Cost-effectiveness of screening of coronary artery disease in patients with type 2 DIABetes at a very high cardiovascular risk (SCADIAB study) rational and design

Kamel Mohammedi, Nathalie Préaubert, Tanguy Cariou, Vincent Rigalleau, Ninon Foussard, Laurent Piazza, Céline Bairras-Martin, Thierry Couffinhal, Julien Bezin, Antoine Benard, Kamel Mohammedi, Nathalie Préaubert, Tanguy Cariou, Vincent Rigalleau, Ninon Foussard, Laurent Piazza, Céline Bairras-Martin, Thierry Couffinhal, Julien Bezin, Antoine Benard

Abstract

Background: Screening for coronary artery disease (CAD) remains broadly performed in patients with type 2 diabetes (T2DM), although the lack of evidence. We conduct a real-world evidence (RWE) study to assess the risk of major clinical outcomes and economic impact of routine CAD screening in T2DM individuals at a very high cardiovascular risk.

Methods: SCADIAB is a comparative nationwide cohort study using data from the French National Health Data System. The main inclusion criteria are: age ≥ 40 years, DT2 diagnosed for ≥ 7 years, with ≥ 2 additional cardiovascular risk factors plus a history of microvascular or macrovascular disease, except CAD. We estimated ≥ 90,000 eligible participants for our study. Data will be extracted from 01/01/2008 to 31/12/2019. Eligible participants will be identified during a first 7-year selection period (2008-2015). Each participant will be assigned either in experimental (CAD screening procedure during the selection period) or control group (no CAD screening) on 01/01/2015, and followed for 5 years. The primary endpoint is the incremental cost per life year saved over 5 years in CAD screening group versus no CAD screening. The main secondary endpoints are: total 5-year direct costs of each strategy; incidence of major cardiovascular (acute coronary syndrome, hospitalization for heart failure, coronary revascularization or all-cause death), cerebrovascular (hospitalization for transient ischemic attack, stroke, or carotid revascularization) and lower-limb events (peripheral artery disease, ischemic diabetic foot, lower-limb revascularization or amputation); and the budget impact for the French Insurance system to promote the cost-effective strategy. Analyses will be adjusted for a high-dimension propensity score taking into account known and unknown confounders. SCADIAB has been funded by the French Ministry of Health and the protocol has been approved by the French ethic authorities. Data management and analyses will start in the second half of 2021.

Discussion: SCADIAB is a large and contemporary RWE study that will assess the economic and clinical impacts of routine CAD screening in T2DM people at a very high cardiovascular risk. It will also evaluate the clinical practice regarding CAD screening and help to make future recommendations and optimize the use of health care resources. Trial registration ClinicalTrials.gov Identifier: NCT04534530 ( https://ichgcp.net/clinical-trials-registry/NCT04534530 ).

Keywords: Cardiovascular risk; Coronary artery disease; Cost-effectiveness; Economic impact; Major adverse cardiac events; Real-world evidence study; Screening; Type 2 diabetes.

Conflict of interest statement

Authors declare no other potential conflict of interest relevant to this article.

