OptimiZation Of Lipid Lowering Therapies Using a Decision Support System In Patients With Acute Coronary Syndrome.
ZODIAC
Implementation of a Decision Support System and Its Effect on Early Optimisation of Lipid-Lowering Therapies in Patients With Acute Coronary Syndrome: a Cluster Randomised Controlled Trial
1 other identifier
interventional
1,139
3 countries
42
Brief Summary
The goal of this clinical trial is to compare implementation of a Decision Support System (DSS) - aligned to the 2019 ESC/EAS Guidelines - in addition to routine clinical care versus routine clinical care without availability of a DSS, in participants aged ≥18 to \< 80 years old presenting with Acute Coronary Syndrome (ACS). The main questions it aims to answer are:
- to assess whether the availability of a DSS (which provides estimates of risk and estimates of potential benefit through LDL-C lowering) to current practice results in an increase in the early initiation of combination Lipid Lowering Therapies (LLTs) or intensification of LLT regimens compared to current practice alone over a 16-week period after an Acute Coronary Syndromes (ACS) event
- To estimate in the study cohort the potential benefits of guideline-based LLT intensification via simulation-based methods using estimates of baseline risk: LLT utilisation, additional LDL-C reductions and LDL-C goal achievement, on simulated risk of CV events through modelling. Participants will give consent to randomised clinical sites to collect their data. The clinical sites will either be randomised to standard of care or the availability of and access to the DSS. Researchers will compare patients from DSS and Non-DSS sites to see if the availability of the DSS results in implementation of more intensive lipid lowering regimens, resulting in the achievement of lower LDL-C values as well as the proportion of patients who reach target LDL-C levels (\<1.4 mmol/L (\<55 mg/dL) by Week 16.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Apr 2023
42 active sites
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
Study Start
First participant enrolled
April 3, 2023
CompletedFirst Submitted
Initial submission to the registry
April 25, 2023
CompletedFirst Posted
Study publicly available on registry
May 6, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 12, 2024
CompletedStudy Completion
Last participant's last visit for all outcomes
December 12, 2024
CompletedResults Posted
Study results publicly available
February 19, 2026
CompletedFebruary 19, 2026
January 1, 2026
1.7 years
April 25, 2023
December 16, 2025
January 30, 2026
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Optimisation of the Intensity of Lipid Lowering Therapy Within 16 Weeks of Index ACS
Proportion of patients treated with combination therapy, or who receive escalated monotherapy, or escalated combination therapy, within 16 weeks of the index ACS.
16 weeks
Secondary Outcomes (3)
Timing of Initiation
16 weeks
LDL-C Level
16 weeks
Target LDL-C Reduction
16 weeks
Study Arms (2)
Decision Support System (DSS)
OTHERPatients of this cohort are seen at a site randomised to the availability of the DSS. These patients will be provided routine clinical care including local/national prescribing guidelines during the course of the study. In addition to routine clinical care, the DSS which is available online, is a tool intended for clinicians to estimate the clinical benefit of any LLT regimen, whether monotherapy or combination therapies.
Non-Decision Support System (Non-DSS)
NO INTERVENTIONPatients of this cohort are seen at a site randomised to no availability of a DSS (Non-DSS). These patients will be provided routine clinical care including local / national prescribing guidelines during the course of the study.
Interventions
This DSS will provide estimates of potential benefits in terms of ASCVD risk reduction (composite endpoint: combined non-fatal myocardial infarction, non-fatal ischaemic stroke and cardiovascular death) as a function of treatment duration and magnitude of LDL-C lowering. The DSS does not recommend treatments but shows the expected ASCVD risk, absolute and relative ASCDV risk reductions and number needed to treat for the various treatments selected by the clinical user on the potential value of initiation of an add-on therapy for reducing the risk of recurrent Cardiovascular (CV) events. Implementing the patient-specific recommendation remains at the clinicians' discretion.
