Tacrolimus in the treatment of childhood nephrotic syndrome: Machine learning detects novel biomarkers and predicts efficacy

Study Objective The pharmacokinetics and pharmacodynamics of tacrolimus (TAC) vary greatly among individuals, hindering its precise utilization. Moreover, effective models for the early prediction of TAC efficacy in patients with nephrotic syndrome (NS) are lacking. We aimed to identify key factors...

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Veröffentlicht in:	Pharmacotherapy 2023-01, Vol.43 (1), p.43-52
Hauptverfasser:	Mo, Xiaolan, Chen, Xiujuan, Zeng, Huasong, Zheng, Wei, Ieong, Chifong, Li, Huixian, Huang, Qiongbo, Xu, Zichuan, Yang, Jinlian, Liang, Qianying, Liang, Huiying, Gao, Xia, Huang, Min, Li, Jiali
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Child Childhood childhood nephrotic syndrome Children Cohort analysis Cohort Studies Connective tissue growth factor DNA Helicases Female Gene polymorphism Humans Immunosuppressive Agents Interleukin 13 Kidney diseases Learning algorithms Machine learning Methylprednisolone Nephrotic syndrome Nephrotic Syndrome - drug therapy Nephrotic Syndrome - genetics Patients Pediatrics Pharmacodynamics Pharmacokinetics Prediction models Prednisone Prednisone - therapeutic use prognostic and predictive biomarkers Remission Single-nucleotide polymorphism Tacrolimus
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