Purpose Older adults are vulnerable to chemotherapy toxicity; however, there are limited data to identify those at risk. The goals of this study are to identify risk factors for chemotherapy toxicity in older adults and develop a risk stratification schema for chemotherapy toxicity. Patients and Methods Patients age ≥ 65 years with cancer from seven institutions completed a prechemotherapy assessment that captured sociodemographics, tumor/treatment variables, laboratory test results, and geriatric assessment variables (function, comorbidity, cognition, psychological state, social activity/support, and nutritional status). Patients were followed through the chemotherapy course to capture grade 3 (severe), grade 4 (life-threatening or disabling), and grade 5 (death) as defined by the National Cancer Institute Common Terminology Criteria for Adverse Events. Results In total, 500 patients with a mean age of 73 years (range, 65 to 91 years) with stage I to IV lung (29%), GI (27%), gynecologic (17%), breast (11%), genitourinary (10%), or other (6%) cancer joined this prospective study. Grade 3 to 5 toxicity occurred in 53% of the patients (39% grade 3, 12% grade 4, 2% grade 5). A predictive model for grade 3 to 5 toxicity was developed that consisted of geriatric assessment variables, laboratory test values, and patient, tumor, and treatment characteristics. A scoring system in which the median risk score was 7 (range, 0 to 19) and risk stratification schema (risk score: percent incidence of grade 3 to 5 toxicity) identified older adults at low (0 to 5 points; 30%), intermediate (6 to 9 points; 52%), or high risk (10 to 19 points; 83%) of chemotherapy toxicity (P < .001). Conclusion A risk stratification schema can establish the risk of chemotherapy toxicity in older adults. Geriatric assessment variables independently predicted the risk of toxicity.

A B S T R A C T PurposeTo update the International Society of Geriatric Oncology (SIOG) 2005 recommendations on geriatric assessment (GA) in older patients with cancer. MethodsSIOG composed a panel with expertise in geriatric oncology to develop consensus statements after literature review of key evidence on the following topics: rationale for performing GA; findings from a GA performed in geriatric oncology patients; ability of GA to predict oncology treatment-related complications; association between GA findings and overall survival (OS); impact of GA findings on oncology treatment decisions; composition of a GA, including domains and tools; and methods for implementing GA in clinical care. ResultsGA can be valuable in oncology practice for following reasons: detection of impairment not identified in routine history or physical examination, ability to predict severe treatment-related toxicity, ability to predict OS in a variety of tumors and treatment settings, and ability to influence treatment choice and intensity. The panel recommended that the following domains be evaluated in a GA: functional status, comorbidity, cognition, mental health status, fatigue, social status and support, nutrition, and presence of geriatric syndromes. Although several combinations of tools and various models are available for implementation of GA in oncology practice, the expert panel could not endorse one over another. ConclusionThere is mounting data regarding the utility of GA in oncology practice; however, additional research is needed to continue to strengthen the evidence base.

Purpose To provide guidance regarding the practical assessment and management of vulnerabilities in older patients undergoing chemotherapy. Methods An Expert Panel was convened to develop clinical practice guideline recommendations based on a systematic review of the medical literature. Results A total of 68 studies met eligibility criteria and form the evidentiary basis for the recommendations. Recommendations In patients ≥ 65 years receiving chemotherapy, geriatric assessment (GA) should be used to identify vulnerabilities that are not routinely captured in oncology assessments. Evidence supports, at a minimum, assessment of function, comorbidity, falls, depression, cognition, and nutrition. The Panel recommends instrumental activities of daily living to assess for function, a thorough history or validated tool to assess comorbidity, a single question for falls, the Geriatric Depression Scale to screen for depression, the Mini-Cog or the Blessed Orientation-Memory-Concentration test to screen for cognitive impairment, and an assessment of unintentional weight loss to evaluate nutrition. Either the CARG (Cancer and Aging Research Group) or CRASH (Chemotherapy Risk Assessment Scale for High-Age Patients) tools are recommended to obtain estimates of chemotherapy toxicity risk; the Geriatric-8 or Vulnerable Elders Survey-13 can help to predict mortality. Clinicians should use a validated tool listed at ePrognosis to estimate noncancer-based life expectancy ≥ 4 years. GA results should be applied to develop an integrated and individualized plan that informs cancer management and to identify nononcologic problems amenable to intervention. Collaborating with caregivers is essential to implementing GA-guided interventions. The Panel suggests that clinicians take into account GA results when recommending chemotherapy and that the information be provided to patients and caregivers to guide treatment decision making. Clinicians should implement targeted, GA-guided interventions to manage nononcologic problems. Additional information is available at www.asco.org/supportive-care-guidelines .

Screening tools do not replace GA but are recommended in a busy practice in order to identify those patients in need of full GA. If abnormal, screening should be followed by GA and guided multidisciplinary interventions. Several tools are available with different performance for various parameters (including sensitivity for addressing the need for further GA). Further research should focus on the ability of screening tools to build clinical pathways and to predict different outcome parameters.

This study externally validated a chemotherapy toxicity predictive model for older adults with cancer. This predictive model should be considered when discussing the risks and benefits of chemotherapy with older adults.