Eligibility Criteria
You may qualify if:
- Sites:
- Manage ACS patients as defined by: Symptoms of myocardial ischemia with an unstable pattern, occurring at rest or with minimal exertion, within 72 hours of an unscheduled hospital admission due to presumed or proven obstructive coronary disease and at least one of the following:
- Elevated cardiac biomarkers
- Resting electrocardiographic changes consistent with ischemia or infarction, plus additional evidence of obstructive coronary disease from regional wall motion or perfusion abnormality, 70% or more epicardial coronary stenosis by angiography, or need for coronary revascularization procedure
- Mange post ACS follow up care of patients including risk factor control
- Ability to provide follow up information on patient care for a minimum of 16 weeks including blood tests
- Willing/ able to access and undertake training for the DSS
- Adequate internet connection at site and the ability to access the DSS
- No restrictions on use of LLTs (within national guidelines/ reimbursement)
- Ability to include all essential parameters and patient information for DSS input
- Participants:
- Aged ≥18 to \< 80 years old
- Provide written informed consent
- Presenting to a study site with ACS as LLT naĂ¯ve, monotherapy or combination therapy (defined as more than one LLT agent)
- Willing to take lipid lowering treatments for the secondary prevention of cardiovascular disease
- +1 more criteria
You may not qualify if:
- Sites:
- Unable to capture/ provide data on patients with ACS during admission and follow up
- Unable or unwilling to use lipid lowering treatments other than statins for ACS care
- Participants:
- Unable to provide written informed consent
- LDL-C measurement \< 1.8 mmol/L at admission
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Imperial College Londonlead
- Sanoficollaborator
- Axtria, Inc.collaborator
- Hospital Universitario La Pazcollaborator
- Hippocrates Researchcollaborator
Study Sites (42)
AUSL di Bologna-Ospedale Maggiore
Bologna, 40133, Italy
Azienda Ospedaliera di Rilievo Nazionale (A.O.R.N.) "Sant'Anna e San Sebastiano" di Caserta
Caserta, 81100, Italy
A.O.U. Ospedali Riuniti U.O.C. Cardiologia e UTIC
Foggia, 71122, Italy
IRCCS. A.O.U. Policlinico San Martino IST
Genova, 16132, Italy
Azienda Ospedaliera Universitaria Gaetano Martino
Messina, 98125, Italy
IRCCS Policlinico San Donato
Milan, 20097, Italy
A.O.U Policlinico di Modena S.C. di Cardiologia
Modena, 41124, Italy
Ospedale di Cisanello - A.U.O.P. Azienda Ospedaliera Universitaria
Pisa, 56124, Italy
AUSL-IRCCS di Reggio Emilia
Reggio Emilia, 42121, Italy
Ospedale Sandro Pertini - ASL Roma 2
Roma, 00157, Italy
Azienda Ospedaliero Universitaria Santa Maria della Misericordia
Udine, 33100, Italy
Hospital ClĂnico Universitario Santiago de Compostela
Santiago de Compostela, A Coruña, 15706, Spain
University Hospital of A Coruña
A Coruña, Coruña, 15006, Spain
Hospital HM MonteprĂncipe
Boadilla del Monte, Madrid, 28660, Spain
Hospital Universitario Rey Juan Carlos
MĂ³stoles, Madrid, 28933, Spain
Hospital ClĂnico Universitario Virgen de la Arrixaca
El Palmar, Murcia, 30120, Spain
Hospital de la Santa Creu i Sant Pau
Barcelona, 08025, Spain
Vall d'Hebron University Hospital
Barcelona, 08035, Spain
Hospital Universitario Reina Sofia
CĂ³rdoba, 14004, Spain
Hospital Universitario La Luz Quiron
Madrid, 28003, Spain
Gregorio MaraĂ±Ă³n General University Hospital
Madrid, 28007, Spain
Hospital Universitario FundaciĂ³n JimĂ©nez DĂaz
Madrid, 28040, Spain
Hospital Universitario La Paz
Madrid, 28046, Spain
Puerta de Hierro Majadahonda University Hospital
Madrid, 28222, Spain
Hospital Universitario Virgen Macarena
Seville, 41009, Spain
Luton and Dunstable University Hospital
Luton, Bedfordshire, LU4 0DZ, United Kingdom
Glan Glwyd Hospital
Bodelwyddan, Denbighshire, LL18 5UJ, United Kingdom
Royal Bournemouth Hospital
Bournemouth, Dorset, BH7 7DW, United Kingdom
Conquest Hospital
Brighton, East Sussex, TN37 7PT, United Kingdom
Scunthorpe General Hospital
Scunthorpe, North Lincolnshire, DN15 7BH, United Kingdom
Kettering General Hospital
Kettering, Northamptonshire, NN16 8UZ, United Kingdom
Southern Health and Social Care Trust, Craigavon Area Hospital
Portadown, Northen Ireland, BT63 5QQ, United Kingdom
Royal United Hospital
Bath, Somerset, BA1 3NG, United Kingdom
Freeman Hospital
Newcastle upon Tyne, Tyne and Wear, NE7 7DN, United Kingdom
North Tyneside General Hospital
North Shields, Tyne and Wear, NE29 8NH, United Kingdom
Sunderland Royal Hospital
Sunderland, Tyne and Wear, SR4 7TP, United Kingdom
Sandwell General Hospital
Birmingham, West Midlands, B71 4HJ, United Kingdom
Russell's Hall Hospital
Dudley, West Midlands, DY12HQ, United Kingdom
Worthing Hospital
Worthing, West Sussex, BN11 2DH, United Kingdom
Calderdale Royal Hospital
Halifax, West Yorkshire, HX3 0PW, United Kingdom
Worcestershire Royal Hospital
Worcester, Worcestershire, WR5 1DD, United Kingdom
Hammersmith Hospital
London, W2 1NY, United Kingdom
Related Publications (27)
Schubert J, Lindahl B, Melhus H, Renlund H, Leosdottir M, Yari A, Ueda P, James S, Reading SR, Dluzniewski PJ, Hamer AW, Jernberg T, Hagstrom E. Low-density lipoprotein cholesterol reduction and statin intensity in myocardial infarction patients and major adverse outcomes: a Swedish nationwide cohort study. Eur Heart J. 2021 Jan 20;42(3):243-252. doi: 10.1093/eurheartj/ehaa1011.
