Integrating Touchscreen-based Geriatric Assessment and Frailty Screening for Adults With Multiple Myeloma
Integrating Touchscreen-based Geriatric Assessment and Frailty Screening for Adults With Multiple Myeloma
The overarching objective of this study is to evaluate the feasibility, usability, and acceptability of an abbreviated, tablet-based geriatric assessment in a population of older 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.
Two recent small studies evaluated feasibility of touchscreen computer based GA, with the majority of older adults in both studies able to complete the assessment. However, the assessment still took an average of 20-27 minutes to complete, which may not be feasible to incorporate into a typical clinical workflow. In one study, although the majority of assessment domains were patient reported, more than half of patients required assistance to complete the touchscreen questionnaires.12 A modified Comprehensive Geriatric Assessment (mCGA) was developed for use in this study to further improve upon feasibility of GA within typical clinical workflow. mCGA domains were chosen by a panel of gero-oncology expert consultants (Drs. Palumbo, Mohile, and Wildes) based on their predictive ability, their length, and the ability to be assessed via patient self-report. The Palumbo frailty index was chosen as the core of the mCGA tool to be used in this study given its development specifically in older adults with multiple myeloma. In addition to the 4 mGA measures comprising the Palumbo FI (age, comorbidity, ADL, and IADL), other GA variables were also added to the mCGA to be used in this study, chosen based on their strong predictive ability in determining toxicity and survival in cancer patients, as well as feasibility of collection in routine clinical practice. In particular, variables needed to complete the Cancer and Aging Research Group's (CARG) "Chemotherapy Toxicity Calculator" (http://www.mycarg.org/SelectQuestionnaire) will be collected in this study, given their strong predictive ability in older adults with solid tumors.
Despite the suggestions that GA/frailty indices could be used to guide therapy selection, the ability to effectively incorporate the use of GA's in to a real-world clinic environment has not yet been established. Thus, in this study, we seek to describe the feasibility of using this shorter mCGA tool, administered via patient self-report on a touchscreen computer, as well as the real-time use and utility by clinicians and the impact of mCGA results on treatment decision-making. These data will be quantitatively assessed through review of patient records, Carevive platform extracts of treatment data, as well as a uniquely designed questionnaire to evaluate physician use and perceived utility of the GA as a part of the treatment decision-making process, and to gain insight on improving the utility and application of the GA in clinical practices.
By streamlining a validated GA tool into the mCGA, including only those domains that have shown to be most predictive of outcomes (survival and toxicity), and incorporating its use at the point of care, the Carevive ePRO provides an opportunity to both gather richly contextualized data on patient experiences as well as address this gap in quality cancer care.
This is a prospective single arm pilot intervention study, using a post-test only quasi-experimental study design. Patients and their providers will participate in the study intervention and then complete post-intervention questionnaires designed to evaluate the feasibility, usability/acceptability, and physician use and utility of the results of a modified Comprehensive Geriatric Assessment (mCGA), administered via electronic tablet to older adults with multiple myeloma (MM) at a treatment decision-making time point, and displayed back to the clinician at a clinic visit where a treatment decision is being discussed. A combination of provider report and retrospective chart review will be used to assess actual treatment decisions made at time of intervention visit. Patient completion and then summary display of the mCGA to physicians is the main study intervention. To promote informed utilization of the mCGA results, clinicians will also participate in continuing education on the topics of a) treatment of MM in older adults, as well as b) use of mCGA to guide treatment decision-making and supportive care in older adults with cancer.
The tool used for collection of patient-reported and clinical variables comprising the mCGA will be the Carevive electronic patient reported outcomes (Carevive ePRO) platform. This ePRO platform collects both ePRO and clinical data, which are processed by a rules engine that enables display of results back to clinicians in a dynamic summary. The mCGA will be used as both a method of determining frailty status of patients as well as to give a more global picture of the patients' functional and medical status, consistent with goals of geriatric assessment.
Providers will complete post-test measures to evaluate feasibility of the intervention as well as, a) provider report of treatment recommendation made for each patient (rolling basis at each intervention visit directly on the Carevive Dashboard), b) the ways the mCGA results influenced treatment decisions for each patient (treatment decision making questionnaire, rolling basis following each intervention visit), and c) usability/acceptability (comprehensive post-test questionnaire, one-time following completion of patient enrollment) and use/utility (treatment decision making questionnaire, rolling basis following each intervention visit) of the mCGA-based intervention, using questions adapted from Cox and colleagues, Berry and colleagues, Mullen and colleagues and expanded with investigator developed questions. Provider questionnaires will be administered via surveymonkey.com, a survey hosting website, or paper.
Inclusion Criteria:
Exclusion Criteria: