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External Validation of Risk Factors for Unplanned Hospitalization in Older Adults With Advanced Cancer Receiving Chemotherapy

Mostafa R. Mohamed, Kah Poh Loh, Supriya G. Mohile, Michael Sohn, Tracy Webb, Megan Wells, Sule Yilmaz, Rachael Tylock, Eva Culakova, Allison Magnuson, Can-Lan Sun, James Bearden, Judith O. Hopkins, Bryan A. Faller, and Heidi D. Klepin

Background: Older adults (age ≥65 years) receiving chemotherapy are at risk for hospitalization. Predictors of unplanned hospitalization among older adults receiving chemotherapy for cancer were recently published using data from a study conducted by the Cancer and Aging Research Group (CARG). Our study aimed to externally validate these predictors in an independent cohort including older adults with advanced cancer receiving chemotherapy. Methods: This validation cohort included patients (n=369) from the GAP70+ trial usual care arm. Enrolled patients were aged ≥70 years with incurable cancer and were starting a new line of chemotherapy. Previously identified risk factors proposed by the CARG study were ≥3 comorbidities, albumin level <3.5 g/dL, creatinine clearance <60 mL/min, gastrointestinal cancer, ≥5 medications, requiring assistance with activities of daily activities (ADLs), and having someone available to take them to the doctor (ie, presence of social support). The primary outcome was unplanned hospitalization within 3 months of treatment initiation. Multivariable logistic regression was applied including the 7 identified risk factors. Discriminative ability of the fitted model was performed by calculating the area under the receiver operating characteristic (AUC) curve. Results: Mean age of the cohort was 77 years, 45% of patients were women, and 29% experienced unplanned hospitalization within the first 3 months of treatment. The proportions of hospitalized patients with 0–3, 4–5, and 6–7 identified risk factors were 24%, 28%, and 47%, respectively (P=.04). Impaired ADLs (odds ratio, 1.76; 95% CI, 1.04–2.99) and albumin level <3.5 g/dL (odds ratio, 2.23; 95% CI, 1.37–3.62) were significantly associated with increased odds of unplanned hospitalization. The AUC of the model, including the 7 identified risk factors, was 0.65 (95% CI, 0.59–0.71). Conclusions: The presence of a higher number of risk factors was associated with increased odds of unplanned hospitalization. This association was largely driven by impairment in ADLs and low albumin level. Validated predictors of unplanned hospitalization can help with counseling and shared decision-making with patients and their caregivers.

ClinicalTrials.gov identifier: NCT02054741

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Community Oncologists' Decision-Making for Treatment of Older Patients With Cancer

Supriya G. Mohile, Allison Magnuson, Chintan Pandya, Carla Velarde, Paul Duberstein, Arti Hurria, Kah Poh Loh, Megan Wells, Sandy Plumb, Nikesha Gilmore, Marie Flannery, Marsha Wittink, Ronald Epstein, Charles E. Heckler, Michelle Janelsins, Karen Mustian, Judith O. Hopkins, Jane Liu, Srihari Peri, and William Dale

Background: This study's objectives were to describe community oncologists' beliefs about and confidence with geriatric care and to determine whether geriatric-relevant information influences cancer treatment decisions. Methods: Community oncologists were recruited to participate in 2 multisite geriatric oncology trials. Participants shared their beliefs about and confidence in caring for older adults. They were also asked to make a first-line chemotherapy recommendation (combination vs single-agent vs no chemotherapy) for a hypothetical vignette of an older patient with advanced pancreatic cancer. Each oncologist received one randomly chosen vignette that varied on 3 variables: age (72/84 years), impaired function (yes/no), and cognitive impairment (yes/no). Other patient characteristics were held constant. Logistic regression models were used to identify associations between oncologist/vignette-patient characteristics and treatment decisions. Results: Oncologist response rate was 61% (n=305/498). Most oncologists agreed that “the care of older adults with cancer needs to be improved” (89%) and that “geriatrics training is essential” (72%). However, <25% were “very confident” in recognizing dementia or conducting a fall risk or functional assessment, and only 23% reported using the geriatric assessment in clinic. Each randomly varied patient characteristic was independently associated with the decision to treat: younger age (adjusted odds ratio [aOR], 5.01; 95% CI, 2.73–9.20), normal cognition (aOR, 5.42; 95% CI, 3.01–9.76), and being functionally intact (aOR, 3.85; 95% CI, 2.12–7.00). Accounting for all vignettes across all scenarios, 161 oncologists (52%) said they would offer chemotherapy. All variables were independently associated with prescribing single-agent over combination chemotherapy (older age: aOR, 3.22; 95% CI 1.43–7.25, impaired cognition: aOR, 3.13; 95% CI, 1.36–7.20, impaired function: aOR, 2.48; 95% CI, 1.12–5.72). Oncologists' characteristics were not associated with decisions about providing chemotherapy. Conclusion: Geriatric-relevant information, when available, strongly influences community oncologists' treatment decisions.