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基于电子健康记录的衰弱指标对老年非小细胞肺癌患者全因死亡率的预后价值。

Prognostic value of electronic health records-based frailty measures for all-cause mortality in older patients with non-small cell lung cancer.

作者信息

Tu Minh-Thao, Tran Thi-Ngoc, Kwon Hoejun, Choi Yoon-Jung, Lee Youngjoo, Cho Hyunsoon

机构信息

Department of Cancer AI and Digital Health, National Cancer Center Graduate School of Cancer Science and Policy, Goyang, Republic of Korea.

Department of Cancer Control and Population Health, National Cancer Center Graduate School of Cancer Science and Policy, Goyang, Republic of Korea.

出版信息

J Geriatr Oncol. 2025 Jan;16(1):102130. doi: 10.1016/j.jgo.2024.102130. Epub 2024 Oct 23.

Abstract

INTRODUCTION

Frailty screening is important to guide treatment decisions for older patients with non-small cell lung cancer (NSCLC). However, the performance of frailty measures (FMs) remains unclear. This study aimed to evaluate the prognostic value of FMs based on electronic health records (EHR) data in clinical settings for all-cause mortality in older patients with NSCLC.

MATERIALS AND METHODS

We retrospectively analyzed 4253 patients aged ≥65 years, newly diagnosed with NSCLC (2007-2018) using EHR data from the National Cancer Center, Korea. Frailty was measured by either laboratory tests (frailty index based on routine laboratory tests [FI-Lab]), comorbidities and performance status (electronic Frailty index [eFI]), or both (combined frailty index [FI-combined]). Patients were categorized as frail or non-frail. Cox proportional hazards models and C-index were used to estimate the predictive ability of FMs for all-cause mortality in 1 year, 3 years, and 5 years post-diagnosis, adjusting for age, sex, and SEER stage.

RESULTS

EHR-based FMs could enhance the prognostic ability to predict the survival of older patients with NSCLC. In the total population, FI-Lab showed the largest predictive value, especially for 1-year mortality with an adjusted hazard ratio for frail vs. non-frail groups of 2.25 (95 % CI 2.02-2.51) and C-index of 0.74 compared to 0.72 in the base model (p-value<0.001). FI-Lab could improve the prognostic ability for 1-year mortality in patients with regional and distant SEER stages and those receiving systemic therapy, whereas FI-combined could improve the prediction of 3-year and 5-year mortality in patients with localized disease and receiving surgery.

DISCUSSION

Easy-to-use FMs derived from EHR data can enhance the prediction of all-cause mortality in older patients with NSCLC. Oncologists can utilize comprehensive FMs comprising comorbidities, functional status, and subclinical tests or FI-Lab, depending on the patient's medical condition, to facilitate shared cancer care planning.

摘要

引言

虚弱筛查对于指导老年非小细胞肺癌(NSCLC)患者的治疗决策非常重要。然而,虚弱测量方法(FMs)的性能仍不明确。本研究旨在评估基于电子健康记录(EHR)数据的FMs在临床环境中对老年NSCLC患者全因死亡率的预后价值。

材料与方法

我们使用韩国国家癌症中心的EHR数据,回顾性分析了4253例年龄≥65岁、新诊断为NSCLC(2007 - 2018年)的患者。通过实验室检查(基于常规实验室检查的虚弱指数[FI-Lab])、合并症和体能状态(电子虚弱指数[eFI])或两者结合(联合虚弱指数[FI-combined])来测量虚弱程度。患者被分为虚弱或非虚弱组。使用Cox比例风险模型和C指数来估计FMs对诊断后1年、3年和5年全因死亡率的预测能力,并对年龄、性别和SEER分期进行调整。

结果

基于EHR的FMs可以提高预测老年NSCLC患者生存的预后能力。在总体人群中,FI-Lab显示出最大的预测价值,尤其是对于1年死亡率,虚弱组与非虚弱组的调整后风险比为2.25(95%CI 2.02 - 2.51),C指数为0.74,而基础模型中的C指数为0.72(p值<0.001)。FI-Lab可以提高区域和远处SEER分期患者以及接受全身治疗患者1年死亡率的预后能力,而FI-combined可以提高局限性疾病且接受手术患者3年和5年死亡率的预测能力。

讨论

从EHR数据中得出的易于使用的FMs可以提高对老年NSCLC患者全因死亡率的预测。肿瘤学家可以根据患者的病情,利用包括合并症、功能状态和亚临床检查或FI-Lab的综合FMs,以促进共同的癌症护理计划。

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