Selecting trial centers using a standardized, automated site assessment survey instrument (SASI).

BACKGROUND: To improve the site selection process for clinical trials, we expanded a site survey to include standardized assessments of site commitment time, team experience, feasibility of tight timelines, and local medical community equipoise as factors that might better predict performance. We also collected contact information about institutional research services ahead of site onboarding. AIM: As a first step, we wanted to confirm that an expanded survey could be feasible and generalizable-that asking site teams for more details upfront was acceptable and that the survey could be completed in a reasonable amount of time, despite the assessment length. METHODS: A standardized, two-part Site Assessment Survey Instrument (SASI), examining qualitative components and with multiple contact list sections, was developed using a publicly accessible dashboard and later transferred to a REDCap platform. After multiple rounds of internal testing, the SASI was deployed 11 times for multicenter trials. Follow-up questionnaires were sent to site teams to confirm that an expanded survey instrument is acceptable to the research community and could be completed during a brief work shift. RESULTS: Respondents thought the SASI collected useful and relevant information about their sites (100%). Sites were "comfortable" (90%) supplying detailed information early in the site selection process and 57% completed the SASI in one to two hours. CONCLUSIONS: Coordinating centers and sites found the SASI tool to be acceptable and helpful when collecting data in consideration of multicenter trial site selection.

Efficacy of Niclosamide vs Placebo in SARS-CoV-2 Respiratory Viral Clearance, Viral Shedding, and Duration of Symptoms Among Patients With Mild to Moderate COVID-19: A Phase 2 Randomized Clinical Trial.

Importance: Oral anthelmintic niclosamide has potent in vitro antiviral activity against SARS-CoV-2. Repurposed niclosamide could be a safe and efficacious COVID-19 therapy. Objective: To investigate whether niclosamide decreased SARS-CoV-2 shedding and duration of symptoms among patients with mild to moderate COVID-19. Design, Setting, and Participants: This randomized, placebo-controlled clinical trial enrolled individuals testing positive for SARS-CoV-2 by polymerase chain reaction with mild to moderate symptoms of COVID. All trial participants, investigators, staff, and laboratory personnel were kept blind to participant assignments. Enrollment was among individuals reporting at Tufts Medical Center and Wellforce Network in Massachusetts for outpatient COVID-19 testing. The trial opened to accrual on October 1, 2020; the last participant enrolled on April 20, 2021. Trial exclusion criteria included hospitalization at time of enrollment or use of any experimental treatment for COVID-19, including vaccination. Enrollment was stopped before attaining the planned sample size when COVID-19 diagnoses decreased precipitously in Massachusetts. Data were analyzed from July through September 2021. Interventions: In addition to receiving current standard of care, participants were randomly assigned on a 1:1 basis to receive niclosamide 2 g by mouth daily for 7 days or identically labeled placebo at the same dosing schedule. Main Outcomes and Measures: Oropharyngeal and fecal samples were self-collected for viral shedding measured by reverse-transcriptase-polymerase-chain-reaction on days 3, 7, 10, and 14, and an additional fecal sample was collected on day 21. A telehealth platform was developed to conduct remote study visits, monitor symptoms, and coordinate sample collection via couriers. The primary end point was the proportion of participants with viral clearance in respiratory samples at day 3 based on the intention-to-treat sample. Mean times to viral clearance and symptom resolution were calculated as restricted mean survival times and accounted for censored observations. Results: Among 73 participants, 36 individuals were enrolled and randomized to niclosamide and 37 individuals to placebo. Participant characteristics were similar across treatment groups; among 34 patients receiving placebo and 33 patients receiving niclosamide in the intention-to-treat sample, mean (SD) age was 36.0 (13.3) years vs 36.8 (12.9) years and there were 21 (61.8%) men vs 20 (60.6%) men. The overall mean (SD) age was 36.4 (13.0) years. For the primary end point, 66.67% (95% CI, 50.74% to 81.81%) of participants receiving niclosamide and 55.88% (95% CI, 40.27% to 72.73%) of participants receiving placebo had oropharyngeal SARS-CoV-2 clearance at day 3 (P = .37). Among 63 participants with symptoms, niclosamide did not significantly shorten symptom duration, which was 12.01 (95% CI, 8.82 to 15.2) days in the niclosamide group vs 14.61 (95% CI, 11.25 to 17.96) days in the placebo group (mean difference, -2.6 [95% CI, -7.23 to 2.03] days). Niclosamide was well-tolerated; the most commonly reported adverse events in the placebo and niclosamide groups were headaches (11 patients [32.4%] vs 7 patients [21.2%]; P = .31) and cough (8 patients [23.5%] vs 7 patients [21.2%]; P = .82). Conclusions and Relevance: In this randomized clinical trial, there was no significant difference in oropharyngeal clearance of SARS-CoV-2 at day 3 between placebo and niclosamide groups. Confirmation in larger studies is warranted. Trial Registration: ClinicalTrials.gov Identifier: NCT04399356.

