Maria García-Gil1, Jordi Blanch2, Marc Comas-Cufí2, Josep Daunis-i-Estadella3, Bonaventura Bolíbar4, Ruth Martí5, Anna Ponjoan5, Lia Alves-Cabratosa2, Rafel Ramos6. 1. Institut Universitari d'Investigació en Atenció Primària Jordi Gol (IDIAP Jordi Gol), Catalunya, Spain; ISV Research Group, Research Unit in Primary Care, Primary Care Services, Girona, Spain; Catalan Institute of Health (ICS), Catalunya, Spain; TransLab Research Group, Department of Medical Sciences, School of Medicine, University of Girona, Spain. Electronic address: mgarcia@idiapjgol.info. 2. Institut Universitari d'Investigació en Atenció Primària Jordi Gol (IDIAP Jordi Gol), Catalunya, Spain; ISV Research Group, Research Unit in Primary Care, Primary Care Services, Girona, Spain; Catalan Institute of Health (ICS), Catalunya, Spain. 3. Department of Computer Sciences, Applied Mathematics and Statistics, University of Girona, Spain. 4. Institut Universitari d'Investigació en Atenció Primària Jordi Gol (IDIAP Jordi Gol), Catalunya, Spain. 5. Institut Universitari d'Investigació en Atenció Primària Jordi Gol (IDIAP Jordi Gol), Catalunya, Spain; ISV Research Group, Research Unit in Primary Care, Primary Care Services, Girona, Spain; Catalan Institute of Health (ICS), Catalunya, Spain; Biomedical Research Institute, Girona (IdIBGi), Catalunya, Spain. 6. Institut Universitari d'Investigació en Atenció Primària Jordi Gol (IDIAP Jordi Gol), Catalunya, Spain; ISV Research Group, Research Unit in Primary Care, Primary Care Services, Girona, Spain; Catalan Institute of Health (ICS), Catalunya, Spain; TransLab Research Group, Department of Medical Sciences, School of Medicine, University of Girona, Spain; Biomedical Research Institute, Girona (IdIBGi), Catalunya, Spain.
Abstract
OBJECTIVE: To describe real-life patterns of statin use and cholesterol goal attainment in a retrospective cohort of patients with high cardiovascular risk. METHODS: Retrospective cohort study of 21,636 individuals, 18.34% women, mean age 63.30 years (standard deviation 6.29). New statin users aged 35 to 74 years at high cardiovascular risk and with no previous cardiovascular disease in primary care electronic medical records (2006-2011). Patterns of statin use were based on statin type, potency, and 1-year statin switches. OUTCOMES: Relative mean reductions over 1 year and probability of goal attainment (<3.3 mmol/L). Natural patterns of statin use were identified using multiple correspondence analysis; general linear and logistic models were used to estimate low-density lipoprotein cholesterol (LDL-C) reductions and goal attainment probability. RESULTS: Three patterns of statin use were defined: low (3.82% of the population), moderate (71.94%), and high intensity (24.24%). After 1 year, potency decreased 42.74%, 64.16%, and 50.94%, respectively, and 37.41%, 29.47%, and 30.16% of the population stopped taking statins in low, moderate, and high patterns, respectively. Relative reductions in LDL-C: low intensity, 15.7% (95% confidence interval [CI]: -22.96 to 54.36); moderate intensity, 29.72% (95% CI: 29.12-30.32); and high intensity, 24.20% (95% CI: -8.08 to 40.32). There was a direct relationship between higher intensity patterns and greater probability of goal attainment. CONCLUSIONS: Three real-life patterns of statin use were identified. Lipid management strategies in primary care should focus on improving adherence to treatment. People starting at low potency should switch to a moderate pattern; more intensive therapies should be considered in who require a larger LDL-C reduction to reach therapeutic targets, patients with good treatment adherence who do not achieve the goal with a moderate pattern of therapy or patients at very high risk.
OBJECTIVE: To describe real-life patterns of statin use and cholesterol goal attainment in a retrospective cohort of patients with high cardiovascular risk. METHODS: Retrospective cohort study of 21,636 individuals, 18.34% women, mean age 63.30 years (standard deviation 6.29). New statin users aged 35 to 74 years at high cardiovascular risk and with no previous cardiovascular disease in primary care electronic medical records (2006-2011). Patterns of statin use were based on statin type, potency, and 1-year statin switches. OUTCOMES: Relative mean reductions over 1 year and probability of goal attainment (<3.3 mmol/L). Natural patterns of statin use were identified using multiple correspondence analysis; general linear and logistic models were used to estimate low-density lipoprotein cholesterol (LDL-C) reductions and goal attainment probability. RESULTS: Three patterns of statin use were defined: low (3.82% of the population), moderate (71.94%), and high intensity (24.24%). After 1 year, potency decreased 42.74%, 64.16%, and 50.94%, respectively, and 37.41%, 29.47%, and 30.16% of the population stopped taking statins in low, moderate, and high patterns, respectively. Relative reductions in LDL-C: low intensity, 15.7% (95% confidence interval [CI]: -22.96 to 54.36); moderate intensity, 29.72% (95% CI: 29.12-30.32); and high intensity, 24.20% (95% CI: -8.08 to 40.32). There was a direct relationship between higher intensity patterns and greater probability of goal attainment. CONCLUSIONS: Three real-life patterns of statin use were identified. Lipid management strategies in primary care should focus on improving adherence to treatment. People starting at low potency should switch to a moderate pattern; more intensive therapies should be considered in who require a larger LDL-C reduction to reach therapeutic targets, patients with good treatment adherence who do not achieve the goal with a moderate pattern of therapy or patients at very high risk.
Authors: Mark D Danese; Michelle Gleeson; Lucie Kutikova; Robert I Griffiths; Kamlesh Khunti; Sreenivasa Rao Kondapally Seshasai; Kausik K Ray Journal: BMJ Open Date: 2017-05-10 Impact factor: 2.692
Authors: Maria Giner-Soriano; Gerard Sotorra Figuerola; Jordi Cortés; Helena Pera Pujadas; Ana Garcia-Sangenis; Rosa Morros Journal: JMIR Res Protoc Date: 2018-03-09
Authors: Lia Alves-Cabratosa; Maria García-Gil; Marc Comas-Cufí; Anna Ponjoan; Ruth Martí-Lluch; Dídac Parramon; Jordi Blanch; Marc Elosua-Bayes; Rafel Ramos Journal: PLoS One Date: 2017-10-26 Impact factor: 3.240
Authors: Rafel Ramos; Marc Comas-Cufí; Ruth Martí-Lluch; Elisabeth Balló; Anna Ponjoan; Lia Alves-Cabratosa; Jordi Blanch; Jaume Marrugat; Roberto Elosua; María Grau; Marc Elosua-Bayes; Luis García-Ortiz; Maria Garcia-Gil Journal: BMJ Date: 2018-09-05