Korean journal of medical education · 2026
The National Medical Admission Test and medical student selection: rethinking cutoff validity and fairness.
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Vergeire-Dalmacion Godofreda Ruiz, Sana Erlyn Aclan, Garcia Fernando Barroga, Dilidili Aiza Lucero, Antonio Diosdado Mayores San, Baja Emmanuel Saporna
Аннотация
PURPOSE: The Commission on Higher Education of the Philippines mandates a minimum National Medical Admission Test (NMAT) percentile rank-typically the 40th percentile-for medical school admission. However, percentile rank is cohort-dependent and varies in meaning across testing years. This study re-examined its validity as an admissions criterion and evaluated whether the NMAT General Performance Score (GPS), a standardized z-score, offers a more stable and valid basis for predicting academic performance.
METHODS: We conducted a retrospective analysis of 42,261 first-time Physician Licensure Examination (PLE) takers from 2012 to 2022. NMAT and PLE records were linked, and logistic regression models were used to assess associations between NMAT scores and PLE outcomes. Predictive performance was evaluated using both receiver operating characteristic (ROC-Youden) and Precision-Recall (PR-F1) analyses to identify optimal cutoffs.
RESULTS: Percentile ranks exhibited substantial year-to-year variability, with the same percentile corresponding to different GPS scores. A pooled GPS-to-percentile crosswalk is provided for interpretive reference but does not indicate fixed rank equivalence. In contrast, PR-F1 analysis of GPS appropriate for an imbalanced dataset showed consistent predictive validity (area under the ROC curve=0.918). The ROC-Youden index identified a cutoff at GPS=581, while the F1-optimized threshold was lower (GPS=377), favoring inclusivity. A midpoint cutoff (GPS=435) balanced stringency and access.
CONCLUSION: The NMAT GPS is a more stable and equitable predictor of licensure performance than percentile rank. Its use may improve the fairness and consistency of medical school admissions and better align selection with long-term academic outcomes.
METHODS: We conducted a retrospective analysis of 42,261 first-time Physician Licensure Examination (PLE) takers from 2012 to 2022. NMAT and PLE records were linked, and logistic regression models were used to assess associations between NMAT scores and PLE outcomes. Predictive performance was evaluated using both receiver operating characteristic (ROC-Youden) and Precision-Recall (PR-F1) analyses to identify optimal cutoffs.
RESULTS: Percentile ranks exhibited substantial year-to-year variability, with the same percentile corresponding to different GPS scores. A pooled GPS-to-percentile crosswalk is provided for interpretive reference but does not indicate fixed rank equivalence. In contrast, PR-F1 analysis of GPS appropriate for an imbalanced dataset showed consistent predictive validity (area under the ROC curve=0.918). The ROC-Youden index identified a cutoff at GPS=581, while the F1-optimized threshold was lower (GPS=377), favoring inclusivity. A midpoint cutoff (GPS=435) balanced stringency and access.
CONCLUSION: The NMAT GPS is a more stable and equitable predictor of licensure performance than percentile rank. Its use may improve the fairness and consistency of medical school admissions and better align selection with long-term academic outcomes.