Comparing survival of older ovarian cancer patients treated with neoadjuvant chemotherapy versus primary cytoreductive surgery: Reducing bias through machine learning.
Comparing survival of older ovarian cancer patients treated with neoadjuvant chemotherapy versus primary cytoreductive surgery: Reducing bias through machine learning.
复制标题
比较接受新辅助化疗与初次细胞减灭术治疗的老年卵巢癌患者的生存率：通过机器学习减少偏差。
DOI：
10.1016/j.ygyno.2024.03.016
复制
发表时间：
2024
影响因子：
4.7
通讯作者：
Melamed,Alexander
中科院分区：
文献类型：
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作者：
Huang,Yongmei;Rauh-Hain,JAlejandro;McCoy,ThomasH;Hou,JuneY;Hillyer,Grace;Ferris,JenniferS;Hershman,Dawn;Wright,JasonD;Melamed,Alexander
ObjectiveDeveloping and evaluate a multidimensional comorbidity index（MCI）that identifies ovarian cancer patients at risk of early mortality more accurately than the Charlson Comorbidity Index（CCI）for use in health services research.MethodsWe utilized SEER-Medicare data to identify patients with stage IIIC and IV ovarian cancer，diagnosed in 2010-2015.我们采用偏最小二乘回归（一种有监督的机器学习算法）通过提取潜在因素来开发MCI，这些因素最佳地捕捉了癌症诊断前一年健康保险索赔的变化和1年死亡率。我们评估了MCI对1年死亡率的区分和校准，并将其性能与常用的CCI进行了比较。最后，我们评估了MCI的能力，以减少新辅助化疗（NACT）和全因mortality.ResultsWe包括4723例患者在开发队列和933在验证队列的关联混淆。MCI对1年死亡率具有良好的区分度（c指数：0.75，95% CI：0.72-0.79），而CCI的区分度较差（c指数：0.59，95% CI：0.56-0.63）。校准图显示MCI与CCI相比，预测和观察到的1年死亡率风险之间的一致性更好。当比较NACT与初次肿瘤细胞减灭术之间的全因死亡率时，在控制肿瘤特征、人口统计学因素和CCI后，NACT与较高的死亡风险相关（HR：1.13，95%CI：1.04-1.23）。然而，当控制MCI而不是CCI时，不再存在显着差异（HR：1.05，95%CI：0.96-1.14）。结论在NACT与初次手术的比较有效性分析中，MCI在预测1年死亡率方面优于传统CCI，并减少了由于基线健康状况差异而产生的混淆。
ObjectiveTo develop and evaluate a multidimensional comorbidity index (MCI) that identifies ovarian cancer patients at risk of early mortality more accurately than the Charlson Comorbidity Index (CCI) for use in health services research.MethodsWe utilized SEER-Medicare data to identify patients with stage IIIC and IV ovarian cancer, diagnosed in 2010–2015. We employed partial least squares regression, a supervised machine learning algorithm, to develop the MCI by extracting latent factors that optimally captured the variation in health insurance claims made in the year preceding cancer diagnosis, and 1-year mortality. We assessed the discrimination and calibration of the MCI for 1-year mortality and compared its performance to the commonly-used CCI. Finally, we evaluated the MCI's ability to reduce confounding in the association of neoadjuvant chemotherapy (NACT) and all-cause mortality.ResultsWe included 4723 patients in the development cohort and 933 in the validation cohort. The MCI demonstrated good discrimination for 1-year mortality (c-index: 0.75, 95% CI: 0.72–0.79), while the CCI had poor discrimination (c-index: 0.59, 95% CI: 0.56–0.63). Calibration plots showed better agreement between predicted and observed 1-year mortality risk for the MCI compared with CCI. When comparing all-cause mortality between NACT with primary cytoreductive surgery, NACT was associated with a higher hazard of death (HR: 1.13, 95% CI: 1.04–1.23) after controlling for tumor characteristics, demographic factors, and the CCI. However, when controlling for the MCI instead of the CCI, there was no longer a significant difference (HR: 1.05, 95% CI: 0.96–1.14).ConclusionsThe MCI outperformed the conventional CCI in predicting 1-year mortality, and reducing confounding due to differences in baseline health status in comparative effectiveness analysis of NACT versus primary surgery.