Integrating Touchscreen-based Geriatric Assessment and Frailty Screening for Adults With Multiple Myeloma

With rapid advances in research, clinicians are challenged to remain current on evolving treatment and supportive care guidelines for the management of Multiple Myeloma, particularly in older adults who present with various degrees of vulnerability to treatment complications. The global population is rapidly growing, and the number of people >80 years is expected to quadruple between 2000 and 2050. According to the International Myeloma Working Group (IMWG), more than 60% of multiple myeloma (MM) diagnoses and nearly 75% of deaths occur in patients over 65 years of age.1 Older patients experience more toxicity, especially with multidrug combinations, and historical treatment approaches for older adults with MM have included dose reductions or avoidance of treatment based on age and performance status alone, despite the poor predictive value of these variables for patient outcomes. Recent studies conclude that while chronological age is an important consideration when making treatment decisions for hematologic malignancies, functional status is more predictive of treatment outcomes. Thus it is important to factor variables beyond age into treatment for the older adult MM patient population, including functional and physical performance and comorbidity.

The Comprehensive Geriatric Assessment (CGA) is a global health evaluation of older adults that extends beyond a disease-focused evaluation in order to identify unrecognized issues amendable to interventions that may prevent future problems.4 The CGA has been used to predict toxicity and survival in patients using the domains of comorbidities, function, cognition, polypharmacy, social support, and depression and/or psychological distress. Most of the studies are in patients with solid tumors and not those with hematologic malignancies. However, there is evidence to support the use of the CGA to predict risk for adverse events and prognosis.

A modified Geriatric Assessment (mGA) tool that utilized age, functional status as determined by assessment of activities of daily living (ADLs) and instrumental activities of daily living (IADLs), plus comorbidity status was used to develop the Palumbo Frailty Index (FI). Frailty is a state of cumulative decline in many physiological systems that results in the diminished resistance to stressors. The FI categorizes patients into groups of fit, intermediate fit, and frail. In a retrospective analysis of data in 867 older adults with MM, toxicity, treatment discontinuation, and survival rates were correlated with the FI. To date, no studies have investigated the prospective ability of the Palumbo frailty index to predict toxicity and treatment outcomes in older adults with MM.

As a result of this retrospective validation work, fit/frailty status can be evaluated for usefulness in the clinical setting by gathering information from a mGA and providing the data to the care provider to guide treatment decisions. The use of decision aids for care and treatment decisions is rapidly growing, given that such aids have been shown to reduce decisional conflict, improve patient-clinician communication, improve the alignment of values and choice, and reduce the use of low value interventions. Use of decision aids is of growing interest as we shift to value-based cancer care models. Value-based cancer care models require the engagement of patients to better understand patient goals and ensure patients are counseled on the risks and benefits of various treatment options.

For older patients, GAs are not routinely performed because they are complex and time-consuming, the optimal tools for administering the GA accurately and efficiently have not been established, many clinicians lack knowledge about how to incorporate GA into decision-making and care of older adults, and integration of a GA into a Health Information System platform has not been adequately studied for feasibility and usage. Hurria and colleagues developed the Cancer Specific Geriatric Assessment (CSGA), a shorter assessment that specifically captures data from seven domains (functional status, comorbid medical conditions, psychological state, cognition, nutritional status, social support, and medications). This CSGA assessment took an average time of 27 minutes to complete.