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Meta-Analysis
. 2020 Aug 18;142(7):621-642.
doi: 10.1161/CIRCULATIONAHA.120.046361. Epub 2020 Jun 17.

Carotid Intima-Media Thickness Progression as Surrogate Marker for Cardiovascular Risk: Meta-Analysis of 119 Clinical Trials Involving 100 667 Patients

Peter Willeit #  1 Lena Tschiderer #  1 Elias Allara  2 Kathrin Reuber  3 Lisa Seekircher  1 Lu Gao  4 Ximing Liao  3 Eva Lonn  5 Hertzel C Gerstein  6 Salim Yusuf  6 Frank P Brouwers  7 Folkert W Asselbergs  8 Wiek van Gilst  9 Sigmund A Anderssen  10 Diederick E Grobbee  11 John J P Kastelein  12 Frank L J Visseren  13 George Ntaios  14 Apostolos I Hatzitolios  15 Christos Savopoulos  15 Pythia T Nieuwkerk  1 Erik Stroes  12 Matthew Walters  16 Peter Higgins  17 Jesse Dawson  17 Paolo Gresele  18 Giuseppe Guglielmini  18 Rino Migliacci  19 Marat Ezhov  20 Maya Safarova  21 Tatyana Balakhonova  22 Eiichi Sato  23 Mayuko Amaha  23 Tsukasa Nakamura  23 Kostas Kapellas  24 Lisa M Jamieson  24 Michael Skilton  25 James A Blumenthal  26 Alan Hinderliter  27 Andrew Sherwood  1 Patrick J Smith  26 Michiel A van Agtmael  28 Peter Reiss  29 Marit G A van Vonderen  30 Stefan Kiechl  31 Gerhard Klingenschmid  1 Matthias Sitzer  32 Coen D A Stehouwer  33 Heiko Uthoff  34 Zhi-Yong Zou  35 Ana R Cunha  36 Mario F Neves  36 Miles D Witham  37 Hyun-Woong Park  38 Moo-Sik Lee  39 Jang-Ho Bae  40 Enrique Bernal  41 Kristian Wachtell  42 Sverre E Kjeldsen  42 Michael H Olsen  43 David Preiss  44 Naveed Sattar  45 Edith Beishuizen  41 Menno V Huisman  46 Mark A Espeland  47 Caroline Schmidt  48 Stefan Agewall  49 Ercan Ok  50 Gülay Aşçi  50 Eric de Groot  51 Muriel P C Grooteman  52 Peter J Blankestijn  53 Michiel L Bots  11 Michael J Sweeting #  54 Simon G Thompson #  2 Matthias W Lorenz #  3 PROG-IMT and the Proof-ATHERO Study Groups
Affiliations
Meta-Analysis

Carotid Intima-Media Thickness Progression as Surrogate Marker for Cardiovascular Risk: Meta-Analysis of 119 Clinical Trials Involving 100 667 Patients

Peter Willeit et al. Circulation. .

Abstract

Background: To quantify the association between effects of interventions on carotid intima-media thickness (cIMT) progression and their effects on cardiovascular disease (CVD) risk.

Methods: We systematically collated data from randomized, controlled trials. cIMT was assessed as the mean value at the common-carotid-artery; if unavailable, the maximum value at the common-carotid-artery or other cIMT measures were used. The primary outcome was a combined CVD end point defined as myocardial infarction, stroke, revascularization procedures, or fatal CVD. We estimated intervention effects on cIMT progression and incident CVD for each trial, before relating the 2 using a Bayesian meta-regression approach.

Results: We analyzed data of 119 randomized, controlled trials involving 100 667 patients (mean age 62 years, 42% female). Over an average follow-up of 3.7 years, 12 038 patients developed the combined CVD end point. Across all interventions, each 10 μm/y reduction of cIMT progression resulted in a relative risk for CVD of 0.91 (95% Credible Interval, 0.87-0.94), with an additional relative risk for CVD of 0.92 (0.87-0.97) being achieved independent of cIMT progression. Taken together, we estimated that interventions reducing cIMT progression by 10, 20, 30, or 40 μm/y would yield relative risks of 0.84 (0.75-0.93), 0.76 (0.67-0.85), 0.69 (0.59-0.79), or 0.63 (0.52-0.74), respectively. Results were similar when grouping trials by type of intervention, time of conduct, time to ultrasound follow-up, availability of individual-participant data, primary versus secondary prevention trials, type of cIMT measurement, and proportion of female patients.

Conclusions: The extent of intervention effects on cIMT progression predicted the degree of CVD risk reduction. This provides a missing link supporting the usefulness of cIMT progression as a surrogate marker for CVD risk in clinical trials.

Keywords: cardiovascular disease; carotid intima-media thickness; clinical trials as topic; meta-analysis; surrogate marker.

