This training grant is being sought by an MD/PhD student preparing to enter the dissertation phase of his PhD in Clinical Epidemiology. The candidate aspires to become a leading academic independent physician- scientist investigator in the fields of therapeutic effectiveness and pharmacogenetic epidemiology. He will devote 100% of his time to this research and training for the duration of his PhD. His direct experience in epidemiological study design and analysis over the course of completing the dissertation, coupled with carefully selected didactic courses, are designed to make him an expert in the use of advanced statistical and epidemiological methods to identify independent risk factors for effective use of pharmacotherapeutics as well as develop and evaluate prediction models that can help translate that knowledge into clinical practice. Moreover, his training will give him experience in the identification and evaluation of novel endpoints for determining the clinical utility of therapeutic strategies. Throughout this award, he will be mentored by senior experts in cardiovascular epidemiology, pharmacogenetics, therapeutic effectiveness, and biostatistics. The research portion of this award will consist of two complimentary projects designed to help determine which patients will respond poorly to warfarin therapy in order to provide a rational basis for the clinical decision of when to use newer alternative anticoagulant agents. In Project 1, the candidate will develop and internally validate a prediction model that predicts the risk of failure to achieve warfarin maintenance dose by 12 weeks based on a variety of clinical and sociodemographic factors. Additionally, the candidate will assess whether the incorporation of genetic factors leads to clinically meaningful improvement in prediction. In Project 2, the candidate will identify which changes in specific clinical factors after warfarin initiation lead t delay in the achievement of maintenance dose. Both projects will be conducted using the IN-RANGE cohort (whose Principal Investigator is the Sponsor of the candidate), a prospectively collected cohort of patients initiating warfarin therapy with extensive clinical, sociodemographic, and genetic data available. When taken together, the results of these projects will ultimately provide relevant information to clinicians to help them determine which patients should be started on warfarin and to help identify points of intervention to improve clinical response in those patients who do start warfarin therapy.

Public Health Relevance

With the recent approval of new drugs that may serve as alternatives to warfarin for oral anticoagulation therapy, there is uncertainty in the clinical community about when to use which agent. Using data that our group is collecting through the IN-RANGE prospective cohort study, this research will develop and internally validate a prediction model that clinicians can use to identify those patients who are most likely to do poorly on warfarin and, thus, may benefit the most from newer alternative therapies. Additionally, this research will help identify potential targets of intervention to improve respons in patients who have already started warfarin therapy.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Individual Predoctoral NRSA for M.D./Ph.D. Fellowships (ADAMHA) (F30)
Project #
1F30HL115992-01
Application #
8396837
Study Section
Special Emphasis Panel (ZRG1-F16-B (20))
Program Officer
Sarkar, Rita
Project Start
2012-09-01
Project End
2015-08-31
Budget Start
2012-09-01
Budget End
2013-08-31
Support Year
1
Fiscal Year
2012
Total Cost
$42,232
Indirect Cost
Name
University of Pennsylvania
Department
Type
Schools of Medicine
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Finkelman, Brian S; French, Benjamin; Bershaw, Luanne et al. (2016) Predicting prolonged dose titration in patients starting warfarin. Pharmacoepidemiol Drug Saf 25:1228-1235
Finkelman, Brian S; French, Benjamin; Kimmel, Stephen E (2016) The prediction accuracy of dynamic mixed-effects models in clustered data. BioData Min 9:5
Finkelman, Brian S; French, Benjamin; Bershaw, Luanne et al. (2015) Factors affecting time to maintenance dose in patients initiating warfarin. Pharmacoepidemiol Drug Saf 24:228-36
Mamtani, Ronac; Pfanzelter, Nick; Haynes, Kevin et al. (2014) Incidence of bladder cancer in patients with type 2 diabetes treated with metformin or sulfonylureas. Diabetes Care 37:1910-7
Mamtani, Ronac; Haynes, Kevin; Finkelman, Brian S et al. (2014) Distinguishing incident and prevalent diabetes in an electronic medical records database. Pharmacoepidemiol Drug Saf 23:111-8