Clinical Endpoints for Evaluating Efficacy in COVID-19 Vaccine Trials.
Ontology highlight
ABSTRACT:
SUBMITTER: Mehrotra DV
PROVIDER: S-EPMC7596738 | biostudies-literature | 2020 Oct
REPOSITORIES: biostudies-literature
Publications
Clinical Endpoints for Evaluating Efficacy in COVID-19 Vaccine Trials.
Mehrotra Devan V DV Janes Holly E HE Fleming Thomas R TR Annunziato Paula W PW Neuzil Kathleen M KM Carpp Lindsay N LN Benkeser David D Brown Elizabeth R ER Carone Marco M Cho Iksung I Donnell Deborah D Fay Michael P MP Fong Youyi Y Han Shu S Hirsch Ian I Huang Ying Y Huang Yunda Y Hyrien Ollivier O Juraska Michal M Luedtke Alex A Nason Martha M Vandebosch An A Zhou Honghong H Cohen Myron S MS Corey Lawrence L Hartzel Jonathan J Follmann Dean D Gilbert Peter B PB
Annals of internal medicine 20201022 2
Several vaccine candidates to protect against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or coronavirus disease 2019 (COVID-19) have entered or will soon enter large-scale, phase 3, placebo-controlled randomized clinical trials. To facilitate harmonized evaluation and comparison of the efficacy of these vaccines, a general set of clinical endpoints is proposed, along with considerations to guide the selection of the primary endpoints on the basis of clinical and stati ...[more]
Similar Datasets
Project description:BackgroundVaccine clinical trials should strive to recruit a racially, socioeconomically, and ethnically diverse range of participants to ensure appropriate representation that matches population characteristics. Yet, full inclusion in research is often limited.MethodsA single-center retrospective study was conducted of adults enrolled at Brigham and Women's Hospital (Boston, MA) between July 2020 and December 2021. Demographic characteristics, including age, race, ethnicity, ZIP code, and sex assigned at birth, were analyzed from both HIV and COVID-19 vaccine trials during the study period, acknowledging the limitations to representation under these parameters. We compared the educational attainment of vaccine trial participants to residents of the Massachusetts metropolitan area, geocoded participants' addresses to their census block group, and linked them to reported median household income levels from publicly available data for 2020. Frequency and quartile analyses were carried out, and spatial analyses were performed using ArcGIS Online web-based mapping software (Esri).ResultsA total of 1030 participants from four COVID-19 vaccine trials (n = 916 participants) and six HIV vaccine trials (n = 114 participants) were included in the analysis. The median age was 49 years (IQR 33-63) and 28 years (IQR 24-34) for the COVID-19 and HIV vaccine trials, respectively. Participants identifying as White were the majority group represented for both the COVID-19 (n = 598, 65.3%) and HIV vaccine trials (n = 83, 72.8%). Fewer than 25% of participants identified as Hispanic or Latin. Based on ZIP code of residence, the median household income for COVID-19 vaccine clinical trial participants (n = 846) was 102,088 USD (IQR = 81,442-126,094). For HIV vaccine clinical trial participants (n = 109), the median household income was 101,266 USD (IQR 75,052-108,832).ConclusionWe described the characteristics of participants enrolled for HIV and COVID-19 vaccine trials at a single center and found similitude in geographical distribution, median incomes, and proportion of underrepresented individuals between the two types of vaccine candidate trials. Further outreach efforts are needed to ensure the inclusion of individuals from lower educational and socioeconomic brackets. In addition, continued and sustained efforts are necessary to ensure inclusion of individuals from diverse racial and ethnic backgrounds.
| S-EPMC11311253 | biostudies-literature
Project description:Zika virus (ZIKV) infection during pregnancy is associated with microcephaly and other birth defects, collectively termed Congenital Zika Syndrome (CZS). During the epidemic in 2015-16, ZIKV spread through the Americas and quickly joined the list of other known teratogenic pathogens, TORCH. Multiple ZIKV vaccines have been developed for protection of pregnant women and women of childbearing age. However, ZIKV infection incidence has since waned substantially, and adverse birth outcomes are rare outcomes of infection. Studying a vaccine's protective efficacy against CZS in a large phase III clinical trial may be infeasible in such times of low incidence. Should trials be initiated, researchers may resort to alternative clinical endpoints. In this study, we simulate a variety of vaccine clinical trial scenarios to evaluate the feasibility of the CZS endpoint in vaccine studies and compare CZS to other potential outcomes: ZIKV infection detected through weekly, biweekly, or monthly testing and laboratory-confirmed, symptomatic Zika Virus Disease. We compare the sample size required for 80% statistical power to detect vaccine efficacy and trial duration for each scenario. Our results show the feasibility of CZS clinical endpoints depends on the timing of simulated clinical trials in the course of a seasonal epidemic, due to CZS risk varying with trimester of infection. This result highlights additional considerations needed when designing vaccine efficacy trials of protection against teratogenic pathogens.
