Correlation of NBME Pharmacology Subject Exam Performance with Medical School Internal Pharmacology Scores and Academic Metrics

Correlation of NBME Pharmacology Subject Exam Performance with Medical School Internal Pharmacology Scores and Academic Metrics | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Correlation of NBME Pharmacology Subject Exam Performance with Medical School Internal Pharmacology Scores and Academic Metrics Keshab Raj Paudel, Mignonette Sotto, Frances Jack-Edwards, Pushparaj Shetty This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7850101/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background This study evaluates the extent to which the National Board of Medical Examiners (NBME) Pharmacology Subject Examination scores correlate with medical school pharmacology internal exam scores and other academic metrics such as undergraduate grade point average (GPA), and Biology, Chemistry, Physics, and Mathematics GPA (BCPM), and Medical College Admission Test (MCAT) scores. This study also aimed at curricular assessment of pharmacology in relation to pharmacology internal exam score with NBME Pharmacology subject exam performance. Methods Data from 290 medical students graduating between 2019 and 2023 were analyzed using R (version 4.3.1). Pearson correlation coefficients were calculated to examine the strength of associations between NBME scores and internal exam scores, GPA, BCPM, and MCAT. A stepwise multiple linear regression model was developed to determine which predictors best explained NBME score variance. Multicollinearity was evaluated using variance inflation factor (VIF) analysis. Results A strong positive correlation was found between NBME Pharmacology scores and internal pharmacology exam scores (r = 0.69, p < 0.001). MCAT scores showed a moderate correlation (r = 0.45, p < 0.001), while GPA and BCPM were weak but statistically significant predictors (r = 0.18 each, p < 0.01). Multiple regression analysis identified internal pharmacology exam score (β = 0.6, p < 0.001) and MCAT (β = 0.3, p < 0.001) as significant predictors, with an adjusted R² of 0.54. VIF scores were ≤ 2.1. Conclusions Performance on the NBME Pharmacology Subject Exam showed a strong correlation with internal pharmacology exam scores and a moderate correlation with MCAT scores. These findings underscore the value of aligning the pharmacology curriculum with the NBME content framework to ensure that internal assessments more accurately reflect and predict students’ pharmacological knowledge and, to some extent, their overall academic performance. Moreover, the observed relationship between MCAT scores and medical school performance indicates that MCAT results may remain a meaningful predictor of future academic success and could help guide admissions decisions and recruitment strategies. In contrast, pre-admission metrics such as GPA and BCPM appear to offer limited predictive value for subsequent success in medical school. Medical Education Pharmacology NBME Background Assessment in medical education plays a pivotal role in ensuring that students achieve the competencies necessary for safe and effective clinical practice. Among the diverse assessment strategies, standardized subject examinations—such as those developed by the National Board of Medical Examiners (NBME)—are widely recognized for their objectivity, reliability, and ability to benchmark student performance across institutions. The NBME Pharmacology Subject Examination, in particular, offers an external metric for evaluating students’ mastery of pharmacological principles, therapeutic applications, and critical reasoning within the biomedical sciences. 1 – 3 The observed moderate-to-large correlations between NBME subject examination results and United States Medical Licensing Examination (USMLE) scores support the validity of NBME subject exam performance as a predictor of success on the USMLE. 1 Therefore, the correlation between institutional internal subject examinations and NBME subject examinations may serve as an additional indirect indicator of potential success on the USMLE. Institutions often integrate NBME subject exams into their summative assessment framework to identify gaps in learning and assess curricular alignment with national standards⁴. Given the importance of these exams in measuring both student learning outcomes and institutional performance, understanding the factors that predict NBME subject exam scores is essential. Accurate identification of academic predictors can inform early intervention strategies, guide individualized remediation, and support data-driven curriculum reforms. Several studies have examined predictors of standardized exam performance, including the USMLE Steps 1 and 2, finding moderate to strong associations with undergraduate metrics and in-program assessments. 1 , 2 , 5 , 6 These predictors include the Medical College Admission Test (MCAT), undergraduate Grade Point Average (GPA), and Biology-Chemistry-Physics-Mathematics GPA (BCPM)—metrics frequently used during the medical school admissions process. 5 , 7 Limited empirical attention has been given specifically to the NBME Pharmacology Subject Examination. Although pharmacology is a foundational subject in medical education, its complexity and interdisciplinary nature—spanning biochemistry, physiology, and pathology—pose significant cognitive challenges for students. Previous research suggests that performance on discipline-specific internal assessments may be more predictive of NBME outcomes than broad pre-admission academic metrics and ultimate success on USMLE. 