Prediction model for overall survival after curative resection of hepatocellular carcinoma based on alkaline phosphatase + gamma-glutamyl transpeptidase / platelet: a multicenter study_CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Authors：

LIU Zhuoran ¹ , LI Jing ² , ZHAO Xin ³ , XIE Qingyun ⁴ , MAO Tianyang ¹ , FU Jinqiang ¹ , DU Bo ¹ , ZHENG Peng ⁵ , WANG Hongyuan ⁵ , ZHOU Heng ⁵ , GAO Fengwei ⁴ ,  JIANG Kangyi ¹

1. Department of Hepatobiliary & Pancreatic Surgery, The People’s Hospital of Leshan, Leshan, Sichuan 614000, P. R. China;
2. Department of Hepatobiliary Surgery, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan 646000, P. R. China;
3. Division of Biliary Tract Surgery, Department of General Surgery, West China Hospital, Sichuan University, Chengdu 610041, P. R. China;
4. Liver Transplant Center, Transplant Center, West China Hospital, Sichuan University, Chengdu 610041, P. R. China;
5. College of Clinical Medicine, North Sichuan Medical College, Nanchong, Sichuan 637000, P. R. China;

Corresponding?author：

JIANG Kangyi, Email: jiangkangyi1988@163.com

Keywords：

hepatocellular carcinoma; alkaline phosphatase + gamma-glutamyl transpeptidase / platelet (AGPR); nomogram; predictive model; prognostic factor

DOI：

10.7507/1007-9424.202601121

Video：

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Objective To investigate the prognostic value of the alkaline phosphatase + gamma-glutamyl transpeptidase / platelet (AGPR) in predicting overall survival in patients with hepatocellular carcinoma (HCC) after curative hepatectomy, and to develop an AGPR-based nomogram prediction model to enhance the accuracy of prognostic risk stratification and individualized treatment decision-making. Methods This multicenter retrospective study included patients who underwent radical resection for HCC at the Affiliated Hospital of Southwest Medical University (2013–2023) as the training and internal validation sets, and at Leshan People’s Hospital (2018–2024) as the external validation set. Baseline characteristics, preoperative laboratory tests, surgical details, and pathological findings were collected. Optimal cutoff values for AGPR and the pan-immune-inflammation value (PIV) were determined using receiver operating characteristic (ROC) curves. Independent prognostic factors for overall survival were identified using univariate and multivariate Cox regression, then a nomogram was developed. Model performance was assessed using the area under the ROC curve (AUC), concordance index (C-index), calibration, and decision curve analysis for clinical utility assessment. Patients were stratified into low- and high-risk groups based on the median nomogram score, and overall survival was compared. Results A total of 618 patients were included: 250 in the training set, 167 in the internal validation set, and 201 in the external validation set. Optimal cutoff values were 1.06 for AGPR and 316.79 for PIV. Multivariate Cox regression identified alpha-fetoprotein (AFP), AGPR, PIV, and tumor diameter as independent prognostic factors (P＜0.05). The nomogram predicting 1-, 3-, and 5-year overall survival rates achieved AUCs of 0.820, 0.734, and 0.727 in the training set; 0.784, 0.722, and 0.705 in the internal validation set; and 0.789, 0.703, and 0.702 in the external validation set. C-indices were 0.748, 0.701, and 0.692, respectively. The Hosmer-Lemeshow test indicated good calibration (P>0.05), and calibration curves aligned closely with the ideal diagonal. Decision curve analysis demonstrated clinical net benefit across all datasets. Low-risk patients had significantly better overall survival than high-risk patients (P＜0.05). Conclusions AGPR is an independent prognostic factor for overall survival in HCC patients after radical resection. The nomogram incorporating AGPR, AFP, PIV, and tumor diameter exhibits favorable discrimination, calibration, and clinical utility, supporting its use for postoperative risk stratification and individualized treatment planning.

