The current standard to assess chemotherapy tolerability relies on patient self-reporting. However, as the sole mechanism of managing symptom burden, this may be inconsistent and fraught with bias. Mobile wearable health devices have the ability to monitor and aggregate objective activity and sleep data over long periods of time, but have not been systematically used in the oncology clinic. The aim of the study was to assess whether the use of mobile wearable technology establishes patterns of "sleep" and "wake" states in newly diagnosed Multiple Myeloma (NDMM) patients receiving therapy, and whether these patterns differ over time.


Patients presenting to the myeloma clinic at Memorial Sloan Kettering Cancer Center (MSKCC) with a new diagnosis of Multiple Myeloma and smart phone or tablet (iOS or Android) compatible with the Garmin Vivofit device were offered to participate in a mobile wearable bio-monitoring study. All eligible participants were required to receive primary chemotherapy treatment at a MSKCC facility. Treatment was determined by physician. NDMM patients were assigned to one of two cohorts (20 in each; Cohort A - patients <65 years; Cohort B - patients ≥ 65 years). Patients were given Garmin Vivofit devices and asked to download a Garmin Vivofit application and Medidata electronic patient reported outcome (ePRO) application on their phone or tablet. Patients were bio-monitored for physical activity and sleep during baseline period (1-7 days prior to chemotherapy initiation) and continuously up to 6 cycles of chemotherapy. Additionally, patients completed mobile ePRO questionnaires [(EORTC - QLQC30 and MY20) and brief pain inventory scales (BPI)] using the Medidata application at baseline and after each induction cycle. Activity, sleep data, and completed ePRO questionnaire data were automatically synced or transferred to Medidata Rave database through Medidata Sensorlink technology. In this abstract, we report initial results on prospective collection of activity measurements. Additional data from the health-related quality of life questionnaires and clinical outcomes will be presented at later date.


Between February 2017-March 2018, 37 patients (19 males and 18 females) enrolled onto the study, with 20 in cohort A and 17 in cohort B. The mean age was 55 years (range 41-64) for cohort A and 72 years (range 65-82) for cohort B. Treatment regimens included Carfilzomib/Revlimid/Dexamethasone 14(38%), Velcade/Revlimid/Dexamethasone 10(27%), Daratumumab/Carfilzomib Revlimid/Dexamethasone, 7(19%), Cyclophosphamide/Velcade/Dexamethasone 3(8%), Revlimid/Dexamethasone 2(5%), and Velcade/Revlimid/Dexamethasone-Lite 1(3%). Twenty-four patients have completed the trial, and 7 remain active. Six patients came off-study due to the following reasons: lost devices (n=4), intolerable rash during cycle 3 (n=1), and incompletion of baseline activity (n=1). Three patients were excluded for incomplete data sets with no baseline data collection at the time of analysis. Fifteen patients were available for data review including 10 in cohort A and 5 in cohort B.

Mean activity for cohort A was 6,437 steps/24 hr period (1,002 - 12,754) versus for cohort B was 3,218.37 steps/24 hr period (387 - 6,155) (p <0.05). In comparing pre- and post-therapy, overall mean activity for cohort A increased from 5,995 to 6,513 steps/24 hr, 8.6% increase (p=0.78), and for cohort B mean activity increased from 2,249 to 3,420 steps/24 hr, a 52% increase (p=0.2140). We assessed short term effects therapy initiation had on activity for NDMM patients by comparing percent changes in activity (steps/24 hrs) from baseline period to cycle 1 period. We found 3 patients had a >100% increase, 1 patient had 50-100% increase, and 11 patients had within +/- 50% change in activity from baseline.


Electronic mobile wearable device monitoring in symptomatic NDMM patients may be a useful tool to assess a patient's overall wellness and health as they are receiving chemotherapy. For three patients, we were able to capture a dramatic increase in activity after initiation of treatment. Overall activity in the elderly NDMM patients is decreased compared to younger patients. Mobile wearable monitoring may be an even more useful strategy for tracking elderly and unfit patients that are more prone to side effects, where the balance of response versus quality of life is paramount.


Mailankody:Physician Education Resource: Honoraria; Janssen: Research Funding; Takeda: Research Funding; Juno: Research Funding. Hassoun:Oncopeptides AB: Research Funding. Lesokhin:Squibb: Consultancy, Honoraria; Serametrix, inc.: Patents & Royalties: Royalties; Janssen: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; Genentech: Research Funding; Takeda: Consultancy, Honoraria. Smith:Celgene: Consultancy, Patents & Royalties: CAR T cell therapies for MM, Research Funding. Shah:Amgen: Research Funding; Janssen: Research Funding. Landgren:Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Research Funding; Pfizer: Consultancy; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Consultancy. Korde:Amgen: Research Funding.

Author notes


Asterisk with author names denotes non-ASH members.

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