Martin Bahls1,2, Matthias W Lorenz3, Marcus Dörr1,2, Lu Gao4, Kazuo Kitagawa5, Tomi-Pekka Tuomainen6, Stefan Agewall7,8, Gerald Berenson9, Alberico L Catapano10,11, Giuseppe D Norata11,12, Michiel L Bots13, Wiek van Gilst14, Folkert W Asselbergs15,16,17, Frank P Brouwers18, Heiko Uthoff19, Dirk Sander20, Holger Poppert21, Michael Hecht Olsen22, Jean Philippe Empana23, Ulf Schminke24, Damiano Baldassarre25,26, Fabrizio Veglia25, Oscar H Franco27,28, Maryam Kavousi27, Eric de Groot29, Ellisiv B Mathiesen30,31, Liliana Grigore32, Joseph F Polak33, Tatjana Rundek34, Coen DA Stehouwer35, Michael R Skilton36, Apostolos I Hatzitolios37, Christos Savopoulos37, George Ntaios38, Matthieu Plichart32,39, Stela McLachlan40, Lars Lind41, Peter Willeit42,43, Helmuth Steinmetz3, Moise Desvarieux44,45, M Arfan Ikram27,46,47, Stein Harald Johnsen30,31, Caroline Schmidt48, Johann Willeit42, Pierre Ducimetiere49, Jackie F Price40, Göran Bergström48,50, Jussi Kauhanen6, Stefan Kiechl42, Matthias Sitzer3,51, Horst Bickel52, Ralph L Sacco34, Albert Hofman27,53, Henry Völzke2,54, Simon G Thompson43. 1. Department of Internal Medicine B, University Medicine Greifswald, Germany. 2. German Centre for Cardiovascular Research (DZHK), partner site Greifswald, Germany. 3. Department of Neurology, Goethe University, Frankfurt am Main, Germany. 4. MRC Biostatistics Unit, Institute of Public Health, University Forvie Site, University of Cambridge, UK. 5. Department of Neurology, Tokyo Women's Medical University, Tokyo, Japan. 6. Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio Campus, Kuopio, Finland. 7. Institute of Clinical Sciences, University of Oslo, Oslo, Norway. 8. Department of Cardiology, Oslo University Hospital Ullevål, Ullevål, Oslo, Norway. 9. Department of Medicine, Pediatrics, Biochemistry, Epidemiology, Tulane University School of Medicine and School of Public Health and Tropical Medicine, New Orleans, USA. 10. IRCSS Multimedica, Milan, Italy. 11. Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy. 12. SISA Center for the Study of Atherosclerosis, Bassini Hospital, Italy. 13. Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands. 14. Department of Experimental Cardiology, University Medical Center Groningen, The Netherlands. 15. Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands. 16. Institute of Cardiovascular Science, University College London, London, UK. 17. Health Data Research UK and Institute of Health Informatics, University College London, London, UK. 18. Department of Cardiology, University Medical Center Groningen, Groningen, The Netherlands. 19. Department of Angiology, University Hospital Basel, Basel, Switzerland. 20. Department of Neurology, Benedictus Hospital Tutzing, Tutzing, Germany. 21. Department of Neurology, Technical University Munich, Munich, Germany. 22. Department of Internal Medicine, Holbaek Hospital and Institute of Regional Health Research, University of Southern Denmark, Denmark. 23. Université de Paris, INSERM U970, Paris Cardiovascular Research Centre, Paris, France. 24. Department of Neurology, University Medicine Greifswald, Greifswald, Germany. 25. Centro Cardiologico Monzino, IRCCS, Milan, Italy. 26. Department of Medical Biotechnology and Translational Medicine, Università di Milano, Milan, Italy. 27. Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands. 28. Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland. 29. Imagelabonline and Cardiovascular, Erichem, The Netherlands. 30. Department of Clinical Medicine, UiT The Arctic University of Norway, Tromsø, Norway. 31. Department of Neurology, University Hospital of North Norway, Tromsø, Norway. 32. Centro Sisa per lo Studio della Aterosclerosi, Bassini Hospital, Cinisello Balsamo, Italy. 33. Tufts University School of Medicine, Tufts Medical Center, Boston, USA. 34. Department of Neurology, Miller School of Medicine, University of Miami, Miami, USA. 35. Department of Internal Medicine and Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Centre, Maastricht, The Netherlands. 36. The Boden Collaboration for Obesity, Nutrition, Exercise and Eating Disorders, The University of Sydney, Sydney, Australia. 37. Propedeutic Department of Internal Medicine, Aristotle University of Thessaloniki - AHEPA Hospital, Greece. 38. Department of Internal Medicine, Faculty of Medicine, School of Health Sciences, University of Thessaly, Larissa, Greece. 39. Assistance Publique, Hôpitaux de Paris, Hôpital Broca, Paris, France. 40. Usher Institute, University of Edinburgh, Edinburgh, UK. 41. Department of Medicine, Uppsala University, Uppsala, Sweden. 42. Department of Neurology, Medical University Innsbruck, Innsbruck, Austria. 43. Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, UK. 44. Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, USA. 45. METHODS Core, Centre de Recherche Epidémiologie et Statistique Paris Sorbonne Cité (CRESS), Institut National de la Santé et de la Recherche Médicale (INSERM) UMR 1153, Paris, France. 