Simultaneous hypothesis testing for multiple competing risks in comparative clinical trials.

Competing risks data are commonly encountered in randomized clinical trials or observational studies. Ignoring competing risks in survival analysis leads to biased risk estimates and improper conclusions. Often, one of the competing events is of primary interest and the rest competing events are handled as nuisances. These approaches can be inadequate when multiple competing events have important clinical interpretations and thus of equal interest. For example, in COVID-19 in-patient treatment trials, the outcomes of COVID-19 related hospitalization are either death or discharge from hospital, which have completely different clinical implications and are of equal interest, especially during the pandemic. In this paper we develop nonparametric estimation and simultaneous inferential methods for multiple cumulative incidence functions (CIFs) and corresponding restricted mean times. Based on Monte Carlo simulations and a data analysis of COVID-19 in-patient treatment clinical trial, we demonstrate that the proposed method provides global insights of the treatment effects across multiple endpoints.

Research Question, Objectives, and Endpoints in Clinical and Oncological Research: A Comprehensive Review.

Clinical research is a systematic process of conducting research work to find solutions for human health-related problems. It is applied to understand the disease process and assist in the diagnosis, treatment, and prevention. Currently, we are experiencing global unrest caused by the coronavirus disease (COVID-19) pandemic. The novel severe acute respiratory syndrome coronavirus (SARS-CoV-2) has been responsible for the deaths of more than 50 million people worldwide. Also, it has resulted in severe morbidity among the affected population. The cause of such a huge amount of influence on human health by the pandemic was the unavailability of drugs and therapeutic interventions to treat and manage the disease. Cancer is a disease condition wherein the normal cell function is deranged, and the cells multiply in an uncontrolled manner. Based on recent reports by the World Health Organization (WHO), cancer is the second leading cause of death globally. Moreover, the rates of cancers have shown an increasing trend in the past decade. Therefore, it is essential to improve the understanding concerning clinical research to address the health concerns of humans. In this review, we comprehensively discuss critical aspects of clinical research that include the research question, research objectives, patient-reported outcome measures (PROMs), intention-to-treat and per-protocol analysis, and endpoints in clinical and oncological research.

Description of the Method for Evaluating Digital Endpoints in Alzheimer Disease Study: Protocol for an Exploratory, Cross-sectional Study.

BACKGROUND: More sensitive and less burdensome efficacy end points are urgently needed to improve the effectiveness of clinical drug development for Alzheimer disease (AD). Although conventional end points lack sensitivity, digital technologies hold promise for amplifying the detection of treatment signals and capturing cognitive anomalies at earlier disease stages. Using digital technologies and combining several test modalities allow for the collection of richer information about cognitive and functional status, which is not ascertainable via conventional paper-and-pencil tests. OBJECTIVE: This study aimed to assess the psychometric properties, operational feasibility, and patient acceptance of 10 promising technologies that are to be used as efficacy end points to measure cognition in future clinical drug trials. METHODS: The Method for Evaluating Digital Endpoints in Alzheimer Disease study is an exploratory, cross-sectional, noninterventional study that will evaluate 10 digital technologies' ability to accurately classify participants into 4 cohorts according to the severity of cognitive impairment and dementia. Moreover, this study will assess the psychometric properties of each of the tested digital technologies, including the acceptable range to assess ceiling and floor effects, concurrent validity to correlate digital outcome measures to traditional paper-and-pencil tests in AD, reliability to compare test and retest, and responsiveness to evaluate the sensitivity to change in a mild cognitive challenge model. This study included 50 eligible male and female participants (aged between 60 and 80 years), of whom 13 (26%) were amyloid-negative, cognitively healthy participants (controls); 12 (24%) were amyloid-positive, cognitively healthy participants (presymptomatic); 13 (26%) had mild cognitive impairment (predementia); and 12 (24%) had mild AD (mild dementia). This study involved 4 in-clinic visits. During the initial visit, all participants completed all conventional paper-and-pencil assessments. During the following 3 visits, the participants underwent a series of novel digital assessments. RESULTS: Participant recruitment and data collection began in June 2020 and continued until June 2021. Hence, the data collection occurred during the COVID-19 pandemic (SARS-CoV-2 virus pandemic). Data were successfully collected from all digital technologies to evaluate statistical and operational performance and patient acceptance. This paper reports the baseline demographics and characteristics of the population studied as well as the study's progress during the pandemic. CONCLUSIONS: This study was designed to generate feasibility insights and validation data to help advance novel digital technologies in clinical drug development. The learnings from this study will help guide future methods for assessing novel digital technologies and inform clinical drug trials in early AD, aiming to enhance clinical end point strategies with digital technologies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/35442.

