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Remiro-Azócar, Antonio; Heath, Anna; Baio, Gianluca – Research Synthesis Methods, 2023
We examine four important considerations in the development of covariate adjustment methodologies for indirect treatment comparisons. First, we consider potential advantages of weighting versus outcome modeling, placing focus on bias-robustness. Second, we outline why model-based extrapolation may be required and useful, in the specific context of…
Descriptors: Medical Research, Outcomes of Treatment, Comparative Analysis, Barriers
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Proctor, Tanja; Zimmermann, Samuel; Seide, Svenja; Kieser, Meinhard – Research Synthesis Methods, 2022
During drug development, a biomarker is sometimes identified as separating a patient population into those with more and those with less benefit from evaluated treatments. Consequently, later studies might be targeted, while earlier ones are performed in mixed patient populations. This poses a challenge in evidence synthesis, especially if only…
Descriptors: Comparative Analysis, Meta Analysis, Patients, Medical Research
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Nejstgaard, Camilla Hansen; Lundh, Andreas; Abdi, Suhayb; Clayton, Gemma; Gelle, Mustafe Hassan Adan; Laursen, David Ruben Teindl; Olorisade, Babatunde Kazeem; Savovic, Jelena; Hróbjartsson, Asbjørn – Research Synthesis Methods, 2022
Randomised trials are often funded by commercial companies and methodological studies support a widely held suspicion that commercial funding may influence trial results and conclusions. However, these studies often have a risk of confounding and reporting bias. The risk of confounding is markedly reduced in meta-epidemiological studies that…
Descriptors: Medical Research, Randomized Controlled Trials, Corporations, Financial Support
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Schmitz, Tom; Bukowski, Mark; Koschmieder, Steffen; Schmitz-Rode, Thomas; Farkas, Robert – Research Synthesis Methods, 2019
Launching biomedical innovations based on clinical demands instead of translating basic research findings to practice reduces the risk that the results will not fit the clinical routine. To realize this type of innovation, a meta-analysis of the body of research is necessary to reveal demand-matching concepts. However, both the data deluge and the…
Descriptors: Innovation, Biomedicine, Medical Research, Meta Analysis
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Leahy, Joy; O'Leary, Aisling; Afdhal, Nezam; Gray, Emma; Milligan, Scott; Wehmeyer, Malte H.; Walsh, Cathal – Research Synthesis Methods, 2018
The use of individual patient data (IPD) in network meta-analysis (NMA) is becoming increasingly popular. However, as most studies do not report IPD, most NMAs are performed using aggregate data for at least some, if not all, of the studies. We investigate the benefits of including varying proportions of IPD studies in an NMA. Several models have…
Descriptors: Patients, Medical Research, Meta Analysis, Network Analysis
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Anderson, Patricia F.; Shannon, Carol; Bickett, Skye; Doucette, Joanne; Herring, Pamela; Kepsel, Andrea; Lyons, Tierney; McLachlan, Scott; Wu, Lin – Research Synthesis Methods, 2018
When the Medical Library Association identified questions critical for the future of the profession, it assigned groups to use systematic reviews to find the answers to these questions. Group 6, whose question was on emerging technologies, recognized early on that the systematic review process would not work well for this question, which looks…
Descriptors: Case Studies, Comparative Analysis, Medical Research, Medical Libraries