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
150
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
460
Risk: a statistician's viewpoint
graemeleehickey
1
1.1k
Joint modelling of multivariate longitudinal and time-to-event data
graemeleehickey
0
440
A comparison of joint models for longitudinal and competing risks data, with application to an epilepsy drug randomized controlled trial
graemeleehickey
0
220
Dynamic survival prediction for multivariate joint models using the R package joineRML
graemeleehickey
0
740
Joint modelling of multivariate longitudinal and time-to-event data
graemeleehickey
0
350
What you need to know about statistics to read a journal article
graemeleehickey
1
440
Checking model assumptions with regression diagnostics
graemeleehickey
1
290
Performing repeated measures analysis
graemeleehickey
0
340
Other Decks in Research
See All in Research
20250725-bet-ai-day
cipepser
2
420
数理最適化と機械学習の融合
mickey_kubo
16
9.3k
AI エージェントを活用した研究再現性の自動定量評価 / scisci2025
upura
1
150
診断前の病歴テキストを対象としたLLMによるエンティティリンキング精度検証
hagino3000
1
130
EOGS: Gaussian Splatting for Efficient Satellite Image Photogrammetry
satai
4
510
Creation and environmental applications of 15-year daily inundation and vegetation maps for Siberia by integrating satellite and meteorological datasets
satai
3
270
2021年度-基盤研究B-研究計画調書
trycycle
PRO
0
290
最適決定木を用いた処方的価格最適化
mickey_kubo
4
1.9k
2025年度人工知能学会全国大会チュートリアル講演「深層基盤モデルの数理」
taiji_suzuki
25
18k
AIによる画像認識技術の進化 -25年の技術変遷を振り返る-
hf149
7
4k
EarthSynth: Generating Informative Earth Observation with Diffusion Models
satai
3
250
IMC の細かすぎる話 2025
smly
2
620
Featured
See All Featured
Git: the NoSQL Database
bkeepers
PRO
431
66k
Faster Mobile Websites
deanohume
309
31k
Building Applications with DynamoDB
mza
96
6.6k
ピンチをチャンスに:未来をつくるプロダクトロードマップ #pmconf2020
aki_iinuma
126
53k
The Web Performance Landscape in 2024 [PerfNow 2024]
tammyeverts
9
810
VelocityConf: Rendering Performance Case Studies
addyosmani
332
24k
GitHub's CSS Performance
jonrohan
1032
460k
Side Projects
sachag
455
43k
Connecting the Dots Between Site Speed, User Experience & Your Business [WebExpo 2025]
tammyeverts
8
520
Stop Working from a Prison Cell
hatefulcrawdad
271
21k
Designing for Performance
lara
610
69k
I Don’t Have Time: Getting Over the Fear to Launch Your Podcast
jcasabona
33
2.4k
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