8 – 10 Nonetheless, comprehensive analyses that integrate internal pharmacology exam scores with traditional academic indicators such as MCAT, GPA, and BCPM are scarce. To address this gap, the present study investigates the extent to which performance on the NBME Pharmacology Subject Examination correlates with medical school pharmacology internal exam scores, MCAT scores, undergraduate GPA, and BCPM scores. We aimed to quantify the strength of these relationships and identify which academic metrics best predict success on the NBME Pharmacology exam. Methods Study Design and Participants This retrospective study involved 290 students who graduated between 2019 and 2023. Ethical approval from the institutional review board was obtained. Data were de-identified and included the following variables: NBME Pharmacology Subject Exam score, medical school pharmacology internal exam score, undergraduate GPA, BCPM, and MCAT scores. Both basic pharmacology and system pharmacology were taught to the students in semesters 3 (term 3) and 4 (term 4). Quizzes, mid-term and final exams (Table 1 ) were conducted as per the curricular structure which were based on different sections of pharmacology. The exams were based on the single response multiple choice questions and were delivered through Exam Soft software. The assessment score reliability (KR-20) for the three exams calculated by the Exam Soft was in the range of satisfactory to good. The scores from all the exams were added to the final grade calculation. The time difference between the last internal pharmacology exam and the NBME Pharmacology Subject Exam was approximately two weeks apart. Students sat for the NBME Pharmacology Subject Exam at the end of the pharmacology course as a mandatory requirement for the pharmacology course completion and academic promotion since the curriculum was discipline-based at the time of the study (Table 1 ). The instructors who taught the pharmacology course were not NBME exam writers, nor were the older NBME exam files available to the institution, and the NBME exams were not customized. No additional therapeutic courses such as rotations or capstone courses were conducted during the time of pharmacology instruction into the curriculum. Statistical Analysis Using R All statistical analyses were performed in R version 4.3.1. After importing the dataset from Excel using the readxl package, missing values were removed using the na.omit() function. Pearson correlation coefficients and p-values were calculated using the cor.test() function. Multiple linear regression analysis was conducted with the lm() function, and variable significance was determined via the summary() function. Variance inflation factors were calculated using the vif() function from the car package to assess multicollinearity. The final model used the NBME Pharmacology Subject Exam score as the dependent variable and internal exam score, GPA, BCPM, and MCAT as predictors. A p-value of < 0.05 was considered statistically significant. Table 1 Pharmacology syllabus delivered during time of the study Topic Hours of instruction (didactic lecture) Term 3 (3rd semester) Orientation to course & introduction to pharmacology 1 Routes of drug administration 1 Pharmacokinetics 4 Pharmacodynamics 3 New drug development & pharmacogenomics 1 Adverse drug reactions, factors modifying drug therapy & chelating agents 2 Quiz 1–20 multiple choice questions (single response) Drugs acting on autonomic nervous system 6 Autacoids and therapy of migraine 2 Diuretics and antidiuretics 2 Antihypertensive drugs 3 Therapy of congestive heart failure 2 Antiarrhythmic drugs 1 Antianginal drugs & hematopoietic agents 1 Hypolipidemic drugs 1 Mid-term exam- 50 multiple choice questions (single response) Anticoagulants 2 Non-steroidal anti-inflammatory drugs 2 Corticosteroids 2 Immunosuppressants 1 Therapy of gout & rheumatoid arthritis 1 Quiz 2–20 multiple choice questions (single response) Gastrointestinal drugs (drugs for peptic ulcer, antiemetics, antidiarrheals, laxatives and purgatives) 3 Therapy of bronchial asthma & chronic obstructive pulmonary disease 2 Nasal decongestants & therapy of cough 1 Final Exam: 50 multiple choice questions (single response) Term 4 (4th semester) Anti-fungal drugs 2 Anti-malarial drugs 1 Anthelminthic drugs 1 Anti-protozoal & anti-leprosy drugs 1 Antiviral drugs 4 Quiz 1–35 multiple choice questions (single response) Antibiotics 10 Oncology drugs 5 Mid-term exam- 60 multiple choice questions (single response) Pharmacology of sedative hypnotics 2 Antidepressant drugs 1 Pharmacology of Parkinson’s disease 1 Anti-epilepsy & anti-seizure drugs 1 Antipsychotics & mood stabilizers 1 Pharmacology of local anesthetics 1 Opioid agonists and antagonists 2 Skeletal Muscle Relaxants, controlled substances, & drugs for attention-deficit/ hyperactivity disorder 2 General anesthetics 2 Drugs for osteoporosis 1 Insulin and analogs, and oral and parenteral drugs for diabetes mellitus 2 Hypothalamic & pituitary hormones 1 Thyroid hormones & antithyroid Drugs 1 Male & female hormones and analogs, and drugs for obesity, & erectile dysfunction 2 Hormonal contraceptives 1 Quiz 2–60 multiple choice questions (single response) NBME Pharmacology Subject Exam Results Table 2 shows multiple linear regression model for NBME Pharmacology Subject scores as explained by pharmacology internal exam, GPA, BCPM and MCAT scores. Table 3 illustrates the VIF scores which were 1.1 for pharmacology internal exam percentage scores and MCAT scores whereas they were 2.1 For GPA and BCPM indicating low level of multicollinearity. Similarly, Table 4 shows the Pearson correlation statistics for NBME pharmacology subject scores with pharmacology internal scores, GPA, BCPM and MCAT scores. The correlation of NBME Pharmacology Subject exam scores for pharmacology internal exam and MCAT scores was significant (< 0.001) with higher predictability for pharmacology internal exam scores. Among undergraduate academic metrics MCAT score was the significant independent predictor for NBME Pharmacology Subject exam scores. Table 2 Multiple linear regression model for NBME Pharmacology Subject scores as explained by pharmacology internal exam, GPA, BCPM and MCAT. Variable Coefficients Standard error P value Pharmacology Internal Exam % 0.6 0.04 < 0.001 GPA -0.5 1.59 0.7 BCPM 0.9 1.26 0.4 MCAT 0.3 0.06 < 0.001 Adjusted R squared 0.54 P < 0.001 Table 3 Multicollinearity statistics for Multiple linear regression model for NBME Pharmacology Subject scores based on variance inflation factor (VIF) Variable scores VIF score Pharmacology Internal Exam % 1.1 GPA 2.1 BCPM 2.1 MCAT 1.1 Table 4 Pearson correlation statistics for NBME pharmacology subject scores with pharmacology internal scores, and GPA, BCPM and MCAT scores (n = 290, degree of freedom = 288). Correlation Correlation coefficient 95% confidence interval P value NBME and Internal scores 0.69 0.63–0.75 < 0.001 NBME and GPA 0.18 0.06–0.29 0.0018 NBME and BCPM 0.18 0.07–0.29 0.0016 NBME and MCAT 0.45 0.35–0.54 < 0.001 Discussion The moderate to strong correlations identified between NBME subject exam scores and USMLE performance reinforce the predictive validity of NBME subject examinations as indicators of success on the USMLE. 