Prospective Validation of Machine Learning Model to Predict Platinum Induced Nephrotoxicity in Cancer Patients

This study aims to investigate the utility of predictive models for chemotherapy-induced nephrotoxicity in the Taiwanese cancer population. The investigators will prospectively collect clinical data from enrolled participants, including demographic information, comorbidities, laboratory data, and chemotherapy treatment details. After chemotherapy administration, participants' renal function will be monitored over time to assess the development of nephrotoxicity, based on changes in serum creatinine (SCr) and other relevant clinical criteria. The primary objective is to evaluate and compare the predictive performance of a machine learning model and clinical physicians, using the area under the receiver operating characteristic curve (AUROC) as the main metric for discrimination performance.

NCT Number	NCT07114276
Lead Sponsor	Taipei Medical University Collaborators: Taipei Medical University WanFang Hospital
Conditions	Chemotherapy Side Effects, Machine Learning, Acute Kidney Injury, Acute Kidney Disease
Enrollment	77 participants
Start Date	2023-10-30
Primary Completion	2025-11-30 (estimated)
Study Completion	2025-11-30 (estimated)
Updated on ClinicalTrials.gov	2026-01-09