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
160
0
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
Making forest and funnel plots
Presented at the 30th Annual EACTS Meeting, Barcelona, Spain (1-5 October 2016)
Graeme Hickey
October 03, 2016
More Decks by Graeme Hickey
See All by Graeme Hickey
Joint modelling of longitudinal and time-to-event data: recent extensions
graemeleehickey
0
490
Risk: a statistician's viewpoint
graemeleehickey
1
1.6k
Joint modelling of multivariate longitudinal and time-to-event data
graemeleehickey
0
480
A comparison of joint models for longitudinal and competing risks data, with application to an epilepsy drug randomized controlled trial
graemeleehickey
0
250
Dynamic survival prediction for multivariate joint models using the R package joineRML
graemeleehickey
0
810
Joint modelling of multivariate longitudinal and time-to-event data
graemeleehickey
0
390
What you need to know about statistics to read a journal article
graemeleehickey
1
500
Checking model assumptions with regression diagnostics
graemeleehickey
1
310
Performing repeated measures analysis
graemeleehickey
0
400
Other Decks in Research
See All in Research
CVPR2026論文紹介_VLMにとって良いvision encoderとは何か?Rethinking Model Selection in VLM Through the Lens of Gromov-Wasserstein Distance
kobayashi31
1
190
「AIとWhyを深堀る」をAIと深堀る
iflection
0
550
敵対生成プロンプト同時探索による内省型プロンプト最適化
kinoue_smarthr
0
350
【ローカルAI LT大会】SSE: Stable Static Embedding ー速度低下を伴わず 静的埋め込みモデルの潜在能力を引き出す Dynamic Tanh手法の提案
rikkabotan7
0
110
EIRによる不正端末のブロッキング 5G時代におけるデバイス識別と不正対策の進化
stellarcraft
0
110
大規模言語モデルは誰を覚えているか / Who Do Large Language Models Memorize?
upura
0
110
SAKURAONE:An Open Ethernet-based AI HPC System And Its Observed Workload Dynamicsin a Single-Tenant LLM Development Environment
yuukit
1
510
【ローカルAIに向き合う展示会vol.2】液体時間定数型モジュールを用いた オリジナルの双方向エンコーダーモデルNexteraBERT 推論速度向上検討並びにダウンストリーム評価
rikkabotan7
0
150
Harness Engineering and Al Agent
kzinmr
3
1.9k
ros2-perf-multihost: 分散システムにおける客観的なアーキテクチャ評価フレームワーク
takasehideki
0
180
LINEヤフー データサイエンス Meetup「三井物産コモディティ予測チャレンジ」の舞台裏-AlpacaTechパート
gamella
1
620
技術は予測を代補する:スティグレールの三次的記憶論と予測処理パラダイムの交差
ktanishima
0
120
Featured
See All Featured
Side Projects
sachag
455
43k
Redefining SEO in the New Era of Traffic Generation
szymonslowik
1
380
Jess Joyce - The Pitfalls of Following Frameworks
techseoconnect
PRO
1
330
Marketing to machines
jonoalderson
1
5.7k
Abbi's Birthday
coloredviolet
3
9.3k
Leading Effective Engineering Teams in the AI Era
addyosmani
9
2.2k
GraphQLとの向き合い方2022年版
quramy
50
15k
Heart Work Chapter 1 - Part 1
lfama
PRO
8
36k
実際に使うSQLの書き方 徹底解説 / pgcon21j-tutorial
soudai
PRO
201
75k
The #1 spot is gone: here's how to win anyway
tamaranovitovic
3
1.1k
Jamie Indigo - Trashchat’s Guide to Black Boxes: Technical SEO Tactics for LLMs
techseoconnect
PRO
0
590
Become a Pro
speakerdeck
PRO
31
6.2k
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