Considerations for the Feasibility of Neutralizing Antibodies as a Surrogate Endpoint for COVID-19 Vaccines.

To effectively control and prevent the pandemic of coronavirus disease 2019 (COVID-19), suitable vaccines have been researched and developed rapidly. Currently, 31 COVID-19 vaccines have been approved for emergency use or authorized for conditional marketing, with more than 9.3 billion doses of vaccines being administered globally. However, the continuous emergence of variants with high transmissibility and an ability to escape the immune responses elicited by vaccines poses severe challenges to the effectiveness of approved vaccines. Hundreds of new COVID-19 vaccines based on different technology platforms are in need of a quick evaluation for their efficiencies. Selection and enrollment of a suitable sample of population for conducting these clinical trials is often challenging because the pandemic so widespread and also due to large scale vaccination. To overcome these hurdles, methods of evaluation of vaccine efficiency based on establishment of surrogate endpoints could expedite the further research and development of vaccines. In this review, we have summarized the studies on neutralizing antibody responses and effectiveness of the various COVID-19 vaccines. Using this data we have analyzed the feasibility of establishing surrogate endpoints for evaluating the efficacy of vaccines based on neutralizing antibody titers. The considerations discussed here open up new avenues for devising novel approaches and strategies for the research and develop as well as application of COVID-19 vaccines.

Landscape of coronavirus disease 2019 clinical trials: New frontiers and challenges.

BACKGROUND/AIM: The number of coronavirus disease 2019 deaths and cases continues to increase globally. Novel therapies are urgently needed to treat patients with coronavirus disease 2019. We sought to provide a critical review of trials designed during the coronavirus disease 2019 pandemic. Our primary goal was to provide a critical review of the landscape of clinical trials designed to address the coronavirus disease 2019 pandemic. Specifically, we were interested in assessing the design of phase II/III and phase III interventional trials. METHODS: We utilized the ClinicalTrials.gov database to include trials registered between 1 December 2019 and 11 April 2021 to survey the current landscape of clinical trials for coronavirus disease 2019. Variables extracted included: National Clinical Trial number, title, location, sponsor, study type, start date, completion date, gender group, age group, primary outcome, secondary outcome, overall status, and associated references. RESULTS: About 57% of studies were interventional, 14.5% were phase III trials, and the majority of the therapeutic trials included hospitalized patients. There were 52 primary composite outcomes and 285 unique interventions spanning 10 drug classes. The outcomes, disease severity, and comparators varied substantially across trials, and the trials were often too small to be definitive. CONCLUSION: These findings are relevant as we strongly advocate for global coordination of efforts through the use of common platforms that enable harmonizing of endpoints, collection of common key variables and clear definition of disease severity to have clinically meaningful results from clinical trials.

Static Balance Digital Endpoints with Mon4t: Smartphone Sensors vs. Force Plate.

Static balance tests are conducted in various clinics for diagnosis and treatment adjustment. As a result of population aging, the accessibility of these tests should be increased, in the clinic, and for remote patient examination. A number of publications have already conducted static balance evaluations using the sensors embedded in a smartphone. This study focuses on the applicability of using smartphone-based balance assessment on a large scale while considering ease of use, safety, and reliability. The Mon4t® app was used to acquire the postural motion using different smartphone devices, different smartphone locations, and various standing postures. The signals derived from the app were compared to the center of pressure displacement derived from a force plate. The results showed moderate to high agreement between the two methods, particularly at the tandem stance (0.69 ≤ r ≤ 0.91). Preliminary data collection was conducted on three healthy participants, followed by 50 additional healthy volunteers, aged 65+. The results demonstrated that the Mon4t app can serve as an accessible and inexpensive static balance assessment tool, both in clinical settings and for remote patient monitoring, which is key for enabling telehealth.

Design and Analysis of Studies Based on Hierarchical Composite Endpoints: Insights from the DARE-19 Trial.