1 So this study investigated the extent to which various academic metrics—including internal pharmacology exam scores, MCAT scores, GPA, and BCPM—predict performance on the NBME Pharmacology Subject Examination. Our findings revealed that internal pharmacology exam scores were the most significant predictors of NBME performance (β = 0.6, p < 0.001), followed by MCAT scores (β = 0.3, p < 0.001), while GPA and BCPM demonstrated non-significant and weak predictors of NBME performance (Table 1 and 2 ). These results offer important insights into the relative contributions of pre-admission and in-program academic metrics in predicting medical student performance. The positive correlation observed between internal pharmacology scores and NBME Pharmacology Subject Exam performance (r = 0.69, p < 0.001) suggests that discipline-specific assessments may serve as useful indicators of content mastery. This is consistent with prior literature emphasizing the predictive strength of in-program performance over pre-admission academic indicators. 11 Furthermore, the findings suggest that the pharmacology syllabus used during this study appears to be reasonably aligned with the content framework of the NBME examination. Internal pharmacology exams are typically designed to align closely with curricular objectives and delivery, making them sensitive to both student learning and instructional effectiveness. Their predictive capacity likely stems from their ability to assess nuanced, course-specific knowledge and application skills, which are highly relevant to NBME content domains. Educators may therefore utilize internal assessment outcomes as a valuable metric for evaluating the alignment between institutional course syllabi and NBME content domains. Regular analysis of internal exam performance in relation to NBME outcomes can help identify areas of curricular strength and gaps in content coverage, thereby guiding continuous quality improvement in course design and instructional strategies. The moderate correlation between NBME scores and MCAT performance (r = 0.45, p < 0.001) observed in this study also merits attention. The MCAT, while not pharmacology-specific, is designed to assess critical thinking, problem-solving, and foundational science knowledge. These cognitive competencies are likely to transfer to success in pharmacology and other content-heavy domains in medical school. Previous research has demonstrated the MCAT's predictive validity for USMLE Step 1 scores and overall academic performance, 8,12,13 and our findings support its relevance in pharmacology-specific assessments as well. MCAT’s moderate correlation with NBME performance suggests that it can still function as an independent, mild-to-moderate predictor of overall academic success. Given that the MCAT evaluates broader cognitive domains—including critical reasoning, problem-solving, and foundational science knowledge—it may continue to play a valuable role in the admissions process by identifying applicants with the general intellectual readiness and analytical skills necessary for medical education, even if it does not directly reflect mastery of specific curricular content. Interestingly, both cumulative undergraduate GPA and BCPM scores showed only weak correlations with NBME Pharmacology performance (r = 0.18 each, p < 0.01). These findings align with earlier studies suggesting that undergraduate academic performance, while useful for admissions screening, may have limited utility in predicting success within specific medical school disciplines. 3,9,14 GPA and BCPM scores reflect a range of courses completed under varying degrees of difficulty, institutional rigor, and grading policies. As such, they may not accurately represent a student's readiness for the depth and pace of medical school coursework, particularly in pharmacology. This observation suggests that incorporating early in-program performance indicators alongside admissions metrics may help provide a more comprehensive understanding of student outcomes. 15 – 20 The use of R supported efficient data management, statistical modeling, and visualization of relationships among variables. Pearson correlation tests and multiple linear regression were applied to examine associations between predictors, while VIF analysis was used to assess potential multicollinearity. All VIF values were below 2.2 (Table 2 ), indicating minimal overlap among predictors and supporting the interpretability of the results. Importantly, the final regression model explained 54% of the variance in NBME Pharmacology Subject Exam scores. While this is a substantial proportion, it also suggests that nearly half of the variability remains unaccounted for. This residual variance could be attributed to several unmeasured factors, such as study strategies, time management, intrinsic motivation, test-taking anxiety, or the quality of instructional delivery. Residual variance could also be explained by factors such as intellect and memory, which, although not easily measurable among medical students, may contribute to variation in outcomes. Future studies incorporating these variables—perhaps through mixed-methods or longitudinal designs—could offer a more holistic understanding of the complex interplay between cognitive, behavioral, and environmental factors influencing NBME performance. 21 – 23 Additionally, the pharmacology syllabus used in this study may serve as a useful reference for others interested in comparing or aligning their curricula (Table 1 ). The strong relationship between internal exam performance and NBME outcomes suggests that early course assessments may be used to flag students who are at risk for underperformance on high-stakes exams. Such early identification could inform tailored remediation plans, resource allocation, and peer or faculty mentoring programs. 24 – 26 Furthermore, recognizing the limited predictive value of GPA and BCPM could prompt admissions committees to reevaluate the weight assigned to these metrics and consider incorporating more holistic measures, such as personal competencies, resilience, or situational judgment. 27 , 28 In summary, our findings suggest that in-program assessments and standardized cognitive measures such as the MCAT may be more useful than traditional undergraduate metrics in predicting performance on internal and NBME subject exams, and ultimately on the USMLE. 1 These results add to existing evidence supporting the use of data-informed approaches to student evaluation, academic support, and curriculum development in medical education. 