This application is being submitted in response to the Notice of Special Interest (NOSI) identified as NOT-CA- 20-036. The overarching goal of this one-year supplement grant proposal is: to evaluate whether sarcopenia is associated with tolerability of treatment for advanced cancer in older patients with age-related conditions. The growing population of older patients remains underrepresented in research that sets cancer care standards leading to significant disparities in outcomes. In our preliminary research, we found that: 1) close to 60% of older patients develop grade 3-5 toxicity (as measured by NCI's clinician-rated Common Terminology Criteria for Adverse Events [CR-CTCAE]); impairment in geriatric assessment (GA) domains were significantly associated with toxicity; 2) 29% of older adults with cancer received chemotherapy at significantly reduced relative dose intensity (RDI); and 3) sarcopenia is highly prevalent (58%) in the geriatric oncology population. U01CA233167 funds secondary analyses of a completed clinical trial to understand how toxicities inform treatment tolerability as part of a NCI U01 tolerability consortium. The operational definition of tolerability we proposed in the U01 is novel because it includes not only adverse outcomes such as toxicity, but also patient-reported outcomes (PROs) valued by older patients. Our analyses utilize data from a completed randomized trial, the GAP study (URCC 13059, clinicaltrials.gov NCT02054741), which evaluated whether provision of a GA summary to oncologists would improve clinical outcomes in adults aged 70+ with advanced cancer receiving treatment (i.e., chemotherapy or other drugs with high risk of toxicity). In this U01 supplement proposal, we will evaluate whether muscle mass (determined by Computed Tomography [CT] scan body composition analysis) is independently associated with treatment tolerability. Our tolerability endpoints include not only toxicity, but also dose intensity, survival, and PROs. Only patients in usual care enrolled to GAP will be included for these analyses (n=369), because many in the intervention group had initial treatment dosages altered based on the GA summary. We will collaborate with Voronoi Health Analytics to accurately measure skeletal muscle mass via CT scan body composition analysis: 1) to determine if sarcopenia is associated with an increased prevalence of grade 3-5 toxicity (CR-CTCAE v4); 2) to determine if sarcopenia is associated with cancer treatment RDI; and 3) to determine if sarcopenia is associated with mortality. Exploratory aims will evaluate if change in muscle mass is associated with clinical outcomes and patient-reported adverse events (as measured by PRO-CTCAE). The team, which includes expertise in clinical trials (Mohile, Mustian, Hezel, Linehan), sarcopenia (Dunne, Hezel, Linehan, Voronoi Health Analytics), geriatric oncology (Mohile and Loh), biostatistics and data science (Culakova, Xu), and PRO measurement (Mohile, Culakova, Loh) is uniquely suited to conduct this research. This research will address a critical gap in knowledge of sarcopenia and its relationship with tolerability of treatment in older patients with advanced cancer and age-related conditions.
The overarching goal of this proposed supplement to U01CA233167 entitled ?Sarcopenia and Treatment Tolerability in Older Patients with Advanced Cancer? is to evaluate whether sarcopenia is associated with treatment tolerability in older adults with advanced cancer and age-related conditions. Our analyses utilize data from a completed randomized trial, the GAP study (URCC 13059, clinicaltrials.gov NCT02054741), which evaluated whether provision of a GA summary to oncologists would improve clinical outcomes in adults aged 70+ with advanced cancer and age-related conditions. This proposal will assess associations between muscle mass and several tolerability metrics, including clinician-rated toxicities (CR-CTCAE), treatment dose intensity, survival, and patient-reported toxicities (PRO-CTCAE) and thus will add significant value to the U01 consortium tolerability analyses.
