zou H. Ability of the ALBI grade to predict posthepatectomy liver failure and long-term survival after liver resection for different BCLC stages of HCC. World J Surg Oncol. 2018;16(1):208. 10.1186/s12957-018-1500-9 . Cited in: Pubmed; PMID 30326907. Epub 2018/10/18. Mao S, Yu X, Shan Y, Fan R, Wu S, Lu C. Albumin-Bilirubin (ALBI) and Monocyte to Lymphocyte Ratio (MLR)-Based Nomogram Model to Predict Tumor Recurrence of AFP-Negative Hepatocellular Carcinoma. J Hepatocell Carcinoma. 2021;8:1355–65. 10.2147/JHC.S339707 . Epub 2021/11/23. Kudo M, Newly Developed Modified ALBI, Grade Shows Better Prognostic and Predictive Value for Hepatocellular Carcinoma. Liver Cancer. 2022;11(1):1–8. 10.1159/000521374 . Epub 2022/03/01. Wu N, Chen G, Hu H, Pang L, Chen Z. Low pretherapeutic serum albumin as a risk factor for poor outcome in esophageal squamous cell carcinomas. Nutr Cancer. 2015;67(3):481–5. Cited in: Pubmed; PMID 25706773. Onate-Ocana LF, Aiello-Crocifoglio V, Gallardo-Rincon D, Herrera-Goepfert R, Brom-Valladares R, Carrillo JF, Cervera E, Mohar-Betancourt A. Serum albumin as a significant prognostic factor for patients with gastric carcinoma. Ann Surg Oncol. 2007;14(2):381–9. 10.1245/s10434-006-9093-x . Epub 2006/12/13. Peters SJ, Vanhaecke T, Papeleu P, Rogiers V, Haagsman HP, van Norren K. Co-culture of primary rat hepatocytes with rat liver epithelial cells enhances interleukin-6-induced acute-phase protein response. Cell Tissue Res. 2010;340(3):451-7. Epub 2010/04/23. 10.1007/s00441-010-0955-y . Cited in: Pubmed; PMID 20411395. Honda H, Qureshi AR, Heimburger O, Barany P, Wang K, Pecoits-Filho R, Stenvinkel P, Lindholm B. Serum albumin, C-reactive protein, interleukin 6, and fetuin a as predictors of malnutrition, cardiovascular disease, and mortality in patients with ESRD. Am J Kidney Dis. 2006;47(1):139–48. 10.1053/j.ajkd.2005.09.014 . Epub 2005/12/27. Shen J, Wen T, Li C, Yan L, Li B, Yang J. The Prognostic Prediction Role of Preoperative Serum Albumin Level in Patients with Intahepatic Cholangiocarcinoma Following Hepatectomy. Dig Dis. 2018;36(4):306–13. 10.1159/000487479 . Epub 2018/04/20. Waghray A, Sobotka A, Marrero CR, Estfan B, Aucejo F, Narayanan Menon KV. Serum albumin predicts survival in patients with hilar cholangiocarcinoma. Gastroenterol Rep (Oxf). 2017;5(1):62–6. 10.1093/gastro/gow021 . Epub 2016/07/09. Nagino M, Takada T, Miyazaki M, Miyakawa S, Tsukada K, Kondo S, Furuse J, Saito H, Tsuyuguchi T, Yoshikawa T, Ohta T, Kimura F, Ohta T, Yoshitomi H, Nozawa S, Yoshida M, Wada K, Amano H, Miura F, Japanese Association of Biliary S, Japanese Society of Hepato-, Biliary-Pancreatic S. Japan Society of Clinical O. Preoperative biliary drainage for biliary tract and ampullary carcinomas. J Hepatobiliary Pancreat Surg. 2008;15(1):25–30. Epub 2008/02/16. 10.1007/s00534-007-1277-7 . Cited in: Pubmed; PMID 18274841. Abdel Wahab M, Fathy O, Elghwalby N, Sultan A, Elebidy E, Abdalla T, Elshobary M, Mostafa M, Foad A, Kandeel T, Abdel Raouf A, Salah T, Abu Zeid M, Abu Elenein A, Gad Elhak N, ElFiky A, Ezzat F. Resectability and prognostic factors after resection of hilar cholangiocarcinoma. Hepatogastroenterology 2006 Jan-Feb;53(67):5–10. Epub 2006/03/02. Cited in: Pubmed; PMID 16506367. Belghiti J, Ogata S. Preoperative optimization of the liver for resection in patients with hilar cholangiocarcinoma. HPB (Oxford). 2005;7(4):252–3. 10.1080/13651820500372335 . Epub 2008/03/12. Li CX, Zhang H, Wang K, Wang X, Li XC. Preoperative Bilirubin Level Predicts Overall Survival and Tumor Recurrence After Resection for Perihilar Cholangiocarcinoma Patients. Cancer Manag Res. 2019;11:10157–65. 10.2147/CMAR.S230620 . Epub 2019/12/11. Xu S, Zhang XP, Zhao GD, Zhao ZM, Gao YX, Hu MG, Tan XL, Liu R. Development and validation of an online calculator to predict early recurrence and long-term survival in patients with distal cholangiocarcinoma after pancreaticoduodenectomy. J Hepatobiliary Pancreat Sci. 2022;29(11):1214–25. 10.1002/jhbp.1058 . Epub 2021/10/23. Sallinen V, Siren J, Makisalo H, Lehtimaki TE, Lantto E, Kokkola A, Nordin A. Differences in Prognostic Factors and Recurrence Patterns After Curative-Intent Resection of Perihilar and Distal Cholangiocarcinomas. Scand J Surg. 2020;109(3):219–27. 10.1177/1457496919832150 . Epub 2019/02/23. Wellner UF, Shen Y, Keck T, Jin W, Xu Z. The survival outcome and prognostic factors for distal cholangiocarcinoma following surgical resection: a meta-analysis for the 5-year survival. Surg Today. 2017;47(3):271–9. 10.1007/s00595-016-1362-0 . Epub 2016/05/30. Andrianello S, Paiella S, Allegrini V, Ramera M, Pulvirenti A, Malleo G, Salvia R, Bassi C. Pancreaticoduodenectomy for distal cholangiocarcinoma: surgical results, prognostic factors, and long-term follow-up. Langenbecks Arch Surg. 2015;400(5):623–8. 10.1007/s00423-015-1320-0 . Epub 2015/07/03. Guilbaud T, Girard E, Lemoine C, Schlienger G, Alao O, Risse O, Berdah S, Chirica M, Moutardier V, Birnbaum DJ. Intra-pancreatic distal cholangiocarcinoma and pancreatic ductal adenocarcinoma: a common short and long-term prognosis? Updates Surg. 2021;73(2):439–50. 10.1007/s13304-021-00981-0 . Epub 2021/01/25. Lyu S, Li L, Zhao X, Ren Z, Cao D, He Q. Prognostic impact of lymph node parameters in distal cholangiocarcinoma after pancreaticoduodenectomy. World J Surg Oncol. 2020;18(1):262. 10.1186/s12957-020-02040-1 . Cited in: Pubmed; PMID 33032609. Epub 2020/10/10. Maeta T, Ebata T, Hayashi E, Kawahara T, Mizuno S, Matsumoto N, Ohta S, Nagino M, Nagoya Surgical Oncology G. Pancreatoduodenectomy with portal vein resection for distal cholangiocarcinoma. Br J Surg. 2017;104(11):1549–57. 10.1002/bjs.10596 . Epub 2017/08/08. Liu J, Wu P, Lai S, Wang J, Hou H, Zhang Y. Prognostic models for upper urinary tract urothelial carcinoma patients after radical nephroureterectomy based on a novel systemic immune-inflammation score with machine learning. BMC Cancer. 2023;23(1):574. 10.1186/s12885-023-11058-z . Epub 2023/06/23. Zhao F, Yang D, He J, Ju X, Ding Y, Li X. Establishment and validation of a prognostic nomogram for extrahepatic cholangiocarcinoma. Front Oncol. 2022;12:1007538. 10.3389/fonc.2022.1007538 . Epub 2022/12/13. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 24 Apr, 2025 Read the published version in World Journal of Surgical Oncology → Version 1 posted Editorial decision: Accepted 13 Apr, 2025 Reviews received at journal 13 Apr, 2025 Reviewers agreed at journal 13 Apr, 2025 Reviewers invited by journal 13 Apr, 2025 Submission checks completed at journal 09 Apr, 2025 First submitted to journal 07 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5958306","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":442428762,"identity":"080f0837-0a79-48b3-96a0-7662505b199e","order_by":0,"name":"Jin-Can Huang","email":"","orcid":"","institution":"Beijing Chao-Yang Hospital Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jin-Can","middleName":"","lastName":"Huang","suffix":""},{"id":442428763,"identity":"eab6430e-ec50-4322-9d4a-541fd0049439","order_by":1,"name":"You-Wei Ma","email":"","orcid":"","institution":"Beijing Chao-Yang Hospital Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"You-Wei","middleName":"","lastName":"Ma","suffix":""},{"id":442428764,"identity":"4e7dc8e5-82b7-46c7-bf16-941b348c63b5","order_by":2,"name":"Han-Xuan Wang","email":"","orcid":"","institution":"Beijing Chao-Yang Hospital Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Han-Xuan","middleName":"","lastName":"Wang","suffix":""},{"id":442428765,"identity":"4c5360de-c234-42cf-9215-dd4872254b38","order_by":3,"name":"Ren Lang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYDCCAwyMByAs5gMHPlQQp4UBqoUt8eCMM6Rp4TE+zNtChA6+2wcYDvzcUZvPL93z4QBvA4M8v9gB/FokzyUwHOw9c9xy5pyzGw5I7mAwnDk7Ab8WA6DrD/C2HTMwuJG74YDhGYYEg9tEaDn4F6jF/kbOgwOJbURqOczbVmNgIJHDcOAgMVokQVpk2w4YSNxIMzjYcEaCsF/4zjAwPnzbVmfAPyP58ec/FTby/NIEtDAw8H8AEodhPAlCyuGgjmiVo2AUjIJRMAIBADCHTYwjaGtZAAAAAElFTkSuQmCC","orcid":"","institution":"Beijing Chao-Yang Hospital Capital Medical University","correspondingAuthor":true,"prefix":"","firstName":"Ren","middleName":"","lastName":"Lang","suffix":""},{"id":442428766,"identity":"55709fc9-2c31-4ae2-82a4-7c23146dbd49","order_by":4,"name":"Tao Jiang","email":"","orcid":"","institution":"Beijing Chao-Yang Hospital Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Tao","middleName":"","lastName":"Jiang","suffix":""}],"badges":[],"createdAt":"2025-02-04 13:08:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5958306/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5958306/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12957-025-03813-2","type":"published","date":"2025-04-24T15:58:27+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80792590,"identity":"d09444f1-256d-4b5e-b612-874e86ead690","added_by":"auto","created_at":"2025-04-17 06:58:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":45581,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves for ALBI in dCCA patients. The ROC curve using preoperative ALBI and the 1-year overall survival rate yielded an area under the curve (AUC) of 0.71 (95% CI = 0.63–0.79; P \u0026lt; 0.001), with an optimal cutoff value of -1.67.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-5958306/v1/6409a541fa6d33775e0a80c9.png"},{"id":80791503,"identity":"07d83c10-39c9-401b-95aa-35218146dd0b","added_by":"auto","created_at":"2025-04-17 06:50:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":192862,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier survival curves for RFS and OS in dCCA patients. (A) Median RFS times in the High-ALBI and Low-ALBI groups were 14 and 50 months, respectively (P \u0026lt; 0.001). (B) Median OS times in the High-ALBI and Low-ALBI groups were 18 and 38 months, respectively (P \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-5958306/v1/c6114a482c9d379fa08d0389.png"},{"id":80791510,"identity":"2aaa8655-f9f9-4eaa-954a-d047b5e20bcf","added_by":"auto","created_at":"2025-04-17 06:50:46","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":142460,"visible":true,"origin":"","legend":"\u003cp\u003eNomograms developed based on multivariate Cox analysis. (A) Nomogram for predicting RFS in dCCA patients. (B) Nomogram for predicting OS in dCCA patients.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-5958306/v1/33ca1993a75b1cc57279434f.png"},{"id":80792588,"identity":"022999a7-30ad-453c-8bac-db9dd31f4ba8","added_by":"auto","created_at":"2025-04-17 06:58:46","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":98225,"visible":true,"origin":"","legend":"\u003cp\u003eDevelopment of the nomograms for dCCA patients. (A) Calibration curve for 5-year RFS. (B) Calibration curve for 5-year OS. (C) Decision curve analysis (DCA) curve for 5-year RFS. (D) DCA curve for 5-year OS.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-5958306/v1/e72604967c8e1160d3e4cd1f.png"},{"id":80791506,"identity":"d119302f-ab15-4071-a131-3bb54f0076d8","added_by":"auto","created_at":"2025-04-17 06:50:46","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":135999,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier survival curves for risk groups. (A) Kaplan-Meier survival curve for RFS in high-point and low-point groups. (B) Kaplan-Meier survival curve for OS in high-point and low-point groups.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-5958306/v1/ff8f1f53f326452ee350426e.png"},{"id":81569949,"identity":"a797e8f1-c1b0-4c51-ad31-e52059440c04","added_by":"auto","created_at":"2025-04-28 16:12:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1711237,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5958306/v1/34468e38-9580-4d18-8c04-020d4786da2b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prognostic impact of albumin-bilirubin score in predicting the long-term survival of distal cholangiocarcinoma after radical surgery","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eDistal cholangiocarcinoma (dCCA) is a malignancy originating from the distal segment of the common bile duct to the ampulla of Vater, constituting 20%-40% of all cholangiocarcinoma(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Notably, the incidence of dCCA is markedly higher in Asian countries as compared with Western nations(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Pancreatoduodenectomy (PD) is the most effective and standardized method in dealing with dCCA compared with other surgical procedures. Patients suffering from dCCA following radical surgery may achieve 5-year survival rates ranging from 13\u0026ndash;54%(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), whereas those who do not have surgical resection experience a considerably lower 5-year survival rate of merely 3%(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Although comprehensive treatment regimens have shown significant effects in improving overall prognosis(\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), radical surgical resection remains the primary treatment option for patients with dCCA. Consequently, precise prognostic assessment of dCCA patients following radical surgery plays a pivotal role in shaping more refined and effective treatment protocols.