BACKGROUND/AIM: DARE-19 (NCT04350593) was a randomized trial studying the effects of dapagliflozin, an SGLT2 inhibitor, in hospitalized patients with COVID-19 pneumonia and cardiometabolic risk factors. The conduct of DARE-19 offered the opportunity to define an innovative and clinically meaningful endpoint in a new disease that would best reflect the known profile of dapagliflozin, accompanied by the statistical challenges of analysis and interpretation of such a novel endpoint. METHODS: Hierarchical composite endpoints (HCEs) are based on clinical outcomes which, unlike traditional composite endpoints incorporate ranking of components according to clinical importance. Design of an HCE requires the clinical considerations specific to the therapeutic area under study and the mechanism of action of the investigational treatment. Statistical aspects for the clinical endpoints include the proper definition of the estimand as suggested by ICH E9(R1) for the precise specification of the treatment effect measured by an HCE. RESULTS: We describe the estimand of the DARE-19 trial, where an HCE was constructed to capture the treatment effect of dapagliflozin in hospitalized patients with COVID-19, and was analyzed using a win odds. Practical aspects of designing new studies based on an HCE are described. These include sample size, power, and minimal detectable effect calculations for an HCE based on the win odds analysis, as well as handling of missing data and the clinical interpretability of the win odds in relation to the estimand. CONCLUSIONS: HCEs are flexible endpoints that can be adapted for use in different therapeutic areas, with win odds as the analysis method. DARE-19 is an example of a COVID-19 trial with an HCE as one of the primary endpoints for estimating a clinically interpretable treatment effect in the COVID-19 setting.

SARS-CoV-2 vaccines: Clinical endpoints and psychological perspectives: A literature review.

BACKGROUND: About 270 million cases have been confirmed, and 5.3 million fatalities Worldwide due to SARS-CoV-2. Several vaccine candidates have entered phase 3 of the clinical trial and are being investigated to provide immunity to the maximum percentage of people. A safe and effective vaccine is required to tackle the current COVID-19 waves. There have been reports that clinical endpoints and psychological parameters are necessary to consider vaccine efficacy. This review examines the clinical endpoints required for a successful SARS-CoV-2 vaccine and the influences of psychological parameters on its efficacy. METHODS: The main research question was to find out the clinical endpoints that determine the vaccine efficacy? And what kind of psychological parameters affect the vaccine efficacy? The information was taken from several journals, databases, and scientific search engines like Googe scholar, Pubmed, Scopus, Web of Science, Science direct, WHO website, and other various sites. The research studies were searched using keywords; SAR-CoV-2 vaccine efficacy, psychological effect on SARS-CoV-2 vaccine, SARS-CoV-2 vaccine endpoints. RESULTS: This review has highlighted various clinical endpoints that are the main determinants of clinical vaccine efficacy. Currently, vaccinations are being carried out throughout the world; it is important to investigate the main determinants affecting vaccine efficacy. We have focused on the clinical endpoints and the influence of psychological parameters that affect the vaccine efficacy in clinical settings. The primary endpoints include the risk of infection, symptoms, and severity of COVID-19, while hospitalization length, supplemental oxygen requirement, and mechanical ventilation are secondary endpoints in the clinical endpoints. Some tangential endpoints were also considered, including organ dysfunction, stroke, and MI. Many psychological associated things have influenced the vaccine efficacy, like the lower antibody titers in the vaccinated people. In addition to that, Short- and long-term stress and sleep deprivation were also found to affect the vaccine efficacy. CONCLUSION: The review summarizes the important clinical endpoints required for a successful vaccine candidate. In addition to primary and secondary endpoints, auxiliary endpoints and the disease burden also play an important role in modulating vaccine efficacy. Moreover, the psychological perspective also influences vaccine efficacy. Effective follow-up of participants should follow to examine the clinical endpoints to reach any conclusion about vaccine efficacy.

Towards Zero Trust: The Design and Implementation of a Secure End-Point Device for Remote Working

COVID-19 pandemic and lockdowns forced employees across the world to work from home. Remote working has become a necessity rather than a choice. However, in order to meet this increasing demand, the most pressing security concerns of organizations should be addressed. In this paper, we present the design and implementation of ProGun, an end-point device (a USB dongle) for remote working. We present the hardware/software co-design of ProGun, by which most security risks due to lack of physical protection could be mitigated. We also discuss choices we made among many alternatives for user authentication and their security and usability implications in a remote working environment. © 2021 IEEE.

