Peng WT, Yang FL, Peng SF, Fu L. Real-world predictive model for immune checkpoint inhibitor-induced hepatitis using baseline cytotoxic T-lymphocyte counts. World J Gastroenterol 2026; 32(47): 121501 [DOI: 10.3748/wjg.121501]
Corresponding Author of This Article
Lei Fu, PhD, Professor, Department of Infectious Diseases, Xiangya Hospital Central South University, No. 87 Xiangya Road, Changsha 410008, Hunan Province, China. fulei92@126.com
Research Domain of This Article
Gastroenterology & Hepatology
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research-article
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Peng WT, Yang FL, Peng SF, Fu L. Real-world predictive model for immune checkpoint inhibitor-induced hepatitis using baseline cytotoxic T-lymphocyte counts. World J Gastroenterol 2026; 32(47): 121501 [DOI: 10.3748/wjg.121501]
World J Gastroenterol. Dec 21, 2026; 32(47): 121501 Published online Dec 21, 2026. doi: 10.3748/wjg.121501
Real-world predictive model for immune checkpoint inhibitor-induced hepatitis using baseline cytotoxic T-lymphocyte counts
Wen-Ting Peng, Fei-Lan Yang, Shi-Fang Peng, Lei Fu
Wen-Ting Peng, Fei-Lan Yang, Shi-Fang Peng, Lei Fu, Department of Infectious Diseases, Xiangya Hospital Central South University, Changsha 410008, Hunan Province, China
Author contributions: Fu L designed the research and supervised the study; Peng WT and Yang FL collected the clinical data; Peng WT performed the experiments and wrote the manuscript; Peng SF assisted in compiling data; all authors critically reviewed the final manuscript.
AI contribution statement: The main manuscript was written without the use of any AI tools. An AI-assisted language tool (DeepSeek) was used solely in the preparation of the response letter to reviewers for language polishing. All scientific content is the sole responsibility of the authors.
Supported by the National Natural Science Foundation of China, No. 82570747; and the Provincial Natural Science Foundation of Hunan Province, No. 2022JJ30954 and No. 2025JJ50599.
Institutional review board statement: This study was reviewed and approved by the Ethics Committee of the Xiangya Hospital Central South University (No. 2026010119).
Informed consent statement: The study is a retrospective study that will maximize the protection of the rights and privacy of the study participants, and the content of the study and the results of the study do not involve personal privacy and commercial interests, exempt from informed consent.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
Data sharing statement: No additional data are available.
Corresponding author: Lei Fu, PhD, Professor, Department of Infectious Diseases, Xiangya Hospital Central South University, No. 87 Xiangya Road, Changsha 410008, Hunan Province, China. fulei92@126.com
Received: March 26, 2026 Revised: April 26, 2026 Accepted: June 9, 2026 Published online: December 21, 2026 Processing time: 215 Days and 18.6 Hours
Abstract
BACKGROUND
Although immune checkpoint inhibitors (ICIs) can trigger immune-mediated hepatitis (IMH) in individuals with cancer, there remains a lack of dependable predictors for this complication.
AIM
To identify risk factors and construct a predictive model for IMH induced by ICIs.
METHODS
A total of 544 individuals with cancer who underwent ICIs treatment at Xiangya Hospital Central South University between January 2019 and June 2024 were enrolled in this retrospective analysis. Using a 7:3 split, the cohort was randomly allocated to a training group (n = 380) and a validation group (n = 164). Univariate and multivariate logistic regression analyses were conducted to identify independent risk factors for IMH, which were then used to construct a nomogram. Model performance was evaluated based on the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis.
RESULTS
Multivariate analysis identified three independent predictors: Elevated baseline alanine transaminase (ALT) [odds ratio (OR) = 1.04, 95% confidence interval (CI): 1.01-1.06, P = 0.028], increased cluster of differentiation (CD) 3+ CD8+ T cell counts (OR = 1.01, 95%CI: 1.01-1.02, P = 0.002), and lower complement 4 levels (OR = 0.99, 95%CI: 0.97-1.00, P = 0.038). The nomogram incorporating these factors achieved an AUC of 0.81 (95%CI: 0.74-0.88) in the training set and 0.80 (95%CI: 0.70-0.90) in the validation set.
CONCLUSION
Baseline CD3+ CD8+ T cell counts, ALT, and complement 4 independently predict IMH. The nomogram provides a clinically useful tool for pre-treatment risk stratification.
Core Tip: This retrospective study of 544 cancer patients receiving immune checkpoint inhibitors identifies baseline peripheral cluster of differentiation (CD) 3+ CD8+ T cell counts as a novel independent predictor of immune-mediated hepatitis. Integrating this immune parameter with alanine transaminase and complement 4, the authors constructed a nomogram that achieved good discriminatory performance (area under the curve 0.81 in training and 0.80 in validation). This model provides a clinically accessible tool for pre-treatment risk stratification.