Citation： LIU Zhuoran, LI Jing, ZHAO Xin, XIE Qingyun, MAO Tianyang, FU Jinqiang, DU Bo, ZHENG Peng, WANG Hongyuan, ZHOU Heng, GAO Fengwei, JIANG Kangyi. Prediction model for overall survival after curative resection of hepatocellular carcinoma based on alkaline phosphatase + gamma-glutamyl transpeptidase / platelet: a multicenter study. CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY, 2026, 33(3): 324-330. doi: 10.7507/1007-9424.202601121 Copy

1.	中國抗癌協會肝癌專業委員會, 陳敏山. 中國肝癌多學科綜合治療專家共識(2025年版). 臨床肝膽病雜志, 2025, 41(7): 1279-1286.
2.	中華人民共和國國家衛生健康委員會醫政司. 原發性肝癌診療指南(2024年版). 協和醫學雜志, 2024, 15(3): 532-558.
3.	Liao MJ, Li J, Dang W, et al. Novel index for the prediction of significant liver fibrosis and cirrhosis in chronic hepatitis B patients in China. World J Gastroenterol, 2022, 28(27): 3503-3513.
4.	藍萍. EVendo評分、INPR、AGPR對乙型肝炎后肝硬化食管靜脈曲張程度的預測價值. 贛州: 贛南醫科大學, 2024.
5.	李光宇. FibroScan與血清學模型對ALT正常的CHB患者肝纖維化的診斷價值. 鎮江: 江蘇大學, 2024.
6.	Yan X, Li Y, Qin W, et al. Radiomics model based on contrast-enhanced computed tomography imaging for early recurrence monitoring after radical resection of AFP-negative hepatocellular carcinoma. BMC Cancer, 2024, 24(1): 700. doi: 10.1186/s12885-024-12436-x.
7.	Fu H, Wang Y, Xiang B. Pan-immune-inflammation value as a prognostic biomarker for hepatocellular carcinoma patients undergoing hepatectomy. J Inflamm Res, 2025, 18: 6411-6425.
8.	Higashino K, Otani R. Alkaline phosphatase as a tumor marker. Nihon Rinsho, 1980, 38(12): 4588-4598.
9.	Zhang X, Xin Y, Chen Y, et al. Prognostic effect of albumin-to-alkaline phosphatase ratio on patients with hepatocellular carcinoma: a systematic review and meta-analysis. Sci Rep, 2023, 13(1): 1808. doi: 10.1038/s41598-023-28889-2.
10.	Sun P, Chen S, Li Y. The association between pretreatment serum alkaline phosphatase and prognosis in hepatocellular carcinoma: a meta-analysis. Medicine (Baltimore), 2020, 99(11): e19438. doi: 10.1097/MD.0000000000019438.
11.	Zhang LX, Lv Y, Xu AM, et al. The prognostic significance of serum gamma-glutamyltransferase levels and AST/ALT in primary hepatic carcinoma. BMC Cancer, 2019, 19(1): 841. doi: 10.1186/s12885-019-6011-8.
12.	Gay LJ, Felding-Habermann B. Contribution of platelets to tumour metastasis. Nat Rev Cancer, 2011, 11(2): 123-134.
13.	Jayarajan S, Daly JM. The relationships of nutrients, routes of delivery, and immunocompetence. Surg Clin North Am, 2011, 91(4): 737-753.
