OptimiZation Of Lipid Lowering Therapies Using a Decision Support System In Patients With Acute Coronary Syndrome.
NCT ID: NCT05844566
Last Updated: 2025-01-23
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
COMPLETED
NA
1139 participants
INTERVENTIONAL
2023-04-03
2024-12-10
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
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.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
Study to Evaluate the Impact of a Targeted Lipid Optimization Program on LDL-C Control in At-risk Adult Patients With Dyslipidemia
NCT07034690
Percentage of Secondary Prevention Patients Treated to Their LDL-C Targets
NCT00536796
Percentage of Secondary Prevention Patients Treated to Their LDL-C Targets
NCT00536965
National Survey on Dyslipidemic Patients
NCT00701402
Cardiovascular Events Based On Statin Initiation In The Elderly
NCT01304641
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
Lowering LDL-C with high intensity lipid lowering therapies (LLTs) initiated within 10 days of an ACS reduces risk more than less intense regimens. In the SWEDEHEART registry which included 40,6007 patients over a median follow up of 3.78 years, patients who achieved the largest absolute reductions in LDL-C or greatest percentage reduction in LDL-C, had the lowest risk of a range of cardiovascular events and mortality. The approach to use of lipid lowering (LLT) was statin based monotherapy with few attaining the recommended cholesterol goals.
The 2019 European Society of Cardiology (ESC) and European Atherosclerosis Society (EAS) dyslipidaemia guidelines categorise patients with an ACS event as very-high risk and recommend an LDL-C goal of \< 1.4 mmol/L (\<55 mg/dL) and \>50% reduction in LDL-C in this population. But several studies in European populations have highlighted gaps between clinical practice/ implementation of treatment recommendations compared with evidence based guideline recommendations. In the DA VINCI study representing 5,888 patients prescribed LLT in 18 European countries, LDL-C goal achievement in very-high risk populations was just 39% per 2016 ESC/EAS guidelines of\<1.8mmol/L with only about 18% achieving the new recommended lower goal of \<1.4mmol/L. It has become clear that greater implementation/ use of available combination therapies will be needed if lower recommended goals are to be achieved. It is unclear what the barriers are to earlier implementation and may include a lack of physician understanding of risk of further CV events or a lack of understanding of the quantifiable benefits from specific magnitudes of LDL-C lowering.
The aim of this trial is to assess whether providing information to those managing ACS patients that quantify absolute risk and the absolute benefit from different lipid lowering regimens through access to a Decision Support Tool (DSS) system is more likely to result in earlier intensification of lipid lowering regimens and thus result in a greater proportion of patients achieving the ESC lipid lowering goals after ACS compared to patients being managed routinely without access to a DSS standard (cluster RCT design). It is well established that unless treatments are initiated through secondary care or as part of acute care pathways, there is considerable inertia in further optimisation of treatment in primary care. Thus, this trial will assess whether presenting quantifiable data on risks and benefits results in behaviour change among secondary care physicians and improves cholesterol management within 4 months of an ACS.
The DSS is available online or remotely accessible via a website intended for clinicians to estimate the clinical benefit of any LLT regimen, whether single or combination therapies. The DSS shows the expected risk, 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 other Cardiovascular (CV) events. This DSS provides a graphical and tabular representation of the time-dependent CV treatment benefit model for LLTs published in a peer-reviewed journal article.
The trial hypothesises that having a pictorial representation of both individual risk and recommended treatments will encourage clinicians to implement clinical guidelines more closely. The clinicians using the DSS will be asked to complete a DSS evaluation at the end of the trial. Implementing the patient-specific recommendation remains at the clinicians' discretion.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
RANDOMIZED
PARALLEL
OTHER
SINGLE
Study Groups
Review each arm or cohort in the study, along with the interventions and objectives associated with them.
Decision Support System (DSS)
Patients 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.
Decision Support System (DSS)
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.
Non-Decision Support System (Non-DSS)
Patients 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.
No interventions assigned to this group
Interventions
Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.
Decision Support System (DSS)
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
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
* 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 naïve, monotherapy or combination therapy (defined as more than one LLT agent)
* Willing to take lipid lowering treatments for the secondary prevention of cardiovascular disease
* Attending the same study site (or same clinical team) for ACS follow up to ensure follow up data can be collected; or ensure that follow up data can be collected from other clinical institutions as part of the clinical pathway.
Exclusion Criteria
* 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
18 Years
79 Years
ALL
No
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
Sanofi
INDUSTRY
Axtria, Inc.
