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Direct linkSuzanne 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
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
Daly, Caitlin H.; Maconachie, Ross; Ades, A. E.; Welton, Nicky J. – Research Synthesis Methods, 2022
Randomised controlled trials of cancer treatments typically report progression free survival (PFS) and overall survival (OS) outcomes. Existing methods to synthesise evidence on PFS and OS either rely on the proportional hazards assumption or make parametric assumptions which may not capture the diverse survival curve shapes across studies and…
Descriptors: Nonparametric Statistics, Randomized Controlled Trials, Evidence, Networks