14.	Gawiński C, Michalski W, Mróz A, et al. Correlation between lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and tumor-infiltrating lymphocytes (TILs) in left-sided colorectal cancer patients. Biology (Basel), 2022, 11(3): 385. doi: 10.3390/biology11030385.
15.	Hassan WA, ElBanna AK, Noufal N, et al. Significance of tumor-associated neutrophils, lymphocytes, and neutrophil-to-lymphocyte ratio in non-invasive and invasive bladder urothelial carcinoma. J Pathol Transl Med, 2023, 57(2): 88-94.
16.	Wang Y, Zhai J, Zhang T, et al. Tumor-associated neutrophils can predict lymph node metastasis in early gastric cancer. Front Oncol, 2020, 10: 570113. doi: 10.3389/fonc.2020.570113.
17.	Kepp O, Liu P, Zitvogel L, et al. Tumor-infiltrating lymphocytes for melanoma immunotherapy. Oncoimmunology, 2023, 12(1): 2175506. doi: 10.1080/2162402X.2023.2175506.
18.	Hong YM, Yoon KT, Hwang TH, et al. Pretreatment peripheral neutrophils, lymphocytes and monocytes predict long-term survival in hepatocellular carcinoma. BMC Cancer, 2020, 20(1): 937. doi: 10.1186/s12885-020-07105-8.
19.	Feng F, Zheng G, Wang Q, et al. Low lymphocyte count and high monocyte count predicts poor prognosis of gastric cancer. BMC Gastroenterol, 2018, 18(1): 148. doi: 10.1186/s12876-018-0877-9.
20.	Zeng J, Chen G, Zeng J, et al. Development of nomograms to predict outcomes for large hepatocellular carcinoma after liver resection. Hepatol Int, 2025, 19(2): 428-440.
21.	Tan J, Yu Y, Lin X, et al. OHCCPredictor: an online risk stratification model for predicting survival duration of older patients with hepatocellular carcinoma. Hepatol Int, 2024, 18(2): 550-567.
22.	Kang X, Liu X, Li Y, et al. Development and evaluation of nomograms and risk stratification systems to predict the overall survival and cancer-specific survival of patients with hepatocellular carcinoma. Clin Exp Med, 2024, 24(1): 44. doi: 10.1007/s10238-024-01296-1.
23.	Li GC, Yao ZY, Mao HS, et al. Association of triglyceride-glucose index with long-term prognosis in advanced hepatocellular carcinoma patients receiving immunotherapy and targeted therapy. World J Gastroenterol, 2025, 31(30): 109863. doi: 10.3748/wjg.v31.i30.109863.
24.	Wang T, Zheng J, Guo L, et al. Use of a pathomics signature to predict the prognosis of hepatocellular carcinoma with cirrhosis: a multicentre retrospective study. Cancers (Basel), 2025, 17(19): 3192. doi: 10.3390/cancers17193192.