A Useful and Sustainable Role for N-of-1 Trials in the Healthcare Ecosystem.

Clinicians and patients often try a treatment for an initial period to inform longer-term therapeutic decisions. A more rigorous approach involves N-of-1 trials. In these single-patient crossover trials, typically conducted in patients with chronic conditions, individual patients are given candidate treatments in a double-blinded, random sequence of alternating periods to determine the most effective treatment for that patient. However, to date, these trials are rarely done outside of research settings and have not been integrated into general care where they could offer substantial benefit. Designating this classical, N-of-1 trial design as type 1, there also are new and evolving uses of N-of-1 trials that we designate as type 2. In these, rather than focusing on optimizing treatment for chronic diseases when multiple approved choices are available, as is typical of type 1, a type 2 N-of-1 trial tests treatments designed specifically for a patient with a rare disease, to facilitate personalized medicine. While the aims differ, both types face the challenge of collecting individual-patient evidence using standard, trusted, widely accepted methods. To fulfill their potential for producing both clinical and research benefits, and to be available for wide use, N-of-1 trials will have to fit into the current healthcare ecosystem. This will require generalizable and accepted processes, platforms, methods, and standards. This also will require sustainable value-based arrangements among key stakeholders. In this article, we review opportunities, stakeholders, issues, and possible approaches that could support general use of N-of-1 trials and deliver benefit to patients and the healthcare enterprise. To assess and expand the benefits of N-of-1 trials, we propose multistakeholder meetings, workshops, and the generation of methods, standards, and platforms that would support wider availability and the value of N-of-1 trials.

Efficacy and Effectiveness Too Trials: Clinical Trial Designs to Generate Evidence on Efficacy and on Effectiveness in Wide Practice.

Efficacy trials, designed to gain regulatory marketing approval, evaluate drugs in optimally selected patients under advantageous conditions for relatively short time periods. Effectiveness trials, designed to evaluate use in usual practice, assess treatments among more typical patients in real-world conditions with longer follow-up periods. In "efficacy-to-effectiveness (E2E) trials," if the initial efficacy trial component is positive, the trial seamlessly transitions to an effectiveness trial component to efficiently yield both types of evidence. Yet more time could be saved by simultaneously addressing efficacy and effectiveness in an "efficacy and effectiveness too (EE2) trial." Additionally, hybrids of the E2E and EE2 approaches with differing degrees of overlap of the two components could allow flexibility for specific drug development needs. In planning EE2 trials, each stakeholder's current and future needs, incentives, and perspective must be considered. Although challenging, the ultimate benefits to stakeholders, the health system, and the public should justify this effort.

An example of medical device-based projection of clinical trial enrollment: Use of electrocardiographic data to identify candidates for a trial in acute coronary syndromes.

BACKGROUND: To identify potential participants for clinical trials, electronic health records (EHRs) are searched at potential sites. As an alternative, we investigated using medical devices used for real-time diagnostic decisions for trial enrollment. METHODS: To project cohorts for a trial in acute coronary syndromes (ACS), we used electrocardiograph-based algorithms that identify ACS or ST elevation myocardial infarction (STEMI) that prompt clinicians to offer patients trial enrollment. We searched six hospitals' electrocardiograph systems for electrocardiograms (ECGs) meeting the planned trial's enrollment criterion: ECGs with STEMI or > 75% probability of ACS by the acute cardiac ischemia time-insensitive predictive instrument (ACI-TIPI). We revised the ACI-TIPI regression to require only data directly from the electrocardiograph, the e-ACI-TIPI using the same data used for the original ACI-TIPI (development set n = 3,453; test set n = 2,315). We also tested both on data from emergency department electrocardiographs from across the US (n = 8,556). We then used ACI-TIPI and e-ACI-TIPI to identify potential cohorts for the ACS trial and compared performance to cohorts from EHR data at the hospitals. RESULTS: Receiver-operating characteristic (ROC) curve areas on the test set were excellent, 0.89 for ACI-TIPI and 0.84 for the e-ACI-TIPI, as was calibration. On the national electrocardiographic database, ROC areas were 0.78 and 0.69, respectively, and with very good calibration. When tested for detection of patients with > 75% ACS probability, both electrocardiograph-based methods identified eligible patients well, and better than did EHRs. CONCLUSION: Using data from medical devices such as electrocardiographs may provide accurate projections of available cohorts for clinical trials.