Michael J Pencina, PhD
Adjunct Professor
Boston University School of Public Health

PhD, Boston University
MA, University of Warsaw

Dr. Michael Pencina is the Duke Clinical Research Institute Director of Biostatistics. He is Professor of Biostatistics & Bioinformatics at Duke and Adjunct Professor in the Department of Biostatistics at Boston University.

As the DCRI Director of Biostatistics, Dr. Pencina serves as a key institutional leader overseeing the strategic and operational direction of our biostatistics talent and resources at the DCRI. In this role, Dr. Pencina guides a strategic vision to meet the needs of DCRI investigators by developing necessary infrastructure while also partnering with the Biostatistics & Bioinformatics Department to assure that the DCRI’s objectives and services are well understood and supported.

Prior to joining the DCRI in 2013, Dr. Pencina served as an associate professor in the Department of Biostatistics at Boston University and as Director of Statistical Consulting at the Harvard Clinical Research Institute. He brings a wealth of experience in both clinical trials and observational analyses. He has worked on a number of large clinical trials as well as Framingham Heart Study projects. Dr. Pencina is an expert in cardiovascular disease risk prediction model development and assessment of performance. The novel metrics (net reclassification improvement and integrated discrimination improvement) for the assessment of usefulness of new biomarkers and genetic factors in risk prediction proposed by Dr. Pencina have been incorporated into the reporting guidelines. For the past year, Dr. Pencina has also served as the Associate Editor for Statistics in Medicine. He has authored more than 150 manuscripts that have been published in peer-reviewed journals. Dr. Pencina earned his PhD in Mathematics and Statistics at Boston University.

Boston University
Evans Center for Interdisciplinary Biomedical Research

Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.

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  1. D'Agostino McGowan L, Pencina M, Sullivan L, D'Agostino RB. In Memoriam: Ralph B. D'Agostino, Sr. (1940-2023). Am J Epidemiol. 2024 Mar 06.View Related Profiles. PMID: 38451245
  2. Economou-Zavlanos NJ, Bessias S, Cary MP, Bedoya AD, Goldstein BA, Jelovsek JE, O'Brien CL, Walden N, Elmore M, Parrish AB, Elengold S, Lytle KS, Balu S, Lipkin ME, Shariff AI, Gao M, Leverenz D, Henao R, Ming DY, Gallagher DM, Pencina MJ, Poon EG. Translating ethical and quality principles for the effective, safe and fair development, deployment and use of artificial intelligence technologies in healthcare. J Am Med Inform Assoc. 2024 Feb 16; 31(3):705-713. PMID: 38031481; PMCID: PMC10873841; DOI: 10.1093/jamia/ocad221;
  3. Shah NH, Halamka JD, Saria S, Pencina M, Tazbaz T, Tripathi M, Callahan A, Hildahl H, Anderson B. A Nationwide Network of Health AI Assurance Laboratories. JAMA. 2024 Jan 16; 331(3):245-249. PMID: 38117493
  4. Mierzynska A, Jaworska I, Piotrowicz R, Kowalik I, Pencina M, Opolski G, Zareba W, Banach M, Orzechowski P, Glówczynska R, Szalewska D, Pluta S, Kalarus Z, Irzmanski R, Piotrowicz E. The Influence of Hybrid Comprehensive Telerehabilitation on Anxiety in Heart Failure Patients: The TELEREH-HF Randomized Clinical Trial. J Clin Psychol Med Settings. 2024 Jun; 31(2):403-416. PMID: 38108961
  5. Hong C, Liu M, Wojdyla DM, Hickey J, Pencina M, Henao R. Trans-Balance: Reducing demographic disparity for prediction models in the presence of class imbalance. J Biomed Inform. 2024 Jan; 149:104532. PMID: 38070817; PMCID: PMC10850917; DOI: 10.1016/j.jbi.2023.104532;
  6. Overgaard SM, Graham MG, Brereton T, Pencina MJ, Halamka JD, Vidal DE, Economou-Zavlanos NJ. Implementing quality management systems to close the AI translation gap and facilitate safe, ethical, and effective health AI solutions. NPJ Digit Med. 2023 Nov 25; 6(1):218. PMID: 38007604; PMCID: PMC10676432; DOI: 10.1038/s41746-023-00968-8;
  7. Khan SS, Coresh J, Pencina MJ, Ndumele CE, Rangaswami J, Chow SL, Palaniappan LP, Sperling LS, Virani SS, Ho JE, Neeland IJ, Tuttle KR, Rajgopal Singh R, Elkind MSV, Lloyd-Jones DM. Novel Prediction Equations for Absolute Risk Assessment of Total Cardiovascular Disease Incorporating Cardiovascular-Kidney-Metabolic Health: A Scientific Statement From the American Heart Association. Circulation. 2023 Dec 12; 148(24):1982-2004. PMID: 37947094
  8. Khan SS, Matsushita K, Sang Y, Ballew SH, Grams ME, Surapaneni A, Blaha MJ, Carson AP, Chang AR, Ciemins E, Go AS, Gutierrez OM, Hwang SJ, Jassal SK, Kovesdy CP, Lloyd-Jones DM, Shlipak MG, Palaniappan LP, Sperling L, Virani SS, Tuttle K, Neeland IJ, Chow SL, Rangaswami J, Pencina MJ, Ndumele CE, Coresh J. Development and Validation of the American Heart Association's PREVENT Equations. Circulation. 2024 Feb 06; 149(6):430-449.View Related Profiles. PMID: 37947085; PMCID: PMC10910659; DOI: 10.1161/CIRCULATIONAHA.123.067626;
  9. Youssef A, Pencina M, Thakur A, Zhu T, Clifton D, Shah NH. External validation of AI models in health should be replaced with recurring local validation. Nat Med. 2023 Nov; 29(11):2686-2687. PMID: 37853136
  10. Mallya P, Stevens LM, Zhao J, Hong C, Henao R, Economou-Zavlanos N, Wojdyla DM, Schibler T, Manchanda V, Pencina MJ, Hall JL. Facilitating Harmonization of Variables in Framingham, MESA, ARIC, and REGARDS Studies Through a Metadata Repository. Circ Cardiovasc Qual Outcomes. 2023 Nov; 16(11):e009938. PMID: 37850400; PMCID: PMC10841164; DOI: 10.1161/CIRCOUTCOMES.123.009938;
Showing 10 of 408 results. Show More

This graph shows the total number of publications by year, by first, middle/unknown, or last author.

Bar chart showing 407 publications over 21 distinct years, with a maximum of 35 publications in 2013


In addition to these self-described keywords below, a list of MeSH based concepts is available here.

cardiovascular disease risk prediction model development
statistics in medicine
data science
machine learning
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