SynthesisStatistics in medicine2021
Prospective individual patient data meta-analysis: Evaluating convalescent plasma for COVID-19.
Synthesis in Statistics in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 6 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- Association between COVID-19 convalescent plasma antibody levels and COVID-19 outcomes stratified by clinical status at presentation.BMC infectious diseases · 2024Pooled it
- Overlapping research efforts in a global pandemic: a rapid systematic review of COVID-19-related individual participant data meta-analyses.BMC health services research · 2023Pooled it
- Developing a Bayesian hierarchical model for a prospective individual patient data meta-analysis with continuous monitoring.BMC medical research methodology · 2023Pooled it
- Association of Convalescent Plasma Treatment With Clinical Status in Patients Hospitalized With COVID-19: A Meta-analysis.JAMA network open · 2022Pooled it
- Hydroxychloroquine/chloroquine for the treatment of hospitalized patients with COVID-19: An individual participant data meta-analysis.PloS one · 2022Pooled it
- Prospective individual patient data meta-analysis: Evaluating convalescent plasma for COVID-19.Statistics in medicine · 2021Pooled it
- A randomized controlled study of convalescent plasma for individuals hospitalized with COVID-19 pneumonia.The Journal of clinical investigation · 2021Trial
- Methods for Analysing Patient-Level Utility Data: Insights from the Literature Review and Recent NICE Technology Appraisals.PharmacoEconomics · 2026Review
- A Bayesian Multi-Factorial Design and Analysis for Estimating Combined Effects of Multiple Interventions in a Pragmatic Clinical Trial to Improve Dementia Care.Statistics in medicine · 2025Article
- A Bayesian multivariate hierarchical model for developing a treatment benefit index using mixed types of outcomes.BMC medical research methodology · 2024Article
- Improving Individualized Treatment Decisions: A Bayesian Multivariate Hierarchical Model for Developing a Treatment Benefit Index using Mixed Types of Outcomes.medRxiv : the preprint server for health sciences · 2024Article
- Hydroxychloroquine/chloroquine for the treatment of hospitalized patients with COVID-19: An individual participant data meta-analysis.medRxiv : the preprint server for health sciences · 2022Article
- Development and Validation of a Treatment Benefit Index to Identify Hospitalized Patients With COVID-19 Who May Benefit From Convalescent Plasma.JAMA network open · 2022Article
- ALL-IN meta-analysis: breathing life into living systematic reviews and prospective meta-analyses.F1000Research · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
As the world faced the devastation of the COVID-19 pandemic in late 2019 and early 2020, numerous clinical trials were initiated in many locations in an effort to establish the efficacy (or lack thereof) of potential treatments. As the pandemic has been shifting locations rapidly, individual studies have been at risk of failing to meet recruitment targets because of declining numbers of eligible patients with COVID-19 encountered at participating sites. It has become clear that it might take several more COVID-19 surges at the same location to achieve full enrollment and to find answers about what treatments are effective for this disease. This paper proposes an innovative approach for pooling patient-level data from multiple ongoing randomized clinical trials (RCTs) that have not been configured as a network of sites. We present the statistical analysis plan of a prospective individual patient data (IPD) meta-analysis (MA) from ongoing RCTs of convalescent plasma (CP). We employ an adaptive Bayesian approach for continuously monitoring the accumulating pooled data via posterior probabilities for safety, efficacy, and harm. Although we focus on RCTs for CP and address specific challenges related to CP treatment for COVID-19, the proposed framework is generally applicable to pooling data from RCTs for other therapies and disease settings in order to find answers in weeks or months, rather than years.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.