Clinical trial results usually tell us how effective a treatment was on average for the overall group of participants, but a key question for clinicians, patients and policy makers is: which individual patients benefit most from the treatment and which don’t benefit as much? In the latest episode of the Trial Talk podcast, Peter Godolphin and David Fisher discuss a new method for determining how treatment effects differ between subgroups of patients across multiple clinical trials, as well as how other meta-analysis researchers can use it.
Resources:
• Estimating interactions and subgroup-specific treatment effects in meta-analysis without aggregation bias: A within-trial framework onlinelibrary.wiley.com/doi/10.1002/jrsm.1590
• Cochrane webinar recording training.cochrane.org/resource/estim…-meta-analysis
• GitHub page for metafloat package in Stata github.com/UCL/metafloat
• WHO REACT Group: IL6 Prospective meta-analysis jamanetwork.com/journals/jama/fullarticle/2781880
• STOPCAP collaborators: Docetaxel IPD meta-analysis
www.thelancet.com/journals/lanonc/…00230-9/fulltext For questions about the within-trial framework for subgroup analysis, you can email
d.fisher@ucl.ac.uk or
p.godolphin@ucl.ac.uk.
For more information and to access the transcript: bit.ly/43boETF
For questions or feedback on the podcast series, message us at
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Date of episode recording: 2024-03-12T
00:00:00Z
Duration:
00:28:44 Language of episode: English
Presenter: Charlotte Hartley
Guests: Peter Godolphin, David Fisher
Producer: Charlotte Hartley