From the Sunnybrook Research Institute, Holland Bone and Joint Research Program, Toronto, Ontario; McGill University, Department of Epidemiology, Biostatistics and Occupational Health; Research Institute of the McGill University Health Centre, Department of Clinical Epidemiology, and Centre for Outcomes Research and Evaluation, Montreal, Quebec; ICES; University of Toronto, Institute of Health Policy, Management and Evaluation, Toronto; McMaster University, Department of Family Medicine, Hamilton; Southlake Regional Health Centre, Department of Medicine, Newmarket; Western University, Department of Epidemiology and Biostatistics; St. Joseph's Health Care, Department of Medicine, London; Mount Sinai Hospital, Department of Medicine, Toronto, Ontario, Canada.
J. Widdifield, PhD, Sunnybrook Research Institute, Holland Bone and Joint Research Program, and McGill University, Department of Epidemiology, Biostatistics and Occupational Health, and Research Institute of the McGill University Health Centre, Department of Clinical Epidemiology, ICES, and University of Toronto, Institute of Health Policy, Management and Evaluation; M. Abrahamowicz, PhD, McGill University, Department of Epidemiology, Biostatistics and Occupational Health, and Research Institute of the McGill University Health Centre, Centre for Outcomes Research and Evaluation; J.M. Paterson, MSc, ICES, and University of Toronto, Institute of Health Policy, Management and Evaluation, and McMaster University, Department of Family Medicine; A. Huang, MSc, ICES; J.C. Thorne, MD, FRCPC, Southlake Regional Health Centre, Department of Medicine; J.E. Pope, MD, FRCPC, MPH, Western University, Department of Epidemiology and Biostatistics, and St. Joseph's Health Care, Department of Medicine; B. Kuriya, MD, FRCPC, SM, Mount Sinai Hospital, Department of Medicine; M.E. Beauchamp, PhD, Research Institute of the McGill University Health Centre, Centre for Outcomes Research and Evaluation; S. Bernatsky, MD, FRCPC, PhD, McGill University, Department of Epidemiology, Biostatistics and Occupational Health, and Research Institute of the McGill University Health Centre, Centre for Outcomes Research and Evaluation.
J Rheumatol. 2019 May;46(5):467-474. doi: 10.3899/jrheum.180427. Epub 2018 Dec 1.
We evaluated the associations between time-varying methotrexate (MTX) use and risk of cardiovascular events (CVE) in patients with rheumatoid arthritis (RA).
We studied an inception cohort of 23,994 patients with RA diagnosed after their 65th birthday. Multivariable Cox regression models were fit to evaluate the associations between time-varying MTX use, controlling for other risk factors, and time to CVE. Alternative models assessed the cumulative duration of MTX use over the (1) first year, (2) previous year (recent use), and (3) entire duration of followup. We also assessed whether the strength of the association varied over time.
Over 115,453 patient-years (PY), 3294 (13.7%) patients experienced a CVE (28.5 events per 1000 PY; 95% CI 27.6-29.5). In the multivariable analyses, the model assessing time-varying continuous use in the most recent year yielded the best fit. Increasing recent MTX use was associated with lower CVE risks (HR 0.79 for continuous use vs no use in past 12 months, 95% CI 0.70-0.88; p < 0.0001). Greater MTX use in the first year after cohort entry was also protective (HR 0.84, 95% CI 0.72-0.96; p = 0.0048), but this effect decreased with increasing followup. In contrast, longer MTX use during the entire followup was not clearly associated with CVE risk (HR 0.98, 95% CI 0.95-1.01; p = 0.1441).
We observed about a 20% decrease in CVE associated with recent continuous MTX use. Greater MTX use in the first year of cohort entry also appeared to be important in the association between MTX and CVE risk.
我们评估了类风湿关节炎(RA)患者中时间变化的甲氨蝶呤(MTX)使用与心血管事件(CVE)风险之间的关联。
我们研究了一个包含 23994 名 65 岁后确诊为 RA 的患者的发病队列。使用多变量 Cox 回归模型评估时间变化的 MTX 使用与 CVE 时间之间的关联,同时控制其他风险因素。替代模型评估了(1)第一年、(2)前一年(近期使用)和(3)整个随访期间 MTX 使用的累积持续时间。我们还评估了关联强度是否随时间变化。
在超过 115453 患者年(PY)中,有 3294 名(13.7%)患者发生了 CVE(28.5 例/1000 PY;95%CI 27.6-29.5)。在多变量分析中,评估最近一年时间变化的连续使用的模型拟合度最佳。近期 MTX 使用量增加与较低的 CVE 风险相关(连续使用与过去 12 个月无使用相比,HR 为 0.79,95%CI 0.70-0.88;p<0.0001)。队列入组后第一年 MTX 使用量增加也具有保护作用(HR 0.84,95%CI 0.72-0.96;p=0.0048),但随着随访时间的增加,这种效果降低。相比之下,整个随访期间较长时间的 MTX 使用与 CVE 风险无明显关联(HR 0.98,95%CI 0.95-1.01;p=0.1441)。
我们观察到,与近期连续 MTX 使用相关的 CVE 风险降低了约 20%。队列入组后第一年 MTX 使用量增加似乎在 MTX 与 CVE 风险之间的关联中也很重要。