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Kollin W. Rott; Gert Bronfort; Haitao Chu; Jared D. Huling; Brent Leininger; Mohammad Hassan Murad; Zhen Wang; James S. Hodges – Research Synthesis Methods, 2024
Meta-analysis is commonly used to combine results from multiple clinical trials, but traditional meta-analysis methods do not refer explicitly to a population of individuals to whom the results apply and it is not clear how to use their results to assess a treatment's effect for a population of interest. We describe recently-introduced causally…
Descriptors: Meta Analysis, Causal Models, Outcomes of Treatment, Medical Research
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Suzanne C. Freeman; Alex J. Sutton; Nicola J. Cooper; Alessandro Gasparini; Michael J. Crowther; Neil Hawkins – Research Synthesis Methods, 2024
Background: Traditionally, meta-analysis of time-to-event outcomes reports a single pooled hazard ratio assuming proportional hazards (PH). For health technology assessment evaluations, hazard ratios are frequently extrapolated across a lifetime horizon. However, when treatment effects vary over time, an assumption of PH is not always valid. The…
Descriptors: Cancer, Medical Research, Bayesian Statistics, Meta Analysis
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Yoneoka, Daisuke; Omae, Katsuhiro; Henmi, Masayuki; Eguchi, Shinto – Research Synthesis Methods, 2023
The number of clinical prediction models sharing the same prediction task has increased in the medical literature. However, evidence synthesis methodologies that use the results of these prediction models have not been sufficiently studied, particularly in the context of meta-analysis settings where only summary statistics are available. In…
Descriptors: Prediction, Task Analysis, Medical Research, Outcomes of Treatment
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Lauren Maxwell; Priya Shreedhar; Mabel Carabali; Brooke Levis – Research Synthesis Methods, 2024
Individual participant data meta-analyses (IPD-MAs) have several benefits over standard aggregate data meta-analyses, including the consideration of additional participants, follow-up time, and the joint consideration of study- and participant-level heterogeneity for improved diagnostic and prognostic model development and evaluation. However,…
Descriptors: Research Methodology, Authors, Guides, Budgets
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Li, Hua; Shih, Ming-Chieh; Tu, Yu-Kang – Research Synthesis Methods, 2023
Component network meta-analysis (CNMA) compares treatments comprising multiple components and estimates the effects of individual components. For network meta-analysis, a standard network plot with nodes for treatments and edges for direct comparisons between treatments is drawn to visualize the evidence structure and the connections between…
Descriptors: Networks, Meta Analysis, Graphs, Comparative Analysis
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Alqaidoom, Zainab; Nguyen, Phi-Yen; Awadh, Maryam; Page, Matthew J. – Research Synthesis Methods, 2023
Systematic reviewers are advised to search trials registers to minimise risk of reporting biases. However, there has been little research on the impact of searching trials registers on the results of meta-analyses. We aimed to evaluate the impact of searching clinical trials registers for systematic reviews of pharmaceutical or non-pharmaceutical…
Descriptors: Experimental Groups, Medical Research, Drug Therapy, Pharmacology
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Evrenoglou, Theodoros; Boutron, Isabelle; Seitidis, Georgios; Ghosn, Lina; Chaimani, Anna – Research Synthesis Methods, 2023
Outputs from living evidence syntheses projects have been used widely during the pandemic by guideline developers to form evidence-based recommendations. However, the needs of different stakeholders cannot be accommodated by solely providing pre-defined non amendable numerical summaries. Stakeholders also need to understand the data and perform…
Descriptors: COVID-19, Pandemics, Meta Analysis, Computer Oriented Programs
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Siemens, Waldemar; Meerpohl, Joerg J.; Rohe, Miriam S.; Buroh, Sabine; Schwarzer, Guido; Becker, Gerhild – Research Synthesis Methods, 2022
Using the Hartung-Knapp method and 95% prediction intervals (PIs) in random-effects meta-analyses is recommended by experts but rarely applied. Therefore, we aimed to reevaluate statistically significant meta-analyses using the Hartung-Knapp method and 95% PIs. In this methodological study, three databases were searched from January 2010 to July…
Descriptors: Cancer, Meta Analysis, Medical Research, Patients
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Siegel, Lianne; Murad, M. Hassan; Chu, Haitao – Research Synthesis Methods, 2021
Often clinicians are interested in determining whether a subject's measurement falls within a normal range, defined as a range of values of a continuous outcome which contains some proportion (eg, 95%) of measurements from a healthy population. Several studies in the biomedical field have estimated reference ranges based on a meta-analysis of…
Descriptors: Meta Analysis, Medical Research, Biomedicine, Bayesian Statistics
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Siegel, Lianne; Chu, Haitao – Research Synthesis Methods, 2023
Reference intervals, or reference ranges, aid medical decision-making by containing a pre-specified proportion (e.g., 95%) of the measurements in a representative healthy population. We recently proposed three approaches for estimating a reference interval from a meta-analysis based on a random effects model: a frequentist approach, a Bayesian…
Descriptors: Bayesian Statistics, Meta Analysis, Intervals, Decision Making
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Prathiba Natesan Batley; Erica B. McClure; Brandy Brewer; Ateka A. Contractor; Nicholas John Batley; Larry Vernon Hedges; Stephanie Chin – Grantee Submission, 2023
N-of-1 trials, a special case of Single Case Experimental Designs (SCEDs), are prominent in clinical medical research and specifically psychiatry due to the growing significance of precision/personalized medicine. It is imperative that these clinical trials be conducted, and their data analyzed, using the highest standards to guard against threats…
Descriptors: Medical Research, Research Design, Data Analysis, Effect Size
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Page, Matthew J.; Sterne, Jonathan A. C.; Higgins, Julian P. T.; Egger, Matthias – Research Synthesis Methods, 2021
A "P" value, or the magnitude or direction of results can influence decisions about whether, when, and how research findings are disseminated. Regardless of whether an entire study or a particular study result is unavailable because investigators considered the results to be unfavorable, bias in a meta-analysis may occur when available…
Descriptors: Publications, Bias, Medical Research, Meta Analysis
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Godolphin, Peter J.; White, Ian R.; Tierney, Jayne F.; Fisher, David J. – Research Synthesis Methods, 2023
Estimation of within-trial interactions in meta-analysis is crucial for reliable assessment of how treatment effects vary across participant subgroups. However, current methods have various limitations. Patients, clinicians and policy-makers need reliable estimates of treatment effects within specific covariate subgroups, on relative and absolute…
Descriptors: Meta Analysis, Outcomes of Treatment, Medical Research, Comparative Analysis
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Weber, Frank; Knapp, Guido; Glass, Änne; Kundt, Günther; Ickstadt, Katja – Research Synthesis Methods, 2021
There exists a variety of interval estimators for the overall treatment effect in a random-effects meta-analysis. A recent literature review summarizing existing methods suggested that in most situations, the Hartung-Knapp/Sidik-Jonkman (HKSJ) method was preferable. However, a quantitative comparison of those methods in a common simulation study…
Descriptors: Meta Analysis, Computation, Intervals, Statistical Analysis
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Noma, Hisashi; Hamura, Yasuyuki; Sugasawa, Shonosuke; Furukawa, Toshi A. – Research Synthesis Methods, 2023
Network meta-analysis has played an important role in evidence-based medicine for assessing the comparative effectiveness of multiple available treatments. The prediction interval has been one of the standard outputs in recent network meta-analysis as an effective measure that enables simultaneous assessment of uncertainties in treatment effects…
Descriptors: Intervals, Meta Analysis, Evidence Based Practice, Comparative Analysis
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