Creating a Proxy for Baseline Eastern Cooperative Oncology Group Performance Status in Electronic Health Records for Comparative Effectiveness Research in Advanced Non-Small Cell Lung Cancer.

IF 2.8 Q2 ONCOLOGY
JCO Clinical Cancer Informatics Pub Date : 2025-04-01 Epub Date: 2025-04-03 DOI:10.1200/CCI-24-00185
Michael Johnson, Peining Tao, Mehmet Burcu, John Kang, Richard Baumgartner, Junshui Ma, Vladimir Svetnik
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引用次数: 0

Abstract

Purpose: Eastern Cooperative Oncology Group performance status (ECOG PS) is a key confounder in comparative effectiveness research, predicting treatment and survival, but is often incomplete in electronic health records (EHRs). Imputation on the basis of classification metrics alone may introduce differences in survival between patients with known and imputed ECOG PS, complicating comparative effectiveness research. We developed an approach to impute ECOG PS so that those with known and imputed ECOG PS are indistinguishable in their survival, reducing potential biases introduced by the imputation.

Methods: We analyzed deidentified data from an EHR-derived database for patients with advanced non-small cell lung cancer (aNSCLC) at their first line of treatment. Our novel imputation method involved (1) sample-splitting patients with known ECOG PS into modeling and thresholding data sets, (2) developing a predictive model of ECOG PS, (3) determining an optimal threshold aligning clinical outcomes, where a choice of outcome metric may depend on the use case, and (4) applying the model and threshold to impute missing ECOG PS. We evaluated the approach using binary classification metrics and alignment of survival metrics between observed and imputed ECOG PS.

Results: Of 62,101 patients, 13,297 (21%) had missing ECOG PS at the start of their first treatment. Our method achieved similar or better performance in accuracy (73.3%), sensitivity (42.4%), and specificity (81%) compared with other techniques, with smaller survival metric differences between observed and imputed ECOG PS, with differences of 0.07 in hazard ratio, -0.36 months in median survival for good ECOG PS (<2), and -0.39 months for poor ECOG PS (≥2).

Conclusion: Our imputed ECOG PS aligning clinical outcomes enhanced the use of real-world EHR data of patients with aNSCLC for comparative effectiveness research.

为晚期非小细胞肺癌的比较有效性研究在电子健康记录中创建东部合作肿瘤组绩效状态基线代理。
目的:东部肿瘤合作小组绩效状况(ECOG PS)是比较有效性研究、预测治疗和生存的关键混杂因素,但在电子健康记录(EHRs)中往往不完整。仅基于分类指标的输入可能会导致已知和输入ECOG PS患者之间的生存差异,使比较有效性研究复杂化。我们开发了一种方法来推算ECOG PS,使已知ECOG PS和推算ECOG PS的人在生存中无法区分,减少了推算带来的潜在偏差。方法:我们分析了来自ehr衍生数据库的晚期非小细胞肺癌(aNSCLC)患者在一线治疗中的未识别数据。我们的新方法包括(1)将已知ECOG PS的患者样本分成建模和阈值数据集,(2)开发ECOG PS的预测模型,(3)确定符合临床结果的最佳阈值,其中结果度量的选择可能取决于用例。(4)应用模型和阈值来计算缺失的ECOG PS。我们使用二元分类指标和观察到的ECOG PS与输入的ECOG PS之间的生存指标的一致性来评估该方法。结果:62,101例患者中,13,297例(21%)在首次治疗开始时缺失ECOG PS。与其他技术相比,我们的方法在准确性(73.3%)、敏感性(42.4%)和特异性(81%)方面取得了类似或更好的表现,观察到的ECOG PS与输入的ECOG PS之间的生存指标差异较小,风险比差异为0.07,良好ECOG PS的中位生存期为-0.36个月(结论:我们输入的ECOG PS与临床结果一致,增强了aNSCLC患者真实世界电子健康记录数据的使用,用于比较有效性研究。
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
CiteScore
6.20
自引率
4.80%
发文量
190
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