Nomogram for Predicting Efficacy and Prognosis After Chemotherapy for Advanced NSCLC

IF 1.9 4区 医学 Q3 RESPIRATORY SYSTEM
Jiaying Gao, Yandong Nan, Gang Liu, Shihong Zhao, Huanqing Xiong, Yifeng Wang, Faguang Jin
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Abstract

Purpose

One major issue is the therapeutic effect following chemotherapy for non–small cell lung cancer (NSCLC). Although numerous risk factors have been identified and novel therapies have been developed, improving patient overall survival (OS) remains a crucial postoperative issue. This study aimed to develop a nomogram for accurately predicting the OS of patients with Stage III–IV NSCLC treated with chemotherapy.

Methods

The Department of Respiration at Tangdu Hospital, Air Force Medical University, prospectively collected data on 321 patients between January 2018 and December 2023. A week before treatment, the platelet-to-lymphocyte ratio (PLR), the neutrophil-to-lymphocyte ratio (NLR), and seven autoantibodies were measured using Youden's index, which was obtained using the ROC curve. The formula was used to compute the values of PLR and NLR. After using multifactor Cox regression analysis to identify risk factors, a nomogram was produced regarding the therapeutic effect following chemotherapy. The performance of the nomogram was assessed using a bootstrapped-concordance index and calibration plots.

Result

It was determined that NLR, sex-determining region Y-box 2 (SOX2), adenosine triphosphate binding RNA deconjugase 4–5 (GBU4-5), and MAGE family member A1 (MAGEA1) were significantly associated factors that could be combined to accurately predict the therapeutic effect following chemotherapy. Utilizing these risk indicators, we were able to develop a nomogram that predicted the patients' survival at 1, 3, and 5 years. At 3 years, the area under the curve representing the expected survival probability was 0.762 (95% confidence interval 0.66–0.87). With a bootstrapped-concordance index of 0.762, the nomogram demonstrated good calibration.

Conclusions

Our nomogram proved to be a valuable instrument in accurately predicting the overall survival of patients.

Abstract Image

预测晚期 NSCLC 化疗后疗效和预后的提名图
目的:一个主要问题是非小细胞肺癌(NSCLC)化疗后的治疗效果。虽然已经发现了许多风险因素,并开发出了新型疗法,但提高患者的总生存率(OS)仍是术后的一个关键问题。本研究旨在开发一种提名图,用于准确预测接受化疗的III-IV期NSCLC患者的OS:空军军医大学唐都医院呼吸科前瞻性地收集了2018年1月至2023年12月期间321名患者的数据。治疗前一周,采用尤登指数(Youden's index)测定血小板与淋巴细胞比值(PLR)、中性粒细胞与淋巴细胞比值(NLR)以及七种自身抗体,利用ROC曲线得出。该公式用于计算 PLR 和 NLR 的值。在使用多因素考克斯回归分析确定风险因素后,生成了化疗后疗效的提名图。使用自引导一致性指数和校准图评估了提名图的性能:结果:NLR、性别决定区Y-盒2(SOX2)、三磷酸腺苷结合RNA解拮抗剂4-5(GBU4-5)和MAGE家族成员A1(MAGEA1)被确定为显著相关的因素,这些因素结合在一起可准确预测化疗后的疗效。利用这些风险指标,我们绘制出了预测患者 1 年、3 年和 5 年生存率的提名图。在 3 年时,代表预期生存概率的曲线下面积为 0.762(95% 置信区间为 0.66-0.87)。自引导一致性指数为 0.762,表明提名图具有良好的校准性:我们的提名图被证明是准确预测患者总生存期的重要工具。
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来源期刊
Clinical Respiratory Journal
Clinical Respiratory Journal 医学-呼吸系统
CiteScore
3.70
自引率
0.00%
发文量
104
审稿时长
>12 weeks
期刊介绍: Overview Effective with the 2016 volume, this journal will be published in an online-only format. Aims and Scope The Clinical Respiratory Journal (CRJ) provides a forum for clinical research in all areas of respiratory medicine from clinical lung disease to basic research relevant to the clinic. We publish original research, review articles, case studies, editorials and book reviews in all areas of clinical lung disease including: Asthma Allergy COPD Non-invasive ventilation Sleep related breathing disorders Interstitial lung diseases Lung cancer Clinical genetics Rhinitis Airway and lung infection Epidemiology Pediatrics CRJ provides a fast-track service for selected Phase II and Phase III trial studies. Keywords Clinical Respiratory Journal, respiratory, pulmonary, medicine, clinical, lung disease, Abstracting and Indexing Information Academic Search (EBSCO Publishing) Academic Search Alumni Edition (EBSCO Publishing) Embase (Elsevier) Health & Medical Collection (ProQuest) Health Research Premium Collection (ProQuest) HEED: Health Economic Evaluations Database (Wiley-Blackwell) Hospital Premium Collection (ProQuest) Journal Citation Reports/Science Edition (Clarivate Analytics) MEDLINE/PubMed (NLM) ProQuest Central (ProQuest) Science Citation Index Expanded (Clarivate Analytics) SCOPUS (Elsevier)
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