University of Alabama Birmingham, Birmingham, AL
Grant Richard Williams , Chen Dai , Mustafa Al Obaidi , Smith Giri , Kelly Kenzik , Andrew Michael McDonald , Crystal Young Smith , Olumide B. Gbolahan , Ravi Kumar Paluri , Joshua Richman , Smita Bhatia
Background: Chronologic age is an imperfect predictor of morbidity and mortality in older patients with newly-diagnosed GI malignancies. Identifying patients with GI malignancies that are at increased risk of mortality within the 1st year remains challenging given no prior studies have focused on this population, yet is critical to developing personalized treatment plans. To fill this gap, we examined predictors of 1y mortality using variables from a patient-reported GA in a prospective cohort of older adults with GI malignancies. Methods: Cancer and Aging Resilience Evaluation (CARE) is a prospective registry of older adults (≥60y) with cancer seen at UAB (J Geri Onc 2019; PMID 31005648). Patients with GI malignancies with GA completed within the timeframe of 3 mo. before and up to 6 mo. after diagnosis were included. Vital status (up to 12/7/2019) was ascertained by linking participants to LexisNexis. Multivariable Cox regression analysis was used to estimate associations between GA variables and 1y mortality, adjusting for age at cancer diagnosis, race, cancer stage (IV vs. I-III), cancer group (high risk: pancreatic, hepatobiliary, esophageal vs. low risk: colorectal, GIST, neuroendocrine, etc.), and planned chemotherapy (yes/no). Results: A total of 356 participants met eligibility criteria. Mean age at enrollment was 70y; 56.4% were females; 25% black; 47.1% had high-risk cancers. In unadjusted analysis, high-risk cancers, cancer stage, malnutrition, impaired performance status, limitations in social activities, impaired instrumental activities of daily living (IADL), physical health, mental health, anxiety, and ≥3 comorbidities were associated with higher 1y mortality. Our base model (demographic and clinical variables) demonstrated good discrimination (c statistic 0.758), but was improved with the addition of all significant GA variables (c-statistic 0.810). Fatigue and malnutrition were identified as the strongest predictors among the GA variables, and a model adding those to the base model retained high discrimination (c-statistic 0.804). The estimated 1yr survival was 53.1% for those with both fatigue and malnutrition compared to 88.1% in those with neither. Conclusions: Among older adults with GI malignancies, malnutrition and fatigue were the strongest GA predictors of 1yr mortality after adjusting for age and clinical factors. These findings provide evidence for developing targeted interventions in older patients with newly-diagnosed GI malignancies to reduce 1y mortality.
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Abstract Disclosures
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