29 , 30 Limitations This study is limited to a single institution and a single discipline. Additionally, qualitative factors such as motivation, learning styles, and teaching quality were not assessed. Future research should involve multi-institutional cohorts, consider demographic variables, and explore longitudinal trends. Conclusions The NBME Pharmacology Subject Exam scores showed the strongest association with internal pharmacology examination performance, followed by a moderate relationship with MCAT scores. These findings suggest that internal pharmacology assessments may reflect student readiness for the NBME examination and, to some extent, for USMLE performance. Furthermore, while pre-admission metrics such as GPA and BCPM may provide limited insight, MCAT performance appears to be a more robust predictor of medical students’ academic success. Abbreviations BCPM: Biology, Chemistry, Physics, and Mathematics GPA GPA: Grade point average MCAT: Medical College Admission Test NBME: National Board of Medical Examiners USMLE: United States Medical Licensing Examination Declarations Funding/Support: None Other disclosures: None Declarations Ethics approval Ethical approval was obtained from Institutional Review Board of Trinity Medical Sciences University- School of Medicine, St. Vincent and the Grenadines. The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. Clinical trial number Not applicable Human ethics and consent to participate Not applicable. The study was waived by Institutional Review Board of Trinity Medical Sciences University- School of Medicine, St. Vincent and the Grenadines. Consent for publication Not applicable Availability of Data and Materials The datasets generated and analyzed during the study are not publicly available but are available from the corresponding author on reasonable request. References Zahn CM, Saguil A, Artino AR Jr, Dong T, Ming G, Servey JT et al. Correlation of National Board of Medical Examiners scores with United States Medical Licensing Examination Step 1 and Step 2 scores. Acad Med. 2012;87(10):1348–54. 10.1097/ACM.0b013e31826a13bd . PMID: 22914528. Rubright JD, Jodoin M, Woodward S, Barone MA. Differential Item Functioning Analysis of United States Medical Licensing Examination Step 1 Items. Acad Med. 2022;97(5):718–22. 10.1097/ACM.0000000000004567 . PMID: 34907964. Monteiro D, Sibbald M, Stasiuk K, Laurence T, McAndrew M. Internal formative assessments are significant predictors of final NBME pharmacology exam performance: a retrospective analysis. Med Educ Online. 2021;26(1):1952963. doi: 10.1080/10872981.2021.1952963. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7850101","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":547770083,"identity":"08e5fd15-0c97-4662-9831-509f118bbbe2","order_by":0,"name":"Keshab Raj 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02:20:26","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":80204,"visible":true,"origin":"","legend":"","description":"","filename":"a44a26de27064092a67aca3d13b4edd41structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7850101/v1/f06ffbdf707984f993cbdd45.xml"},{"id":96504349,"identity":"19622673-faa8-4529-abe2-07c00a5c4d68","added_by":"auto","created_at":"2025-11-22 02:20:26","extension":"html","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":90188,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7850101/v1/ef9655837430969fbba963ab.html"},{"id":98284761,"identity":"606803e0-e616-4ffc-98fe-bf36a5707576","added_by":"auto","created_at":"2025-12-16 06:39:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":811012,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7850101/v1/937d51b5-3cd3-4ada-9f79-a5e2f7a24df0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Correlation of NBME Pharmacology Subject Exam Performance with Medical School Internal Pharmacology Scores and Academic Metrics","fulltext":[{"header":"Background","content":"\u003cp\u003eAssessment in medical education plays a pivotal role in ensuring that students achieve the competencies necessary for safe and effective clinical practice. Among the diverse assessment strategies, standardized subject examinations\u0026mdash;such as those developed by the National Board of Medical Examiners (NBME)\u0026mdash;are widely recognized for their objectivity, reliability, and ability to benchmark student performance across institutions. The NBME Pharmacology Subject Examination, in particular, offers an external metric for evaluating students\u0026rsquo; mastery of pharmacological principles, therapeutic applications, and critical reasoning within the biomedical sciences.\u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e The observed moderate-to-large correlations between NBME subject examination results and United States Medical Licensing Examination (USMLE) scores support the validity of NBME subject exam performance as a predictor of success on the USMLE.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Therefore, the correlation between institutional internal subject examinations and NBME subject examinations may serve as an additional indirect indicator of potential success on the USMLE. Institutions often integrate NBME subject exams into their summative assessment framework to identify gaps in learning and assess curricular alignment with national standards⁴.\u003c/p\u003e\u003cp\u003eGiven the importance of these exams in measuring both student learning outcomes and institutional performance, understanding the factors that predict NBME subject exam scores is essential. Accurate identification of academic predictors can inform early intervention strategies, guide individualized remediation, and support data-driven curriculum reforms. Several studies have examined predictors of standardized exam performance, including the USMLE Steps 1 and 2, finding moderate to strong associations with undergraduate metrics and in-program assessments.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThese predictors include the Medical College Admission Test (MCAT), undergraduate Grade Point Average (GPA), and Biology-Chemistry-Physics-Mathematics GPA (BCPM)\u0026mdash;metrics frequently used during the medical school admissions process.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eLimited empirical attention has been given specifically to the NBME Pharmacology Subject Examination. Although pharmacology is a foundational subject in medical education, its complexity and interdisciplinary nature\u0026mdash;spanning biochemistry, physiology, and pathology\u0026mdash;pose significant cognitive challenges for students. Previous research suggests that performance on discipline-specific internal assessments may be more predictive of NBME outcomes than broad pre-admission academic metrics and ultimate success on USMLE.