Assessing Change in Intervention Research: The Benefits of Composite Outcomes

Intervention research is often time- and resource-intensive, with numerous participants involved over extended periods of time. To maximize the value of intervention studies, multiple outcome measures are often included, either to ensure a diverse set of outcomes is being assessed or to refine assessments of specific outcomes. Here, we advocate for combining assessments, rather than relying on individual measures assessed separately, to better evaluate the effectiveness of interventions. Specifically, we argue that by pooling information from individual measures into a single outcome, composite scores can provide finer estimates of the underlying theoretical construct of interest while retaining important properties more sophisticated methods often forgo, such as transparency and interpretability. We describe different methods to compute, evaluate, and use composites depending on the goals, design, and data. To promote usability, we also provide a preregistration template that includes examples in the context of psychological interventions with supporting R code. Finally, we make a number of recommendations to help ensure that intervention studies are designed in a way that maximizes discoveries. A Shiny app and detailed R code accompany this article and are available at .

Performance of the inFLUenza Patient-Reported Outcome Plus (FLU-PRO Plus) Instrument in Patients With Coronavirus Disease 2019.

BACKGROUND: The inFLUenza Patient-Reported Outcome Plus (FLU-PRO Plus) is a patient-reported outcome data collection instrument assessing symptoms of viral respiratory tract infections across 8 body systems. This study evaluated the measurement properties of FLU-PRO Plus in a study enrolling individuals with coronavirus disease 2019 (COVID-19). METHODS: Data from a prospective cohort study (EPICC) in US Military Health System beneficiaries evaluated for COVID-19 was utilized. Adults with symptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with FLU-PRO Plus survey information within 1 week of symptom onset were included. Reliability of FLU-PRO Plus was estimated using intraclass correlation coefficient (ICC; 2 days' reproducibility). Known-groups validity was assessed using patient global assessment (PGA) of disease severity. Patient report of return to usual health was used to assess responsiveness (day 1-6/7). RESULTS: Two hundred twenty-six SARS-CoV-2-positive participants were included in the analysis. Reliability among those who reported no change in their symptoms from one day to the next was high for most domains (ICC range, 0.68-0.94 for day 1 to day 2). Construct validity was demonstrated by moderate to high correlation between the PGA rating of disease severity and domain and total scores (eg, total scores correlation: 0.69 [influenza-like illness severity], 0.69 [interference in daily activities], and -0.58 [physical health]). In addition, FLU-PRO Plus demonstrated good known-groups validity, with increasing domain and total scores observed with increasing severity ratings. CONCLUSIONS: FLU-PRO Plus performs well in measuring signs and symptoms in SARS-CoV-2 infection with excellent construct validity, known-groups validity, and responsiveness to change. Standardized data collection instruments facilitate meta-analyses, vaccine effectiveness studies, and other COVID-19 research activities.

Definitions and elements of endpoints in phase III randomized trials for the treatment of COVID-19: a cross-sectional analysis of trials registered in ClinicalTrials.gov.

BACKGROUND: There are several challenges in designing clinical trials for the treatment of novel infectious diseases, such as COVID-19. In particular, the definition of endpoints related to the severity, time frame, and clinical course remains unclear. Therefore, we conducted a cross-sectional analysis of phase III randomized trials for COVID-19 registered at ClinicalTrials.gov . METHODS: We collected the data from ClinicalTrials.gov on March 31, 2021, by specifying the following search conditions under Advanced Search: Condition or disease: (COVID-19) OR (SARS-CoV-2); Study type: Interventional Studies; Study Results: All Studies; Recruitment: Not yet recruiting, Recruiting, Enrolling by invitation, Active, Not recruiting, Suspended, Completed; Sex: All; and Phase: Phase 3. From the downloaded search results, we selected trials that met the following criteria: Primary Purpose: Treatment; Allocation: Randomized. We manually transcribed information not included in the downloaded file, such as Primary Outcome Measures, Secondary Outcome Measures, Time Frame, and Inclusion Criteria. In the analysis, we examined primary and secondary endpoints in trials with severe and non-severe patients, including the types of endpoints, time frame, clinical course, and sample size. RESULTS: A total of 406 trials were included in the analysis. The median numbers of endpoints in trials with severe and non-severe patients were 9 and 7, respectively. Approximately 25% of the trials used multiple primary endpoints. Regardless of the type of endpoint, the time frames were longer in the trials with severe patients than in the trials with non-severe patients. In the evaluation of the clinical course, worsening was often considered in binary endpoints, and improvement was considered in time-to-event endpoints. The sample size was the largest in clinical trials using binary endpoints. CONCLUSIONS: Endpoints can differ with respect to severity, and the clinical course and time frame are important for defining endpoints. This study provides information that can facilitate the achievement of a consensus for the endpoints in evaluating COVID-19 treatments.

Digital Endpoints: Definition, Benefits, and Current Barriers in Accelerating Development and Adoption.

