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Lu Y, Van Zandt M, Liu Y, Li J, Wang X, Chen Y, Chen Z, Cho J, Dorajoo SR, Feng M, Hsu MH, Hsu JC, Iqbal U, Jonnagaddala J, Li YC, Liaw ST, Lim HS, Ngiam KY, Nguyen PA, Park RW, Pratt N, Reich C, Rhee SY, Sathappan SMK, Shin SJ, Tan HX, You SC, Zhang X, Krumholz HM, Suchard MA, Xu H. Analysis of Dual Combination Therapies Used in Treatment of Hypertension in a Multinational Cohort. JAMA Netw Open 2022; 5:e223877. [PMID: 35323951 PMCID: PMC8948532 DOI: 10.1001/jamanetworkopen.2022.3877] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
IMPORTANCE More than 1 billion adults have hypertension globally, of whom 70% cannot achieve their hypertension control goal with monotherapy alone. Data are lacking on clinical use patterns of dual combination therapies prescribed to patients who escalate from monotherapy. OBJECTIVE To investigate the most common dual combinations prescribed for treatment escalation in different countries and how treatment use varies by age, sex, and history of cardiovascular disease. DESIGN, SETTING, AND PARTICIPANTS This cohort study used data from 11 electronic health record databases that cover 118 million patients across 8 countries and regions between January 2000 and December 2019. Included participants were adult patients (ages ≥18 years) who newly initiated antihypertensive dual combination therapy after escalating from monotherapy. There were 2 databases included for 3 countries: the Iqvia Longitudinal Patient Database (LPD) Australia and Electronic Practice-based Research Network 2019 linked data set from South Western Sydney Local Health District (ePBRN SWSLHD) from Australia, Ajou University School of Medicine (AUSOM) and Kyung Hee University Hospital (KHMC) databases from South Korea, and Khoo Teck Puat Hospital (KTPH) and National University Hospital (NUH) databases from Singapore. Data were analyzed from June 2020 through August 2021. EXPOSURES Treatment with dual combinations of the 4 most commonly used antihypertensive drug classes (angiotensin-converting enzyme inhibitor [ACEI] or angiotensin receptor blocker [ARB]; calcium channel blocker [CCB]; β-blocker; and thiazide or thiazide-like diuretic). MAIN OUTCOMES AND MEASURES The proportion of patients receiving each dual combination regimen, overall and by country and demographic subgroup. RESULTS Among 970 335 patients with hypertension who newly initiated dual combination therapy included in the final analysis, there were 11 494 patients from Australia (including 9291 patients in Australia LPD and 2203 patients in ePBRN SWSLHD), 6980 patients from South Korea (including 6029 patients in Ajou University and 951 patients in KHMC), 2096 patients from Singapore (including 842 patients in KTPH and 1254 patients in NUH), 7008 patients from China, 8544 patients from Taiwan, 103 994 patients from France, 76 082 patients from Italy, and 754 137 patients from the US. The mean (SD) age ranged from 57.6 (14.8) years in China to 67.7 (15.9) years in the Singapore KTPH database, and the proportion of patients by sex ranged from 24 358 (36.9%) women in Italy to 408 964 (54.3%) women in the US. Among 12 dual combinations of antihypertensive drug classes commonly used, there were significant variations in use across country and patient subgroup. For example starting an ACEI or ARB monotherapy followed by a CCB (ie, ACEI or ARB + CCB) was the most commonly prescribed combination in Australia (698 patients in ePBRN SWSLHD [31.7%] and 3842 patients in Australia LPD [41.4%]) and Singapore (216 patients in KTPH [25.7%] and 439 patients in NUH [35.0%]), while in South Korea, CCB + ACEI or ARB (191 patients in KHMC [20.1%] and 1487 patients in Ajou University [24.7%]), CCB + β-blocker (814 patients in Ajou University [13.5%] and 217 patients in KHMC [22.8%]), and ACEI or ARB + CCB (147 patients in KHMC [15.5%] and 1216 patients in Ajou University [20.2%]) were the 3 most commonly prescribed combinations. The distribution of 12 dual combination therapies were significantly different by age and sex in almost all databases. For example, use of ACEI or ARB + CCB varied from 873 of 3737 patients ages 18 to 64 years (23.4%) to 343 of 2292 patients ages 65 years or older (15.0%) in South Korea's Ajou University database (P for database distribution by age < .001), while use of ACEI or ARB + CCB varied from 2121 of 4718 (44.8%) men to 1721 of 4549 (37.7%) women in Australian LPD (P for drug combination distributions by sex < .001). CONCLUSIONS AND RELEVANCE In this study, large variation in the transition between monotherapy and dual combination therapy for hypertension was observed across countries and by demographic group. These findings suggest that future research may be needed to investigate what dual combinations are associated with best outcomes for which patients.