PMID: 33367526BACKGROUNDWilliams B, Mancia G, Spiering W, Agabiti Rosei E, Azizi M, Burnier M, Clement DL, Coca A, de Simone G, Dominiczak A, Kahan T, Mahfoud F, Redon J, Ruilope L, Zanchetti A, Kerins M, Kjeldsen SE, Kreutz R, Laurent S, Lip GYH, McManus R, Narkiewicz K, Ruschitzka F, Schmieder RE, Shlyakhto E, Tsioufis C, Aboyans V, Desormais I; ESC Scientific Document Group. 2018 ESC/ESH Guidelines for the management of arterial hypertension. Eur Heart J. 2018 Sep 1;39(33):3021-3104. doi: 10.1093/eurheartj/ehy339. No abstract available.
PMID: 30165516BACKGROUNDMach F, Baigent C, Catapano AL, Koskinas KC, Casula M, Badimon L, Chapman MJ, De Backer GG, Delgado V, Ference BA, Graham IM, Halliday A, Landmesser U, Mihaylova B, Pedersen TR, Riccardi G, Richter DJ, Sabatine MS, Taskinen MR, Tokgozoglu L, Wiklund O; ESC Scientific Document Group. 2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk. Eur Heart J. 2020 Jan 1;41(1):111-188. doi: 10.1093/eurheartj/ehz455. No abstract available.
PMID: 31504418BACKGROUNDBohula EA, Morrow DA, Giugliano RP, Blazing MA, He P, Park JG, Murphy SA, White JA, Kesaniemi YA, Pedersen TR, Brady AJ, Mitchel Y, Cannon CP, Braunwald E. Atherothrombotic Risk Stratification and Ezetimibe for Secondary Prevention. J Am Coll Cardiol. 2017 Feb 28;69(8):911-921. doi: 10.1016/j.jacc.2016.11.070.
PMID: 28231942BACKGROUNDFerence BA, Ginsberg HN, Graham I, Ray KK, Packard CJ, Bruckert E, Hegele RA, Krauss RM, Raal FJ, Schunkert H, Watts GF, Boren J, Fazio S, Horton JD, Masana L, Nicholls SJ, Nordestgaard BG, van de Sluis B, Taskinen MR, Tokgozoglu L, Landmesser U, Laufs U, Wiklund O, Stock JK, Chapman MJ, Catapano AL. Low-density lipoproteins cause atherosclerotic cardiovascular disease. 1. Evidence from genetic, epidemiologic, and clinical studies. A consensus statement from the European Atherosclerosis Society Consensus Panel. Eur Heart J. 2017 Aug 21;38(32):2459-2472. doi: 10.1093/eurheartj/ehx144.
PMID: 28444290BACKGROUNDKhan I, Peterson ED, Cannon CP, Sedita LE, Edelberg JM, Ray KK. Time-Dependent Cardiovascular Treatment Benefit Model for Lipid-Lowering Therapies. J Am Heart Assoc. 2020 Aug 4;9(15):e016506. doi: 10.1161/JAHA.120.016506. Epub 2020 Jul 28.
PMID: 32720582BACKGROUNDRay KK, Reeskamp LF, Laufs U, Banach M, Mach F, Tokgozoglu LS, Connolly DL, Gerrits AJ, Stroes ESG, Masana L, Kastelein JJP. Combination lipid-lowering therapy as first-line strategy in very high-risk patients. Eur Heart J. 2022 Feb 22;43(8):830-833. doi: 10.1093/eurheartj/ehab718. No abstract available.