\u003c/p\u003e \u003cp\u003eThe preoperative nutritional state has a considerable impact on the prognosis of cancer patients(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Although ALBI, a novel nutritional evaluation score, has demonstrated its prognostic impact in several types of tumors(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), its relationship with the survival outcomes of dCCA remains unexplored. Albumin is the main protein synthesized by the liver, reflecting its synthetic function, while total bilirubin is a metabolic waste product of the liver, with elevated levels typically indicating liver dysfunction. These two factors are combined in the ALBI score, which provides a comprehensive assessment of liver function and can predict clinical outcomes of patients. Therefore, we believe that a higher ALBI score may reflect poorer liver function, which may affect the long-term prognosis of patients with dCCA. Physicians may apply nomograms, predictive models capable of integrating several prognostic signals, to boost the accuracy of forecasting patient survival (\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Despite the widespread use of nomograms in various prognostic assessments, few have been developed for predicting the survival outcomes of dCCA patients.\u003c/p\u003e \u003cp\u003eTherefore, this study proposes to explore the impact of ALBI on the survival outcomes of dCCA patients following radical surgery, and to create an innovative nomogram that integrates ALBI and other clinicopathological factors for predicting RFS and OS in dCCA patients. The findings of the research are likely to inform more effective treatment strategies for physicians.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Patient Selection\u003c/h2\u003e \u003cp\u003e We conducted a retrospective assessment of clinical data and follow-up information from 177 patients based on specific inclusion and exclusion criteria. Inclusion criteria included: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) patients who underwent surgery in the Department of Hepatobiliary Surgery at Beijing Chaoyang Hospital from January 2011 to January 2022; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) preoperative imaging confirming dCCA; (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) patients who underwent radical PD or PD with allogeneic venous replacement; (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) postoperative pathology confirmed bile duct adenocarcinoma. Exclusion criteria included: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) survival of less than one month; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) presence of distant metastases; (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) absence of surgery; (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) multiple primary malignancies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Data collection and follow-up\u003c/h2\u003e \u003cp\u003eAll dCCA patients received blood routine and liver function testing 3\u0026ndash;7 days before surgery. The ALBI score was computed using the formula: ALBI = (log10 total bilirubin [\u0026micro;mol/L]\u0026times;0.66)+(albumin [g/L]\u0026times;\u0026minus;0.0852)(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). According to the optimal cut-off value for the ALBI score, all patients were categorized into two groups: \u0026le; \u0026minus;\u0026thinsp;1.67 as Low-ALBI group and \u0026gt;\u0026ndash;1.67 as High-ALBI group.\u003c/p\u003e \u003cp\u003e Demographic data, preoperative medical records, and pathology findings were obtained. Preoperative biliary drainage was performed in selected dCCA patients based on specific clinical indications(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). All patients received adjuvant chemotherapy postoperatively in accordance with the guidelines established by the National Comprehensive Cancer Network(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Postoperative follow-ups included regular radiological scans and blood testing. Any new lesion suggesting a recurrence of the initial dCCA was categorized as postoperative recurrence and diagnosed using clinical assessment, which included computed tomography, magnetic resonance imaging, and bone scintigraphy, or by pathology as appropriate. RFS was defined as the period from the original operation to the first reported recurrence and all death. Postoperative OS was calculated from the operation date to the date of death from any cause.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Ethics and informed consent\u003c/h2\u003e \u003cp\u003e The Ethics Committee of Beijing Chao-Yang Hospital approved the study protocol (Approval No. 2020-D-301) and waived the requirement for informed consent for the use of anonymized patient data. This study conforms to the provisions of the Declaration of Helsinki. All information was collected after obtaining written informed consent from the participants.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Statistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were summarized employing either the mean and standard deviation (SD) or the median and interquartile range (IQR), while categorical variables were tested using Chi-square tests or Fisher\u0026rsquo;s exact tests. Kaplan-Meier curves were applied to examine survival outcomes with log-rank testing. The Cox proportional hazards model was utilized for both univariate and multivariate studies to uncover independent prognostic variables. A significance level of P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was employed. We built nomograms utilizing the independent prognostic variables. The consistency index (C-index), calibration curves, and DCA curves were applied to assess the nomogram's accuracy. Statistical analysis was performed using SPSS (IBM 22.0) and R 4.3.1 software.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Associations between clinicopathological factors and the ALBI score\u003c/h2\u003e \u003cp\u003eThe study included 177 dCCA patients who experienced aggressive surgery, comprising 105 males and 72 females with an average age of 66 years. A total of 51 patients (28.8%) experienced postoperative complications. Among these complications, biochemical fistula occurred in 19 cases (10.7%), clinically relevant pancreatic fistula was observed in 13 cases (7.3%), and hemorrhage was noted in 7 cases (4.0%). Additionally, abdominal infection was present in 6 cases (3.4%), and disturbance of gastric emptying was found in 6 cases (3.4%).