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Conflict of interest statement

Conflict of Interest Disclosures

P. Willeit reports grants from the German Research Foundation DFG, the Austrian Science Fund FWF, the Austrian Research Promotion Agency FFG and the Dr.-Johannes-and-Hertha-Tuba Foundation during the conduct of the study. L. Tschiderer reports grants from the Dr.-Johannes-and-Hertha-Tuba Foundation during the conduct of the study and non-financial support from Sanofi outside the submitted work. E. Allara was supported by a National Institute for Health Research PhD studentship (NIHR BTRU-2014-10024) during the conduction of this study and reports support from EU/EFPIA Innovative Medicines Initiative Joint Undertaking BigData@Heart grant n° 116074 outside the submitted work. L. Seekircher reports non-financial support from Sanofi outside the submitted work. H.C. Gerstein reports grants from Sanofi, Eli Lilly, Astra Zeneca, Boehringer Ingelheim, Novo Nordisk, Merck, and Abbott, and personal fees from Sanofi, Eli Lilly, Astra Zeneca, Boehringer Ingelheim, Abbott, Novo Nordisk, Merck, Jannsen, Kowa Research Institute, and Cirius outside the submitted work. E. Stroes reports Lecturing/ad-boards fees paid to institution by Amgen, Sanofi-Regeneron, Novartis, Athera, Mylan unrelated to the present work. K. Kapellas reports grants from the National Health and Medical Research Council during the conduct of the study. M. Skilton reports grants from the National Health and Medical Research Council of Australia during the conduct of the study. M.G.A. van Vonderen reports grants from Abbott International and Boehringer Ingelheim during the conduct of the study. S. Kiechl reports grants from the Austrian Promotion Agency FFG outside the submitted work. G. Klingenschmid reports non-financial support from Sanofi and Pfizer outside the submitted work. S.E. Kjeldsen reports personal fees from Bayer, Merck KGaA, MSD, Sanofi, and Takeda outside the submitted work. M.H. Olsen reports grants from the Novo Nordic Foundation outside the submitted work. N. Sattar reports personal fees from Amgen, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Janssen, NAPP Pharmaceuticals, Novo Nordisk, and Sanofi, and grants from Boehringer Ingelheim outside the submitted work. M.P.C. Grooteman reports grants from the Dutch Kidney Foundation, Fresenius Medical Care Netherlands BV, Gambro Sweden, the Twiss Fund, and ZON MW during the conduct of the study. P.J. Blankestijn reports grants from the European Commission and other financial activities from Medtronic, Baxter, and Braun outside the submitted work. M.L. Bots reports grants from AstraZeneca outside the submitted work. M.J. Sweeting reports grants from the German Research Foundation during the conduct of the study. S.G. Thompson reports grants from the UK Medical Research Council, the British Heart Foundation, and the German Research Foundation DFG during the conduct of the study. M.W. Lorenz reports grants from the German Research Foundation DFG during the conduct of the study. Other authors have no conflicts of interests.

Figures

Figure 1
Figure 1. Intervention effects on cIMT progression plotted against intervention effects on risk for the primary CVD endpoint.
The intercept of the primary model was 0.92 (95% CI 0.87-0.97). Each bubble represents a trial. Trials with point estimates outside of this area are indicated with the symbol x. The areas of the bubbles are proportional to the inverse variance of the log relative risk for the primary CVD endpoint. The shaded areas around lines-of-fit are 95% prediction intervals. For purpose of presentation, the graph area was limited to -80 to 80 μm/year on the horizontal axis and 0.25 to 4 on the vertical axis. Abbreviations: CI=credible interval. cIMT=carotid intima-media thickness. CVD=cardiovascular disease. RR=relative risk.
Figure 2
Figure 2. Intervention effects on risk for individual CVD endpoints and all-cause mortality per 10 µm/year slower cIMT progression.
*The RRs for intercepts are the effects achieved independent of cIMT progression. Abbreviations: CI=credible interval. cIMT=carotid intima-media thickness. CVD=cardiovascular disease. RR=relative risk.
Figure 3
Figure 3. Intervention effects on cIMT progression plotted against intervention effects on risk for the primary CVD endpoint, according to type of intervention.
The RRs for intercepts as well as P values for heterogeneity of intercept and slope are provided in Figure 4. The areas of the bubbles are proportional to the inverse variance of the log relative risk for the primary CVD endpoint. For purpose of presentation, the graph area was limited to -80 to 80 μm/year on the horizontal axis and 0.25 to 4 on the vertical axis. Trials with point estimates outside of this area are indicated with the symbol x. Abbreviations: cIMT=carotid intima-media thickness. CVD=cardiovascular disease. RR=relative risk.
Figure 4
Figure 4. Intervention effects on risk for the primary CVD endpoint per 10 µm/year slower cIMT progression, according to trial characteristics.
Abbreviations: CCA-IMT=intima-media thickness of the common-carotid-artery. CI=credible interval. cIMT=carotid intima-media thickness. IPD=individual-participant data. RR=relative risk. *P values for heterogeneity. §The RRs for intercepts are the effects achieved independent of cIMT progression.||Numbers of trials across some subgroups do not sum up to 119 because of missing information or contribution of trials to multiple subgroups.
Figure 5
Figure 5. Summary of key findings of our study.
Abbreviations: CI=credible interval. cIMT=carotid intima-media thickness. CVD=cardiovascular disease. RCTs= randomized controlled trials.

Comment in

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