Ms. LILAC: Muscle Mass in the Life and Longevity After Cancer (LILAC) Study

ABSTRACT
There is emerging evidence that cancer and its treatments may accelerate the normal aging
process, increasing the magnitude and rate of decline in functional capacity. This accelerated
aging process is hypothesized to hasten the occurrence of common adverse age-related
outcomes in cancer survivors, including loss of muscle mass and decrease in physical function.
However, there is no data describing age-related loss of muscle mass and its relation to physical
function in the long-term in cancer survivors. This project will directly address three key
methodological challenges in research on cancer survivorship: 1) obtaining accurate measures
of skeletal muscle mass in large population-based cohorts of community dwelling older adults, 2)
disentangling the effect of age versus cancer on the relationship between muscle mass, physical
function (gait speed, balance, strength), and functional decline, and 3) the large sample size
required to understand predictors of low muscle mass using big data (machine learning)
approaches. The D3-creatine dilution method (D3Cr) will be used to obtain a direct measure of
muscle mass remotely, using a protocol that has been previously validated in clinical and
epidemiologic research. This study will measure D3Cr muscle mass in 6614 participants (3044
cancer survivors and 3570 cancer-free controls) in the Women’s Health Initiative (WHI), a large
prospective cohort study (n=161,808) of postmenopausal women with over 25 years of follow-up.
Participants will be drawn from two sub-cohorts embedded within the WHI using an incidence
density sampling approach. Cancer survivors will be drawn from an existing NCI-funded
survivorship cohort, the Life and Longevity After Cancer (LILAC) cohort, and cancer-free controls
will be drawn from the WHI Long Life Study 2. The overall objective of this application is to
examine the antecedents and consequences of low muscle mass in cancer survivors, using
innovative methods to overcome major sources of bias common in cancer research. The study
aims are to: 1) create age-standardized muscle mass percentile curves and z-scores to
characterize the distribution of D3- muscle mass in cancer survivors and non-cancer controls, 2)
compare muscle mass, physical function, and functional decline in cancer survivors and non-
cancer controls, and 3) use machine learning approaches to generate multivariate risk-prediction
algorithms to detect low muscle mass. This project addresses an urgent need identified by the
NCI for research in older and long-term cancer survivors. The results of this study will be used to
develop interventions to mitigate the harmful effects of low muscle mass in older adults and
promote healthy survivorship in cancer survivors in the old (>65) and oldest-old (>85) age groups.

Grant Number: 3R37CA258761-05S1
NIH Institute/Center: NIH
Principal Investigator: Hailey Banack