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Affiliation(s)
- Yuan Lu
- Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, Connecticut
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
| | | | - Yun Liu
- School of Biomedical Engineering and Informatics, Department of Medical Informatics, Nanjing Medical University, Jiangsu, China
| | - Jing Li
- Real World Solutions, Iqvia, Durham, North Carolina
| | - Xialin Wang
- Real World Solutions, Iqvia, Durham, North Carolina
| | - Yong Chen
- Perelman School of Medicine, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania
| | - Zhengfeng Chen
- National University Heart Center, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Jaehyeong Cho
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Republic of Korea
| | | | - Mengling Feng
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
- Institute of Data Science, National University of Singapore, Singapore
| | | | - Jason C. Hsu
- International PhD Program in Biotech and Healthcare Management, College of Management, Taipei Medical University, Taipei, Taiwan
| | - Usman Iqbal
- International Center for Health Information Technology, Taipei Medical University, Taipei City, Taiwan
| | - Jitendra Jonnagaddala
- World Health Organization Collaborating Center on eHealth, School of Population Health, University of New South Wales Sydney, Australia
| | - Yu-Chuan Li
- Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei City, Taiwan
| | - Siaw-Teng Liaw
- World Health Organization Collaborating Center on eHealth, School of Population Health, University of New South Wales Sydney, Australia
| | - Hong-Seok Lim
- Department of Cardiology, Ajou University School of Medicine, Suwon, Republic of Korea
| | - Kee Yuan Ngiam
- Group Chief Technology Office, National University Health System, Singapore
| | - Phung-Anh Nguyen
- International Center for Health Information Technology, Taipei Medical University, Taipei, Taiwan
- School of Health Technology, Taiwan Department of Healthcare Information and Management, Ming Chuan University, Taipei, Taiwan
| | - Rae Woong Park
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Republic of Korea
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Republic of Korea
| | - Nicole Pratt
- Quality Use of Medicines and Pharmacy Research Center, Clinical and Health Sciences, University of South Australia, Adelaide, Australia
| | | | - Sang Youl Rhee
- Kyung Hee University Medical Center, Seoul, Republic of Korea
| | - Selva Muthu Kumaran Sathappan
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
- National University of Singapore, Singapore
| | - Seo Jeong Shin
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Republic of Korea
| | | | - Seng Chan You
- Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Xin Zhang
- School of Biomedical Engineering and Informatics, Department of Medical Informatics, Nanjing Medical University, Jiangsu, China
| | - Harlan M. Krumholz
- Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, Connecticut
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
- Department of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut
| | - Marc A. Suchard
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles
| | - Hua Xu
- University of Texas Health Science Center at Houston, Houston
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Lane JCE, Weaver J, Kostka K, Duarte-Salles T, Abrahao MTF, Alghoul H, Alser O, Alshammari TM, Biedermann P, Banda JM, Burn E, Casajust P, Conover MM, Culhane AC, Davydov A, DuVall SL, Dymshyts D, Fernandez-Bertolin S, Fišter K, Hardin J, Hester L, Hripcsak G, Kaas-Hansen BS, Kent S, Khosla S, Kolovos S, Lambert CG, van der Lei J, Lynch KE, Makadia R, Margulis AV, Matheny ME, Mehta P, Morales DR, Morgan-Stewart H, Mosseveld M, Newby D, Nyberg F, Ostropolets A, Park RW, Prats-Uribe A, Rao GA, Reich C, Reps J, Rijnbeek P, Sathappan SMK, Schuemie M, Seager S, Sena AG, Shoaibi