Personalized glucose-lowering effect of chiglitazar in type 2 diabetes
Qi Huang,
Xiantong Zou,
Yingli Chen,
Leili Gao,
Xiaoling Cai,
Lingli Zhou,
Fei Gao,
Jian Zhou,
Weiping Jia,
Linong Ji
Affiliations
Qi Huang
Department of Endocrinology and Metabolism, Peking University People’s Hospital, Beijing 100044, China
Xiantong Zou
Department of Endocrinology and Metabolism, Peking University People’s Hospital, Beijing 100044, China
Yingli Chen
Department of Endocrinology and Metabolism, Peking University People’s Hospital, Beijing 100044, China
Leili Gao
Department of Endocrinology and Metabolism, Peking University People’s Hospital, Beijing 100044, China
Xiaoling Cai
Department of Endocrinology and Metabolism, Peking University People’s Hospital, Beijing 100044, China
Lingli Zhou
Department of Endocrinology and Metabolism, Peking University People’s Hospital, Beijing 100044, China
Fei Gao
Department of Endocrinology and Metabolism, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China
Jian Zhou
Department of Endocrinology and Metabolism, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China
Weiping Jia
Department of Endocrinology and Metabolism, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China; Corresponding author
Linong Ji
Department of Endocrinology and Metabolism, Peking University People’s Hospital, Beijing 100044, China; Corresponding author
Summary: Chiglitazar (carfloglitazar) is a peroxisome proliferator-activated receptor pan-agonist presenting non-inferior glucose-lowering efficacy with sitagliptin in patients with type 2 diabetes. To delineate the subgroup of patients with greater benefit from chiglitazar, we conducted a machine learning-based post-hoc analysis in two randomized controlled trials. We established a character phenomap based on 13 variables and estimated HbA1c decline to the effects of chiglitazar in reference to sitagliptin. Out of 1,069 patients, 63.3% were found to have greater reduction in HbA1c levels with chiglitazar, while 36.7% showed greater reduction with sitagliptin. This distinction in treatment response was statistically significant between groups (pinteraction<0.001). To identify patients who would gain the most glycemic control benefit from chiglitazar, we developed a machine learning model, ML-PANPPAR, which demonstrated robust performance using sex, BMI, HbA1c, HDL, and fasting insulin. The phenomapping-derived tool successfully identified chiglitazar responders and enabled personalized drug allocation in patients with drug-naïve diabetes.