The assessment of health and disease requires a set of criteria to define health status and progression. These health measures are referred to as "endpoints." A "digital endpoint" is defined by its use of sensor-generated data often collected outside of a clinical setting such as in a patient's free-living environment. Applicable sensors exist in an array of devices and can be applied in a diverse set of contexts. For example, a smartphone's microphone might be used to diagnose or predict mild cognitive impairment due to Alzheimer's disease or a wrist-worn activity monitor (such as those found in smartwatches) may be used to measure a drug's effect on the nocturnal activity of patients with sickle cell disease. Digital endpoints are generating considerable excitement because they permit a more authentic assessment of the patient's experience, reveal formerly untold realities of disease burden, and can cut drug discovery costs in half. However, before these benefits can be realized, effort must be applied not only to the technical creation of digital endpoints but also to the environment that allows for their development and application. The future of digital endpoints rests on meaningful interdisciplinary collaboration, sufficient evidence that digital endpoints can realize their promise, and the development of an ecosystem in which the vast quantities of data that digital endpoints generate can be analyzed. The fundamental nature of health care is changing. With coronavirus disease 2019 serving as a catalyst, there has been a rapid expansion of home care models, telehealth, and remote patient monitoring. The increasing adoption of these health-care innovations will expedite the requirement for a digital characterization of clinical status as current assessment tools often rely upon direct interaction with patients and thus are not fit for purpose to be administered remotely. With the ubiquity of relatively inexpensive sensors, digital endpoints are positioned to drive this consequential change. It is therefore not surprising that regulators, physicians, researchers, and consultants have each offered their assessment of these novel tools. However, as we further describe later, the broad adoption of digital endpoints will require a cooperative effort. In this article, we present an analysis of the current state of digital endpoints. We also attempt to unify the perspectives of the parties involved in the development and deployment of these tools. We conclude with an interdependent list of challenges that must be collaboratively addressed before these endpoints are widely adopted.

Placing the results of the SOLIDARITY trial with regards to remdesivir in perspective.

Remdesivir, a repurposed antiviral, was first accorded approval by the US Food Drug Administration (FDA) for the treatment of COVID-19 which necessitates hospitalization. However, the interim data of SOLIDARITY trial revealed no benefits with remdesivir for COVID-19 patients which led immediate debates in social media and the press about the utility of the drug. Both preclinical and clinical data demonstrated its efficacy in COVID-19. The recently concluded ACTT-1 trial showed its efficacy in reducing the duration of hospital stay which is of utmost importance for a country like India where reduction in bed occupancy can save lives of many and eases the financial burden of patient and government. Our benefit-risk analysis of ACTT-1 trial also favored the use of remdesivir over standard of care. The SOLIDARITY trial was fundamentally different from other clinical trials on remdesivir with respect to its design, adaptive nature, and selection of endpoints. Moreover, the success of antiviral therapy also depends on the timing of initiation and combination with other drugs. Hence we believe that drugs like Remdesivir are very important for countries like India where soft end points such as time to recovery and clinical improvement and early discharge become extremely significant during a pandemic.

Thrombocytopathies: Not Just Aggregation Defects-The Clinical Relevance of Procoagulant Platelets.

Platelets are active key players in haemostasis. Qualitative platelet dysfunctions result in thrombocytopathies variously characterized by defects of their adhesive and procoagulant activation endpoints. In this review, we summarize the traditional platelet defects in adhesion, secretion, and aggregation. In addition, we review the current knowledge about procoagulant platelets, focusing on their role in bleeding or thrombotic pathologies and their pharmaceutical modulation. Procoagulant activity is an important feature of platelet activation, which should be specifically evaluated during the investigation of a suspected thrombocytopathy.

Discussion on "Improving precision and power in randomized trials for COVID-19 treatments using covariate adjustment for binary, ordinal, and time-to-event outcomes".

Benkeser et al. present a very informative paper evaluating the efficiency gains of covariate adjustment in settings with binary, ordinal, and time-to-event outcomes. The adjustment method focuses on estimating the marginal treatment effect averaged over the covariate distribution in both arms combined. The authors show that covariate adjustment can achieve power gains that could find answers more quickly. The suggested approach is an important weapon in the armamentarium against epidemics like COVID-19. I recommend evaluating the procedure against more traditional approaches for conditional analyses (e.g., logistic regression) and against blinded methods of building prediction models followed by randomization-based inference.

Evaluating the Efficacy of Therapies in Patients With Coronavirus Disease 2019.

