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J Am Med Inform Assoc. 2015 Jan;22(1):179-91. doi: 10.1136/amiajnl-2014-002649. Epub 2014 Jul 22.

Validating drug repurposing signals using electronic health records: a case study of metformin associated with reduced cancer mortality.

Author information

1
The University of Texas School of Biomedical Informatics at Houston, Houston, Texas, USA.
2
Department of Thoracic Surgery, Vanderbilt University School of Medicine, Nashville, Tennessee, USA Division of Epidemiology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
3
Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
4
Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, USA.
5
Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
6
Division of Epidemiology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
7
Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
8
Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
9
Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
10
Department of Biomedical Informatics, Columbia University, New York, New York, USA.
11
Department of Thoracic Surgery, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
12
Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA Department of Pharmacology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.

Abstract

OBJECTIVES:

Drug repurposing, which finds new indications for existing drugs, has received great attention recently. The goal of our work is to assess the feasibility of using electronic health records (EHRs) and automated informatics methods to efficiently validate a recent drug repurposing association of metformin with reduced cancer mortality.

METHODS:

By linking two large EHRs from Vanderbilt University Medical Center and Mayo Clinic to their tumor registries, we constructed a cohort including 32,415 adults with a cancer diagnosis at Vanderbilt and 79,258 cancer patients at Mayo from 1995 to 2010. Using automated informatics methods, we further identified type 2 diabetes patients within the cancer cohort and determined their drug exposure information, as well as other covariates such as smoking status. We then estimated HRs for all-cause mortality and their associated 95% CIs using stratified Cox proportional hazard models. HRs were estimated according to metformin exposure, adjusted for age at diagnosis, sex, race, body mass index, tobacco use, insulin use, cancer type, and non-cancer Charlson comorbidity index.

RESULTS:

Among all Vanderbilt cancer patients, metformin was associated with a 22% decrease in overall mortality compared to other oral hypoglycemic medications (HR 0.78; 95% CI 0.69 to 0.88) and with a 39% decrease compared to type 2 diabetes patients on insulin only (HR 0.61; 95% CI 0.50 to 0.73). Diabetic patients on metformin also had a 23% improved survival compared with non-diabetic patients (HR 0.77; 95% CI 0.71 to 0.85). These associations were replicated using the Mayo Clinic EHR data. Many site-specific cancers including breast, colorectal, lung, and prostate demonstrated reduced mortality with metformin use in at least one EHR.

CONCLUSIONS:

EHR data suggested that the use of metformin was associated with decreased mortality after a cancer diagnosis compared with diabetic and non-diabetic cancer patients not on metformin, indicating its potential as a chemotherapeutic regimen. This study serves as a model for robust and inexpensive validation studies for drug repurposing signals using EHR data.

KEYWORDS:

drug repurposing; electronic health records; metformin; natural language processing

PMID:
25053577
PMCID:
PMC4433365
DOI:
10.1136/amiajnl-2014-002649
[Indexed for MEDLINE]
Free PMC Article

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