Risk factors and model construction of immune therapy-related thyroid dysfunction in non-small cell lung cancer
10.3969/j.issn.1006-5725.2025.17.014
- VernacularTitle:非小细胞肺癌免疫治疗相关甲状腺功能障碍的危险因素分析及模型构建
- Author:
Lingchun CAO
1
;
Fanliang MENG
;
Xiaoan SHENG
Author Information
1. 安徽医科大学附属巢湖医院呼吸内科(安徽巢湖 238000)
- Publication Type:Journal Article
- Keywords:
non-small cell lung cancer;
immunotherapy;
thyroid dysfunction;
nomogram
- From:
The Journal of Practical Medicine
2025;41(17):2705-2714
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the related risk factors for thyroid dysfunction(irTD)after immuno-therapy in patients with non-small cell lung cancer(NSCLC)and to construct a predictive model.Methods A retrospective analysis was conducted on 197 NSCLC patients who received immunotherapy at Chaohu Hospital,Anhui Medical University between January 2019 and June 2024.The patients were divided into a training set(n=137)and a validation set(n=60)in a 7∶3 ratio.Risk factors were screened through Lasso and logistic regression,and a dynamic nomogram model was constructed.The model's performance was evaluated using ROC curve,calibration curve,decision curve analysis(DCA),and clinical impact curve(CIC).Results Multivariate analysis showed that Gender(OR=0.172,95%CI:0.047～0.623),M stage(OR=2.919,95%CI:1.063～8.015),ln(SII)(OR=0.167,95%CI:0.066～0.423),ALC(OR=3.395,95%CI:1.493～7.716),and TSH(OR=1.464,95%CI:1.126～1.904)were independent risk factors for the occurrence of irTD.The model formula based on these factors is:logit(P)=9.261-1.760×Gender+1.071×M stage-1.787×ln(SII)+1.222×ALC+0.381×TSH.The model achieved an AUC of 0.832(95%CI:0.719～0.945)in the validation set,which was similar to the results in the training set.The calibration curve demonstrated good consistency between the predicted probability and actual observed values.DCA and CIC confirmed that the model has good clinical applicability.Conclusion This study identifies key risk factors for the occurrence of irTD after immunotherapy in NSCLC patients.The dynamic nomogram model developed(web calculator:https://lingchun.shinyapps.io/dynnomapp/)can effectively identify high-risk populations for irTD,providing a reliable tool for clinical decision-making.