PMID: 34636884BACKGROUNDRay KK, Molemans B, Schoonen WM, Giovas P, Bray S, Kiru G, Murphy J, Banach M, De Servi S, Gaita D, Gouni-Berthold I, Hovingh GK, Jozwiak JJ, Jukema JW, Kiss RG, Kownator S, Iversen HK, Maher V, Masana L, Parkhomenko A, Peeters A, Clifford P, Raslova K, Siostrzonek P, Romeo S, Tousoulis D, Vlachopoulos C, Vrablik M, Catapano AL, Poulter NR; DA VINCI study. EU-Wide Cross-Sectional Observational Study of Lipid-Modifying Therapy Use in Secondary and Primary Care: the DA VINCI study. Eur J Prev Cardiol. 2021 Sep 20;28(11):1279-1289. doi: 10.1093/eurjpc/zwaa047.
PMID: 33580789BACKGROUNDSteen DL, Khan I, Ansell D, Sanchez RJ, Ray KK. Retrospective examination of lipid-lowering treatment patterns in a real-world high-risk cohort in the UK in 2014: comparison with the National Institute for Health and Care Excellence (NICE) 2014 lipid modification guidelines. BMJ Open. 2017 Feb 17;7(2):e013255. doi: 10.1136/bmjopen-2016-013255.
PMID: 28213597BACKGROUNDFerrieres J, Gorcyca K, Iorga SR, Ansell D, Steen DL. Lipid-lowering Therapy and Goal Achievement in High-risk Patients From French General Practice. Clin Ther. 2018 Sep;40(9):1484-1495.e22. doi: 10.1016/j.clinthera.2018.07.008. Epub 2018 Aug 18.
PMID: 30126705BACKGROUNDArca M, Ansell D, Averna M, Fanelli F, Gorcyca K, Iorga SR, Maggioni AP, Paizis G, Tomic R, Catapano AL. Statin utilization and lipid goal attainment in high or very-high cardiovascular risk patients: Insights from Italian general practice. Atherosclerosis. 2018 Apr;271:120-127. doi: 10.1016/j.atherosclerosis.2018.02.024. Epub 2018 Feb 17.
PMID: 29499359BACKGROUNDBlaum C, Seiffert M, Gossling A, Kroger F, Bay B, Lorenz T, Braetz J, Graef A, Zeller T, Schnabel R, Clemmensen P, Westermann D, Blankenberg S, Brunner FJ, Waldeyer C. The need for PCSK9 inhibitors and associated treatment costs according to the 2019 ESC dyslipidaemia guidelines vs. the risk-based allocation algorithm of the 2017 ESC consensus statement: a simulation study in a contemporary CAD cohort. Eur J Prev Cardiol. 2021 Mar 23;28(1):47-56. doi: 10.1093/eurjpc/zwaa088.
PMID: 33580772BACKGROUNDMarz W, Dippel FW, Theobald K, Gorcyca K, Iorga SR, Ansell D. Utilization of lipid-modifying therapy and low-density lipoprotein cholesterol goal attainment in patients at high and very-high cardiovascular risk: Real-world evidence from Germany. Atherosclerosis. 2018 Jan;268:99-107. doi: 10.1016/j.atherosclerosis.2017.11.020. Epub 2017 Nov 20.
PMID: 29197254BACKGROUNDKuiper JG, Sanchez RJ, Houben E, Heintjes EM, Penning-van Beest FJA, Khan I, van Riemsdijk M, Herings RMC. Use of Lipid-modifying Therapy and LDL-C Goal Attainment in a High-Cardiovascular-Risk Population in the Netherlands. Clin Ther. 2017 Apr;39(4):819-827.e1. doi: 10.1016/j.clinthera.2017.03.001. Epub 2017 Mar 27.
PMID: 28347514BACKGROUNDKoskinas KC, Gencer B, Nanchen D, Branca M, Carballo D, Klingenberg R, Blum MR, Carballo S, Muller O, Matter CM, Luscher TF, Rodondi N, Heg D, Wilhelm M, Raber L, Mach F, Windecker S. Eligibility for PCSK9 inhibitors based on the 2019 ESC/EAS and 2018 ACC/AHA guidelines. Eur J Prev Cardiol. 2021 Mar 23;28(1):59-65. doi: 10.1177/2047487320940102. Epub 2020 Jul 20.
PMID: 33755142BACKGROUNDAllahyari A, Jernberg T, Hagstrom E, Leosdottir M, Lundman P, Ueda P. Application of the 2019 ESC/EAS dyslipidaemia guidelines to nationwide data of patients with a recent myocardial infarction: a simulation study. Eur Heart J. 2020 Oct 21;41(40):3900-3909. doi: 10.1093/eurheartj/ehaa034.