\u003c/p\u003e \u003cp\u003ePatients were classified into two groups based on the best cut-off value of the ROC curve using preoperative ALBI and the 1-year overall survival rate: the Low-ALBI group (ALBI\u0026le;\u0026ndash;1.67, n\u0026thinsp;=\u0026thinsp;93) and the High-ALBI group (ALBI\u0026gt;-1.67, n\u0026thinsp;=\u0026thinsp;84). The area under the ROC curve for ALBI was 0.71, indicating a sensitivity of 60.3% and a specificity of 77.0% (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). As demonstrated in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the preoperative albumin level was significantly greater in the Low-ALBI group, and the total bilirubin and ALBI score were significantly lower compared with the High-ALBI group. There were no significant differences between the two groups in other clinicopathological characteristics.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographics and clinicopathological characteristics of dCCA patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;177)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow-ALBI\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;93)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh-ALBI\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;84)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, median (IQR), y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66(60,72.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64 (60,70.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e67.5(60,73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.799\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105(59.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56(60.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49(58.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72(40.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37(39.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35(41.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, mean (SD), kg/m2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.78(3.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.77(3.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.78(3.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT, median (IQR), U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68(35.5,146.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66(29.5,163)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e77.5(44.25,144)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.608\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTB, median (IQR), \u0026micro;mol /L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105.5(41.85,203.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49(20.55,115.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e193.15(110.4,260.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbumin, mean (SD), g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.51(5.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.52(3.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.08(4.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALBI score, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.75(0.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-2.27(0.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.18(0.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA19-9, median (IQR), U/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68(26,245.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59.2(23.65,205.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75.5(28.6,381.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCEA, median (IQR), U/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2(1.2,3.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.8(1.2,3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.15(1.23,3.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.542\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiliary drainage, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.732\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84(47.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43(46.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41(48.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93(52.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50(53.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43(51.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiliary drainage duration, mean (SD), days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.82(0.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.85(1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.80(1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.849\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDegree of differentiation, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.682\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60(33.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30(32.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30(35.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate-Well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117(66.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63(67.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54(64.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor size, median (IQR), cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2(1.5,2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2(1.5,2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2(1.5,2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.693\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResection margin, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.883\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e169(95.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e89(95.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80(95.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8(4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4(4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4(4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePortal vein invasion, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.167\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9(9.