Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, United States of America; Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH, United States of America.
Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, United States of America; Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, OH, United States of America.
J Geriatr Oncol. 2022 Nov;13(8):1244-1252. doi: 10.1016/j.jgo.2022.06.011. Epub 2022 Jul 1.
The high prevalence of multiple chronic conditions (MCC), multimorbidity, and frailty may affect treatment and outcomes for older adults with cancer. The goal of this study was to use three conceptually distinct measures of morbidity to examine the association between these measures and mortality.
Using Medicare claims data linked with the 2012-2016 Ohio Cancer Incidence Surveillance System we identified older adults with incident primary cancer sites of breast, colorectal, lung, or prostate (n = 29,140). We used claims data to identify their Elixhauser comorbidities, Multimorbidity-Weighted Index (MWI), and Claims Frailty Index (CFI) as measures of MCC, multimorbidity, and frailty, respectively. We used Cox proportional hazard models to examine the association between these measures and survival time since diagnosis.
Lung cancer patients had the highest levels of MCC, multimorbidity, and frailty. There was a positive association between all three measures and a greater hazard of death after adjusting for age, sex (colorectal and lung only), and stage. Breast cancer patients with 5+ comorbidities had an adjusted hazard ratio (aHR) of 1.63 (95% confidence interval [CI]: 1.38, 1.93), and those with mild frailty had an aHR of 3.38 (95% CI; 2.12, 5.41). The C statistics for breast cancer were 0.79, 0.78, and 0.79 for the MCC, MWI, and CFI respectively. Similarly, lung cancer patients who were moderately or severely frail had an aHR of 1.82 (95% CI: 1.53, 2.18) while prostate cancer patients had an aHR of 3.39 (95% CI: 2.12, 5.41) and colorectal cancer patients had an aHR of 4.51 (95% CI: 3.23, 6.29). Model performance was nearly identical across the MCC, multimorbidity, and frailty models within cancer type. The models performed best for prostate and breast cancer, and notably worse for lung cancer. The frailty models showed the greatest separation in unadjusted survival curves.
The MCC, multimorbidity, and frailty indices performed similarly well in predicting mortality among a large cohort of older cancer patients. However, there were notable differences by cancer type. This work highlights that although model performance is similar, frailty may serve as a clearer indicator in risk stratification of geriatric oncology patients than simple MCCs or multimorbidity.
多种慢性疾病（MCC）、多种合并症和虚弱的高发率可能会影响老年癌症患者的治疗和预后。本研究的目的是使用三种概念上不同的发病率衡量标准来检查这些衡量标准与死亡率之间的关联。
使用医疗保险索赔数据与 2012-2016 年俄亥俄州癌症发病率监测系统相关联，我们确定了患有乳腺癌、结直肠癌、肺癌或前列腺癌的初发癌症部位的老年人（n=29,140）。我们使用索赔数据来确定他们的 Elixhauser 合并症、多重合并症加权指数（MWI）和索赔虚弱指数（CFI），分别作为 MCC、多种合并症和虚弱的衡量标准。我们使用 Cox 比例风险模型来检查这些措施与诊断后生存时间之间的关联。
肺癌患者的 MCC、多种合并症和虚弱程度最高。在调整年龄、性别（仅结直肠癌和肺癌）和阶段后，所有三种措施与死亡风险增加呈正相关。患有 5 种以上合并症的乳腺癌患者的调整后危险比（aHR）为 1.63（95%置信区间[CI]：1.38，1.93），患有轻度虚弱的患者的 aHR 为 3.38（95% CI；2.12，5.41）。乳腺癌的 C 统计量分别为 MCC、MWI 和 CFI 的 0.79、0.78 和 0.79。同样，中度或重度虚弱的肺癌患者的 aHR 为 1.82（95% CI：1.53，2.18），而前列腺癌患者的 aHR 为 3.39（95% CI：1.53，2.18），结直肠癌患者的 aHR 为 4.51（95% CI：3.23，6.29）。在癌症类型内，MCC、多种合并症和虚弱模型的模型性能几乎相同。该模型在前列腺癌和乳腺癌中的性能最好，而在肺癌中的性能明显更差。虚弱模型在未经调整的生存曲线中显示出最大的分离。
在一个大型老年癌症患者队列中，MCC、多种合并症和虚弱指数在预测死亡率方面表现相似。然而，癌症类型之间存在显著差异。这项工作强调，尽管模型性能相似，但在老年肿瘤患者的风险分层中，虚弱可能比简单的 MCC 或多种合并症更能清晰地指示。
