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

NCT07114276 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 77

Last updated 2026-01-09

No results posted yet for this study

Summary

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.

Conditions

Interventions

OTHER

Machine learning models predictions of acute kidney injury and acute kidney disease

Comparison of the performances of machine learning models and clinicians in predicting AKI within 14 days and AKD within 89 days

Sponsors & Collaborators

  • Taipei Medical University WanFang Hospital

    collaborator OTHER

  • Taipei Medical University

    lead OTHER

Principal Investigators

  • Hsiang-Yin Chen, Pharm.D. · School of Pharmacy, Taipei Medical University

Eligibility

Min Age
20 Years
Max Age
89 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2023-10-30
Primary Completion
2025-11-30
Completion
2025-11-30

Countries

  • Taiwan

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07114276 on ClinicalTrials.gov