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14(16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e154(87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84(90.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e70(83.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymph node invasion, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80(45.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37(39.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43(51.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97 (54.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56(60.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41(48.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative chemotherapy, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.705\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53(29.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29(31.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24(28.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e124(70.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64(68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60(71.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Correlation between the ALBI grade and survival outcomes\u003c/h2\u003e \u003cp\u003eAmong the patients included in this study, the median RFS duration was 22 months, with corresponding RFS rates of 65.6%, 38.9%, and 32.0% at 1, 3, and 5 years, respectively. The median OS duration was 26 months, with OS rates at 1, 3, and 5 years following radical surgery of 80.0%, 35.83%, and 27.5%, respectively. In the Kaplan-Meier analysis of RFS and OS based on the ALBI score, the High-ALBI group displayed significantly improved RFS and OS (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to the Low-ALBI group. The median RFS for patients in the High-ALBI and Low-ALBI groups was 14 and 50 months, with corresponding 1-, 3-, and 5-year RFS rates of 55.8%, 23.5%, 11.7%, and 74.2%, 52.1%, 48.4%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The median OS in the two groups was 18 and 38 months, with 1-, 3-, and 5-year OS rates of 68.6%, 20.3%, 10.1%, and 90.2%, 50.1%, 43.1%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Univariate and multivariate analysis of prognostic factors for RFS and OS\u003c/h2\u003e \u003cp\u003eIn univariate Cox regression, albumin, total bilirubin, ALBI, CA19-9, degree of differentiation, lymph node invasion, and portal vein invasion were significant for RFS and OS (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In the multivariate Cox regression of OS, the ALBI (HR: 2.091; 95%CI: 1.294\u0026ndash;3.377; P\u0026thinsp;=\u0026thinsp;0.003), CA19-9(HR: 1.655; 95%CI: 1.067\u0026ndash;2.569; P\u0026thinsp;=\u0026thinsp;0.025), degree of differentiation(HR: 1.556; 95%CI: 1.047\u0026ndash;2.312; P\u0026thinsp;=\u0026thinsp;0.029), lymph node invasion (HR: 2.312; 95%CI: 1.562\u0026ndash;3.421; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and portal vein invasion (HR: 2.182; 95%CI: 1.293\u0026ndash;3.683; P\u0026thinsp;=\u0026thinsp;0.003) were independent prognostic factors (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).In the multivariate Cox regression of RFS, the ALBI (HR: 2.073; 95%CI: 1.261\u0026ndash;3.408; P\u0026thinsp;=\u0026thinsp;0.004), degree of differentiation(HR: 1.597; 95%CI: 1.056\u0026ndash;2.415; P\u0026thinsp;=\u0026thinsp;0.027), lymph node invasion (HR: 2.700; 95%CI: 1.791\u0026ndash;4.070; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and portal vein invasion (HR: 1.800; 95%CI: 1.035\u0026ndash;3.128; P\u0026thinsp;=\u0026thinsp;0.037) were independent prognostic factors (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariable and multivariable analysis of the prognostic factors for RFS\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eUnivariate Analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eMultivariate Analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHR(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.868\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.033(0.702\u0026ndash;1.521)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (y)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.936\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.982(0.613\u0026ndash;1.528)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbumin (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.970\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.676(1.019\u0026ndash;2.754)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.011(0.559\u0026ndash;1.830)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal bilirubin (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.849\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.732(1.042\u0026ndash;2.878)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.849(0.460\u0026ndash;1.564)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALBI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;-1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;-1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.208(1.504\u0026ndash;3.243)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.073(1.261\u0026ndash;3.408)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA19-9 (U/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.776(1.167\u0026ndash;2.703)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.471(0.947\u0026ndash;2.284)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT(U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.145(0.773\u0026ndash;1.697)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCEA (U/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.666(0.948\u0026ndash;2.926)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDegree of differentiation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate-Well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.934(1.307\u0026ndash;2.862)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.597(1.056\u0026ndash;2.415)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor size (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.419(0.893\u0026ndash;2.253)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResection margin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.806\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.119(0.456\u0026ndash;2.750)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymph node invasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.258(2.190\u0026ndash;4.828)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.700(1.791\u0026ndash;4.070)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePortal vein invasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.753(1.605\u0026ndash;4.720)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.800(1.035\u0026ndash;3.128)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative chemotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.920\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.979(0.650\u0026ndash;1.475)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariable and multivariable analysis of the prognostic factors for OS\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eUnivariate Analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eMultivariate Analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHR(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.729\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.068(0.735\u0026ndash;1.553)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (y)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.105(0.714\u0026ndash;1.711)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbumin (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.542\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.103(1.256\u0026ndash;3.523)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.206(0.660\u0026ndash;2.206)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal bilirubin (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.863\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.104(1.256\u0026ndash;3.525)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.947(0.509\u0026ndash;1.760)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALBI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;-1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;-1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.532(1.741\u0026ndash;3.683)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.091(1.294\u0026ndash;3.377)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA19-9 (U/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.158(1.420\u0026ndash;3.279)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.665(1.067\u0026ndash;2.569)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT(U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.175(0.803\u0026ndash;1.719)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCEA (U/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.348(0.770\u0026ndash;2.359)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDegree of differentiation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate-Well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.961(1.348\u0026ndash;2.852)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.556(1.047\u0026ndash;2.312)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor size (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.499(0.968\u0026ndash;2.322)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResection margin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.855\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.087(0.444\u0026ndash;2.665)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymph node invasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.792(1.914\u0026ndash;4.072)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.312(1.562\u0026ndash;3.421)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePortal vein invasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.214(1.927\u0026ndash;5.359)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.182(1.293\u0026ndash;3.683)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative chemotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.246(0.822\u0026ndash;1.889)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Construction of the prognostic nomogram\u003c/h2\u003e \u003cp\u003eUsing a multivariable COX regression analysis, we developed nomograms for predicting 1-year, 3-year, and 5-year RFS and OS in dCCA patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-B). The RFS nomogram has a C-index value of 0.74, while the OS nomogram's C-index value is 0.75, suggesting their accurate prognostic prediction capability. Calibration curves indicate that the predictions of the 5-year survival probability models for RFS and OS closely correspond with the actual observations (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-B). Furthermore, DCA curves were built to test the prediction ability of the nomograms in comparison to the AJCC TNM stage. The results demonstrated a significantly greater benefit from our model compared to the TNM stage (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC-D). Each factor was assigned points based on the nomogram, and the total points were calculated by summing the assigned points for all factors. Patients were classified into low-point and high-point groups according to specified cutoff values in the RFS and OS nomograms (215.4 and 262.3, respectively). Kaplan-Meier survival curves (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-B) demonstrated that patients in the high-point group exhibited markedly superior prognoses compared to those in the low-point group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eAs a malignant tumor emerging from the epithelium distal to the insertion of the cystic duct, dCCA may rapidly infiltrate the biliary tree in a short period, and it\u0026rsquo;s crucial to treat with dCCA in an early stage(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). With the advancement of chemotherapy and radiology, radical surgery remains the foundation of curative therapy for dCCA. The surgical excision of dCCA typically involves a pancreaticoduodenectomy and lymphadenectomy of nodes surrounding the common bile duct and porta hepatis(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). In a large cohort of cholangiocarcinoma patients who had surgical resection, 78% of those with dCCA achieved R0 resection(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). In addition to surgical details, the preoperative nutritional status and pathological findings significantly impact postoperative complications and the survival outcomes of patients with dCCA after surgery(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDue to the anatomical location of the primary tumor, the majority of advanced-stage dCCA patients present at the hospital with obstructive jaundice in a malnourished state. Furthermore, surgery causes an inflammatory response corresponding with the level of surgical trauma, prompting a metabolic stress response. Preoperative nutritional assessment plays a vital role in advising physicians to establish appropriate treatment regimens. While some research has explored some nutritional evaluation tools in dCCA(\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), the effect of ALBI in dCCA still needs more evaluation.