| S-EPMC6450563 | biostudies-literature
Project description:Abstract Background Phase III trials have estimated COVID-19 vaccine efficacy (VE) against symptomatic and asymptomatic infection. We explore the direction and magnitude of potential biases in these estimates and their implications for vaccine protection against infection and against disease in breakthrough infections. Methods We developed a mathematical model that accounts for natural and vaccine-induced immunity, changes in serostatus and imperfect sensitivity and specificity of tests for infection and antibodies. We estimated expected biases in VE against symptomatic, asymptomatic and any SARS͏CoV2 infections and against disease following infection for a range of vaccine characteristics and measurement approaches, and the likely overall biases for published trial results that included asymptomatic infections. Results VE against asymptomatic infection measured by PCR or serology is expected to be low or negative for vaccines that prevent disease but not infection. VE against any infection is overestimated when asymptomatic infections are less likely to be detected than symptomatic infections and the vaccine protects against symptom development. A competing bias towards underestimation arises for estimates based on tests with imperfect specificity, especially when testing is performed frequently. Our model indicates considerable uncertainty in Oxford-AstraZeneca ChAdOx1 and Janssen Ad26.COV2.S VE against any infection, with slightly higher than published, bias-adjusted values of 59.0% (95% uncertainty interval [UI] 38.4 to 77.1) and 70.9% (95% UI 49.8 to 80.7) respectively. Conclusions Multiple biases are likely to influence COVID-19 VE estimates, potentially explaining the observed difference between ChAdOx1 and Ad26.COV2.S vaccines. These biases should be considered when interpreting both efficacy and effectiveness study results.
| S-EPMC8586723 | biostudies-literature
Project description:The first cases of coronavirus disease 2019 (COVID-19) were reported in December 2019 and the outbreak of SARS-CoV-2 was declared a pandemic in March 2020 by the World Health Organization. This sparked a plethora of investigations into diagnostics and vaccination for SARS-CoV-2, as well as treatments for COVID-19. Since COVID-19 is a severe disease associated with a high mortality, clinical trials in this disease should be monitored by a data monitoring committee (DMC), also known as data safety monitoring board (DSMB). DMCs in this indication face a number of challenges including fast recruitment requiring an unusually high frequency of safety reviews, more frequent use of complex designs and virtually no prior experience with the disease. In this paper, we provide a perspective on the work of DMCs for clinical trials of treatments for COVID-19. More specifically, we discuss organizational aspects of setting up and running DMCs for COVID-19 trials, in particular for trials with more complex designs such as platform trials or adaptive designs. Furthermore, statistical aspects of monitoring clinical trials of treatments for COVID-19 are considered. Some recommendations are made regarding the presentation of the data, stopping rules for safety monitoring and the use of external data. The proposed stopping boundaries are assessed in a simulation study motivated by clinical trials in COVID-19.
| S-EPMC7833551 | biostudies-literature
Project description:Several candidate vaccines to prevent COVID-19 disease have entered large-scale phase 3 placebo-controlled randomized clinical trials and some have demonstrated substantial short-term efficacy. Efficacious vaccines should, at some point, be offered to placebo participants, which will occur before long-term efficacy and safety are known. Following vaccination of the placebo group, we show that placebo-controlled vaccine efficacy can be derived by assuming the benefit of vaccination over time has the same profile for the original vaccine recipients and the placebo crossovers. This reconstruction allows estimation of both vaccine durability and potential vaccine-associated enhanced disease. Post-crossover estimates of vaccine efficacy can provide insights about durability, identify waning efficacy, and identify late enhancement of disease, but are less reliable estimates than those obtained by a standard trial where the placebo cohort is maintained. As vaccine efficacy estimates for post-crossover periods depend on prior vaccine efficacy estimates, longer pre-crossover periods with higher case counts provide better estimates of late vaccine efficacy. Further, open-label crossover may lead to riskier behavior in the immediate crossover period for the unblinded vaccine arm, confounding vaccine efficacy estimates for all post-crossover periods. We advocate blinded crossover and continued follow-up of trial participants to best assess vaccine durability and potential delayed enhancement of disease. This approach allows placebo recipients timely access to the vaccine when it would no longer be proper to maintain participants on placebo, yet still allows important insights about immunological and clinical effectiveness over time.
| S-EPMC7745130 | biostudies-literature
Project description:To speed the development of vaccines against SARS-CoV-2, the United States Federal Government has funded multiple phase 3 trials of candidate vaccines. A single 11-member data and safety monitoring board (DSMB) monitors all government-funded trials to ensure coordinated oversight, promote harmonized designs, and allow shared insights related to safety across trials. DSMB reviews encompass 3 domains: (1) the conduct of trials, including overall and subgroup accrual and data quality and completeness; (2) safety, including individual events of concern and comparisons by randomized group; and (3) interim analyses of efficacy when event-driven milestones are met. Challenges have included the scale and pace of the trials, the frequency of safety events related to the combined enrollment of over 100 000 participants, many of whom are older adults or have comorbid conditions that place them at independent risk of serious health events, and the politicized environment in which the trials have taken place.
