[R-meta] R: R-sig-meta-analysis Digest, Vol 21, Issue 8

[Prof. Mario Petretta]

DOMANI Inoltrare i file per AV

-----Messaggio originale-----
Da: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org] Per conto di r-sig-meta-analysis-request using r-project.org
Inviato: giovedì 14 febbraio 2019 12.00
A: r-sig-meta-analysis using r-project.org
Oggetto: R-sig-meta-analysis Digest, Vol 21, Issue 8

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Today's Topics:

   1. Re: Meta Analysis with HR values (Guido Schwarzer)
   2. Re: Meta Analysis with HR values (Awais Wahab)

----------------------------------------------------------------------

Message: 1
Date: Wed, 13 Feb 2019 12:44:34 +0100
From: Guido Schwarzer <sc using imbi.uni-freiburg.de>
To: Awais Wahab <aligners79 using gmail.com>,
	r-sig-meta-analysis using r-project.org
Subject: Re: [R-meta] Meta Analysis with HR values
Message-ID:
	<a01e4bea-d1d8-a6a4-52ca-7f118a7b0c52 using imbi.uni-freiburg.de>
Content-Type: text/plain; charset="utf-8"; Format="flowed"

Dear Awais,

Survival data using the hazard ratio as effect measure are typically meta-analysed using the inverse variance method. The following general R packages for meta-analysis provide this method: *epiR*, *meta*, *metafor*, *rmeta* (see https://cran.r-project.org/web/views/MetaAnalysis.html).

The inverse variance method needs, for each study, the _log_ hazard ratio and its standard error as input. You write that you have hazard ratios and CIs which is sufficient as standard errors can be calculated from CIs (see Parmar et al., 1999).

Please find attached R code using R package *meta* which conducts a meta-analysis for survival data from a Cochrane review I was involved. 
Note, the minor differences in the results of the two meta-analyses can be explained by rounding hazard ratios and confidence limits to only two significant digits; we would get identical results with more significant digits.

Best wishes, Guido

Reference: Parmar MK, Torri V, Stewart L. Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints. Statistics in Medicine. 1998;17(24):2815–34.

--
Dr. Guido Schwarzer
Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg

Postal address: Stefan-Meier-Str. 26, D-79104 Freiburg

Phone: +49/761/203-6668
Mail: sc using imbi.uni-freiburg.de
Homepage: http://www.imbi.uni-freiburg.de


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Message: 2
Date: Wed, 13 Feb 2019 14:41:39 +0200
From: Awais Wahab <aligners79 using gmail.com>
To: Guido Schwarzer <sc using imbi.uni-freiburg.de>
Cc: r-sig-meta-analysis using r-project.org
Subject: Re: [R-meta] Meta Analysis with HR values
Message-ID:
	<CAHdcJs4Cta5EywXeEHKKR5SZ4Qvmu7QWGZ=cSVOQtBPT-M2f6Q using mail.gmail.com>
Content-Type: text/plain; charset="utf-8"

Dear Doctor Guido!
Thank you very much for your much valuable e-mail.

I will start working on it and will let you know if there is any concern.

best regards,
Awais

On Wed, Feb 13, 2019 at 1:44 PM Guido Schwarzer <sc using imbi.uni-freiburg.de>
wrote:

> Dear Awais,
>
> Survival data using the hazard ratio as effect measure are typically 
> meta-analysed using the inverse variance method. The following general 
> R packages for meta-analysis provide this method: *epiR*, *meta*, 
> *metafor*,
> *rmeta* (see https://cran.r-project.org/web/views/MetaAnalysis.html).
>
> The inverse variance method needs, for each study, the *log* hazard 
> ratio and its standard error as input. You write that you have hazard 
> ratios and CIs which is sufficient as standard errors can be 
> calculated from CIs (see Parmar et al., 1999).
>
> Please find attached R code using R package *meta* which conducts a 
> meta-analysis for survival data from a Cochrane review I was involved.
> Note, the minor differences in the results of the two meta-analyses 
> can be explained by rounding hazard ratios and confidence limits to 
> only two significant digits; we would get identical results with more 
> significant digits.
>
> Best wishes, Guido
>
> Reference: Parmar MK, Torri V, Stewart L. Extracting summary 
> statistics to perform meta-analyses of the published literature for survival endpoints.
> Statistics in Medicine. 1998;17(24):2815–34.
>
> --
> Dr. Guido Schwarzer
> Institute of Medical Biometry and Statistics, Faculty of Medicine and 
> Medical Center - University of Freiburg
>
> Postal address: Stefan-Meier-Str. 26, D-79104 Freiburg
>
> Phone: +49/761/203-6668
> Mail: sc using imbi.uni-freiburg.de
> Homepage: http://www.imbi.uni-freiburg.de
>
>

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End of R-sig-meta-analysis Digest, Vol 21, Issue 8