[R-meta] Meta-Analisys whit events numbers, RR, OR and HR. It's possibe?

Fri Jan 29 16:29:50 CET 2021

Dear Gerta and Michael,
Thank you very much for your answers.
I thought it was easier than what is shown in the papers, but maybe I did not explain it well.
I have six studies that report HR and its 95% CI. 2 studies that report number of events in the two branches. 3 studies that report OR and its 95% CI.

In the Cochrane manual, it says that these data can be meta-analyzed with the generic inverse of variance method.
but I don't understand if these measures can really be meta-analyzed together or not.
I will exemplify with less studies what you can find to see what you think

Suppose I have 4 studies that report:

HR (1.05, 0.44, 0.31, 0.77)
CI95% L (0.65, 0.16, 0.09, 0.68)
CI95% U (1.69, 1.22, 1.01, 0.87)
In the META package with the metagen function, this could be done according to the following example:
Conduct meta-analysis using hazard ratios and 95% confidence intervals
#
# Data from Steurer et al. (2006), Analysis 1.1 Overall survival
# https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.CD004270.pub2/abstract
#
study <- c("FCG on CLL 1996", "Leporrier 2001", "Rai 2000", "Robak 2000")
HR <- c(1.05, 0.44, 0.31, 0.77)
lower.HR <- c(0.65, 0.16, 0.09, 0.68)
upper.HR <- (1.69, 1.22, 1.01, 0.87)
#
# Input must be log hazard ratios, not hazard ratios
#
metagen(log(HR), lower = log(lower.HR), upper = log(upper.HR),
        studlab = study, sm = "HR")

Now, I could add the data of the papers that report OR for example:

OR (0,47 , 0.77, 072)
IC95% L (0.24, 0.52, 0.55)
IC95% U (0.91, 0.81, 0.89)

HR <- c(log(1.05),log(0.44), log(0.31), log(0.77), 0.47,0.77,0.72)
lower.HR <- c(log(0.65), log(0.16), log(0.09), log(0.68),0.24, 0.52, 0.55)
upper.HR <- (log(1.69), log(1.22), log(1.01),log( 0.87),0.91, 0.81, 0.89)

metagen(log(HR), lower = log(lower.HR), upper = log(upper.HR),
        studlab = study, sm = "HR")

Is this correct or should I analyze the HR on the one hand and the OR on the other?

By last. There is a study that reports HR backwards. In other words, not the HR for those who were taking the drug but for those who were not taking it. Is there a way to report it backwards so that you can meta-analyze it with the other HR.

For example, all studies report HR of statin patients. HR 0.78 patients taking statins had 22% fewer events than those not taking it.

One study reports the HR of patients not taking statins. HR2.17 (95% CI 1.04-4.54). In other words, those who did not take statins had twice the number of events.

Best regards

Lorenzo Martín Lobo MTSAC, FACC, FESC
Especialista Jerarquizado en Cardiología
Jefe de Dpto Enf. Cardiovasculares y Cardiometabolismo Hospital Militar Campo de Mayo.
Jefe de Cardiología Hospital Militar Campo de Mayo
Ex Jefe de Unidad Coronaria Hospital Militar Campo de Mayo
Miembro Titular de la Sociedad Argentina de Cardiología
Fellow American College of Cardiology
Fellow European Society of Cardiology
Ex Miembro del Area de Investigación de la SAC
Ex Director del Consejo de Aterosclerosis y Trombosis de la SAC
Miembro Asesor del Consejo de Aterosclerosis y Trombosis de la SAC
Ex Director del Consejo de Epidemiología y Prevención Cardiovascular de la SAC

Miembro Asesor del Consejo de Epidemiología y Prevención Cardiovascular de la SAC

Experto en Lipidos de la Sociedad Argentina de Lipidos.
Miembro de la Sociedad Argentina de Lipidos.
Instructor de ACLS de la American Heart Association

________________________________
De: Michael Dewey <lists using dewey.myzen.co.uk>
Enviado: domingo, 24 de enero de 2021 09:12
Para: Martin Lobo <mlobo4370 using hotmail.com>; Dr. Gerta Rücker <ruecker using imbi.uni-freiburg.de>; r-sig-meta-analysis using r-project.org <r-sig-meta-analysis using r-project.org>
Asunto: Re: [R-meta] Meta-Analisys whit events numbers, RR, OR and HR. It's possibe?

Dear Martin

As Gerta says HR is different but if you want to try to retrieve the raw
frequencies from OR and RR there is a package on CRAN which claims to do
that

https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fcran.r-project.org%2Fpackage%3Destimraw&data=04%7C01%7C%7Cace608e63672411b5a9408d8c0614ecb%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637470871448901402%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=%2F5Mpbg0S7piNjMhK5IdziSh1nE4ifaHX8SOq4YOHQdE%3D&reserved=0

There is a reference to a supporting article as well you you can check
what they are doing.