PMID: 32072178BACKGROUNDMancia G, Rea F, Corrao G, Grassi G. Two-Drug Combinations as First-Step Antihypertensive Treatment. Circ Res. 2019 Mar 29;124(7):1113-1123. doi: 10.1161/CIRCRESAHA.118.313294.
PMID: 30920930BACKGROUNDDorresteijn JA, Visseren FL, Wassink AM, Gondrie MJ, Steyerberg EW, Ridker PM, Cook NR, van der Graaf Y; SMART Study Group. Development and validation of a prediction rule for recurrent vascular events based on a cohort study of patients with arterial disease: the SMART risk score. Heart. 2013 Jun;99(12):866-72. doi: 10.1136/heartjnl-2013-303640. Epub 2013 Apr 10.
PMID: 23574971BACKGROUNDMcKay AJ, Gunn LH, Ference BA, Dorresteijn JAN, Berkelmans GFN, Visseren FLJ, Ray KK. Is the SMART risk prediction model ready for real-world implementation? A validation study in a routine care setting of approximately 380 000 individuals. Eur J Prev Cardiol. 2022 Mar 30;29(4):654-663. doi: 10.1093/eurjpc/zwab093.
PMID: 34160035BACKGROUNDGao F, Earnest A, Matchar DB, Campbell MJ, Machin D. Sample size calculations for the design of cluster randomized trials: A summary of methodology. Contemp Clin Trials. 2015 May;42:41-50. doi: 10.1016/j.cct.2015.02.011. Epub 2015 Mar 9.
PMID: 25766887BACKGROUNDCampbell MK, Piaggio G, Elbourne DR, Altman DG; CONSORT Group. Consort 2010 statement: extension to cluster randomised trials. BMJ. 2012 Sep 4;345:e5661. doi: 10.1136/bmj.e5661. No abstract available.
PMID: 22951546BACKGROUNDBellamy SL, Gibberd R, Hancock L, Howley P, Kennedy B, Klar N, Lipsitz S, Ryan L. Analysis of dichotomous outcome data for community intervention studies. Stat Methods Med Res. 2000 Apr;9(2):135-59. doi: 10.1177/096228020000900205.
PMID: 10946431BACKGROUNDCampbell MJ, Donner A, Klar N. Developments in cluster randomized trials and Statistics in Medicine. Stat Med. 2007 Jan 15;26(1):2-19. doi: 10.1002/sim.2731.
PMID: 17136746BACKGROUNDParker RA, Weir CJ. Multiple secondary outcome analyses: precise interpretation is important. Trials. 2022 Jan 10;23(1):27. doi: 10.1186/s13063-021-05975-2.
PMID: 35012627BACKGROUNDCannon CP, Khan I, Klimchak AC, Reynolds MR, Sanchez RJ, Sasiela WJ. Simulation of Lipid-Lowering Therapy Intensification in a Population With Atherosclerotic Cardiovascular Disease. JAMA Cardiol. 2017 Sep 1;2(9):959-966. doi: 10.1001/jamacardio.2017.2289.
PMID: 28768335BACKGROUNDRubin, M. When to adjust alpha during multiple testing: a consideration of disjunction, conjunction, and individual testing. Synthese 199, 10969-11000 (2021).
BACKGROUNDRitz J, Spiegelman D. Equivalence of conditional and marginal regression models for clustered and longitudinal data. Statistical Methods in Medical Research. 2004;13(4):309-323. doi:10.1191/0962280204sm368ra
BACKGROUND
Related Links
- Framework to aid in the creation of apps across multiple platforms including iOS, Android and Windows.
- Angular is a development platform, built on TypeScript. This link can help you understand Angular: what Angular is, what advantages it provides, and what you might expect as you start to build applications
- Empirical estimates of ICCs from changing professional practice studies. (Very small ICCs rounded to 0.0001; Negative ICCs truncated at zero; n/a = not applicable).
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Results Point of Contact
- Title
- Prof. Kausik K Ray
- Organization
- Imperial College London
Study Officials
- PRINCIPAL INVESTIGATOR
Kausik Ray, Professor
Imperial College London
Publication Agreements
- PI is Sponsor Employee
- Yes
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- SINGLE
- Who Masked
- PARTICIPANT
- Masking Details
- The patient will be notified at the end of the study in regard to allocation.
- Purpose
- OTHER
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
April 25, 2023
First Posted
May 6, 2023
Study Start
April 3, 2023
Primary Completion
December 12, 2024
Study Completion
December 12, 2024
Last Updated
February 19, 2026
Results First Posted
February 19, 2026
Record last verified: 2026-01
Data Sharing
- IPD Sharing
- Will not share