UNKNOWN
Hospital Universitario La Paz
OTHER
Hippocrates Research
OTHER
Imperial College London
OTHER
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Principal Investigators
Learn about the lead researchers overseeing the trial and their institutional affiliations.
Kausik Ray, Professor
Role: PRINCIPAL_INVESTIGATOR
Imperial College London
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
AUSL di Bologna-Ospedale Maggiore
Bologna, , Italy
Azienda Ospedaliera di Rilievo Nazionale (A.O.R.N.) "Sant'Anna e San Sebastiano" di Caserta
Caserta, , Italy
A.O.U. Ospedali Riuniti U.O.C. Cardiologia e UTIC
Foggia, , Italy
IRCCS. A.O.U. Policlinico San Martino IST
Genova, , Italy
Azienda Ospedaliera Universitaria Gaetano Martino
Messina, , Italy
IRCCS Policlinico San Donato
Milan, , Italy
A.O.U Policlinico di Modena S.C. di Cardiologia
Modena, , Italy
Ospedale di Cisanello - A.U.O.P. Azienda Ospedaliera Universitaria
Pisa, , Italy
AUSL-IRCCS di Reggio Emilia
Reggio Emilia, , Italy
Ospedale Sandro Pertini - ASL Roma 2
Roma, , Italy
Azienda Ospedaliero Universitaria Santa Maria della Misericordia
Udine, , Italy
Hospital Clínico Universitario Santiago de Compostela
Santiago de Compostela, A Coruña, Spain
University Hospital of A Coruña
A Coruña, Coruña, Spain
Hospital HM Montepríncipe
Boadilla del Monte, Madrid, Spain
Puerta de Hierro Majadahonda University Hospital
Majadahona, Madrid, Spain
Hospital Universitario Rey Juan Carlos
Móstoles, Madrid, Spain
Hospital Clínico Universitario Virgen de la Arrixaca
El Palmar, Murcia, Spain
Hospital de la Santa Creu i Sant Pau
Barcelona, , Spain
Vall d'Hebron University Hospital
Barcelona, , Spain
Hospital Universitario Reina Sofia
Córdoba, , Spain
Hospital Universitario La Luz Quiron
Madrid, , Spain
Gregorio Marañón General University Hospital
Madrid, , Spain
Hospital Universitario Fundación Jiménez Díaz
Madrid, , Spain
Hospital Universitario La Paz
Madrid, , Spain
Hospital Universitario Virgen Macarena
Seville, , Spain
Luton and Dunstable University Hospital
Luton, Bedfordshire, United Kingdom
Glan Glwyd Hospital
Bodelwyddan, Denbighshire, United Kingdom
Royal Bournemouth Hospital
Bournemouth, Dorset, United Kingdom
Conquest Hospital
Brighton, East Sussex, United Kingdom
Scunthorpe General Hospital
Scunthorpe, North Lincolnshire, United Kingdom
Kettering General Hospital
Kettering, Northamptonshire, United Kingdom
Southern Health and Social Care Trust, Craigavon Area Hospital
Portadown, Northen Ireland, United Kingdom
Royal United Hospital
Bath, Somerset, United Kingdom
Freeman Hospital
Newcastle upon Tyne, Tyne and Wear, United Kingdom
North Tyneside General Hospital
North Shields, Tyne and Wear, United Kingdom
Sunderland Royal Hospital
Sunderland, Tyne and Wear, United Kingdom
Sandwell General Hospital
Birmingham, West Midlands, United Kingdom
Russell's Hall Hospital
Dudley, West Midlands, United Kingdom
Worthing Hospital
Worthing, West Sussex, United Kingdom
Calderdale Royal Hospital
Halifax, West Yorkshire, United Kingdom
Worcestershire Royal Hospital
Worcester, Worcestershire, United Kingdom
Hammersmith Hospital
London, , United Kingdom
Countries
Review the countries where the study has at least one active or historical site.
References
Explore related publications, articles, or registry entries linked to this study.
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.
Williams 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.
Mach 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.
Bohula 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.
Ference 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.
Khan 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.
Ray 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.
Ray 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.
Steen 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.
Ferrieres 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.
Arca 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.
Blaum 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.
Marz 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.
Kuiper 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.
Koskinas 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.
Allahyari 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.
Mancia 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.
Dorresteijn 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.
McKay 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.
Gao 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.
Campbell 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.
Bellamy 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.
Campbell 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.
Parker 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.
Cannon 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.
Rubin, M. When to adjust alpha during multiple testing: a consideration of disjunction, conjunction, and individual testing. Synthese 199, 10969-11000 (2021).
Ritz 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
Related Links
Access external resources that provide additional context or updates about the study.
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).
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
22HH7982
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.