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

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.     

Impact of socio-economic status on hospital length of stay following injury: a multicenter cohort study

Background

Injury is second only to cardiovascular disease in terms of acute care costs in North America. One key to improving injury care efficiency is to generate knowledge on the determinants of resource use. Socio-economic status (SES) is a documented risk factor for injury severity and mortality but its impact on length of stay (LOS) for injury admissions is unknown. This study aimed to examine the relationship between SES and LOS following injury.This multicenter retrospective cohort study was based on adults discharged alive from any trauma center (2007–2012; 57 hospitals; 65,486 patients) in a Canadian integrated provincial trauma system. SES was determined using ecological indices of material and social deprivation. Mean differences in LOS adjusted for age, gender, comorbidities, and injury severity were generated using multivariate linear regression.

Results

Mean LOS was 13.5 days. Patients in the highest quintile of material/social deprivation had a mean LOS 0.5 days (95 % CI 0.1-0.9)/1.4 days (1.1-1.8) longer than those in the lowest quintile. Patients in the highest quintiles of both social and material deprivation had a mean LOS 2.6 days (1.8-3.5) longer than those in the lowest quintiles.

Conclusions

Results suggest that patients admitted for traumatic injury who suffer from high social and/or material deprivation have longer acute care LOS in a universal-access health care system. The reasons behind observed differences need to be further explored but may indicate that discharge planning should take patient SES into consideration.

     

Myofilament lattice structure in presence of a skeletal myopathy-related tropomyosin mutation

Human tropomyosin mutations deregulate skeletal muscle contraction at the cellular level. One key feature is the slowing of the kinetics of force development. The aim of the present study was to characterize the potential underlying molecular mechanisms by recording and analyzing the X-ray diffraction patterns of human membrane-permeabilized muscle cells expressing a particular β-tropomyosin mutation (E41K). During resting conditions, the d_1,0 lattice spacing, Δ_1,0 and I_1,1 to I_1,0 ratio were not different from control values. These results suggest that, in presence of the E41K β-tropomyosin mutation, the myofilament lattice geometry is well maintained and therefore may not have any detrimental influence on the contraction mechanisms and thus, on the rate of force generation.     

Variation in the HTR1A and HTR2A genes and social adjustment in depressed patients

Background

Social adjustment is impaired in depressed patients. The difficulty to adjust to social circumstances has been hypothesized to be one of the causes of depression, as well as a consequence of the disorder. Genetic variation in the serotonin transporter gene has been previously associated with social adjustment levels in patients with mood disorders.

Methods

We investigated whether variations on the HTR1A (rs6295) and HTR2A (rs7997012) genes were associated with levels of social adjustment using the Social Adjustment Scale in two samples of depressed patients (total n=156).

Results

Patients carrying the GG genotype of the HTR2A-rs7997012 showed better social adjustment in areas of work and family unit bonding.

Limitations

These findings did not survive correction for multiple testing and should be interpreted with caution.

Conclusion

Our finding is in line with previous observations that have associated the G allele of the HTR2A-rs7997012 with higher rate of antidepressant response. The HTR2A-rs7997012 is worthy of further investigation in studies examining factors that are related to depression course and outcome.