A, Spotnitz M, Suchard MA, Torre CO, Vizcaya D, Wen H, de Wilde M, Xie J, You SC, Zhang L, Zhuk O, Ryan P, Prieto-Alhambra D. Risk of hydroxychloroquine alone and in combination with azithromycin in the treatment of rheumatoid arthritis: a multinational, retrospective study. Lancet Rheumatol 2020; 2:e698-e711. [PMID: 32864627 PMCID: PMC7442425 DOI: 10.1016/s2665-9913(20)30276-9] [Citation(s) in RCA: 89] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Background Hydroxychloroquine, a drug commonly used in the treatment of rheumatoid arthritis, has received much negative publicity for adverse events associated with its authorisation for emergency use to treat patients with COVID-19 pneumonia. We studied the safety of hydroxychloroquine, alone and in combination with azithromycin, to determine the risk associated with its use in routine care in patients with rheumatoid arthritis. Methods In this multinational, retrospective study, new user cohort studies in patients with rheumatoid arthritis aged 18 years or older and initiating hydroxychloroquine were compared with those initiating sulfasalazine and followed up over 30 days, with 16 severe adverse events studied. Self-controlled case series were done to further establish safety in wider populations, and included all users of hydroxychloroquine regardless of rheumatoid arthritis status or indication. Separately, severe adverse events associated with hydroxychloroquine plus azithromycin (compared with hydroxychloroquine plus amoxicillin) were studied. Data comprised 14 sources of claims data or electronic medical records from Germany, Japan, the Netherlands, Spain, the UK, and the USA. Propensity score stratification and calibration using negative control outcomes were used to address confounding. Cox models were fitted to estimate calibrated hazard ratios (HRs) according to drug use. Estimates were pooled where the I 2 value was less than 0·4. Findings The study included 956 374 users of hydroxychloroquine, 310 350 users of sulfasalazine, 323 122 users of hydroxychloroquine plus azithromycin, and 351 956 users of hydroxychloroquine plus amoxicillin. No excess risk of severe adverse events was identified when 30-day hydroxychloroquine and sulfasalazine use were compared. Self-controlled case series confirmed these findings. However, long-term use of hydroxychloroquine appeared to be associated with increased cardiovascular mortality (calibrated HR 1·65 [95% CI 1·12-2·44]). Addition of azithromycin appeared to be associated with an increased risk of 30-day cardiovascular mortality (calibrated HR 2·19 [95% CI 1·22-3·95]), chest pain or angina (1·15 [1·05-1·26]), and heart failure (1·22 [1·02-1·45]). Interpretation Hydroxychloroquine treatment appears to have no increased risk in the short term among patients with rheumatoid arthritis, but in the long term it appears to be associated with excess cardiovascular mortality. The addition of azithromycin increases the risk of heart failure and cardiovascular mortality even in the short term. We call for careful consideration of the benefit-risk trade-off when counselling those on hydroxychloroquine treatment. Funding National Institute for Health Research (NIHR) Oxford Biomedical Research Centre, NIHR Senior Research Fellowship programme, US National Institutes of Health, US Department of Veterans Affairs, Janssen Research and Development, IQVIA, Korea Health Industry Development Institute through the Ministry of Health and Welfare Republic of Korea, Versus Arthritis, UK Medical Research Council Doctoral Training Partnership, Foundation Alfonso Martin Escudero, Innovation Fund Denmark, Novo Nordisk Foundation, Singapore Ministry of Health's National Medical Research Council Open Fund Large Collaborative Grant, VINCI, Innovative Medicines Initiative 2 Joint Undertaking, EU's Horizon 2020 research and innovation programme, and European Federation of Pharmaceutical Industries and Associations.
