ABSTRACT
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 HealthP30 CA 008748, Awards - Kroll Award 2019.
ABSTRACT
AKT inhibitors have promising activity in AKT1 E17K-mutant estrogen receptor (ER)-positive metastatic breast cancer, but the natural history of this rare genomic subtype remains unknown. Utilizing AACR Project GENIE, an international clinicogenomic data-sharing consortium, we conducted a comparative analysis of clinical outcomes of patients with matched AKT1 E17K-mutant (n = 153) and AKT1-wild-type (n = 302) metastatic breast cancer. AKT1-mutant cases had similar adjusted overall survival (OS) compared with AKT1-wild-type controls (median OS, 24.1 vs. 29.9, respectively; P = 0.98). AKT1-mutant cases enjoyed longer durations on mTOR inhibitor therapy, an observation previously unrecognized in pivotal clinical trials due to the rarity of this alteration. Other baseline clinicopathologic features, as well as durations on other classes of therapy, were broadly similar. In summary, we demonstrate the feasibility of using a novel and publicly accessible clincogenomic registry to define outcomes in a rare genomically defined cancer subtype, an approach with broad applicability to precision oncology. SIGNIFICANCE: We delineate the natural history of a rare genomically distinct cancer, AKT1 E17K-mutant ER-positive breast cancer, using a publicly accessible registry of real-world patient data, thereby illustrating the potential to inform drug registration through synthetic control data.See related commentary by Castellanos and Baxi, p. 490.
