Faculty Bibliography

Clinical trials are constantly evolving in the context of increasingly complex research questions and potentially limited resources. In this review article, we discuss the emergence of "adaptive" clinical trials that allow for the preplanned modification of an ongoing clinical trial based on the accumulating evidence with application across translational research. These modifications may include terminating a trial before completion due to futility or efficacy, re-estimating the needed sample size to ensure adequate power, enriching the target population enrolled in the study, selecting across multiple treatment arms, revising allocation ratios used for randomization, or selecting the most appropriate endpoint. Emerging topics related to borrowing information from historic or supplemental data sources, sequential multiple assignment randomized trials (SMART), master protocol and seamless designs, and phase I dose-finding studies are also presented. Each design element includes a brief overview with an accompanying case study to illustrate the design method in practice. We close with brief discussions relating to the statistical considerations for these contemporary designs.

BACKGROUND:Patient-reported outcomes (PROs) capture patients' views on their health conditions and its management, and are increasingly used in clinical trials, including those targeting type 2 diabetes (T2D). Mobile health (mHealth) tools offer novel solutions for collecting PRO data in real time. Although patients are at the center of any PRO-based intervention, few studies have examined user engagement with PRO mHealth tools. OBJECTIVE:This study aimed to evaluate user engagement with a PRO mHealth tool for T2D management, identify patterns of user engagement and similarities and differences between the patients, and identify the characteristics of patients who are likely to drop out or be less engaged with a PRO mHealth tool. METHODS:We extracted user engagement data from an ongoing clinical trial that tested the efficacy of a PRO mHealth tool designed to improve hemoglobin A1c levels in patients with uncontrolled T2D. To date, 61 patients have been randomized to the intervention, where they are sent 6 PRO text messages a day that are relevant to T2D self-management (healthy eating and medication adherence) over the 12-month study. To analyze user engagement, we first compared the response rate (RR) and response time between patients who completed the 12-month intervention and those who dropped out early (noncompleters). Next, we leveraged latent class trajectory modeling to classify patients from the completer group into 3 subgroups based on similarity in the longitudinal engagement data. Finally, we investigated the differences between the subgroups of completers from various cross-sections (time of the day and day of the week) and PRO types. We also explored the patient demographics and their distribution among the subgroups. RESULTS:Overall, 19 noncompleters had a lower RR to PRO questions and took longer to respond to PRO questions than 42 completers. Among completers, the longitudinal RRs demonstrated differences in engagement patterns over time. The completers with the lowest engagement showed peak engagement during month 5, almost at the midstage of the program. The remaining subgroups showed peak engagement at the beginning of the intervention, followed by either a steady decline or sustained high engagement. Comparisons of the demographic characteristics showed significant differences between the high engaged and low engaged subgroups. The high engaged completers were predominantly older, of Hispanic descent, bilingual, and had a graduate degree. In comparison, the low engaged subgroup was composed mostly of African American patients who reported the lowest annual income, with one of every 3 patients earning less than US $20,000 annually. CONCLUSIONS:There are discernible engagement phenotypes based on individual PRO responses, and their patterns vary in the timing of peak engagement and demographics. Future studies could use these findings to predict engagement categories and tailor interventions to promote longitudinal engagement. TRIAL REGISTRATION/BACKGROUND:Clinicaltrials.gov NCT03652389; https://clinicaltrials.gov/ct2/show/NCT03652389. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)/UNASSIGNED:RR2-10.2196/18554.