\u003csup\u003e\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eNonetheless, comprehensive analyses that integrate internal pharmacology exam scores with traditional academic indicators such as MCAT, GPA, and BCPM are scarce. To address this gap, the present study investigates the extent to which performance on the NBME Pharmacology Subject Examination correlates with medical school pharmacology internal exam scores, MCAT scores, undergraduate GPA, and BCPM scores. We aimed to quantify the strength of these relationships and identify which academic metrics best predict success on the NBME Pharmacology exam.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Participants\u003c/h2\u003e\u003cp\u003eThis retrospective study involved 290 students who graduated between 2019 and 2023. Ethical approval from the institutional review board was obtained. Data were de-identified and included the following variables: NBME Pharmacology Subject Exam score, medical school pharmacology internal exam score, undergraduate GPA, BCPM, and MCAT scores. Both basic pharmacology and system pharmacology were taught to the students in semesters 3 (term 3) and 4 (term 4). Quizzes, mid-term and final exams (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) were conducted as per the curricular structure which were based on different sections of pharmacology. The exams were based on the single response multiple choice questions and were delivered through Exam Soft software. The assessment score reliability (KR-20) for the three exams calculated by the Exam Soft was in the range of satisfactory to good. The scores from all the exams were added to the final grade calculation. The time difference between the last internal pharmacology exam and the NBME Pharmacology Subject Exam was approximately two weeks apart. Students sat for the NBME Pharmacology Subject Exam at the end of the pharmacology course as a mandatory requirement for the pharmacology course completion and academic promotion since the curriculum was discipline-based at the time of the study (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe instructors who taught the pharmacology course were not NBME exam writers, nor were the older NBME exam files available to the institution, and the NBME exams were not customized. No additional therapeutic courses such as rotations or capstone courses were conducted during the time of pharmacology instruction into the curriculum.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStatistical Analysis Using R\u003c/h3\u003e\n\u003cp\u003eAll statistical analyses were performed in R version 4.3.1. After importing the dataset from Excel using the readxl package, missing values were removed using the na.omit() function. Pearson correlation coefficients and p-values were calculated using the cor.test() function. Multiple linear regression analysis was conducted with the lm() function, and variable significance was determined via the summary() function. Variance inflation factors were calculated using the vif() function from the car package to assess multicollinearity.\u003c/p\u003e\u003cp\u003eThe final model used the NBME Pharmacology Subject Exam score as the dependent variable and internal exam score, GPA, BCPM, and MCAT as predictors. A p-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePharmacology syllabus delivered during time of the study\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTopic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHours of instruction\u003c/p\u003e\u003cp\u003e(didactic lecture)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTerm 3 (3rd semester)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOrientation to course \u0026amp; introduction to pharmacology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRoutes of drug administration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePharmacokinetics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePharmacodynamics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNew drug development \u0026amp; pharmacogenomics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdverse drug reactions, factors modifying drug therapy \u0026amp; chelating agents\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eQuiz 1\u0026ndash;20 multiple choice questions (single response)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrugs acting on autonomic nervous system\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAutacoids and therapy of migraine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiuretics and antidiuretics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAntihypertensive drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTherapy of congestive heart failure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAntiarrhythmic drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAntianginal drugs \u0026amp; hematopoietic agents\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypolipidemic drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMid-term exam- 50 multiple choice questions (single response)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnticoagulants\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon-steroidal anti-inflammatory drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCorticosteroids\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eImmunosuppressants\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTherapy of gout \u0026amp; rheumatoid arthritis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eQuiz 2\u0026ndash;20 multiple choice questions (single response)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGastrointestinal drugs (drugs for peptic ulcer, antiemetics, antidiarrheals, laxatives and purgatives)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTherapy of bronchial asthma \u0026amp; chronic obstructive pulmonary disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNasal decongestants \u0026amp; therapy of cough\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFinal Exam: 50 multiple choice questions (single response)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTerm 4 (4th semester)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnti-fungal drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnti-malarial drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnthelminthic drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnti-protozoal \u0026amp; anti-leprosy drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAntiviral drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eQuiz 1\u0026ndash;35 multiple choice