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.

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:

- 65 years of age or older

- Diagnosis of multiple myeloma

- Newly diagnoses or needing a new line of therapy and have not yet made a treatment
decision

- Must be able to understand English

Exclusion Criteria:

- Any patient who cannot understand written or spoken English

- Any prisoner and/or other vulnerable persons as defined by NIH (45 CFR 46, Subpart B,
C, and D)