EClinicalMedicine (Mar 2023)

Association of patient activity bio-profiles with health-related quality of life in patients with newly diagnosed multiple myeloma: a prospective observational cohort studyResearch in context

  • Neha Korde,
  • Elizabet Tavitian,
  • Donna Mastey,
  • Joseph Lengfellner,
  • Gil Hevroni,
  • Andrew Zarski,
  • Meghan Salcedo,
  • Sham Mailankody,
  • Hani Hassoun,
  • Eric L. Smith,
  • Malin Hultcrantz,
  • Urvi Shah,
  • Carlyn Tan,
  • Benjamin Diamond,
  • Gunjan Shah,
  • Michael Scordo,
  • Oscar Lahoud,
  • David J. Chung,
  • Heather Landau,
  • Sergio Giralt,
  • Andriy Derkach,
  • Thomas M. Atkinson,
  • Paul Sabbatini,
  • Francesca König,
  • Saad Z. Usmani,
  • Ola Landgren,
  • Alexander M. Lesokhin

Journal volume & issue
Vol. 57
p. 101854

Abstract

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Summary: Background: Due to the nature of their disease, patients with multiple myeloma (MM) often have bone disease-related pain that limits physical activity and diminishes health-related quality of life (HRQOL). Digital health technology with wearables and electronic patient reported outcome (ePRO) tools can provide insights into MM HRQoL. Methods: In this prospective observational cohort study conducted at Memorial Sloan Kettering Cancer in NY, NY, USA, patients with newly diagnosed MM (n = 40) in two cohorts (Cohort A – patients <65 years; Cohort B – patients ≥65 years) were passively remote-monitored for physical activity at baseline and continuously for up to 6 cycles of induction therapy from Feb 20, 2017 to Sep 10, 2019. The primary endpoint of the study was to determine feasibility of continuous data capture, defined as 13 or more patients of each 20-patient cohort compliant with capturing data for ≥16 h of a 24-hr period in ≥60% of days of ≥4 induction cycles. Secondary aims explored activity trends with treatment and association to ePRO outcomes. Patients completed ePRO surveys (EORTC - QLQC30 and MY20) at baseline and after each cycle. Associations between physical activity measurements, QLQC30 and MY20 scores, and time from the start of treatment were estimated using a linear mixed model with a random intercept. Findings: Forty patients were enrolled onto study, and activity bioprofiles were compiled among 24/40 (60%) wearable user participants (wearing the device for at least one cycle). In an intention to treat feasibility analysis, 21/40 (53%) patients [12/20 (60%) Cohort A; 9/20 (45%) Cohort B] had continuous data capture. Among data captured, overall activity trended upward cycle over cycle for the entire study cohort (+179 steps/24 h per cycle; p = 0.0014, 95% CI: 68–289). Older patients (age ≥65 years) had higher increases in activity (+260 steps/24 h per cycle; p < 0.0001, 95% CI: −154 to 366) compared to younger patients (+116 steps/24 h per cycle; p = 0.21, 95% CI: −60 to 293). Activity trends associated with improvement of ePRO domains, including physical functioning scores (p < 0.0001), global health scores (p = 0.02), and declining disease burden symptom scores (p = 0.042). Interpretation: Our study demonstrates that feasibility of passive wearable monitoring is challenging in a newly diagnosed MM patient population due to patient use. However, overall continuous data capture monitoring remains high among willing user participants. As therapy is initiated, we show improving activity trends, mainly in older patients, and that activity bioprofiles correlate with traditional HRQOL measurements. Funding: Grants –National Institutes of Health P30 CA 008748, Awards – Kroll Award 2019.

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