Figures

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Fig. 1
Study design

References

    1. Gregg EW, Li Y, Wang J, Burrows NR, Ali MK, Rolka D, et al. Changes in diabetes-related complications in the United States, 1990–2010. N Engl J Med. 2014;370(16):1514–1523. doi: 10.1056/NEJMoa1310799.
    1. Nativel M, Potier L, Alexandre L, Baillet-Blanco L, Ducasse E, Velho G, et al. Lower extremity arterial disease in patients with diabetes: a contemporary narrative review. Cardiovasc Diabetol. 2018;17(1):138. doi: 10.1186/s12933-018-0781-1.
    1. Mohammedi K, Woodward M, Marre M, Colagiuri S, Cooper M, Harrap S, et al. Comparative effects of microvascular and macrovascular disease on the risk of major outcomes in patients with type 2 diabetes. Cardiovasc Diabetol. 2017;16(1):95. doi: 10.1186/s12933-017-0574-y.
    1. Arnold SV, Khunti K, Bonnet F, Charbonnel B, Chen H, Cid-Ruzafa J, et al. Type 2 diabetes and heart failure: insights from the global DISCOVER study. ESC Heart Fail. 2021 doi: 10.1002/ehf2.13235.
    1. Rawshani A, Rawshani A, Franzen S, Eliasson B, Svensson AM, Miftaraj M, et al. Mortality and cardiovascular disease in type 1 and type 2 diabetes. N Engl J Med. 2017;376(15):1407–1418. doi: 10.1056/NEJMoa1608664.
    1. Tsujimoto T, Kajio H, Takahashi Y, Kishimoto M, Noto H, Yamamoto-Honda R, et al. Asymptomatic coronary heart disease in patients with type 2 diabetes with vascular complications: a cross-sectional study. BMJ Open. 2011;1(2):e000139. doi: 10.1136/bmjopen-2011-000139.
    1. Thai PV, Tien HA, Van Minh H, Valensi P. Triglyceride glucose index for the detection of asymptomatic coronary artery stenosis in patients with type 2 diabetes. Cardiovasc Diabetol. 2020;19(1):137. doi: 10.1186/s12933-020-01108-2.
    1. Eser P, Marcin T, Prescott E, Prins LF, Kolkman E, Bruins W, et al. Clinical outcomes after cardiac rehabilitation in elderly patients with and without diabetes mellitus: The EU-CaRE multicenter cohort study. Cardiovasc Diabetol. 2020;19(1):37. doi: 10.1186/s12933-020-01013-8.
    1. Battermann S, Milzi A, Dettori R, Burgmaier K, Marx N, Burgmaier M, et al. High cardiovascular risk of patients with type 2 diabetes is only partially attributed to angiographic burden of atherosclerosis. Diab Vasc Dis Res. 2020;17(9):1479164120953612.
    1. Funamizu T, Iwata H, Nishida Y, Miyosawa K, Doi S, Chikata Y, et al. Increased risk of cardiovascular mortality by strict glycemic control (pre-procedural HbA1c < 6.5%) in Japanese medically-treated diabetic patients following percutaneous coronary intervention: a 10-year follow-up study. Cardiovasc Diabetol. 2020;19(1):21.
    1. Young LH, Wackers FJ, Chyun DA, Davey JA, Barrett EJ, Taillefer R, et al. Cardiac outcomes after screening for asymptomatic coronary artery disease in patients with type 2 diabetes: the DIAD study: a randomized controlled trial. JAMA. 2009;301(15):1547–1555. doi: 10.1001/jama.2009.476.
    1. Lievre MM, Moulin P, Thivolet C, Rodier M, Rigalleau V, Penfornis A, et al. Detection of silent myocardial ischemia in asymptomatic patients with diabetes: results of a randomized trial and meta-analysis assessing the effectiveness of systematic screening. Trials. 2011;12:23. doi: 10.1186/1745-6215-12-23.
    1. Muhlestein JB, Lappe DL, Lima JA, Rosen BD, May HT, Knight S, et al. Effect of screening for coronary artery disease using CT angiography on mortality and cardiac events in high-risk patients with diabetes: the FACTOR-64 randomized clinical trial. JAMA. 2014;312(21):2234–2243. doi: 10.1001/jama.2014.15825.
    1. Turrini F, Scarlini S, Mannucci C, Messora R, Giovanardi P, Magnavacchi P, et al. Does coronary Atherosclerosis Deserve to be Diagnosed earlY in Diabetic patients? The DADDY-D trial Screening diabetic patients for unknown coronary disease. Eur J Intern Med. 2015;26(6):407–413. doi: 10.1016/j.ejim.2015.05.006.
    1. Rados DV, Pinto LC, Leitao CB, Gross JL. Screening for coronary artery disease in patients with type 2 diabetes: a meta-analysis and trial sequential analysis. BMJ Open. 2017;7(5):e015089. doi: 10.1136/bmjopen-2016-015089.
    1. Faglia E, Manuela M, Antonella Q, Michela G, Vincenzo C, Maurizio C, et al. Risk reduction of cardiac events by screening of unknown asymptomatic coronary artery disease in subjects with type 2 diabetes mellitus at high cardiovascular risk: an open-label randomized pilot study. Am Heart J. 2005;149(2):e1–6. doi: 10.1016/j.ahj.2004.07.027.
    1. Budoff MJ, Raggi P, Beller GA, Berman DS, Druz RS, Malik S, et al. Noninvasive Cardiovascular Risk Assessment of the Asymptomatic Diabetic Patient: The Imaging Council of the American College of Cardiology. JACC Cardiovasc Imaging. 2016;9(2):176–192. doi: 10.1016/j.jcmg.2015.11.011.
