# Quantifying and improving radiotherapy outcomes among Veterans

> **NIH VA IK2** · PORTLAND VA MEDICAL CENTER · 2020 · —

## Abstract

For more than a century, radiation has been used as an effective therapeutic modality
for many different cancers and other diseases. Today, radiation therapy is clinically indicated for
more than half of all cancer patients, with the ability to provide cure, local or regional control,
and symptomatic palliation depending upon the clinical context. However, radiation can leave a
lasting mark on the normal tissues left behind. In particular, it has long been known that ionizing
radiation can promote cancer in otherwise normal tissue. While it is relatively rare for an
individual to develop a secondary malignancy (radiation-induced cancer following treatment for
a separate cancer), actual estimates of this rate vary widely according to different studies.
Furthermore, patient-level discussions of secondary malignancy rates are understandably
variable, neglect any understanding of the role of radiation dose or treatment site, and are
generally universal assumptions not tailored to the disease or the patient themselves.
 My goal is to better understand the individualized risk of cancer induced by ionizing
radiation. My central hypothesis is that individual genetic variability is likely to modify the risks of
radiation-induced malignancy. However we have poor quantitative insights and an overall
incomplete picture of the identity, nature, and effect size of genetic determinants of these risks.
The ultimate goal of this proposal is to develop improved risk prediction frameworks
incorporating prospective genetic stratification. This would be invaluable for treatment-related
clinical decision-making, patient counseling, and tailoring post-radiation screening paradigms.
 I plan to test my central hypothesis by pursuing the following three Specific Aims:
Aim 1. Identify a high-confidence cohort of Veterans receiving radiation therapy
Aim 2. Characterize second and secondary malignancy rates within the VA
Aim 3. Quantify genetic risk factors of radiation-induced secondary malignancies
 To accomplish these aims, I will first implement, validate, and apply automated dose
quantification tools to national-level cohort data from the VA Corporate Data Warehouse (CDW),
to extract radiotherapy details such as date, modality, dose, and fractionation, among other
clinically important radiotherapy treatment variables. I will then identify new cancer diagnos(es)
following initial cancer treatment and perform propensity matching of second cancer risk for
Veterans exposed or unexposed to radiotherapy. Moreover, I will quantify second and
presumed secondary malignancy rates among individuals as a function of estimated integral
radiation dose. Using genetic data from the Million Veteran Program (MVP), I will measure
enrichment and potential functional significance of genetic variants among a cohort of Veterans
with radiation-induced secondary malignancy. I will also identify putative DNA repair defects and
other rare variants in known cancer predisposition genes among Vetera...

## Key facts

- **NIH application ID:** 9892367
- **Project number:** 1IK2CX002049-01
- **Recipient organization:** PORTLAND VA MEDICAL CENTER
- **Principal Investigator:** Reid Thompson
- **Activity code:** IK2 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2020
- **Award amount:** —
- **Award type:** 1
- **Project period:** 2020-01-01 → 2024-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9892367

## Citation

> US National Institutes of Health, RePORTER application 9892367, Quantifying and improving radiotherapy outcomes among Veterans (1IK2CX002049-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9892367. Licensed CC0.

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