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Predictive Validity of Preclerkship Performance Metrics on USMLE Step 2 CK Outcomes in the Step 1 Pass/Fail Era
Karl Aharonian1, Maggie Sanders1, Tal Schlesinger1
1Kirk Kerkorian School of Medicine, Las Vegas, NV, USA.
Purpose:
With the transition of USMLE Step 1 to pass/fail, Step 2 CK has become a critical factor in residency selection. This study evaluates the predictive value of preclinical academic metrics for Step 2 CK outcomes to help students assess their metrics for residency before starting clerkships.
Methods:
We analyzed data from 58 students at the Kirk Kerkorian School of Medicine at UNLV. Academic metrics included MCAT scores, NBME-style Phase 1 exam performance, and CBSE scores. Pearson correlation coefficients were calculated between each predictor and Step 2 CK scores. Binary logistic regression was used, with Step 2 CK upper quartile (score >255) as the dependent variable and thresholds for each predictor as independent variables.
Results:
MCAT scores showed a moderate positive correlation with Step 2 CK (r=0.37, p=0.004). Students scoring >510 on the MCAT were significantly more likely to achieve >255 on Step 2 CK. Phase 1 NBME exam performance had the strongest correlation (r=0.67, p<0.0001), with students scoring above the national mean on >75% of exams more likely to achieve >255. While CBSE scores showed a similar correlation (r=0.67, p<0.0001), logistic regression analysis revealed that their predictive ability was less consistent for students in the middle performance range, indicating variability in classification utility.
Conclusion:
Preclinical NBME exam performance emerged as the strongest predictor of Step 2 CK success in our cohort, with MCAT and CBSE scores offering additional, though less robust, predictive value. These findings highlight the importance of early academic guidance to optimize residency preparedness and provide actionable insights for students assessing their readiness within the new Step 1 pass/fail framework. Further multi-institutional research is warranted to validate and generalize these results.
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