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BackgroundA fixed-dose combination of ledipasvir/sofosbuvir (LDV/SOF) is efficacious in treating chronic hepatitis C virus (HCV) infection; however, objective adherence to prescribed regimens in real-world clinical settings has not been well studied. ObjectiveThis study aimed to evaluate adherence and virologic outcomes in patients with chronic HCV infection treated with LDV/SOF using a novel digital medicine program that directly measures drug ingestion adherence. MethodsThis prospective, observational, open-label, single-arm pilot study was conducted at 2 clinical research sites and followed patients with HCV infection who were prescribed LDV/SOF along with an ingestible sensor. Patients were treated for 8 or 12 weeks. The main outcomes were ingestion adherence, medical interventions, virologic response, safety, and patient satisfaction. ResultsOf the 28 patients (mean 59 years, SD 7), 61% (17/28) were male, 61% (17/28) were non-Caucasian, and 93% (26/28) were treatment naïve. All 28 had genotype 1 HCV, and of these, 27 completed an 8- or 12-week treatment. Patients used the digital medicine program for 92% of the expected days; the overall mean ingestion adherence rate was 97%. Providers used the digital medicine program data for same-day medication therapy management in 39% (11/28) of patients. End-of-treatment response was achieved in all the available 21 of 28 patients. Sustained virologic response at 12 weeks or more was achieved in 26 of 28 patients; of the 2 patients who relapsed, one had less than 90% adherence and the other had greater than or equal to 95% adherence, lending insights into reasons for treatment failure. A total of 4 subjects reported nonserious adverse events, which were resolved. ConclusionsThe findings of this study suggest that digital medicines can be used for wirelessly observed therapy to support adherence to antiviral HCV therapy, reduce unnecessary medication wastage and retreatment costs, and potentially optimize sustained virologic response rates, especially in populations at high risk for nonadherence.

Background: We conducted a systematic literature review to identify key trends associated with remote patient monitoring (RPM) via noninvasive digital technologies over the last decade., Materials and Methods: A search was conducted in EMBASE and Ovid MEDLINE. Citations were screened for relevance against predefined selection criteria based on the PICOTS (Population, Intervention, Comparator, Outcomes, Timeframe, and Study Design) format. We included studies published between January 1, 2005 and September 15, 2015 that used RPM via noninvasive digital technology (smartphones/personal digital assistants [PDAs], wearables, biosensors, computerized systems, or multiple components of the formerly mentioned) in evaluating health outcomes compared to standard of care or another technology. Studies were quality appraised according to Critical Appraisal Skills Programme., Results: Of 347 articles identified, 62 met the selection criteria. Most studies were randomized control trials with older adult populations, small sample sizes, and limited follow-up. There was a trend toward multicomponent interventions (n = 26), followed by smartphones/PDAs (n = 12), wearables (n = 11), biosensor devices (n = 7), and computerized systems (n = 6). Another key trend was the monitoring of chronic conditions, including respiratory (23%), weight management (17%), metabolic (18%), and cardiovascular diseases (16%). Although substantial diversity in health-related outcomes was noted, studies predominantly reported positive findings., Conclusions: This review will help decision makers develop a better understanding of the current landscape of peer-reviewed literature, demonstrating the utility of noninvasive RPM in various patient populations. Future research is needed to determine the effectiveness of RPM via noninvasive digital technologies in delivering patient healthcare benefits and the feasibility of large-scale implementation., Competing Interests: Statement A.V. is a postdoctoral student from Jefferson College of Population Health and a US HEOR Fellow at Novartis Pharmaceuticals Corporation. M.T. is a postdoctoral student from Scott & White Health Plan, University of Texas at Austin and a US HEOR Fellow at Novartis Pharmaceuticals Corporation. S.A. and M.A. are employees of Novartis Pharmaceuticals Corporation. Novartis Pharmaceuticals Corporation provided funding for this work.