There is a proliferation of clinical trials worldwide to find effective therapies for patients diagnosed with coronavirus disease 2019 (COVID-19). The endpoints that are currently used to evaluate the efficacy of therapeutic agents against COVID-19 are focused on clinical status at a particular day or on time to a specific change of clinical status. To provide a full picture of the clinical course of a patient and make complete use of available data, we consider the trajectory of clinical status over the entire follow-up period. We also show how to combine the evidence of treatment effects on the occurrences of various clinical events. We compare the proposed and existing endpoints through extensive simulation studies. Finally, we provide guidelines on establishing the benefits of treatments.

Analysis of clinical and methodological characteristics of early COVID-19 treatment clinical trials: so much work, so many lost opportunities.

BACKGROUND: The COVID-19 pandemic continues to rage on, and clinical research has been promoted worldwide. We aimed to assess the clinical and methodological characteristics of treatment clinical trials that have been set forth as an early response to the COVID-19 pandemic. METHODS: First, we reviewed all registered clinical trials on COVID-19. The World Health Organization International Trials Registry Platform and national trial registries were searched for COVID-19 trials through April 19th, 2020. For each record, independent researchers extracted interventions, participants, and methodological characteristics. Second, on September 14th, 2020 we evaluated the recruitment status and availability of the results of COVID-19 treatment trials previously identified. RESULTS: In April 2020, a total of 580 trials evaluating COVID-19 treatment were registered. Reporting quality was poor (core participant information was missing in 24.1 to 92.7%). Between 54.0 and 93.8% of the trials did not plan to include older people or those with a higher baseline risk. Most studies were randomised (67.9%), single-centre (58.3%), non-industry-funded (81.1%), to be conducted in China (47.6%), with a median duration of 184 days and a median sample size of 100 participants. Core endpoints (mortality, clinical status, and hospitalization length) were planned to be assessed in 5.2 to 13.1% of the trials. Five months later, 66 trials (11.4%) were reported as "Completed", and only 46 (7.9%) had public results available. One hundred forty-four of 580 trials (24.8%) either had the status "Not yet recruiting" or "Suspended", and 18 (3.1%) trials were prematurely stopped ("Terminated" or "Withdrawn") The number of completed trials and trials with results are much lower than anticipated, considering the planned follow-up. CONCLUSIONS: Our results raise concerns about the success of the initial global research effort on COVID-19 treatment. The clinical and methodological characteristics of early COVID-19 treatment trials limit their capability to produce clear answers to critical questions in the shortest possible time.

Impact of COVID-19 Outbreak through Telemedicine Implementation on Data Reporting During Oncology Clinical Trials.

Coronavirus disease outbreak has affected all aspect of clinical care including cancer clinical trials. To minimize exposure of frail cancer patients, an implementation of telemedicine was retained. The impact of this implementation on primary and secondary endpoints criteria of ongoing clinical trials was analyzed. Out of 128 oncology clinical trials, 25 (19%) had an implementation of teleconsultation. Poor data reporting induced mainly a bias on qualitative and descriptive primary endpoints than those assessing efficacy (80% vs 20%; p < 0.001). The integration of telemedicine and E-technologies in the medical practices and clinical trials must be designed and validated.

Outcomes Evaluated in Controlled Clinical Trials on the Management of COVID-19: A Methodological Systematic Review.

It is crucial that randomized controlled trials (RCTs) on the management of coronavirus disease 2019 (COVID-19) evaluate the outcomes that are critical to patients and clinicians, to facilitate relevance, interpretability, and comparability. This methodological systematic review describes the outcomes evaluated in 415 RCTs on the management of COVID-19, that were registered with ClinicalTrials.gov, by 5 May 2020, and the instruments used to measure these outcomes. Significant heterogeneity was observed in the selection of outcomes and instruments. Mortality, adverse events and treatment success or failure are only evaluated in 64.4%, 48.4% and 43% of the included studies, respectively, while other outcomes are selected less often. Studies focusing on more severe presentations (hospitalized patients or requiring intensive care) most frequently evaluate mortality (72.5%) and adverse events (55.6%), while hospital admission (50.8%) and viral detection/load (55.6%) are most frequently assessed in the community setting. Outcome measurement instruments are poorly reported and heterogeneous. Follow-up does not exceed one month in 64.3% of these earlier trials, and long-term COVID-19 burden is rarely assessed. The methodological issues identified could delay the introduction of potentially life-saving treatments in clinical practice. Our findings demonstrate the need for greater consistency, to enable decision makers to compare and contrast studies.