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Affiliation(s)
- Jennifer C E Lane
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - James Weaver
- Janssen Research and Development, Titusville, NJ, USA
| | | | - Talita Duarte-Salles
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | | | - Heba Alghoul
- Faculty of Medicine, Islamic University of Gaza, Palestine
| | - Osaid Alser
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Thamir M Alshammari
- Medication Safety Research Chair, King Saud University, Riyadh, Saudi Arabia
| | | | - Juan M Banda
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
| | - Edward Burn
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford, UK.,Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Paula Casajust
- Real-World Evidence, Trial Form Support, Barcelona, Spain
| | | | - Aedin C Culhane
- Department of Data Sciences, Dana-Farber Cancer Institute, Department of Biostatistics, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Alexander Davydov
- Medical Ontology Solutions, Odysseus Data Services, Cambridge MA, USA
| | - Scott L DuVall
- Western Institute for Biomedical Research, Department of Veterans Affairs, Salt Lake City, UT, USA.,Department of Internal Medicine, Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Dmitry Dymshyts
- Medical Ontology Solutions, Odysseus Data Services, Cambridge MA, USA
| | - Sergio Fernandez-Bertolin
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Kristina Fišter
- School of Medicine, Andrija Štampar School of Public Health, University of Zagreb, Zagreb, Croatia
| | - Jill Hardin
- Janssen Research and Development, Titusville, NJ, USA
| | - Laura Hester
- Janssen Research and Development, Titusville, NJ, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA.,New York-Presbyterian Hospital, New York, NY, USA
| | - Benjamin Skov Kaas-Hansen
- Clinical Pharmacology Unit, Zealand University Hospital, Roskilde, Denmark.,NNF Centre for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Seamus Kent
- National Institute for Health and Care Excellence, London, UK
| | - Sajan Khosla
- Real World Science and Digital, AstraZeneca, Cambridge, UK
| | - Spyros Kolovos
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Christophe G Lambert
- Department of Internal Medicine, Center for Global Health and Division of Translational Informatics, Albuquerque, NM, USA
| | - Johan van der Lei
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Kristine E Lynch
- Western Institute for Biomedical Research, Department of Veterans Affairs, Salt Lake City, UT, USA.,Department of Internal Medicine, Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Rupa Makadia
- Janssen Research and Development, Titusville, NJ, USA
| | | | - Michael E Matheny
- Geriatrics Research Education and Clinical Care Center, Tennessee Valley Healthcare System VA, Nashville, TN, USA.,Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Paras Mehta
- College of Medicine, University of Arizona, Tucson, AZ, USA
| | - Daniel R Morales
- Division of Population Health and Genomics, University of Dundee, UK
| | | | - Mees Mosseveld
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Danielle Newby
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK
| | - Fredrik Nyberg
- School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Anna Ostropolets
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Rae Woong Park
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon-si Gyeonggi-do, South Korea
| | - Albert Prats-Uribe
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Gowtham A Rao
- Janssen Research and Development, Titusville, NJ, USA
| | | | - Jenna Reps
- Janssen Research and Development, Titusville, NJ, USA
| | - Peter Rijnbeek
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | | | | | | | - Anthony G Sena
- Janssen Research and Development, Titusville, NJ, USA.,Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Azza Shoaibi
- Janssen Research and Development, Titusville, NJ, USA
| | - Matthew Spotnitz
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Marc A Suchard
- Department of Biomathematics and Department of Human Genetics, David Geffen School of Medicine at UCLA, and Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, CA, USA
| | | | | | - Haini Wen
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Marcel de Wilde
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Junqing Xie
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Seng Chan You
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon-si Gyeonggi-do, South Korea
| | - Lin Zhang
- School of Population Medicine and Public Health, Peking Union Medical College/Chinese Academy of Medical Sciences, Beijing, China.,Melbourne School of Population and Global Health, University of Melbourne, VIC, Australia
| | - Oleg Zhuk
- Medical Ontology Solutions, Odysseus Data Services, Cambridge MA, USA
| | - Patrick Ryan
- Janssen Research and Development, Titusville, NJ, USA.,Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Daniel Prieto-Alhambra
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford, UK.,Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
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