Construction of predictive model for programmed death-1 inhibitor-related endocrine adverse events
10.12025/j.issn.1008-6358.2025.20250533
- VernacularTitle:程序性死亡受体1抑制剂相关内分泌不良反应预测模型构建
- Author:
Jiaying SHI
1
;
Wei WEI
2
;
Ting HAN
3
;
Xiao ZHOU
4
;
Meng ZHUO
3
;
Xiaolin LIN
3
;
Tao TAO
5
;
Xiuying XIAO
3
Author Information
1. School of Clinical Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China.
2. Department of Endocrinology, Ningbo Hangzhou Bay Hospital, Ningbo 315000, Zhejiang, China.
3. Department of Oncology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China.
4. Department of Oncology, Ningbo Hangzhou Bay Hospital, Ningbo 315000, Zhejiang, China.
5. Department of Endocrinology and Metabolism, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai200127, China.
- Publication Type:Monographicreport:Diagnosisandtreatmentoftumorimmunotherapy-relatedendocrinecomplications
- Keywords:
immune checkpoint inhibitor;
immune-related adverse event;
endocrine;
predictive model
- From:
Chinese Journal of Clinical Medicine
2025;32(4):551-560
- CountryChina
- Language:Chinese
-
Abstract:
Objective To identify the independent predictors of programmed death-1 (PD-1) inhibitor-related endocrine adverse events and construct a clinically usable risk prediction model. Methods A total of 302 patients with solid tumors treated with PD-1 inhibitors were retrospectively enrolled. According to the presence or absence of endocrine immune-related adverse events (irAEs), the patients were divided into case group and control group. The clinical and laboratory indexes were compared between the two groups. Multivariable logistic regression was used to confirm independent predictors of endocrine irAEs. The nomogram was constructed, while the receiver operating characteristic (ROC) curve was used to test the prediction performance of the model. Results The overall incidence of endocrine irAEs was 21.9% (66/302), and the incidence of hypothyroidism was 19.5% (59/302). The age, PD-1 inhibitors, free thyroxine, thyroid peroxidase antibody (TPOAb), thyroglobulin, amylase, lymphocyte subset CD3 expression were statistically different between the two groups (P＜0.05). Multivariable logistic regression showed that higher expression of lymphocyte subset CD3 was a protective factor to prevent endocrine irAEs occurrence (P＝0.004), while age＜60 years, higher TPOAb and use of pembrolizumab were independent risk factors of endocrine irAEs (P＜0.05). The nomogram model thus constructed, and when the threshold probability of the model exceeded 0.1, its net benefit was higher. ROC curve showed that the AUC of the model to predict endocrine irAEs was 0.760. The prediction result of the model was highly consistent with the actual result. Conclusions The age, type of PD-1 inhibitor, baseline TPOAb level, and baseline CD3 expression can independently predict endocrine irAEs occurrence or not. The nomogram model based on this model has good predictive efficiency, which can provide reference for early identification of high-risk patients and immunotherapy management.