\u003c/p\u003e \u003cp\u003eALBI, a novel nutritional status scoring system, is derived from the values of albumin and total bilirubin. ALBI has a great effect on the prognosis of some malignant tumors(\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). The result above with in consistent with our study, low-ALBI was an independent prognostic factor in predicting the OS of dCCA patients. Additionally, we observed that patients in Low-ALBI group have a much longer RFS.\u003c/p\u003e \u003cp\u003eAs a part of ALBI, albumin was usually defined as a simple yet efficient indication for reflecting the body\u0026rsquo;s nutritional state, which plays a key role in cancer cell immunological responses. Previous studies have consistently identified serum albumin as a significant prognostic factor in a wide range of malignancies(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Furthermore, hypoalbuminemia impairs the systemic immune system while boosting tumor cell growth. Research has demonstrated that reduced serum albumin levels may be induced by pro-inflammatory cytokines, which affect albumin synthesis by hepatocytes(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Numerous studies have indicated that low preoperative serum albumin levels are linked to poor OS in patients with intrahepatic and perihilar cholangiocarcinoma(\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). The univariate analysis of albumin in our study also indicates the potential predictive ability of OS and RFS in dCCA.\u003c/p\u003e \u003cp\u003eHyperbilirubinemia was associated with dysfunction of the liver, kidneys, and immune system, and heightened gut mucosa permeability(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Recent studies have indicated a significant correlation between low serum bilirubin levels following biliary drainage and reduced mortality rates(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). However, despite performing preoperative biliary drainage to reduce total bilirubin levels, full liver function recovery may take 4\u0026ndash;6 weeks. From the univariate analysis of our study, a high level of total bilirubin may have a negative effect on the prognosis of dCCA. A retrospective study analyzing 115 perihilar cholangiocarcinoma patients arrived at a similar conclusion. Patients with low preoperative bilirubin levels exhibited significantly superior OS and RFS rates compared to patients with high preoperative bilirubin levels(\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eApart from the ALBI reflecting the nutritional status of dCCA patients, CA19-9 and tumor differentiation represent tumor malignancy from some perspective. Some previous studies have found a relationship between CA19-9 and the survival of dCCA(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Patients who had poor differentiation tend to have poor overall survival and early recurrence(\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). Besides, the invasion of the portal vein and lymph node also reflects the malignancy of the tumor and results in a poor prognosis in dCCA patients (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). We must consider all these nutritional and oncological factors in predicting survival in a more accurate method.\u003c/p\u003e \u003cp\u003eNomograms have been developed and demonstrated superior accuracy compared to conventional staging systems in predicting prognosis for certain cancers(\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Therefore, we constructed a prognostic nomogram that integrates nutritional status and oncological factors for patients with dCCA following radical surgery. The nomogram exhibited strong predictive performance for survival, which was verified by the C-index and calibration curve. Comparing the nomogram to the AJCC staging system revealed that the nomogram exhibited superior predictive accuracy and greater clinical utility. Using the scores predicted by the nomogram, patients could be categorized into two groups. The Kaplan\u0026ndash;Meier data revealed significant differences in RFS and OS between these two groups. Given the dismal prognosis of the low-points group, patients in this category should receive heightened care. The nomogram can enable clinicians in early prognosis evaluation, guide adjuvant treatment options, and stratify patients based on the anticipated risk score.\u003c/p\u003e \u003cp\u003eThe research has several limitations that should be addressed in future research. First, the relatively small sample size from a single-center cohort may limit the generalizability and accuracy of our findings. The results might not fully reflect the broader population of dCCA patients, and larger, multi-center studies are needed to validate these conclusions. Second, due to the limited sample size, we were unable to conduct both internal and external validation of the nomograms. This step is crucial to ensure the robustness and applicability of the predictive model across diverse patient populations. In future studies, we aspire to validate the ALBI score in diverse patient cohorts and utilize these findings to guide the design of future clinical trials.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, ALBI was an independent prognostic factor in predicting RFS and OS of dCCA patients after radical surgery. The nomograms based on ALBI can provide reliable, personalized survival prediction for patients with dCCA following radical surgery.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Ethics Committee of Beijing Chao-Yang Hospital (No. 2020-D-301) and individual consent for this retrospective analysis was waived.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used and analyzed in this study is included in the article and is also available from the corresponding and first authors on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJin-Can Huang: data analysis \u0026amp; collection, manuscript writing; You-Wei Ma: data analysis \u0026amp; collection, manuscript writing; Han-Xuan Wang: data collection; Ren Lang and Tao Jiang: project development, manuscript editing. All authors read and approved the final version of the manuscript. Jin-Can Huang, You-Wei Ma contribute equally to this manuscript and share the first authorship.