Michael

On 23/01/2021 18:14, Martin Lobo wrote:
> Hi Gerta !!!
> yes gerta, it's like you said.
> I have seen that with metagen it could be done but I think it would open to pass everything to RR, OR or HR to use the Ln of these, and with the p, or IC95% I could get the standard errors.
> But I don't quite understand what it would be like.
> Thanks
>
>
>
>
>
>
>
> Lorenzo Martín Lobo MTSAC, FACC, FESC
> Especialista Jerarquizado en Cardiología
> Jefe de Dpto Enf. Cardiovasculares y Cardiometabolismo Hospital Militar Campo de Mayo.
> Jefe de Cardiología Hospital Militar Campo de Mayo
> Ex Jefe de Unidad Coronaria Hospital Militar Campo de Mayo
> Miembro Titular de la Sociedad Argentina de Cardiología
> Fellow American College of Cardiology
> Fellow European Society of Cardiology
> Ex Miembro del Area de Investigación de la SAC
> Ex Director del Consejo de Aterosclerosis y Trombosis de la SAC
> Miembro Asesor del Consejo de Aterosclerosis y Trombosis de la SAC
> Ex Director del Consejo de Epidemiología y Prevención Cardiovascular de la SAC
>
> Miembro Asesor del Consejo de Epidemiología y Prevención Cardiovascular de la SAC
>
>
> Experto en Lipidos de la Sociedad Argentina de Lipidos.
> Miembro de la Sociedad Argentina de Lipidos.
> Instructor de ACLS de la American Heart Association
>
>
> ________________________________
> De: Dr. Gerta Rücker <ruecker using imbi.uni-freiburg.de>
> Enviado: sábado, 23 de enero de 2021 15:09
> Para: Martin Lobo <mlobo4370 using hotmail.com>; r-sig-meta-analysis using r-project.org <r-sig-meta-analysis using r-project.org>
> Asunto: Re: [R-meta] Meta-Analisys whit events numbers, RR, OR and HR. It's possibe?
>
>
> Dear Martin,
>
> My first question is: What kind of outcome do you have? HR is for a time-to-event outcome, for example survival, the others are for a binary outcome, for example death within a certain (fixed) time interval. They don't describe the same thing.
>
> For extracting data for a time-to-event outcome, there are a number of papers, for example
>
> Tierney et al. (providing an excel sheet): https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Ftrialsjournal.biomedcentral.com%2Farticles%2F10.1186%2F1745-6215-8-16&data=04%7C01%7C%7Cace608e63672411b5a9408d8c0614ecb%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637470871448911396%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=cGI%2Bq9HFrnx6Xg7gD8gB8L4pnBPYAIqI%2FmbxHUu7YdE%3D&reserved=0<https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Ftrialsjournal.biomedcentral.com%2Farticles%2F10.1186%2F1745-6215-8-16&data=04%7C01%7C%7Cace608e63672411b5a9408d8c0614ecb%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637470871448911396%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=cGI%2Bq9HFrnx6Xg7gD8gB8L4pnBPYAIqI%2FmbxHUu7YdE%3D&reserved=0>
>
> Parmar et al.: https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.1002%2F&data=04%7C01%7C%7Cace608e63672411b5a9408d8c0614ecb%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637470871448911396%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=t%2BI5heztN7Q1fIugPeHS24Gv%2BAmo5hsJHu%2ForRvwztA%3D&reserved=0(SICI)1097-0258(19981230)17:24<2815::AID-SIM110>3.0.CO;2-8<https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.1002%2F(SICI)1097-0258(19981230)17%3A24%253C2815%3A%3AAID-SIM110%253E3.0.CO%3B2-8&data=04%7C01%7C%7Cd4e0812098a143f04ac608d8bfc9f345%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637470221384529519%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=pm5gaiTo5k6etxSAXGyDdHej3DZNvyhSm03saP7hu9o%3D&reserved=0>
>
> Best,
> Gerta
>
> Am 23.01.2021 um 13:23 schrieb Martin Lobo:
>
> Hi everyone !!!
> I need performed a meta-analisys, but i have a problem whith de data extractions.
> In 3 papers I have:
> event.e, n.e, event.c, n.c (or  ai=tpos, bi=tneg, ci=cpos, di=cneg)
>
> In another papers I have:
>
> n.e, n.c and HR
> In another papers I have:
>
> n.e, n.c and OR
> In another papers I have:
>
> n.e, n.c and RR
>
> I have read in the cochraine manual that it could be meta-analyzed, but I don't know how.
>
> Should I transform everything to the same summary measure?
>
> How would these measures be transformed?
>
> How would the meta-analysis with the transformed measurements.
>
> Sorry so many questions but I need your help.
>
> Regards
>
>
>
>
>
>
> Lorenzo Mart�n Lobo MTSAC, FACC, FESC
> Especialista Jerarquizado en Cardiolog�a
> Jefe de Dpto Enf. Cardiovasculares y Cardiometabolismo Hospital Militar Campo de Mayo.
> Jefe de Cardiolog�a Hospital Militar Campo de Mayo
> Ex Jefe de Unidad Coronaria Hospital Militar Campo de Mayo
> Miembro Titular de la Sociedad Argentina de Cardiolog�a
> Fellow American College of Cardiology
> Fellow European Society of Cardiology
> Ex Miembro del Area de Investigaci�n de la SAC
> Ex Director del Consejo de Aterosclerosis y Trombosis de la SAC
> Miembro Asesor del Consejo de Aterosclerosis y Trombosis de la SAC
> Ex Director del Consejo de Epidemiolog�a y Prevenci�n Cardiovascular de la SAC
>
> Miembro Asesor del Consejo de Epidemiolog�a y Prevenci�n Cardiovascular de la SAC
>
>
> Experto en Lipidos de la Sociedad Argentina de Lipidos.
> Miembro de la Sociedad Argentina de Lipidos.
> Instructor de ACLS de la American Heart Association
>
>
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--
Michael
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