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Re: st: RE: Meta-Analysis using --metan-- how to ensure comparison to ES=1 not ES=0
From
Belinda Butcher <[email protected]>
To
[email protected]
Subject
Re: st: RE: Meta-Analysis using --metan-- how to ensure comparison to ES=1 not ES=0
Date
Fri, 19 Oct 2012 14:41:50 +1100
Thank you - worked perfectly!
Belinda Butcher BSc(Hons) MBiostat PhD
Director - Biostatistics & Medical Writing
WriteSource Medical Pty Ltd
PO Box 1521
Lane Cove NSW 1595
M: 0418 286 014
E: [email protected]
On 15/10/2012, at 8:47 PM, Trelle Sven wrote:
> Hi Belinda,
> You will need to log-transform your hazard ratios and confidence
> interval (and use the eform option in metan):
>
> foreach var of varlist pfshr pfsll pfsul {
> gen ln_`var' = ln(`var')
> }
> metan ln_pfshr ln_pfsll ln_pfsul, eform effect("Hazard Ratio") fixed
> lcols(study author year treatment) double by(drug) astext(50)
> xlabel(0.2, 0.5, 1, 2, 5) textsize(100) title("RR of PFS") null(1)
> force
>
> Best
> Sven
>
> p.s. the null-option only refers to the graph (at least to my knowledge)
>
>
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]] On Behalf Of Belinda
> Butcher
> Sent: Montag, 15. Oktober 2012 05:14
> To: [email protected]
> Subject: st: Meta-Analysis using --metan-- how to ensure comparison to
> ES=1 not ES=0
>
> Hi,
>
> I use Stata/MP for Mac 11.2, dated 16 May 2012. All files are up to
> date..
>
> I am using the --metan-- command (available from SSC:
> http://ideas.repec.org/c/boc/bocode/s456798.html) to combine the results
> of some oncology studies.
>
> I am combining the hazard ratios for progression free survival, using
> the upper and lower confidence interals).
>
> I am using the following command:
>
> metan pfshr pfsll pfsul, effect("Hazard Ratio") fixed lcols(study author
> year treatment) double by(drug) astext(50) xlabel(0.2, 0.5, 1, 2, 5)
> textsize(100) title("RR of PFS") null(1) force
>
> I need to compare the resultant overall HR to one, rather than zero. To
> do this, I have included "null(1)" in my command. However, when I run
> the command, I get a comparison to ES=0 (see output below).
>
> Study | ES [95% Conf. Interval] % Weight
> ---------------------+--------------------------------------------------
> ---------------------+-
> A
> 1 | 0.680 0.590 0.780 12.38
> 2 | 0.758 0.661 0.869 10.33
> Sub-total |
> I-V pooled ES | 0.715 0.645 0.786 22.72
> ---------------------+--------------------------------------------------
> ---------------------+-
> B
> 3 | 0.493 0.418 0.581 16.83
> 4 | 1.190 0.720 1.960 0.29
> 5 | 1.100 0.570 2.120 0.19
> 6 | 0.720 0.620 0.840 9.24
> Sub-total |
> I-V pooled ES | 0.584 0.519 0.649 26.54
> ---------------------+--------------------------------------------------
> ---------------------+-
> C
> 7 | 0.540 0.420 0.710 5.32
> 8 | 0.680 0.570 0.800 8.45
> 9 | 0.540 0.440 0.660 9.24
> 10 | 0.692 0.617 0.776 17.68
> | 0.590 0.480 0.720 7.76
> Sub-total |
> I-V pooled ES | 0.628 0.580 0.676 48.45
> ---------------------+--------------------------------------------------
> ---------------------+-
> D
> 11 | 1.210 0.820 1.800 0.47
> 12 | 1.410 0.960 2.070 0.36
> Sub-total |
> I-V pooled ES | 1.298 0.930 1.665 0.83
> ---------------------+--------------------------------------------------
> ---------------------+-
> E
> 13 | 0.690 0.490 1.140 1.06
> 14 | 1.010 0.610 1.660 0.41
> Sub-total |
> I-V pooled ES | 0.779 0.502 1.055 1.46
> ---------------------+--------------------------------------------------
> ---------------------+-
> Overall |
> I-V pooled ES | 0.644 0.610 0.677 100.00
> ---------------------+--------------------------------------------------
> ---------------------+-
> Heterogeneity calculated by formula
> Q = SIGMA_i{ (1/variance_i)*(effect_i - effect_pooled)^2 } where
> variance_i = ((upper limit - lower limit)/(2*z))^2
>
> Test(s) of heterogeneity:
> Heterogeneity degrees of
> statistic freedom P I-squared**
> A 1.18 1 0.278 15.1%
> B 16.03 3 0.001 81.3%
> C 7.53 4 0.110 46.9%
> D 0.28 1 0.596 0.0%
> E 1.03 1 0.310 3.1%
> Overall 46.85 14 0.000 70.1%
> Overall Test for heterogeneity between sub-groups:
> 20.79 4 0.000
>
> ** I-squared: the variation in ES attributable to heterogeneity)
>
> Considerable heterogeneity observed (up to 81.3%) in one or more
> sub-groups, Test for heterogeneity between sub-groups likely to be
> invalid
>
> Significance test(s) of ES=0
>
> A z= 19.99 p = 0.000
> B z= 17.64 p = 0.000
> C z= 25.62 p = 0.000
> D z= 6.92 p = 0.000
> E z= 5.52 p = 0.000
> Overall z= 37.75 p = 0.000
> ------------------------------------------------------------------------
> -
>
> I have looked in Sterne's book on Meta-Analysis (Sterne J.A.C (2009)
> Meta-Analysis in Stata: An updated collection from the Stata Journal),
> but haven't been able to work this out.
>
> Your help is appreciated.
>
> Kind regards,
>
> Belinda Butcher BSc(Hons) MBiostat PhD
> Director - Biostatistics & Medical Writing WriteSource Medical Pty Ltd
>
> PO Box 1521
> Lane Cove NSW 1595
>
> M: 0418 286 014
> E: [email protected]
>
>
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