questions (single response)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAntibiotics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOncology drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMid-term exam- 60 multiple choice questions (single response)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePharmacology of sedative hypnotics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAntidepressant drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePharmacology of Parkinson\u0026rsquo;s disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnti-epilepsy \u0026amp; anti-seizure drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAntipsychotics \u0026amp; mood stabilizers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePharmacology of local anesthetics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOpioid agonists and antagonists\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSkeletal Muscle Relaxants, controlled substances, \u0026amp; drugs for attention-deficit/ hyperactivity disorder\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGeneral anesthetics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrugs for osteoporosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInsulin and analogs, and oral and parenteral drugs for diabetes mellitus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypothalamic \u0026amp; pituitary hormones\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThyroid hormones \u0026amp; antithyroid Drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale \u0026amp; female hormones and analogs, and drugs for obesity, \u0026amp; erectile dysfunction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHormonal contraceptives\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eQuiz 2\u0026ndash;60 multiple choice questions (single response)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNBME Pharmacology Subject Exam\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows multiple linear regression model for NBME Pharmacology Subject scores as explained by pharmacology internal exam, GPA, BCPM and MCAT scores. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates the VIF scores which were 1.1 for pharmacology internal exam percentage scores and MCAT scores whereas they were 2.1 For GPA and BCPM indicating low level of multicollinearity. Similarly, Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the Pearson correlation statistics for NBME pharmacology subject scores with pharmacology internal scores, GPA, BCPM and MCAT scores. The correlation of NBME Pharmacology Subject exam scores for pharmacology internal exam and MCAT scores was significant (\u0026lt;\u0026thinsp;0.001) with higher predictability for pharmacology internal exam scores. Among undergraduate academic metrics MCAT score was the significant independent predictor for NBME Pharmacology Subject exam scores.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultiple linear regression model for NBME Pharmacology Subject scores as explained by pharmacology internal exam, GPA, BCPM and MCAT.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCoefficients\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStandard error\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePharmacology Internal Exam %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGPA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBCPM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMCAT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdjusted R squared\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMulticollinearity statistics for Multiple linear regression model for NBME Pharmacology Subject scores based on variance inflation factor (VIF)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable scores\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVIF score\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePharmacology Internal Exam %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGPA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBCPM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMCAT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePearson correlation statistics for NBME pharmacology subject scores with pharmacology internal scores, and GPA, BCPM and MCAT scores (n\u0026thinsp;=\u0026thinsp;290, degree of freedom\u0026thinsp;=\u0026thinsp;288).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCorrelation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCorrelation coefficient\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95% confidence interval\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNBME and Internal scores\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.63\u0026ndash;0.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNBME and GPA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.06\u0026ndash;0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0018\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNBME and BCPM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.07\u0026ndash;0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0016\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNBME and MCAT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.35\u0026ndash;0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe moderate to strong correlations identified between NBME subject exam scores and USMLE performance reinforce the predictive validity of NBME subject examinations as indicators of success on the USMLE. \u003csup\u003e1\u003c/sup\u003e So this study investigated the extent to which various academic metrics\u0026mdash;including internal pharmacology exam scores, MCAT scores, GPA, and BCPM\u0026mdash;predict performance on the NBME Pharmacology Subject Examination. Our findings revealed that internal pharmacology exam scores were the most significant predictors of NBME performance (β\u0026thinsp;=\u0026thinsp;0.6, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), followed by MCAT scores (β\u0026thinsp;=\u0026thinsp;0.3, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while GPA and BCPM demonstrated non-significant and weak predictors of NBME performance (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These results offer important insights into the relative contributions of pre-admission and in-program academic metrics in predicting medical student performance.