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

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.
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.

  1. Pencina MJ, Steyerberg EW, D'Agostino RB. Single-number summary and decision analytic measures can happily coexist. Stat Med. 2019 Feb 10; 38(3):499-500.View Related Profiles. PMID: 30609149.
  2. Pencina MJ, Navar AM, Wojdyla D, Sanchez RJ, Khan I, Elassal J, D'Agostino RB, Peterson ED, Sniderman AD. Quantifying Importance of Major Risk Factors for Coronary Heart Disease. Circulation. 2018 Dec 07.View Related Profiles. PMID: 30586759.
  3. Rosenstock J, Perkovic V, Johansen OE, Cooper ME, Kahn SE, Marx N, Alexander JH, Pencina M, Toto RD, Wanner C, Zinman B, Woerle HJ, Baanstra D, Pfarr E, Schnaidt S, Meinicke T, George JT, von Eynatten M, McGuire DK. Effect of Linagliptin vs Placebo on Major Cardiovascular Events in Adults With Type 2 Diabetes and High Cardiovascular and Renal Risk: The CARMELINA Randomized Clinical Trial. JAMA. 2018 Nov 09. PMID: 30418475.
  4. Thanassoulis G, Sniderman AD, Pencina MJ. A Long-term Benefit Approach vs Standard Risk-Based Approaches for Statin Eligibility in Primary Prevention. JAMA Cardiol. 2018 Nov 01; 3(11):1090-1095. PMID: 30422172.
  5. Robinson JG, Williams KJ, Gidding S, Borén J, Tabas I, Fisher EA, Packard C, Pencina M, Fayad ZA, Mani V, Rye KA, Nordestgaard BG, Tybjærg-Hansen A, Douglas PS, Nicholls SJ, Pagidipati N, Sniderman A. Eradicating the Burden of Atherosclerotic Cardiovascular Disease by Lowering Apolipoprotein B Lipoproteins Earlier in Life. J Am Heart Assoc. 2018 Oct 16; 7(20):e009778. PMID: 30371276.
  6. Sniderman AD, Thanassoulis G, Wilkins JT, Furberg CD, Pencina M. Sick Individuals and Sick Populations by Geoffrey Rose: Cardiovascular Prevention Updated. J Am Heart Assoc. 2018 Oct 02; 7(19):e010049. PMID: 30371337.
  7. Pencina KM, D'Agostino RB, Vasan RS, Pencina MJ. Microsimulation model to predict incremental value of biomarkers added to prognostic models. J Am Med Inform Assoc. 2018 Oct 01; 25(10):1382-1385.View Related Profiles. PMID: 30169699.
  8. Carin L, Pencina MJ. On Deep Learning for Medical Image Analysis. JAMA. 2018 Sep 18; 320(11):1192-1193. PMID: 30422287.
  9. Pagidipati NJ, Hellkamp AS, Sharma PP, Wang TY, Fonarow GC, Pencina M. High-sensitivity C-reactive protein elevation in patients with prior myocardial infarction in the United States. Am Heart J. 2018 Oct; 204:151-155. PMID: 30121016.
  10. O'Brien EC, Holmes DN, Thomas L, Singer DE, Fonarow GC, Mahaffey KW, Kowey PR, Hylek EM, Pokorney SD, Ansell JE, Pencina MJ, Peterson ED, Piccini JP. Incremental prognostic value of renal function for stroke prediction in atrial fibrillation. Int J Cardiol. 2019 Jan 01; 274:152-157.View Related Profiles. PMID: 30144994.
Showing 10 of 327 results. Show More

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

Bar chart showing 327 publications over 16 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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801 Massachusetts Ave Crosstown Center
Boston MA 02118
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