Establishment and Validation of a Survival Benefit Prediction Model for Non-small Cell Lung Cancer after Immunotherapy.

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-10-01

Rui Duan, Hao Li, Jie Yang, Yong Xin

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引用次数: 0

Abstract

Objective: This study aimed to analyze the prognosis of patients with non-small cell lung cancer (NSCLC) after receiving immunotherapy and construct a prediction model to evaluate the overall survival rate of patients.

Methods: This study was a retrospective study that collected data from 493 NSCLC patients who received immunotherapy for the first time. Survival data were analyzed using Cox regression models and the Kaplan-Meier method. The average age of patients was 56 years, and the data collection process included regular outpatient follow-up and observation of overall survival (OS) in the last 36 months.

Results: Multivariate analysis identified significant risk factors such as smoking history, age, T stage, and M stage on survival and disease progression. The model's performance indicators (C-index and AUC) and calibration curve verified the model's accuracy and predictive ability. In the training set, the AUCs of 3-year and 5-year survival were 0.761 and 0.763, respectively, and in the validation set, they were 0.739 and 0.761.

Conclusion: This study developed a prediction model for evaluating the survival of NSCLC patients after immunotherapy that integrates multiple influencing factors. This predictive model can be used as a tool to assess individual risks in NSCLC patients after immunotherapy, helping clinicians to develop more precise treatment and follow-up plans, potentially improving patient outcomes.

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非小细胞肺癌免疫疗法后生存获益预测模型的建立与验证

研究目的本研究旨在分析非小细胞肺癌（NSCLC）患者接受免疫治疗后的预后，并构建一个预测模型来评估患者的总生存率：本研究是一项回顾性研究，收集了493名首次接受免疫疗法的非小细胞肺癌患者的数据。研究采用Cox回归模型和Kaplan-Meier法对生存数据进行了分析。患者平均年龄为56岁，数据收集过程包括定期门诊随访和观察过去36个月的总生存期（OS）：多变量分析确定了吸烟史、年龄、T期和M期等对生存率和疾病进展有显著影响的风险因素。模型的性能指标（C-指数和AUC）和校正曲线验证了模型的准确性和预测能力。在训练集中，3年和5年生存率的AUC分别为0.761和0.763，在验证集中，分别为0.739和0.761：本研究建立了一个评估免疫治疗后NSCLC患者生存率的预测模型，该模型综合了多种影响因素。该预测模型可作为评估免疫治疗后NSCLC患者个体风险的工具，帮助临床医生制定更精确的治疗和随访计划，从而改善患者的预后。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.