Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Making forest and funnel plots
Search
Graeme Hickey
October 03, 2016
Research
0
140
Making forest and funnel plots
Presented at the 30th Annual EACTS Meeting, Barcelona, Spain (1-5 October 2016)
Graeme Hickey
October 03, 2016
Tweet
Share
More Decks by Graeme Hickey
See All by Graeme Hickey
Joint modelling of longitudinal and time-to-event data: recent extensions
graemeleehickey
0
400
Risk: a statistician's viewpoint
graemeleehickey
1
670
Joint modelling of multivariate longitudinal and time-to-event data
graemeleehickey
0
400
A comparison of joint models for longitudinal and competing risks data, with application to an epilepsy drug randomized controlled trial
graemeleehickey
0
210
Dynamic survival prediction for multivariate joint models using the R package joineRML
graemeleehickey
0
590
Joint modelling of multivariate longitudinal and time-to-event data
graemeleehickey
0
310
What you need to know about statistics to read a journal article
graemeleehickey
1
370
Checking model assumptions with regression diagnostics
graemeleehickey
1
260
Performing repeated measures analysis
graemeleehickey
0
240
Other Decks in Research
See All in Research
リサーチに組織を巻き込むための「準備8割」の話
terasho
0
470
論文紹介 DSRNet: Single Image Reflection Separation via Component Synergy (ICCV 2023)
tattaka
0
180
The Theory behind Vector DB
matsui_528
0
1.6k
Generative AI - practice and theory
gpeyre
1
560
Prompt Tuning から Fine Tuning への移行時期推定
icoxfog417
17
7k
Alternative Photographic Processes Reimagined: The Role of Digital Technology in Revitalizing Classic Printing Techniques【SIGGRAPH Asia 2023】
toremolo72
0
430
How to Perform Manual Classification for Deep Learning Using CloudCompare
kentaitakura
0
650
Azure Arc-enabled Serversを利用した ハイブリッド・マルチクラウド環境の管理 / Managing Hybrid Multi-cloud Environments with Azure Arc-enabled Servers
nttcom
0
210
論文紹介 DISN: Deep Implicit Surface Network for High quality Single-view 3D Reconstruction / DISN: Deep Implicit Surface Network for High quality Single-view 3D Reconstruction
nttcom
0
120
フルリモートワークでのスクラムのスケール
kmorita1111
2
1k
メタ動画データセットによる動作認識の現状と可能性
yuyay
0
180
自己教師あり学習による事前学習(CVIMチュートリアル)
naok615
2
1.4k
Featured
See All Featured
Visualizing Your Data: Incorporating Mongo into Loggly Infrastructure
mongodb
34
8.9k
Refactoring Trust on Your Teams (GOTO; Chicago 2020)
rmw
25
2.3k
The Illustrated Children's Guide to Kubernetes
chrisshort
31
46k
It's Worth the Effort
3n
180
27k
5 minutes of I Can Smell Your CMS
philhawksworth
199
19k
CSS Pre-Processors: Stylus, Less & Sass
bermonpainter
352
28k
Done Done
chrislema
178
15k
Optimising Largest Contentful Paint
csswizardry
8
2.4k
Sharpening the Axe: The Primacy of Toolmaking
bcantrill
17
1.4k
JavaScript: Past, Present, and Future - NDC Porto 2020
reverentgeek
40
4.4k
Build The Right Thing And Hit Your Dates
maggiecrowley
24
2k
Build your cross-platform service in a week with App Engine
jlugia
225
17k
Transcript
Meta-analysis from start to finish Graeme L. Hickey* Department of
Biostatistics, University of Liverpool * No conflicts of interest
None
Early all-cause mortality Five randomized trials
TAVI SAVR Trial Year of publication Events, n Total, n
Events, n Total, n NOTION 2015 3 139 5 135 PARTNER 2011 12 348 22 351 PARTNER 2A 2016 39 1011 41 1021 STACCATO 2012 2 34 0 36 US CoreValve 2014 13 390 16 357 Outcome: early all-cause mortality
Jones et al (39) Kobrin et al (40) Latib et
