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Episode 3: Subgroup analysis - Who benefits most from a treatment?

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内容由UCL Minds提供。所有播客内容(包括剧集、图形和播客描述)均由 UCL Minds 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

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 mrcctu.engage@ucl.ac.uk
As a listener, your opinion is very valuable to us. Please help us to improve the podcast in the future by filling in this short survey: forms.office.com/e/PjfjQ5Mn6g

Date of episode recording: 2024-03-12T00:00:00Z
Duration: 00:28:44
Language of episode: English
Presenter: Charlotte Hartley
Guests: Peter Godolphin, David Fisher
Producer: Charlotte Hartley

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Artwork
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Manage episode 406407988 series 3419901
内容由UCL Minds提供。所有播客内容(包括剧集、图形和播客描述)均由 UCL Minds 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

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 mrcctu.engage@ucl.ac.uk
As a listener, your opinion is very valuable to us. Please help us to improve the podcast in the future by filling in this short survey: forms.office.com/e/PjfjQ5Mn6g

Date of episode recording: 2024-03-12T00:00:00Z
Duration: 00:28:44
Language of episode: English
Presenter: Charlotte Hartley
Guests: Peter Godolphin, David Fisher
Producer: Charlotte Hartley

  continue reading

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