1. 中國抗癌協會肝癌專業委員會, 陳敏山. 中國肝癌多學科綜合治療專家共識(2025年版). 臨床肝膽病雜志, 2025, 41(7): 1279-1286.
2. 中華人民共和國國家衛生健康委員會醫政司. 原發性肝癌診療指南(2024年版). 協和醫學雜志, 2024, 15(3): 532-558.
3. Liao MJ, Li J, Dang W, et al. Novel index for the prediction of significant liver fibrosis and cirrhosis in chronic hepatitis B patients in China. World J Gastroenterol, 2022, 28(27): 3503-3513.
4. 藍萍. EVendo評分、INPR、AGPR對乙型肝炎后肝硬化食管靜脈曲張程度的預測價值. 贛州: 贛南醫科大學, 2024.
5. 李光宇. FibroScan與血清學模型對ALT正常的CHB患者肝纖維化的診斷價值. 鎮江: 江蘇大學, 2024.
6. Yan X, Li Y, Qin W, et al. Radiomics model based on contrast-enhanced computed tomography imaging for early recurrence monitoring after radical resection of AFP-negative hepatocellular carcinoma. BMC Cancer, 2024, 24(1): 700. doi: 10.1186/s12885-024-12436-x.
7. Fu H, Wang Y, Xiang B. Pan-immune-inflammation value as a prognostic biomarker for hepatocellular carcinoma patients undergoing hepatectomy. J Inflamm Res, 2025, 18: 6411-6425.
8. Higashino K, Otani R. Alkaline phosphatase as a tumor marker. Nihon Rinsho, 1980, 38(12): 4588-4598.
9. Zhang X, Xin Y, Chen Y, et al. Prognostic effect of albumin-to-alkaline phosphatase ratio on patients with hepatocellular carcinoma: a systematic review and meta-analysis. Sci Rep, 2023, 13(1): 1808. doi: 10.1038/s41598-023-28889-2.
10. Sun P, Chen S, Li Y. The association between pretreatment serum alkaline phosphatase and prognosis in hepatocellular carcinoma: a meta-analysis. Medicine (Baltimore), 2020, 99(11): e19438. doi: 10.1097/MD.0000000000019438.
11. Zhang LX, Lv Y, Xu AM, et al. The prognostic significance of serum gamma-glutamyltransferase levels and AST/ALT in primary hepatic carcinoma. BMC Cancer, 2019, 19(1): 841. doi: 10.1186/s12885-019-6011-8.
12. Gay LJ, Felding-Habermann B. Contribution of platelets to tumour metastasis. Nat Rev Cancer, 2011, 11(2): 123-134.
13. Jayarajan S, Daly JM. The relationships of nutrients, routes of delivery, and immunocompetence. Surg Clin North Am, 2011, 91(4): 737-753.
14. Gawiński C, Michalski W, Mróz A, et al. Correlation between lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and tumor-infiltrating lymphocytes (TILs) in left-sided colorectal cancer patients. Biology (Basel), 2022, 11(3): 385. doi: 10.3390/biology11030385.
15. Hassan WA, ElBanna AK, Noufal N, et al. Significance of tumor-associated neutrophils, lymphocytes, and neutrophil-to-lymphocyte ratio in non-invasive and invasive bladder urothelial carcinoma. J Pathol Transl Med, 2023, 57(2): 88-94.
16. Wang Y, Zhai J, Zhang T, et al. Tumor-associated neutrophils can predict lymph node metastasis in early gastric cancer. Front Oncol, 2020, 10: 570113. doi: 10.3389/fonc.2020.570113.
17. Kepp O, Liu P, Zitvogel L, et al. Tumor-infiltrating lymphocytes for melanoma immunotherapy. Oncoimmunology, 2023, 12(1): 2175506. doi: 10.1080/2162402X.2023.2175506.
18. Hong YM, Yoon KT, Hwang TH, et al. Pretreatment peripheral neutrophils, lymphocytes and monocytes predict long-term survival in hepatocellular carcinoma. BMC Cancer, 2020, 20(1): 937. doi: 10.1186/s12885-020-07105-8.
19. Feng F, Zheng G, Wang Q, et al. Low lymphocyte count and high monocyte count predicts poor prognosis of gastric cancer. BMC Gastroenterol, 2018, 18(1): 148. doi: 10.1186/s12876-018-0877-9.
20. Zeng J, Chen G, Zeng J, et al. Development of nomograms to predict outcomes for large hepatocellular carcinoma after liver resection. Hepatol Int, 2025, 19(2): 428-440.
21. Tan J, Yu Y, Lin X, et al. OHCCPredictor: an online risk stratification model for predicting survival duration of older patients with hepatocellular carcinoma. Hepatol Int, 2024, 18(2): 550-567.
22. Kang X, Liu X, Li Y, et al. Development and evaluation of nomograms and risk stratification systems to predict the overall survival and cancer-specific survival of patients with hepatocellular carcinoma. Clin Exp Med, 2024, 24(1): 44. doi: 10.1007/s10238-024-01296-1.
23. Li GC, Yao ZY, Mao HS, et al. Association of triglyceride-glucose index with long-term prognosis in advanced hepatocellular carcinoma patients receiving immunotherapy and targeted therapy. World J Gastroenterol, 2025, 31(30): 109863. doi: 10.3748/wjg.v31.i30.109863.
24. Wang T, Zheng J, Guo L, et al. Use of a pathomics signature to predict the prognosis of hepatocellular carcinoma with cirrhosis: a multicentre retrospective study. Cancers (Basel), 2025, 17(19): 3192. doi: 10.3390/cancers17193192.

CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Prediction model for overall survival after curative resection of hepatocellular carcinoma based on alkaline phosphatase + gamma-glutamyl transpeptidase / platelet: a multicenter study

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