Grant Details
Grant Number: |
1R21CA263489-01A1 Interpret this number |
Primary Investigator: |
Du, Mengmeng |
Organization: |
Sloan-Kettering Inst Can Research |
Project Title: |
Leveraging Medicare Linkages to Identify New Associations: Prescription Drugs and Digestive Cancer Risk |
Fiscal Year: |
2022 |
Abstract
PROJECT SUMMARY
Nearly 90% of US adults ages 65 and older use prescription drugs; however, surprisingly little is known about
the long-term health effects of these drugs beyond the conditions for which they are indicated. Such
unforeseen risks and benefits, particularly for diseases with a long latency period, such as cancer, are not well
suited to detection in clinical trials, given that such trials are inadequate in size and duration of follow-up to
detect drug-cancer associations. Multiple lines of evidence suggest that use of common prescription drugs may
influence the development of various digestive cancers. However, prior studies have largely focused on broad,
common classes of drugs, rather than individual drugs. The availability of Medicare linkages—featuring an
extremely large diverse population of older adults, detailed prescription drug data, and follow-up for cancer
outcomes—enables the comprehensive scan of associations between individual drugs and cancer risk. Given
the high prevalence of prescription drug use among older adults and increased risk of cancer in this group, it is
especially critical to understand the long-term effects of prescription drugs in aging populations.
We will leverage data from the National Cancer Institute Surveillance, Epidemiology, and End Results Program
(SEER)-Medicare linked database to discover and follow-up novel associations between prescription drugs
and risk of digestive cancer, both overall and specific to the five most common digestive sites (colorectum,
pancreas, stomach, oropharynx, and liver). First, we will conduct a Drug-Wide Association Study (‘DrugWAS’)
to identify associations between prescription drugs and risk of digestive cancers, using bootstrapping to correct
for multiple testing. Second, we will assess the influence of potential confounding by indication by evaluating
whether the associations hold when compared directly to drugs taken for the same indication. For associations
that remain after applying the steps above, we will perform propensity score calibration using additional data
from the Medicare Current Beneficiary Survey (MCBS); this will allow us to estimate associations after
accounting for additional sources of confounding.
Our proposed hybrid approach—integrating a hypothesis-free framework with careful adjustment for multiple
testing and confounding—will identify novel drug signals in older adults and further refine these signals to
those that withstand correction for multiple testing and adjustment for confounding. This exploratory study will
generate hypotheses of novel drug-cancer associations as well as provide impetus for follow-up in resource-
intensive settings. Moreover, we will provide proof of principle for a multi-phased approach that leverages large
publicly available datasets created through decades of NIH investment to identify novel and meaningful cancer
associations; this approach can be applied in long-term surveillance efforts of drug effects on health.
Publications
None