Yang Cheng-Hong, Chen Yin-Syuan, Moi Sin-Hua, Chen Jin-Bor, Wang Lin, Chuang Li-Yeh
Department of Information Management, Tainan University of Technology, Tainan.
Department of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung.
Ther Adv Chronic Dis. 2022 Aug 30;13:20406223221119617. doi: 10.1177/20406223221119617. eCollection 2022.
Mortality is a major primary endpoint for long-term hemodialysis (HD) patients. The clinical status of HD patients generally relies on longitudinal clinical observations such as monthly laboratory examinations and physical examinations.
A total of 829 HD patients who met the inclusion criteria were analyzed. All patients were tracked from January 2009 to December 2013. Taken together, this study performed full-adjusted-Cox proportional hazards (CoxPH), stepwise-CoxPH, random survival forest (RSF)-CoxPH, and whale optimization algorithm (WOA)-CoxPH model for the all-cause mortality risk assessment in HD patients. The model performance between proposed selections of CoxPH models were evaluated using concordance index.
The WOA-CoxPH model obtained the highest concordance index compared with RSF-CoxPH and typical selection CoxPH model. The eight significant parameters obtained from the WOA-CoxPH model, including age, diabetes mellitus (DM), hemoglobin (Hb), albumin, creatinine (Cr), potassium (K), Kt/V, and cardiothoracic ratio, have also showed significant survival difference between low- and high-risk characteristics in single-factor analysis. By integrating the risk characteristics of each single factor, patients who obtained seven or more risk characteristics of eight selected parameters were dichotomized as high-risk subgroup, and remaining is considered as low-risk subgroup. The integrated low- and high-risk subgroup showed greater discrepancy compared with each single risk factor selected by WOA-CoxPH model.
The study findings revealed WOA-CoxPH model could provide better risk assessment performance compared with RSF-CoxPH and typical selection CoxPH model in the HD patients. In summary, patients who had seven or more risk characteristics of eight selected parameters were at potentially increased risk of all-cause mortality in HD population.
死亡率是长期血液透析（HD）患者的主要主要终点。HD患者的临床状况通常依赖于纵向临床观察，如每月的实验室检查和体格检查。
对829例符合纳入标准的HD患者进行分析。所有患者从2009年1月至2013年12月进行跟踪。本研究共进行了全调整Cox比例风险（CoxPH）、逐步CoxPH、随机生存森林（RSF）-CoxPH和鲸鱼优化算法（WOA）-CoxPH模型，用于评估HD患者的全因死亡风险。使用一致性指数评估所提出的CoxPH模型选择之间的模型性能。
与RSF-CoxPH和典型选择的CoxPH模型相比，WOA-CoxPH模型获得了最高的一致性指数。从WOA-CoxPH模型获得的八个显著参数，包括年龄、糖尿病（DM）、血红蛋白（Hb）、白蛋白、肌酐（Cr）、钾（K）、Kt/V和心胸比，在单因素分析中也显示出低风险和高风险特征之间的显著生存差异。通过整合每个单因素的风险特征，将获得八个选定参数中七个或更多风险特征的患者分为高风险亚组，其余患者视为低风险亚组。与WOA-CoxPH模型选择的每个单一风险因素相比，整合后的低风险和高风险亚组显示出更大的差异。
研究结果表明，与RSF-CoxPH和典型选择的CoxPH模型相比，WOA-CoxPH模型在HD患者中可以提供更好的风险评估性能。总之，在HD人群中，具有八个选定参数中七个或更多风险特征的患者全因死亡风险可能增加。
