Background: Clinicians must closely monitor patients for toxicities after chimeric antigen receptor T-cell therapy (CAR-T). Patient-reported outcomes (PROs) (e.g., toxicities, quality of life) and activity data (e.g., steps, sleep) may complement clinicians’ observations. This study tested the feasibility and acceptability of collecting PROs and activity data from patients with hematologic malignancies during CAR-T and explored preliminary data patterns. Methods: Participants wore a Fitbit tracker and completed PROs at several timepoints through 90-days post-infusion. Feasibility was assessed with a priori benchmarks for recruitment (≥50%), retention (≥70%), PRO completion (≥70%), and days wearing the Fitbit (≥50%). Acceptability was assessed with participant satisfaction (a priori benchmark > 2 on a 0–4 scale). Results: Participants (N = 12) were M = 66 years old (SD = 7). Rates of recruitment (68%), retention (83%), PRO completion (85%), and days wearing the Fitbit (85%) indicated feasibility. Satisfaction with completing the PROs (M = 3.2, SD = 0.5) and wearing the Fitbit (M = 2.9, SD = 0.5) indicated acceptability. Preliminary data patterns suggested that participants with better treatment response (vs. progressive disease) had a higher toxicity burden. Conclusions: Longitudinal PRO and activity data collection was feasible and acceptable. Data collected on a larger scale may be used to specify risk prediction models to identify predictors of severe CAR-T-related toxicities and inform early interventions.

Data integration, the processes by which data are aggregated, combined, and made available for use, has been key to the development and growth of many technological solutions. In health care, we are experiencing a revolution in the use of sensors to collect data on patient behaviors and experiences. Yet, the potential of this data to transform health outcomes is being held back. Deficits in standards, lexicons, data rights, permissioning, and security have been well documented, less so the cultural adoption of sensor data integration as a priority for large-scale deployment and impact on patient lives. The use and reuse of trustworthy data to make better and faster decisions across drug development and care delivery will require an understanding of all stakeholder needs and best practices to ensure these needs are met. The Digital Medicine Society is launching a new multistakeholder Sensor Data Integration Tour of Duty to address these challenges and more, providing a clear direction on how sensor data can fulfill its potential to enhance patient lives.

African American men experience a 60% higher incidence of prostate cancer and are more than twice as likely to die from it than White men. Evidence is insufficient to conclude that definitively screening for prostate cancer reduces the likelihood of morbidity or death. Patients are encouraged to discuss screening alternatives with health care providers for informed decision-making (IDM). The extent of IDM in clinical or community setting is not known. This study uses data from a community-based, computer-mediated, IDM intervention that targeted 152 African American aged 40 to 70. Pretest-posttest differences in means for prostate cancer knowledge, screening decisional conflict, and screening decisional self-efficacy were examined by two-tailed t-tests. Overall, the intervention significantly improved respondents’ prostate cancer knowledge (p<.0001), significantly improved decisional self-efficacy (p<.0001) and significantly reduced decisional conflict (p<.0001). Specifically, the intervention significantly promoted IDM among men who reported more education, being married, having financial resources, and younger age.

Inherited variation at MC1R is associated with elevated melanoma risk among non-Hispanic whites (NHWs). MC1R genetic testing may unmask previously unrecognized disease risk, especially among individuals with few melanoma phenotypic risk factors. We recruited NHW individuals with limited phenotypic risk factors from two primary care clinics in west-central Florida. Participants (n = 1134) were randomized within MC1R genotype risk group (average/higher) to receive mailed precision prevention (i.e., intervention) or generic prevention materials. Participants reported hours of weekday and weekend sun exposure, frequency of intentional outdoor tanning and sun protection behaviors, number of sunburns, indoor tanning episodes, and skin examinations at baseline, and after 6 and 12 months. Among MC1R higher-risk participants, the intervention increased the likelihood of often or always wearing a shirt with sleeves (OR = 1.49, p = 0.03) and seeking shade or using an umbrella (OR = 1.42, p = 0.046), and it decreased the number of sunburns among their young children (β = −0.13, p = 0.03). Intervention effects were not noted among MC1R average-risk participants. Moderation analyses identified intervention effects within subgroups in average-risk and higher-risk participants. Precision prevention information conveying MC1R testing results can increase the practice of some sun protection behaviors among at-risk individuals with limited melanoma risk phenotypes and may provide a cross-generational tool to counteract increasing incidence of melanoma.

The heterogeneous cell types of the tumor-immune microenvironment (TIME) play key roles in determining cancer progression, metastasis and response to treatment. We report the development of TIMEx, a novel TIME deconvolution method emphasizing on estimating infiltrating immune cells for bulk transcriptomics using pan-cancer single-cell RNA-seq signatures. We also implemented a comprehensive, user-friendly web-portal for users to evaluate TIMEx and other deconvolution methods with bulk transcriptomic profiles. TIMEx web-portal is freely accessible at http://timex.moffitt.org. Supplementary data are available at Bioinformatics online.