# Evaluation of clinical and social factors associated with deficit accumulation trajectories in older survivors with early-stage non-small cell lung cancer

> **NIH NIH K01** · WEILL MEDICAL COLL OF CORNELL UNIV · 2024 · $115,411

## Abstract

Project Summary
Aging involves a gradual clinical decline in cognitive and physical function and often the development of
various comorbidities. However, significant life events, such as cancer diagnosis and treatment, can potentially
accelerate clinical decline and aging. Various individual-level and neighborhood-level social determinants of
health (SDOH) can also accelerate aging in cancer survivors, but a comprehensive approach to identifying and
intervening on multilevel aging risk factors for cancer survivors is lacking. To investigate multilevel aging risk
factors, a reliable measure is needed to quantify aging and monitor dynamic changes in aging-related health
status over time. An electronic deficit accumulation index (eDAI) measures aging-related clinical declines over
time by counting the accumulation of aging-related deficits using electronic health records (EHRs). However,
the eDAI in cancer research has primarily been used at the time of diagnosis to manage comorbidity and
reduce treatment toxicity, but it has been understudied in the context of cancer survivorship and aging
trajectories. The broad goal of this project is to evaluate dynamic changes in aging-related clinical decline in
cancer survivors using eDAI through real-world data analytics, identify multilevel determinants associated with
SDOH disparities in clinical decline, and highlight potential interventions for healthy aging. Lung cancer is an
ideal disease setting for achieving these goals. Lung cancer is the leading cause of cancer death, with a
median age at diagnosis of 71 years. With recent increases in survival due to screening and new treatment
paradigms, this disease is becoming a chronic disease of older age. More importantly, while cancer survivors
are traditionally defined as people who survive long after treatment completion, many lung cancer patients live
for a long time while still undergoing active treatment, highlighting the importance of longitudinal exposures to
treatment or other time-varying risk factors on aging. Given that aging is also an evolving process, studying
dynamic longitudinal risk factors for aging in lung cancer survivors could serve as a useful model in aging
epidemiologic research. The study cohort will comprise >89,000 survivors (age≥65) with early-stage non-small
cell lung cancer who are healthy (i.e., including both robust [eDAI<0.2] and pre-clinical decline [eDAI: 0.2-
0.34]) at diagnosis in SEER-Medicare (2013-2017). The primary outcome will be the time to clinical decline
(eDAI≥0.35). The aims are (AIM 1) to identify key individual-level risk factors affecting clinical decline, (AIM 2)
to investigate neighborhood-level SDOH to develop a comprehensive risk prediction model for clinical decline,
and (AIM 3) to conduct real-world validation using an integrated EHR database of academic and community
healthcare systems. Completing these research aims and training goals (in real-world data analytics, SDOH
disparities, and aging epidemi...

## Key facts

- **NIH application ID:** 10950224
- **Project number:** 1K01AG088449-01
- **Recipient organization:** WEILL MEDICAL COLL OF CORNELL UNIV
- **Principal Investigator:** Eunji Choi
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $115,411
- **Award type:** 1
- **Project period:** 2024-08-15 → 2029-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10950224

## Citation

> US National Institutes of Health, RePORTER application 10950224, Evaluation of clinical and social factors associated with deficit accumulation trajectories in older survivors with early-stage non-small cell lung cancer (1K01AG088449-01). Retrieved via AI Analytics 2026-06-14 from https://api.ai-analytics.org/grant/nih/10950224. Licensed CC0.

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