Abstract

Musculoskeletal toxicity is a typical side effect of daptomycin (DAP). However, the risk factors have not been well established. Here, we aimed to identify independent factors affecting DAP-induced musculoskeletal toxicity using a combination of machine learning and conventional statistical methods. A population-based, retrospective, observational cohort study was conducted using the Japanese electronic medical record database. Patients who received DAP between October 2011 and December 2020 were enrolled. Two definitions of musculoskeletal toxicity were employed: (1) elevation of creatine phosphokinase (CPK) value more than twice from baseline and >200 IU/L, and (2) >1000 IU/L. First, multiple logistic regression analyses (a conventional statistical method) were performed to identify independent factors affecting CPK elevation. Then, decision tree analyses, a machine learning method, were performed to detect combinations of factors that change CPK elevation risk. Of the 2970 patients who received DAP, 706 were included. Elevation of CPK values >200 IU/L and >1000 IU/L occurred in 83 (11.8%) and 17 (2.41%) patients, respectively. In multiple logistic regression analysis, baseline CPK value and concomitant use of hydrophobic statins were commonly extracted as independent factors affecting each CPK elevation, but concomitant use of hydrophilic statins was not. In decision tree analysis, patients who received hydrophobic statins and had high baseline CPK values were classified into the high-risk group. Our novel approach revealed new risk factors for CPK elevation. Our findings suggest that high-risk patients require frequent CPK monitoring.

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