| S-EPMC8240876 | biostudies-literature
Project description:To rapidly evaluate the safety and efficacy of COVID-19 vaccine candidates, prioritizing vaccine trial sites in areas with high expected disease incidence can speed endpoint accrual and shorten trial duration. Mathematical and statistical forecast models can inform the process of site selection, integrating available data sources and facilitating comparisons across locations. We recommend the use of ensemble forecast modeling - combining projections from independent modeling groups - to guide investigators identifying suitable sites for COVID-19 vaccine efficacy trials. We describe an appropriate structure for this process, including minimum requirements, suggested output, and a user-friendly tool for displaying results. Importantly, we advise that this process be repeated regularly throughout the trial, to inform decisions about enrolling new participants at existing sites with waning incidence versus adding entirely new sites. These types of data-driven models can support the implementation of flexible efficacy trials tailored to the outbreak setting.
| S-EPMC7492005 | biostudies-literature
Project description:BackgroundCystic fibrosis (CF) pulmonary exacerbations can be serious respiratory events and reduction in exacerbation rate or risk are important efficacy endpoints for CF therapeutic trials. Variability in exacerbation diagnoses and treatment have led drug developers to employ "objective" exacerbation definitions combining antimicrobial treatment (AT) and the presence of ?4 of 12 respiratory criteria (first published by Fuchs et al. [NEJM 1994;331(10):637-42]). Assumptions underlying this approach have yet to be formally evaluated.MethodsRespiratory events (RE) observed during a 48-week trial of ataluren (NCT02139306), a read-through agent for premature nonsense codons, were compared across six exacerbation definitions: any AT, intravenous AT (IVAT), ?4 Fuchs criteria present, AT plus ?4 Fuchs criteria, IVAT plus ?4 Fuchs criteria, and investigator assessment. Fuchs definitions were evaluated by assessing missingness of individual criteria and associations between criteria presence and clinician exacerbation assessment.ResultsAmong 751 RE, more than one third had ?4 Fuchs criteria present but were not assessed as exacerbations by investigators. Data for ?1 and for 4 Fuchs criteria, respectively, were missing for ~ 90% and >30% of RE. Only 6/12 Fuchs criteria were present more often when investigators assessed RE as exacerbations than when they did not.Conclusions"Objective" definitions have shortcomings inconsistent with their purpose of optimizing exacerbation capture in clinical trials : 1) they capture events clinicians do not consider exacerbations, 2) are prone to data missingness which can bias the likelihood of meeting the definition, and 3) employ criteria that are not associated with investigator assessment of exacerbation.
| S-EPMC7362840 | biostudies-literature
Project description:The global effort to develop a coronavirus disease 2019 (COVID-19) vaccine is on track to produce one or more authorized vaccines. We examine how different definitions and thresholds of vaccine efficacy, coupled with different levels of implementation effectiveness and background epidemic severity, translate into outcomes including cumulative infections, hospitalizations, and deaths. Using a mathematical simulation of vaccination, we find that factors related to implementation will contribute more to the success of vaccination programs than a vaccine's efficacy as determined in clinical trials. The benefits of a vaccine will decline substantially in the event of manufacturing or deployment delays, significant vaccine hesitancy, or greater epidemic severity. Our findings demonstrate the urgent need for health officials to invest greater financial resources and attention to vaccine production and distribution programs, to redouble efforts to promote public confidence in COVID-19 vaccines, and to encourage continued adherence to other mitigation approaches, even after a vaccine becomes available.
| S-EPMC7931245 | biostudies-literature
Project description:Supplemental Digital Content is available in the text Abstract The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to scale up around the world, costing severe health and economic losses. The development of an effective COVID-19 vaccine is of utmost importance. Most vaccine designs can be classified into three camps: protein based (inactivated vaccines, protein subunit, VLP and T-cell based vaccines), gene based (DNA or RNA vaccines, replicating or non-replicating viral/bacterial vectored vaccines), and a combination of both protein-based and gene-based (live-attenuated virus vaccines). Up to now, 237 candidate vaccines against SARS-CoV-2 are in development worldwide, of which 63 have been approved for clinical trials and 27 are evaluated in phase 3 clinical trials. Six candidate vaccines have been authorized for emergency use or conditional licensed, based on their efficacy data in phase 3 trials. This review summarizes the strengths and weaknesses of the candidate COVID-19 vaccines from various platforms, compares, and discusses their protective efficacy, safety, and immunogenicity according to the published clinical trials results.
| S-EPMC8057314 | biostudies-literature