BACKGROUND:The integration of behavioral economics (BE) principles and electronic health records (EHRs) using clinical decision support (CDS) tools is a novel approach to improving health outcomes. Meanwhile, the American Geriatrics Society has created the Choosing Wisely (CW) initiative to promote less aggressive glycemic targets and reduction in pharmacologic therapy in older adults with type 2 diabetes mellitus. To date, few studies have shown the effectiveness of combined BE and EHR approaches for managing chronic conditions, and none have addressed guideline-driven deprescribing specifically in type 2 diabetes. We previously conducted a pilot study aimed at promoting appropriate CW guideline adherence using BE nudges and EHRs embedded within CDS tools at 5 clinics within the New York University Langone Health (NYULH) system. The BE-EHR module intervention was tested for usability, adoption, and early effectiveness. Preliminary results suggested a modest improvement of 5.1% in CW compliance. OBJECTIVE:This paper presents the protocol for a study that will investigate the effectiveness of a BE-EHR module intervention that leverages BE nudges with EHR technology and CDS tools to reduce overtreatment of type 2 diabetes in adults aged 76 years and older, per the CW guideline. METHODS:A pragmatic, investigator-blind, cluster randomized controlled trial was designed to evaluate the BE-EHR module. A total of 66 NYULH clinics will be randomized 1:1 to receive for 18 months either (1) a 6-component BE-EHR module intervention + standard care within the NYULH EHR, or (2) standard care only. The intervention will be administered to clinicians during any patient encounter (eg, in person, telemedicine, medication refill, etc). The primary outcome will be patient-level CW compliance. Secondary outcomes will measure the frequency of intervention component firings within the NYULH EHR, and provider utilization and interaction with the BE-EHR module components. RESULTS:Study recruitment commenced on December 7, 2020, with the activation of all 6 BE-EHR components in the NYULH EHR. CONCLUSIONS:This study will test the effectiveness of a previously developed, iteratively refined, user-tested, and pilot-tested BE-EHR module aimed at providing appropriate diabetes care to elderly adults, compared to usual care via a cluster randomized controlled trial. This innovative research will be the first pragmatic randomized controlled trial to use BE principles embedded within the EHR and delivered using CDS tools to specifically promote CW guideline adherence in type 2 diabetes. The study will also collect valuable information on clinician workflow and interaction with the BE-EHR module, guiding future research in optimizing the timely delivery of BE nudges within CDS tools. This work will address the effectiveness of BE-inspired interventions in diabetes and chronic disease management. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov NCT04181307; https://clinicaltrials.gov/ct2/show/NCT04181307. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)/UNASSIGNED:DERR1-10.2196/28723.

OBJECTIVES/OBJECTIVE:To determine if the Integrated Community-Based Health Systems-Strengthening (ICBHSS) initiative was effective in expanding health coverage, improving care quality, and reducing child mortality in Togo. METHODS:Population-representative cross-sectional household surveys adapted from the Demographic Household Survey and Multiple Indicator Cluster Surveys were conducted at baseline (2015) and then annually (2016-2020) in 4 ICBHSS catchment sites in Kara, Togo. The primary outcome was under-5 mortality, with health service coverage and health-seeking behavior as secondary outcomes. Costing analyses were calculated by using "top-down" methodology with audited financial statements and programmatic data. RESULTS:There were 10 022 household surveys completed from 2015 to 2020. At baseline (2015), under-5 mortality was 51.1 per 1000 live births (95% confidence interval [CI]: 35.5-66.8), and at the study end period (2020), under-5 mortality was 35.8 (95% CI: 23.4-48.2). From 2015 to 2020, home-based treatment by a community health worker increased from 24.1% (95% CI: 21.9%-26.4%) to 45.7% (95% CI: 43.3%-48.2%), and respondents reporting prenatal care in the first trimester likewise increased (37.5% to 50.1%). Among respondents who sought care for a child with fever, presenting for care within 1 day increased from 51.9% (95% CI: 47.1%-56.6%) in 2015 to 80.3% (95% CI: 74.6%-85.0%) in 2020. The estimated annual additional intervention cost was $8.84 per person. CONCLUSIONS:Our findings suggest that the ICBHSS initiative, a bundle of evidence-based interventions implemented with a community-based strategy, improves care access and quality and was associated with reduction in child mortality.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) poses a public health threat for which preventive and therapeutic agents are urgently needed. Neutralizing antibodies are a key class of therapeutics which may bridge widespread vaccination campaigns and offer a treatment solution in populations less responsive to vaccination. Herein, we report that high-throughput microfluidic screening of antigen-specific B-cells led to the identification of LY-CoV555 (also known as bamlanivimab), a potent anti-spike neutralizing antibody from a hospitalized, convalescent patient with coronavirus disease 2019 (COVID-19). Biochemical, structural, and functional characterization of LY-CoV555 revealed high-affinity binding to the receptor-binding domain, angiotensin converting enzyme 2 binding inhibition, and potent neutralizing activity. A pharmacokinetic study of LY-CoV555 conducted in cynomolgus monkeys demonstrated a mean half-life of 13 days, and clearance of 0.22 mL/hr/kg, consistent with a typical human therapeutic antibody. In a rhesus macaque challenge model, prophylactic doses as low as 2.5 mg/kg reduced viral replication in the upper and lower respiratory tract in samples collected through study Day 6 following viral inoculation. This antibody has entered clinical testing and is being evaluated across a spectrum of COVID-19 indications, including prevention and treatment.

