A primer on effectiveness and efficacy trials.
Ontology highlight
ABSTRACT:
SUBMITTER: Singal AG
PROVIDER: S-EPMC3912314 | biostudies-other | 2014
REPOSITORIES: biostudies-other
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Project description:We propose an "efficacy-to-effectiveness" (E2E) clinical trial design, in which an effectiveness trial would commence seamlessly upon completion of the efficacy trial. Efficacy trials use inclusion/exclusion criteria to produce relatively homogeneous samples of participants with the target condition, conducted in settings that foster adherence to rigorous clinical protocols. Effectiveness trials use inclusion/exclusion criteria that generate heterogeneous samples that are more similar to the general patient spectrum, conducted in more varied settings, with protocols that approximate typical clinical care. In E2E trials, results from the efficacy trial component would be used to design the effectiveness trial component, to confirm and/or discern associations between clinical characteristics and treatment effects in typical care, and potentially to test new hypotheses. An E2E approach may improve the evidentiary basis for selecting treatments, expand understanding of the effectiveness of treatments in subgroups with particular clinical features, and foster incorporation of effectiveness information into regulatory processes.
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Project description:In prevention trials, outcomes of interest frequently include data that are best quantified as proportion scores. In some cases, however, proportion scores may violate the statistical assumptions underlying common analytic methods. In this paper, we provide guidelines for analyzing frequency and proportion data as primary outcomes. We describe standard methods including generalized linear regression models to compare mean proportion scores and examine tools for testing normality and other assumptions for each model. Recommendations are made for instances when the assumptions are not met, including transformations for proportion scores that are non-normal. We also discuss more sophisticated analytical tools to model change in proportion scores over time. The guidelines provide ready-to-use analytical strategies for frequency and proportion data that are commonly encountered in prevention science.
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Project description:Background and aimsThe emergence of SARS CoV2 or COVID 19 pandemic has shocking results on major global public health. This review aims to discuss the nine prominent COVID 19 vaccines with regard to their immunogenicity, efficacy, and effectiveness against the SARS CoV2 variants.MethodsElectronic databases such as Medline/PubMed, EMBASE, Scopus, science websites, and Google scholar were accessed to retrieve the research published about COVID 19 vaccines.ResultsAll the adverse impact ranging from mild to moderate in the clinical trials were analysed, however, there were less reports in which COVID 19 patients either developed severe reactions or died due to the different experimental vaccines. Moreover, SARS CoV2 variants like Delta could escape the immune response.ConclusionOverall, the data suggest that the two doses of COVID 19 vaccines are extremely effective against the original SARS CoV2 virus, and also provide well protection against SARS CoV2 variants, especially in severe illnesses. However, a third dose of the COVID 19 vaccine (also said to be the booster dose) will be needed in some immune-compromised people.
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Project description:Genotyping of allelic variants of Plasmodium falciparum merozoite surface proteins 1 and 2 (msp-1 and msp-2), and the glutamate-rich protein is the gold standard for distinguishing reinfections from recrudescences in antimalarial drug trials. We compared performance of the recently developed 24-single-nucleotide polymorphism (SNP) Barcoding Assay against msp-1 and msp-2 genotyping in a cluster-randomized effectiveness trial of artemether-lumefantrine and dihydroartemisinin-piperaquine in Malawi. Rates of recrudescence and reinfection estimated by the two methods did not differ significantly (Fisher's exact test; P = 0.887 and P = 0.768, respectively). There was a strong agreement between the two methods in predicting treatment outcomes and resolving the genetic complexity of malaria infections in this setting. These results support the use of this SNP assay as an alternative method for correcting antimalarial efficacy/effectiveness data.
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Project description:BackgroundPolymerase chain reaction (PCR) is very useful in many areas of molecular biology research. It is commonly observed that PCR success is critically dependent on design of an effective primer pair. Current tools for primer design do not adequately address the problem of PCR failure due to mis-priming on target-related sequences and structural variations in the genome.MethodsWe have developed an integrated graphical web-based application for primer design, called RExPrimer, which was written in Python language. The software uses Primer3 as the primer designing core algorithm. Locally stored sequence information and genomic variant information were hosted on MySQLv5.0 and were incorporated into RExPrimer.ResultsRExPrimer provides many functionalities for improved PCR primer design. Several databases, namely annotated human SNP databases, insertion/deletion (indel) polymorphisms database, pseudogene database, and structural genomic variation databases were integrated into RExPrimer, enabling an effective without-leaving-the-website validation of the resulting primers. By incorporating these databases, the primers reported by RExPrimer avoid mis-priming to related sequences (e.g. pseudogene, segmental duplication) as well as possible PCR failure because of structural polymorphisms (SNP, indel, and copy number variation (CNV)). To prevent mismatching caused by unexpected SNPs in the designed primers, in particular the 3' end (SNP-in-Primer), several SNP databases covering the broad range of population-specific SNP information are utilized to report SNPs present in the primer sequences. Population-specific SNP information also helps customize primer design for a specific population. Furthermore, RExPrimer offers a graphical user-friendly interface through the use of scalable vector graphic image that intuitively presents resulting primers along with the corresponding gene structure. In this study, we demonstrated the program effectiveness in successfully generating primers for strong homologous sequences.ConclusionThe improvements for primer design incorporated into RExPrimer were demonstrated to be effective in designing primers for challenging PCR experiments. Integration of SNP and structural variation databases allows for robust primer design for a variety of PCR applications, irrespective of the sequence complexity in the region of interest. This software is freely available at http://www4a.biotec.or.th/rexprimer.