\u003c/p\u003e\u003cp\u003eThe positive correlation observed between internal pharmacology scores and NBME Pharmacology Subject Exam performance (r\u0026thinsp;=\u0026thinsp;0.69, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) suggests that discipline-specific assessments may serve as useful indicators of content mastery. This is consistent with prior literature emphasizing the predictive strength of in-program performance over pre-admission academic indicators.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Furthermore, the findings suggest that the pharmacology syllabus used during this study appears to be reasonably aligned with the content framework of the NBME examination. Internal pharmacology exams are typically designed to align closely with curricular objectives and delivery, making them sensitive to both student learning and instructional effectiveness. Their predictive capacity likely stems from their ability to assess nuanced, course-specific knowledge and application skills, which are highly relevant to NBME content domains. Educators may therefore utilize internal assessment outcomes as a valuable metric for evaluating the alignment between institutional course syllabi and NBME content domains. Regular analysis of internal exam performance in relation to NBME outcomes can help identify areas of curricular strength and gaps in content coverage, thereby guiding continuous quality improvement in course design and instructional strategies.\u003c/p\u003e\u003cp\u003eThe moderate correlation between NBME scores and MCAT performance (r\u0026thinsp;=\u0026thinsp;0.45, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) observed in this study also merits attention. The MCAT, while not pharmacology-specific, is designed to assess critical thinking, problem-solving, and foundational science knowledge. These cognitive competencies are likely to transfer to success in pharmacology and other content-heavy domains in medical school. Previous research has demonstrated the MCAT's predictive validity for USMLE Step 1 scores and overall academic performance,\u003csup\u003e8,12,13\u003c/sup\u003e and our findings support its relevance in pharmacology-specific assessments as well. MCAT\u0026rsquo;s moderate correlation with NBME performance suggests that it can still function as an independent, mild-to-moderate predictor of overall academic success. Given that the MCAT evaluates broader cognitive domains\u0026mdash;including critical reasoning, problem-solving, and foundational science knowledge\u0026mdash;it may continue to play a valuable role in the admissions process by identifying applicants with the general intellectual readiness and analytical skills necessary for medical education, even if it does not directly reflect mastery of specific curricular content.\u003c/p\u003e\u003cp\u003eInterestingly, both cumulative undergraduate GPA and BCPM scores showed only weak correlations with NBME Pharmacology performance (r\u0026thinsp;=\u0026thinsp;0.18 each, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). These findings align with earlier studies suggesting that undergraduate academic performance, while useful for admissions screening, may have limited utility in predicting success within specific medical school disciplines. \u003csup\u003e3,9,14\u003c/sup\u003e GPA and BCPM scores reflect a range of courses completed under varying degrees of difficulty, institutional rigor, and grading policies. As such, they may not accurately represent a student's readiness for the depth and pace of medical school coursework, particularly in pharmacology. This observation suggests that incorporating early in-program performance indicators alongside admissions metrics may help provide a more comprehensive understanding of student outcomes.\u003csup\u003e\u003cspan additionalcitationids=\"CR16 CR17 CR18 CR19\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThe use of R supported efficient data management, statistical modeling, and visualization of relationships among variables. Pearson correlation tests and multiple linear regression were applied to examine associations between predictors, while VIF analysis was used to assess potential multicollinearity. All VIF values were below 2.2 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), indicating minimal overlap among predictors and supporting the interpretability of the results.\u003c/p\u003e\u003cp\u003eImportantly, the final regression model explained 54% of the variance in NBME Pharmacology Subject Exam scores. While this is a substantial proportion, it also suggests that nearly half of the variability remains unaccounted for. This residual variance could be attributed to several unmeasured factors, such as study strategies, time management, intrinsic motivation, test-taking anxiety, or the quality of instructional delivery. Residual variance could also be explained by factors such as intellect and memory, which, although not easily measurable among medical students, may contribute to variation in outcomes.\u003c/p\u003e\u003cp\u003eFuture studies incorporating these variables\u0026mdash;perhaps through mixed-methods or longitudinal designs\u0026mdash;could offer a more holistic understanding of the complex interplay between cognitive, behavioral, and environmental factors influencing NBME performance.\u003csup\u003e\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eAdditionally, the pharmacology syllabus used in this study may serve as a useful reference for others interested in comparing or aligning their curricula (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The strong relationship between internal exam performance and NBME outcomes suggests that early course assessments may be used to flag students who are at risk for underperformance on high-stakes exams. Such early identification could inform tailored remediation plans, resource allocation, and peer or faculty mentoring programs.\u003csup\u003e\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e Furthermore, recognizing the limited predictive value of GPA and BCPM could prompt admissions committees to reevaluate the weight assigned to these metrics and consider incorporating more holistic measures, such as personal competencies, resilience, or situational judgment.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eIn summary, our findings suggest that in-program assessments and standardized cognitive measures such as the MCAT may be more useful than traditional undergraduate metrics in predicting performance on internal and NBME subject exams, and ultimately on the USMLE.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e These results add to existing evidence supporting the use of data-informed approaches to student evaluation, academic support, and curriculum development in medical education.