BACKGROUND:Digital diabetes prevention programs (dDPPs) are effective behavior change tools to prevent disease progression in patients at risk for diabetes. At present, these programs are poorly integrated into existing health information technology infrastructure and clinical workflows, resulting in barriers to provider-level knowledge of, interaction with, and support of patients who use dDPPs. Tools that can facilitate patient-provider interaction around dDPPs may contribute to improved patient engagement and adherence to these programs and improved health outcomes. OBJECTIVE:This study aims to use a rigorous, user-centered design (UCD) methodology to develop a theory-driven system that supports patient engagement with dDPPs and their primary care providers with their care. METHODS:at 6 and 12 months. Secondary outcomes will be patient engagement (use and activity) in the dDPP. The mediator variables (self-efficacy, digital health literacy, and patient-provider relationship) will be measured. RESULTS:The project was initiated in 2018 and funded in September 2019. Enrollment and data collection for phase 1 began in September 2019 under an Institutional Review Board quality improvement waiver granted in July 2019. As of December 2020, 27 patients have been enrolled and first results are expected to be submitted for publication in early 2021. The study received Institutional Review Board approval for phases 2 and 3 in December 2020, and phase 2 enrollment is expected to begin in early 2021. CONCLUSIONS:Our findings will provide guidance for the design and development of technology to integrate dDPP platforms into existing clinical workflows. This will facilitate patient engagement in digital behavior change interventions and provider engagement in patients' use of dDPPs. Integrated clinical tools that can facilitate patient-provider interaction around dDPPs may contribute to improved patient adherence to these programs and improved health outcomes by addressing barriers faced by both patients and providers. Further evaluation with pilot testing and a clinical trial will assess the effectiveness and implementation of these tools. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov NCT04049500; https://clinicaltrials.gov/ct2/show/NCT04049500. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)/UNASSIGNED:DERR1-10.2196/26750.

