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
Sponsored
·
Your Podcast. Everywhere. Effortlessly.
Share. Educate. Inspire. Entertain. You do you. We'll handle the rest.
→
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
470
Risk: a statistician's viewpoint
graemeleehickey
1
1.4k
Joint modelling of multivariate longitudinal and time-to-event data
graemeleehickey
0
460
A comparison of joint models for longitudinal and competing risks data, with application to an epilepsy drug randomized controlled trial
graemeleehickey
0
230
Dynamic survival prediction for multivariate joint models using the R package joineRML
graemeleehickey
0
790
Joint modelling of multivariate longitudinal and time-to-event data
graemeleehickey
0
370
What you need to know about statistics to read a journal article
graemeleehickey
1
470
Checking model assumptions with regression diagnostics
graemeleehickey
1
300
Performing repeated measures analysis
graemeleehickey
0
360
Other Decks in Research
See All in Research
ウェブ・ソーシャルメディア論文読み会 第36回: The Stepwise Deception: Simulating the Evolution from True News to Fake News with LLM Agents (EMNLP, 2025)
hkefka385
0
160
Collective Predictive Coding and World Models in LLMs: A System 0/1/2/3 Perspective on Hierarchical Physical AI (IEEE SII 2026 Plenary Talk)
tanichu
1
250
製造業主導型経済からサービス経済化における中間層形成メカニズムのパラダイムシフト
yamotty
0
480
Tiaccoon: Unified Access Control with Multiple Transports in Container Networks
hiroyaonoe
0
620
世界モデルにおける分布外データ対応の方法論
koukyo1994
7
1.5k
R&Dチームを起ち上げる
shibuiwilliam
1
160
教師あり学習と強化学習で作る 最強の数学特化LLM
analokmaus
2
890
Upgrading Multi-Agent Pathfinding for the Real World
kei18
0
210
湯村研究室の紹介2025 / yumulab2025
yumulab
0
300
Can AI Generated Ambrotype Chain the Aura of Alternative Process? In SIGGRAPH Asia 2024 Art Papers
toremolo72
0
140
LLM-Assisted Semantic Guidance for Sparsely Annotated Remote Sensing Object Detection
satai
3
470
競合や要望に流されない─B2B SaaSでミニマム要件を決めるリアルな取り組み / Don't be swayed by competitors or requests - A real effort to determine minimum requirements for B2B SaaS
kaminashi
0
740
Featured
See All Featured
I Don’t Have Time: Getting Over the Fear to Launch Your Podcast
jcasabona
34
2.6k
AI Search: Implications for SEO and How to Move Forward - #ShenzhenSEOConference
aleyda
1
1.1k
Principles of Awesome APIs and How to Build Them.
keavy
128
17k
Stop Working from a Prison Cell
hatefulcrawdad
273
21k
The browser strikes back
jonoalderson
0
390
A designer walks into a library…
pauljervisheath
210
24k
Measuring Dark Social's Impact On Conversion and Attribution
stephenakadiri
1
130
The Invisible Side of Design
smashingmag
302
51k
Ethics towards AI in product and experience design
skipperchong
2
200
Discover your Explorer Soul
emna__ayadi
2
1.1k
The B2B funnel & how to create a winning content strategy
katarinadahlin
PRO
1
280
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
128
55k
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