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e"},{"header":"Limitations","content":"\u003cp\u003eThis study is limited to a single institution and a single discipline. Additionally, qualitative factors such as motivation, learning styles, and teaching quality were not assessed. Future research should involve multi-institutional cohorts, consider demographic variables, and explore longitudinal trends.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe NBME Pharmacology Subject Exam scores showed the strongest association with internal pharmacology examination performance, followed by a moderate relationship with MCAT scores. These findings suggest that internal pharmacology assessments may reflect student readiness for the NBME examination and, to some extent, for USMLE performance. Furthermore, while pre-admission metrics such as GPA and BCPM may provide limited insight, MCAT performance appears to be a more robust predictor of medical students\u0026rsquo; academic success.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBCPM: Biology, Chemistry, Physics, and Mathematics GPA\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGPA: Grade point average\u003c/p\u003e\n\u003cp\u003eMCAT: Medical College Admission Test\u003c/p\u003e\n\u003cp\u003eNBME: National Board of Medical Examiners\u003c/p\u003e\n\u003cp\u003eUSMLE: United States Medical Licensing Examination\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eFunding/Support:\u003c/em\u003e None\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eOther disclosures:\u003c/em\u003e None\u003c/p\u003e\n\u003cp\u003eDeclarations\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEthics approval\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from Institutional Review Board of Trinity Medical Sciences University- School of Medicine, St. Vincent and the Grenadines. The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eClinical trial number\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHuman ethics and consent to participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. The study was waived by Institutional Review Board of Trinity Medical Sciences University- School of Medicine, St. Vincent and the Grenadines.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of Data and Materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the study are not publicly available but are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eZahn CM, Saguil A, Artino AR Jr, Dong T, Ming G, Servey JT et al. Correlation of National Board of Medical Examiners scores with United States Medical Licensing Examination Step 1 and Step 2 scores. 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PMID: 11029858.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Medical, Education, Pharmacology, NBME","lastPublishedDoi":"10.21203/rs.3.rs-7850101/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7850101/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eThis study evaluates the extent to which the National Board of Medical Examiners (NBME) Pharmacology Subject Examination scores correlate with medical school pharmacology internal exam scores and other academic metrics such as undergraduate grade point average (GPA), and Biology, Chemistry, Physics, and Mathematics GPA (BCPM), and Medical College Admission Test (MCAT) scores. This study also aimed at curricular assessment of pharmacology in relation to pharmacology internal exam score with NBME Pharmacology subject exam performance.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eData from 290 medical students graduating between 2019 and 2023 were analyzed using R (version 4.3.1). Pearson correlation coefficients were calculated to examine the strength of associations between NBME scores and internal exam scores, GPA, BCPM, and MCAT. A stepwise multiple linear regression model was developed to determine which predictors best explained NBME score variance. Multicollinearity was evaluated using variance inflation factor (VIF) analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eA strong positive correlation was found between NBME Pharmacology scores and internal pharmacology exam scores (r\u0026thinsp;=\u0026thinsp;0.69, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). MCAT scores showed a moderate correlation (r\u0026thinsp;=\u0026thinsp;0.45, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while GPA and BCPM were weak but statistically significant predictors (r\u0026thinsp;=\u0026thinsp;0.18 each, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Multiple regression analysis identified internal pharmacology exam score (β\u0026thinsp;=\u0026thinsp;0.6, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and MCAT (β\u0026thinsp;=\u0026thinsp;0.3, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) as significant predictors, with an adjusted R\u0026sup2; of 0.54. VIF scores were \u0026le;\u0026thinsp;2.1.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003ePerformance on the NBME Pharmacology Subject Exam showed a strong correlation with internal pharmacology exam scores and a moderate correlation with MCAT scores. These findings underscore the value of aligning the pharmacology curriculum with the NBME content framework to ensure that internal assessments more accurately reflect and predict students\u0026rsquo; pharmacological knowledge and, to some extent, their overall academic performance. Moreover, the observed relationship between MCAT scores and medical school performance indicates that MCAT results may remain a meaningful predictor of future academic success and could help guide admissions decisions and recruitment strategies. In contrast, pre-admission metrics such as GPA and BCPM appear to offer limited predictive value for subsequent success in medical school.\u003c/p\u003e","manuscriptTitle":"Correlation of NBME Pharmacology Subject Exam Performance with Medical School Internal Pharmacology Scores and Academic Metrics","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-22 02:20:21","doi":"10.21203/rs.3.rs-7850101/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5f163493-d85e-482b-a741-3ddbb23d80e3","owner":[],"postedDate":"November 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-24T02:25:43+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-22 02:20:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7850101","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7850101","identity":"rs-7850101","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}