Muscle mass and physical function in long-term cancer survivors

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

NIH-funded research State University of New York at Buffalo · NIH-11285496

Researchers will measure muscle mass and walking, balance, and strength in older women with and without prior cancer to learn whether cancer speeds age-related muscle loss.

Quick facts

Grant typeR37 grant
Study typeNIH-funded research
Funding institutionState University of New York at Buffalo NIH-funded
Lab location1 site (Amherst, United States)
Project IDNIH-11285496 on NIH RePORTER

What this research studies

You would provide a D3-creatine dose and return samples so researchers can measure your total muscle mass remotely. The study compares about 3,044 women who survived cancer with 3,570 matched cancer-free women from the Women’s Health Initiative to track changes in muscle and physical function over time. Investigators will combine these direct muscle measures with prior clinical data, physical performance tests (gait speed, balance, strength), and available imaging to separate aging effects from cancer-related effects. Large-scale machine-learning analyses will be used to find predictors of low muscle mass and declining function.

Who could benefit from this research

Good fit: Postmenopausal women enrolled in the Women’s Health Initiative, including long-term cancer survivors and matched cancer-free participants, are the intended candidates.

Not a fit: Men, younger adults, and people not enrolled in the WHI are unlikely to be eligible or directly benefit, and the project does not test treatments so immediate clinical benefit is unlikely.

Why it matters

Potential benefit: If successful, this work could identify survivors at high risk for muscle loss and inform targeted strategies to preserve strength and independence.

How similar studies have performed: The D3-creatine dilution method is validated for measuring muscle mass, but applying it at this large scale to long-term cancer survivors combined with machine-learning is a novel effort.

Where this research is happening

Amherst, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.