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Background: Structured care processes that provide a framework for how oncologists can incorporate geriatric assessment (GA) into clinical practice could improve outcomes for vulnerable older adults with cancer, a growing population at high risk of toxicity from cancer treatment. We sought to obtain consensus from an expert panel on the use of GA in clinical practice and to develop algorithms of GA-guided care processes. Methods: The Delphi technique, a well-recognized structured and reiterative process to reach consensus, was used. Participants were geriatric oncology experts who attended NIH-funded U13 or Cancer and Aging Research Group conferences. Consensus was defined as an interquartile range of 2 or more units, or 66.7% or greater, selecting a utility/helpfulness rating of 7 or greater on a 10-point Likert scale. For nominal data, consensus was defined as agreement among 66.7% or more of the group. Results: From 33 invited, 30 participants completed all 3 rounds. Most experts (75%) used GA in clinical care, and the remainder were involved in geriatric oncology research. The panel met consensus that “all patients aged 75 years or older and those who are younger with age-related health concerns” should undergo GA and that all domains (function, physical performance, comorbidity/polypharmacy, cognition, nutrition, psychological status, and social support) should be included. Consensus was met for how GA could guide nononcologic interventions and cancer treatment decisions. Algorithms for GA-guided care processes were developed. Conclusions: This Delphi investigation of geriatric oncology experts demonstrated that GA should be performed for older patients with cancer to guide care processes.

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

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.