46. Department of Neurology, Erasmus University Medical Center, Rotterdam, The Netherlands. 47. Department of Radiology, Erasmus University Medical Center, Rotterdam, The Netherlands. 48. Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, Gothenburg, Sweden. 49. University Paris Sud Xi, Kremlin-Bicêtre, Le Kremlin-Bicêtre, France. 50. Region Västra Götaland, Sahlgrenska University Hospital, Clinical Physiology, Gothenburg, Sweden. 51. Department of Neurology, Klinikum Herford, Herford, Germany. 52. Department of Psychiatry and Psychotherapy, Technische Universität München, Munich, Germany. 53. Department of Epidemiology | Harvard T.H. Chan School of Public Health, Boston, MA, USA. 54. Institute for Community Medicine, SHIP/Clinical-Epidemiological Research, University Medicine Greifswald, Greifswald, Germany.
Abstract
AIMS: Averaged measurements, but not the progression based on multiple assessments of carotid intima-media thickness, (cIMT) are predictive of cardiovascular disease (CVD) events in individuals. Whether this is true for conventional risk factors is unclear. METHODS AND RESULTS: An individual participant meta-analysis was used to associate the annualised progression of systolic blood pressure, total cholesterol, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol with future cardiovascular disease risk in 13 prospective cohort studies of the PROG-IMT collaboration (n = 34,072). Follow-up data included information on a combined cardiovascular disease endpoint of myocardial infarction, stroke, or vascular death. In secondary analyses, annualised progression was replaced with average. Log hazard ratios per standard deviation difference were pooled across studies by a random effects meta-analysis. In primary analysis, the annualised progression of total cholesterol was marginally related to a higher cardiovascular disease risk (hazard ratio (HR) 1.04, 95% confidence interval (CI) 1.00 to 1.07). The annualised progression of systolic blood pressure, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol was not associated with future cardiovascular disease risk. In secondary analysis, average systolic blood pressure (HR 1.20 95% CI 1.11 to 1.29) and low-density lipoprotein cholesterol (HR 1.09, 95% CI 1.02 to 1.16) were related to a greater, while high-density lipoprotein cholesterol (HR 0.92, 95% CI 0.88 to 0.97) was related to a lower risk of future cardiovascular disease events. CONCLUSION: Averaged measurements of systolic blood pressure, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol displayed significant linear relationships with the risk of future cardiovascular disease events. However, there was no clear association between the annualised progression of these conventional risk factors in individuals with the risk of future clinical endpoints.
AIMS: Averaged measurements, but not the progression based on multiple assessments of carotid intima-media thickness, (cIMT) are predictive of cardiovascular disease (CVD) events in individuals. Whether this is true for conventional risk factors is unclear. METHODS AND RESULTS: An individual participant meta-analysis was used to associate the annualised progression of systolic blood pressure, total cholesterol, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol with future cardiovascular disease risk in 13 prospective cohort studies of the PROG-IMT collaboration (n = 34,072). Follow-up data included information on a combined cardiovascular disease endpoint of myocardial infarction, stroke, or vascular death. In secondary analyses, annualised progression was replaced with average. Log hazard ratios per standard deviation difference were pooled across studies by a random effects meta-analysis. In primary analysis, the annualised progression of total cholesterol was marginally related to a higher cardiovascular disease risk (hazard ratio (HR) 1.04, 95% confidence interval (CI) 1.00 to 1.07). The annualised progression of systolic blood pressure, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol was not associated with future cardiovascular disease risk. In secondary analysis, average systolic blood pressure (HR 1.20 95% CI 1.11 to 1.29) and low-density lipoprotein cholesterol (HR 1.09, 95% CI 1.02 to 1.16) were related to a greater, while high-density lipoprotein cholesterol (HR 0.92, 95% CI 0.88 to 0.97) was related to a lower risk of future cardiovascular disease events. CONCLUSION: Averaged measurements of systolic blood pressure, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol displayed significant linear relationships with the risk of future cardiovascular disease events. However, there was no clear association between the annualised progression of these conventional risk factors in individuals with the risk of future clinical endpoints.
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