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Project description:Background and objectiveRandomized trials may be designed to provide evidence more strongly related to efficacy or effectiveness of an intervention. When systematic reviews are used to inform clinical or policy decisions, it is important to know the efficacy-effectiveness nature of the included trials. The objective of this study was to develop a tool to characterize randomized trials included in a systematic review on an efficacy-effectiveness continuum.MethodsWe extracted rating domains and descriptors from existing tools and used a modified Delphi procedure to condense the domains and develop a new tool. The feasibility and interrater reliability of the tool was tested on trials from four systematic reviews.ResultsThe Rating of Included Trials on the Efficacy-Effectiveness Spectrum (RITES) tool rates clinical trials on a five-point Likert scale in four domains: (1) participant characteristics, (2) trial setting, (3) flexibility of interventions, and (4) clinical relevance of interventions. When RITES was piloted on trials from three reviews by unaffiliated raters, ratings were variable (intraclass correlation coefficient [ICC] 0.25-0.66 for the four domains); but, when RITES was used on one review by the review authors with expertise on the topic, the ratings were consistent (ICCs > 0.80.ConclusionRITES may help to characterize the efficacy-effectiveness nature of trials included in systematic reviews.
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Project description:SummaryThe coronavirus disease-2019 (COVID-19) pandemic has resulted in a proliferation of clinical trials designed to slow the spread of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). Many therapeutic agents that are being used to treat patients with COVID-19 are repurposed treatments for influenza, Ebola, or for malaria that were developed decades ago and are unlikely to be familiar to the cardiovascular and cardio-oncology communities. Here, the authors provide a foundation for cardiovascular and cardio-oncology physicians on the front line providing care to patients with COVID-19, so that they may better understand the emerging cardiovascular epidemiology and the biological rationale for the clinical trials that are ongoing for the treatment of patients with COVID-19.
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Project description:The coronavirus disease-2019 (COVID-19) pandemic has resulted in a proliferation of clinical trials designed to slow the spread of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). Many therapeutic agents that are being used to treat patients with COVID-19 are repurposed treatments for influenza, Ebola, or for malaria that were developed decades ago and are unlikely to be familiar to the cardiovascular and cardio-oncology communities. Here, we provide a foundation for cardiovascular and cardio-oncology physicians on the front line providing care to patients with COVID-19, so that they may better understand the emerging cardiovascular epidemiology and the biological rationale for the clinical trials that are ongoing for the treatment of patients with COVID-19.
| S-EPMC7164888 | biostudies-literature
Project description:The coronavirus disease-2019 (COVID-19) pandemic has resulted in a proliferation of clinical trials designed to slow the spread of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). Many therapeutic agents that are being used to treat patients with COVID-19 are repurposed treatments for influenza, Ebola, or for malaria that were developed decades ago and are unlikely to be familiar to the cardiovascular and cardio-oncology communities. Here, the authors provide a foundation for cardiovascular and cardio-oncology physicians on the front line providing care to patients with COVID-19, so that they may better understand the emerging cardiovascular epidemiology and the biological rationale for the clinical trials that are ongoing for the treatment of patients with COVID-19.
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Project description:BackgroundConsidered one of the highest levels of evidence, results of randomized controlled trials (RCTs) remain an essential building block in mental health research. They are frequently used to confirm that an intervention "works" and to guide treatment decisions. Given their importance in the field, it is concerning that the quality of many RCT evaluations in mental health research remains poor. Common errors range from inadequate missing data handling and inappropriate analyses (e.g., baseline randomization tests or analyses of within-group changes) to unduly interpretations of trial results and insufficient reporting. These deficiencies pose a threat to the robustness of mental health research and its impact on patient care. Many of these issues may be avoided in the future if mental health researchers are provided with a better understanding of what constitutes a high-quality RCT evaluation.MethodsIn this primer article, we give an introduction to core concepts and caveats of clinical trial evaluations in mental health research. We also show how to implement current best practices using open-source statistical software.ResultsDrawing on Rubin's potential outcome framework, we describe that RCTs put us in a privileged position to study causality by ensuring that the potential outcomes of the randomized groups become exchangeable. We discuss how missing data can threaten the validity of our results if dropouts systematically differ from non-dropouts, introduce trial estimands as a way to co-align analyses with the goals of the evaluation, and explain how to set up an appropriate analysis model to test the treatment effect at one or several assessment points. A novice-friendly tutorial is provided alongside this primer. It lays out concepts in greater detail and showcases how to implement techniques using the statistical software R, based on a real-world RCT dataset.DiscussionMany problems of RCTs already arise at the design stage, and we examine some avoidable and unavoidable "weak spots" of this design in mental health research. For instance, we discuss how lack of prospective registration can give way to issues like outcome switching and selective reporting, how allegiance biases can inflate effect estimates, review recommendations and challenges in blinding patients in mental health RCTs, and describe problems arising from underpowered trials. Lastly, we discuss why not all randomized trials necessarily have a limited external validity and examine how RCTs relate to ongoing efforts to personalize mental health care.
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