    1. Greenland P, Alpert JS, Beller GA, Benjamin EJ, Budoff MJ, Fayad ZA, et al. 2010 ACCF/AHA guideline for assessment of cardiovascular risk in asymptomatic adults: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2010;56(25):e50–103. doi: 10.1016/j.jacc.2010.09.001.
    1. Ryden L, Grant PJ, Anker SD, Berne C, Cosentino F, Danchin N, et al. ESC Guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD: the Task Force on diabetes, pre-diabetes, and cardiovascular diseases of the European Society of Cardiology (ESC) and developed in collaboration with the European Association for the Study of Diabetes (EASD) Eur Heart J. 2013;34(39):3035–3087. doi: 10.1093/eurheartj/eht108.
    1. Valensi P, Henry P, Boccara F, Cosson E, Prevost G, Emmerich J, et al. Risk stratification and screening for coronary artery disease in asymptomatic patients with diabetes mellitus: Position paper of the French Society of Cardiology and the French-speaking Society of Diabetology. Arch Cardiovasc Dis. 2020.
    1. Hayashino Y, Nagata-Kobayashi S, Morimoto T, Maeda K, Shimbo T, Fukui T. Cost-effectiveness of screening for coronary artery disease in asymptomatic patients with Type 2 diabetes and additional atherogenic risk factors. J Gen Intern Med. 2004;19(12):1181–1191. doi: 10.1111/j.1525-1497.2004.40012.x.
    1. Hayashino Y, Shimbo T, Tsujii S, Ishii H, Kondo H, Nakamura T, et al. Cost-effectiveness of coronary artery disease screening in asymptomatic patients with type 2 diabetes and other atherogenic risk factors in Japan: factors influencing on international application of evidence-based guidelines. Int J Cardiol. 2007;118(1):88–96. doi: 10.1016/j.ijcard.2006.03.086.
    1. Bezin J, Duong M, Lassalle R, Droz C, Pariente A, Blin P, et al. The national healthcare system claims databases in France, SNIIRAM and EGB: Powerful tools for pharmacoepidemiology. Pharmacoepidemiol Drug Saf. 2017;26(8):954–962. doi: 10.1002/pds.4233.
    1. Clara Piffaretti AF-C, Grégoire Rey, Juliana Antero-Jacquemin, Aurélien Latouche, Laurence Mandereau-Bruno, Sandrine Fosse-Edorh. DÉTERMINANTS DE LA MORTALITÉ DES PERSONNES DIABÉTIQUES DE TYPE 2. COHORTES ENTRED, FRANCE, 2002–2013. Bulletin épidémiologique hebdomadaire. 2016;37–38 681 - 90.
    1. Fosse-Edorh S M-BL, Piffaretti C. Le poids du diabète en France en 2016. Synthèse épidémiologique. Synthèse épidémiologique. . Saint-Maurice : Santé publique France. 2018:8.
    1. Rassen JA, Schneeweiss S. Using high-dimensional propensity scores to automate confounding control in a distributed medical product safety surveillance system. Pharmacoepidemiol Drug Saf. 2012;21(Suppl 1):41–49. doi: 10.1002/pds.2328.
    1. Austin PC. Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Stat Med. 2009;28(25):3083–3107. doi: 10.1002/sim.3697.
    1. Zellweger MJ, Maraun M, Osterhues HH, Keller U, Muller-Brand J, Jeger R, et al. Progression to overt or silent CAD in asymptomatic patients with diabetes mellitus at high coronary risk: main findings of the prospective multicenter BARDOT trial with a pilot randomized treatment substudy. JACC Cardiovasc Imaging. 2014;7(10):1001–1010. doi: 10.1016/j.jcmg.2014.07.010.
    1. Aboa-Eboule C, Mengue D, Benzenine E, Hommel M, Giroud M, Bejot Y, et al. How accurate is the reporting of stroke in hospital discharge data? A pilot validation study using a population-based stroke registry as control. J Neurol. 2013;260(2):605–613. doi: 10.1007/s00415-012-6686-0.
    1. Bezin J, Girodet PO, Rambelomanana S, Touya M, Ferreira P, Gilleron V, et al. Choice of ICD-10 codes for the identification of acute coronary syndrome in the French hospitalization database. Fundam Clin Pharmacol. 2015;29(6):586–591. doi: 10.1111/fcp.12143.
    1. Giroud MHM, Benzenine E, Fauconnier J, Béjot Y, Quantin C. Evaluation of metrologic quality of the french national hospital discharge database for stroke. BEH. 2016;1:8–15.
    1. Schneeweiss S, Rassen JA, Glynn RJ, Avorn J, Mogun H, Brookhart MA. High-dimensional propensity score adjustment in studies of treatment effects using health care claims data. Epidemiology. 2009;20(4):512–522. doi: 10.1097/EDE.0b013e3181a663cc.
    1. Toh S, Garcia Rodriguez LA, Hernan MA. Confounding adjustment via a semi-automated high-dimensional propensity score algorithm: an application to electronic medical records. Pharmacoepidemiol Drug Saf. 2011;20(8):849–857. doi: 10.1002/pds.2152.
    1. Rassen JA, Glynn RJ, Brookhart MA, Schneeweiss S. Covariate selection in high-dimensional propensity score analyses of treatment effects in small samples. Am J Epidemiol. 2011;173(12):1404–1413. doi: 10.1093/aje/kwr001.

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