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRizvi S, Gores GJ. Pathogenesis, diagnosis, and management of cholangiocarcinoma. Gastroenterology. 2013;145(6):1215\u0026ndash;29. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1053/j.gastro.2013.10.013\u003c/span\u003e\u003cspan address=\"10.1053/j.gastro.2013.10.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Cited in: Pubmed; PMID 24140396. Epub 2013/10/22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNakeeb A, Pitt HA, Sohn TA, Coleman J, Abrams RA, Piantadosi S, Hruban RH, Lillemoe KD, Yeo CJ, Cameron JL. Cholangiocarcinoma. A spectrum of intrahepatic, perihilar, and distal tumors. 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Establishment and validation of a prognostic nomogram for extrahepatic cholangiocarcinoma. Front Oncol. 2022;12:1007538. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fonc.2022.1007538\u003c/span\u003e\u003cspan address=\"10.3389/fonc.2022.1007538\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2022/12/13.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"world-journal-of-surgical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wjso","sideBox":"Learn more about [World Journal of Surgical Oncology](http://wjso.biomedcentral.com)","snPcode":"12957","submissionUrl":"https://submission.nature.com/new-submission/12957/3","title":"World Journal of Surgical Oncology","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Distal cholangiocarcinoma, Albumin-bilirubin score, Nomogram, Prognosis","lastPublishedDoi":"10.21203/rs.3.rs-5958306/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5958306/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe Albumin-Bilirubin Score (ALBI) serves as an indicator of nutritional status and is a widely recognized prognostic biomarker in cancer patients. The purpose of this research is to evaluate the association between ALBI and survival outcomes in patients with distal cholangiocarcinoma (dCCA) after radical surgery, and develop a nomogram model based on the ALBI to predict individual survival.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA total of 177 individuals with dCCA receiving surgery from Jan 2011 to Jan 2022 were enrolled in the research. The association between ALBI and clinicopathologic factors was investigated. The impact of ALBI on recurrence-free survival (RFS) and overall survival (OS) was evaluated by Kaplan-Meier curves and Cox proportional hazards models. Nomograms based on ALBI and other prognostic variables screened by multivariate analysis were produced in predicting RFS and OS of dCCA patients following radical surgery, and the nomograms were evaluated by the consistency index (C-index), calibration curve and decision curve analysis (DCA) curve.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe optimal cut-off value for ALBI was \u0026minus;\u0026thinsp;1.67, and the area under the ROC curve (AUC) was 0.71. The High-ALBI group had a considerably shorter RFS and OS (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Multivariate analysis revealed that the ALBI, degree of differentiation, portal vein invasion, and lymph node invasion were significant prognostic factors for RFS, and that the ALBI, CA19-9, degree of differentiation, lymph node invasion, and portal vein invasion were significant prognostic factors for OS. The nomograms were constructed based on these significant prognostic factors. The calibration curves displayed good consistency between actual and predicted probability. Nomograms based on these variables have better discriminant ability in predicting RFS and OS compared with the American Joint Committee on Cancer (AJCC) TNM stage. Moreover, the scores predicted by the nomogram enabled patient stratification into low-points and high-points groups. Kaplan-Meier curves demonstrated that patients in the high-points group had considerably better prognoses than those in the low-points group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eALBI was an independent prognostic factor in predicting RFS and OS of dCCA patients after radical surgery. The nomograms based on ALBI can provide reliable, personalized survival prediction for dCCA.\u003c/p\u003e","manuscriptTitle":"Prognostic impact of albumin-bilirubin score in predicting the long-term survival of distal cholangiocarcinoma after radical surgery","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-17 06:50:39","doi":"10.21203/rs.3.rs-5958306/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accepted","date":"2025-04-14T02:28:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-13T15:27:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"189533987921899568283501173743213772282","date":"2025-04-13T15:25:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-13T14:59:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-09T11:34:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"World Journal of Surgical Oncology","date":"2025-04-07T14:04:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"world-journal-of-surgical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wjso","sideBox":"Learn more about [World Journal of Surgical Oncology](http://wjso.biomedcentral.com)","snPcode":"12957","submissionUrl":"https://submission.nature.com/new-submission/12957/3","title":"World Journal of Surgical Oncology","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"15c74699-4021-46af-8192-92f9ee4b7831","owner":[],"postedDate":"April 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-04-28T16:07:52+00:00","versionOfRecord":{"articleIdentity":"rs-5958306","link":"https://doi.org/10.1186/s12957-025-03813-2","journal":{"identity":"world-journal-of-surgical-oncology","isVorOnly":false,"title":"World Journal of Surgical Oncology"},"publishedOn":"2025-04-24 15:58:27","publishedOnDateReadable":"April 24th, 2025"},"versionCreatedAt":"2025-04-17 06:50:39","video":"","vorDoi":"10.1186/s12957-025-03813-2","vorDoiUrl":"https://doi.org/10.1186/s12957-025-03813-2","workflowStages":[]},"version":"v1","identity":"rs-5958306","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5958306","identity":"rs-5958306","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}
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