[R-meta] diagnostic meta-analysis of studies with multiple readers

Mario Petretta petretta at unina.it
Mon Feb 5 18:19:51 CET 2018


Dear Prof. Doebler
 
Many thanks again for comments and suggestion.
I downloaded the paper of Verde, but  I will try with a GLMM software.

Again many thanks.

Mario




 

-----Messaggio originale-----
Da: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces at r-project.org]
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Inviato: domenica 4 febbraio 2018 12.00
A: r-sig-meta-analysis at r-project.org
Oggetto: R-sig-meta-analysis Digest, Vol 9, Issue 6


Today's Topics:

   1. Re: diagnostic meta-analysis of studies with multiple	readers
      (Philipp Doebler)


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

Message: 1
Date: Sat, 3 Feb 2018 14:20:28 +0100
From: Philipp Doebler <doebler at statistik.tu-dortmund.de>
To: Mario Petretta <petretta at unina.it>
Cc: r-sig-meta-analysis at r-project.org
Subject: Re: [R-meta] diagnostic meta-analysis of studies with
	multiple	readers
Message-ID:
	<CAMU7UxFAbUTu3sjZs0fPzyKrC+HptO_UnuQWsssoiqaQVND9jQ at mail.gmail.com>
Content-Type: text/plain; charset="UTF-8"

Dear Mario,

your are correct to note that dependencies among readers must be respected.
I would also recommend you try a bivariate approach.

As a consequence I suggest you work with a logit-link function and aim to
estimate two random effects:

1. a bivariate within-study (reader-level) effect that captures the
deviations of the reader from the study mean, and 2. a between study effect,
similar to the Reitsma et al. (2005) bivariate model, which you are probably
aware of.

Estimating 1. is a bit tricky, as some studies will report only two readers,
which is clearly suboptimal.  There are two ways to go:

(i) it could pay to "borrow strength" (in the Bayesian sense) by specifying
an (Inverse-Wishart) prior distribution for the within study effect, that is
maybe scaled by a study specific factor. This amounts to the assumption,
that the covariance matrix of the deviations from the study mean is similar
in all studies. I am aware of one paper with a similar idea by Verde (
http://onlinelibrary.wiley.com/doi/10.1002/sim.4055/abstract) which also has
WinBUGS code.
(ii) Try and use your favourite GLMM software (say glmer or SAS PROC MIXED).
It could be tricky to take into account that the within study covariance
matrix is (probably) not the same for all studies, so you will probably have
to assume it is the same.

I hope this rough sketch is helpful. Let me know if you need more precise
ideas.

Kind wishes,
  Philipp


On Fri, Feb 2, 2018 at 7:53 PM, Mario Petretta <petretta at unina.it> wrote:

> Thanks for your kindly replay.
> At this time I have 14 studies and 4 of them give information useful 
> to obtain the number of true-positive, true-negative, false-positive 
> and false negative for more than one reader (two in two studies and 
> three in the other two); three  studies  include reproducibility 
> information (Bland Altman plots or ICC).
> For all the four studies with multiple readers, the readers evaluated 
> the same imaging examination of all study patients, i.e. there was a 
> unique study for patient but the imaging studies were read 
> independently and blinded. Thus, sensitivity and specificity vary across
the readers.
>
> Among the various possibilities I thought to report the same study 
> several times in the analysis with the different 2 x 2 tables, but the 
> problem is how do you take into account that it is for some studies of 
> the same population (a sort of cluster). I also hypothesize to do, 
> thereafter, a sensitivity analysis including only the results of the 
> best or worst readers or the average of the different readers.
>
> Thanks for the attention.
> Mario
>
>
> __________________________________________________
> Date: Fri, 2 Feb 2018 18:57:33 +0100
> From: Philipp Doebler <doebler at statistik.tu-dortmund.de>
> To: Mario Petretta <petretta at unina.it>
> Cc: r-sig-meta-analysis at r-project.org
> Subject: Re: [R-meta] diagnostic meta-analysis of studies with
>         multiple        reader
> Message-ID:
>         <CAMU7UxFGYpLYesqKc2+2xpphqkQWhzsn=Py9M9C08VL6k9BoD
> w at mail.gmail.com>
> Content-Type: text/plain; charset="UTF-8"
>
> Dear Mario,
>
> could you give us some more details? Is it realistic to obtain a 
> 2x2-table for each reader?
>
> Best,
>   Philipp
>
> On Fri, Feb 2, 2018 at 6:18 PM, Mario Petretta <petretta at unina.it> wrote:
>
> > Dear all.
> > I'm planning a diagnostic meta-analysis with an imaging test and a 
> > binary outcome (yes/no) .
> > Some (not all) studies contain multiple readers, which means that 
> > more than one physician interprets each examination.
> >
> > At present, it appears that there are no recommendations for which 
> > strategy is optimal (see Eur J Radiol. 2017;93:59-64 Systematic 
> > Reviews
> 2017;6:194).
> >
> > I would appreciate very much suggestions on this topic.
> > Thanks for the attention.
> > Sincerely
> > Mario Petretta
> > ___________________________________________
> > Mario Petretta, MD, FAHA
> > Associate Professor of Internal Medicine Department of Translational 
> > Medical Sciences Naples University "Federico II" - Italy 
> > _______________________________________________
> > R-sig-meta-analysis mailing list
> > R-sig-meta-analysis at r-project.org
> > https://stat.ethz.ch/mailman/listinfo/r-sig-meta-analysis
> >
> --
> Prof. Dr. Philipp Doebler
> Technische Universit?t Dortmund
> Fakult?t Statistik
> Vogelpothsweg 87
> 44227 Dortmund
>
> Tel.: +49 231-755 8259
> Fax: +49 231-755 3918
> doebler at statistik.tu-dortmund.de
> www.statistik.tu-dortmund.de/1261.html
>
>
>


--
Prof. Dr. Philipp Doebler
Technische Universit?t Dortmund
Fakult?t Statistik
Vogelpothsweg 87
44227 Dortmund

Tel.: +49 231-755 8259
Fax: +49 231-755 3918
doebler at statistik.tu-dortmund.de
www.statistik.tu-dortmund.de/1261.html


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