al (12) Minutello et al (41) Muneretto et al (42) Onorati et al (43) Osnabrugge et al (13) Papadopoulos et al (44) Piazza et al (14) Santarpino et al (45) Schymik et al (15) Stöhr et al (46) Tamburino et al (16) Thakkar et al (47) Thongprayoon et al (48) Thourani et al (17) Walther et al (49) Wendt et al (50) Zweng et al (51) Random-effects model Heterogeneity: l2 = 39.3%; tau-squared = 0.1507; P = 0.017 Random-effects model Heterogeneity: l2 = 37%; tau-squared = 0.1253; P = 0.0172 Test for overall effect: P = 0.9041 Test for subgroup differences: Q = 2.2; P = 0.1415 0 20 2 20 20 1 2 3 33 3 3 21 20 2 3 12 10 9 2 287 356 1.37 (0.68–2.77) 1.00 (0.14–7.23) 1.34 (0.79–2.30) 2.23 (1.16–4.27) 3.11 (0.12–79.64) 0.65 (0.10–4.10) 0.46 (0.11–1.98) 1.35 (0.79–2.31) 0.59 (0.14–2.53) 0.32 (0.09–1.21) 1.70 (0.82–3.51) 0.83 (0.45–1.51) 1.00 (0.13–7.60) 1.51 (0.25–9.12) 0.27 (0.14–0.52) 0.63 (0.27–1.48) 2.72 (0.69–10.63) 1.00 (0.13–7.43) 1.08 (0.84–1.38) 1.01 (0.81–1.26) 0.0 4.8 1.1 6.1 5.2 0.4 1.2 1.8 6.1 1.8 2.1 4.6 5.5 1.0 1.3 5.1 3.9 2.0 1.0 81.7 100 0 15 2 45 19 0 3 6 25 5 9 13 24 2 2 38 15 3 2 309 393 20 194 111 595 204 28 42 40 405 102 216 175 650 30 195 1077 100 62 44 5657 7579 20 194 111 1785 408 28 42 40 405 102 216 175 650 30 195 944 100 51 44 6907 8807 0.01 0.1 1 10 100 Favors TAVI Favors SAVR Knapp–Hartung random-effects OR and 95% CI for 30-day all-cause mortality stratified by study design. NOTION = Nordic Aortic Valve Intervention; OR = odds ratio; PARTNER = Placement of Aortic Transcatheter Valves; SAVR = surgical aortic valve replacement; STACCATO = A Prospective, Randomised Trial of Transapical Transcatheter Aortic Valve Implantation Versus Surgical Aortic Valve Replacement in Operable Elderly Patients With Aortic Stenosis; TAVI = transcatheter aortic valve implantation. * Percentages do not sum to 18.3% and 81.7% for randomized and matched studies, respectively, because of rounding. www.annals.org Annals of Internal Medicine • Vol. 165 No. 5 • 6 September 2016 337 Downloaded From: http://annals.org/ by a University of Liverpool User on 09/21/2016 Figure 1. Forest plot for early all-cause mortality in the overall population. Study (Reference) Randomized studies NOTION (9, 10) PARTNER (3–5) PARTNER 2A (11) STACCATO (26) U.S. CoreValve (6–8) Random-effects model Heterogeneity: l2 = 0%; tau-squared = 0; P = 0.4571 Matched studies Ailawadi et al (27) Appel et al (28) Biancari et al (29) Conradi et al (30) D'Onofrio et al (31) Fusari et al (33) Guarracino et al (34) Hannan et al (35) Higgins et al (36) Holzhey et al (37) Johansson et al (38) Jones et al (39) Kobrin et al (40) Latib et al (12) Minutello et al (41) Muneretto et al (42) Onorati et al (43) Events, n 3 12 39 2 13 69 34 3 10 6 2 0 3 19 6 14 4 0 20 2 20 20 1 OR (95% CI) 0.57 (0.13–2.45) 0.53 (0.26–1.10) 0.96 (0.61–1.50) 5.62 (0.26–121.32) 0.73 (0.35–1.55) 0.80 (0.51–1.25) 1.61 (0.92–2.81) 1.54 (0.24–9.66) 5.30 (1.14–24.63) 0.85 (0.27–2.63) 5.27 (0.24–113.60) 0.19 (0.01–4.06) 3.22 (0.32–32.89) 1.00 (0.52–1.92) 1.57 (0.41–6.00) 0.76 (0.36–1.58) 1.00 (0.23–4.31) 1.37 (0.68–2.77) 1.00 (0.14–7.23) 1.34 (0.79–2.30) 2.23 (1.16–4.27) 3.11 (0.12–79.64) Weight (Random), %* 1.8 4.7 6.9 0.5 4.5 18.3 5.9 1.2 1.6 2.6 0.5 0.5 0.8 5.2 2.1 4.6 1.8 0.0 4.8 1.1 6.1 5.2 0.4 Events, n 5 22 41 0 16 84 22 2 2 7 0 2 1 19 4 18 4 0 15 2 45 19 0 Total, n 139 348 1011 34 390 1922 340 45 144 82 38 30 30 405 46 167 40 20 194 111 595 204 28 Total, n 135 351 1021 36 357 1900 340 45 144 82 38 30 30 405 46 167 40 20 194 111 1785 408 28 TAVI SAVR Systematic Review and Meta-analysis of TAVI Versus SAVR REVIEW NB. 31 observational studies have been deleted from the reported forest plot Heterogeneity statistics Labelled table of raw data Effect sizes & confidence intervals Weights Pooled estimate Direction labels Nicely formatted axes Forest plot with null line
Systematic review Data extraction Software 51 packages available for meta-analysis
71 packages available for meta-analysis RevMan $$$
+ other software packages & online web calculators
* Only for preparation of Cochrane Reviews or for purely
academic use.
None
None
None
None
1 2 3 5 4 > Finish 6
None
None
None
None
None
None