Convalescent plasma is an investigational product, not approved by the Food and Drug Administration for any use, that has been administered for the prevention and treatment of epidemic infections, including Ebola and most recently COVID-19. On 3 April 2020, Food and Drug Administration authorized an Expanded Access Program for treatment use of convalescent plasma in hospitalized COVID-19 patients, with Mayo Clinic as the coordinating site for this nationwide effort. Expanded Access, historically referred to as ''compassionate use,'' is a regulatory pathway that allows patients to use an investigational product outside of a clinical trial when four conditions are met: the patient has a life-threatening or serious disease, no comparable or satisfactory alternative treatment options are available, clinical trial enrollment is not possible, and non-trial use does not pose a threat to timely clinical development. Food and Drug Administration can authorize Expanded Access through requests for single patients, intermediate-size patient populations, and widespread treatment programs. The convalescent plasma Expanded Access Program was the largest in US history, leading to infusion of more than 94,000 patients. In comparison, the largest prior Expanded Access Programs-for lamivudine (HIV) and gefitinib (cancer)-each provided unapproved drugs to approximately 30,000 patients outside of clinical trials. Expanded Access Programs of this size are unusual and dwarf most clinical trials. However, Expanded Access Programs are intended for treatment, not research. Therefore, even when they involve sizable patient populations, they lack features of rigorous trial design, including control groups and randomization. Nevertheless, Expanded Access Program data have been considered pivotal by both the Food and Drug Administration and European Medicines Agency, often in the context of rare disease and the collection of safety data, and it was primarily the convalescent plasma Expanded Access Program data that led Food and Drug Administration to issue an emergency use authorization for that product. Although Expanded Access Programs are by regulation not supposed to hinder clinical trials, large Expanded Access Programs can create circular challenges, as when a lack of trial opportunities makes an Expanded Access Program an important pathway for initial access to an investigational product, but then the Expanded Access Program becomes a barrier to launching new trials. In this session, we will discuss the statistical, ethical, and regulatory issues that arise in the context of Expanded Access Programs, using the convalescent plasma Expanded Access Program as a case study in contrast to clinical trials, with a focus on issues arising in the context of a global pandemic. We will first discuss biostatistical considerations for extracting realworld evidence from Expanded Access Program data, as well as the role of these data in supplementing results from clinical trials. We will also consider the perspective of the patient in deciding whether to enroll in an Expanded Access Program versus clinical trial, including the opportunity for personal benefit or harm, potential for participation to impact the greater good, and the patient understanding of an unproven investigational treatment. Then, we will address the gatekeeping role of clinicians, institutions, and regulators, to ensure that Expanded Access Programs do not interfere with clinical trials. Finally, we will address patient pathways for accessing investigational drugs, especially in the context of a global pandemic, and the capacity for collecting rigorous data via these mechanisms, while prioritizing rigorous trials

BACKGROUND:Intensive glycemic control is of unclear benefit and carries increased risk for older adults with diabetes. The American Geriatrics Society's (AGS) Choosing Wisely (CW) guideline promotes less aggressive glycemic targets and reduction in pharmacologic therapy for older adults with type II diabetes. Meanwhile, behavioral economic (BE) approaches offer promise in influencing hard-to-change behavior, and previous studies have shown the benefits of using electronic health record (EHR) technology to encourage guideline adherence. OBJECTIVE:This study aimed to develop and pilot test an intervention that leverages BE with EHR technology to promote appropriate diabetes management in older adults. DESIGN/METHODS:A pilot study within the New York University Langone Health (NYULH) EHR and Epic system to deliver BE-inspired nudges at five NYULH clinics at varying time points from July 12, 2018, through October 31, 2019. PARTICIPANTS/METHODS:Clinicians across five practices in the NYULH system whose patients were older adults (age 76 and older) with type II diabetes. INTERVENTIONS/METHODS:A BE-EHR module comprising six nudges was developed through a series of design workshops, interviews, user-testing sessions, and clinic visits. BE principles utilized in the nudges include framing, social norming, accountable justification, defaults, affirmation, and gamification. MAIN MEASURES/METHODS:Patient-level CW compliance. KEY RESULTS/RESULTS:CW compliance increased 5.1% from a 16-week interval at baseline to a 16-week interval post intervention. From February 14 to June 5, 2018 (prior to the first nudge launch in Vanguard clinics), CW compliance for 1278 patients was mean (95% CI)-16.1% (14.1%, 18.1%). From July 3 to October 22, 2019 (after BE-EHR module launch at all five clinics), CW compliance for 680 patients was 21.2% (18.1%, 24.3%). CONCLUSIONS:The BE-EHR module shows promise for promoting the AGS CW guideline and improving diabetes management in older adults. A randomized controlled trial will commence to test the effectiveness of the intervention across 66 NYULH clinics. NIH TRIAL REGISTRY NUMBER/UNASSIGNED:NCT03409523.