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      Casual effect of methotrexate+etanercept/infliximab on survival of patients with rheumatoid arthritis

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          Abstract

          Background and objectives: Following the discovery of new drugs, physicians and pharmaceutical companies have become interested in examining patients’ mortality and morbidity rates. In this respect, the effects of methotrexate (MTX)+etanercept/infliximab (ETA/INF) therapy on the survival of rheumatoid arthritis patients (RA) were evaluated in this study using marginal structural piecewise constant baseline hazard model.

          Patients and methods: According to the standard protocol, MTX is considered as the first-line treatment for RA patients. If there is no adequate response to MTX, biologic drugs will be added. To compare the survival rates of RA patients in MTX- and MTX+ETA/INF-treated groups, the piecewise constant baseline hazard model was fitted. Then, due to the existence of the time-dependent confounder (VAS) which was affected by previous treatment, the weight for each person-time was calculated via the inverse probability treatment weighting method. These weights were then used by marginal structural piecewise constant baseline hazard model. Finally, these models were compared.

          Results: The median (IQR) of the follow-up period in patients receiving MTX+ETN/INF and MTX was 11 (15.25) and 11 (31), respectively, and the 8-year survival rate was reported by 70% versus 68%, respectively. First, the piece-wise constant baseline hazard model was fitted. Fitting the given model showed that MTX+ETA/INF had a significant effect on patients’ survival (HR=0.789, 95% CI [0.634, 0.983]). Second, marginal structural piecewise constant baseline hazard model was fitted. But, the results of this model revealed that MTX+ETA/INF did not have a significant impact on patients’ survival (HR=0.968, 95% CI [0.860, 1.090]).

          Conclusion: Adjusting the pain score over time as a time-dependent confounder via marginal structural piecewise constant baseline hazard model, it has been demonstrated that MTX+ETA/INF does not have a significant effect on patients’ survival rates. Therefore, a significant difference can be found between survival rates of these groups using longitudinal studies.

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          Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men.

          Standard methods for survival analysis, such as the time-dependent Cox model, may produce biased effect estimates when there exist time-dependent confounders that are themselves affected by previous treatment or exposure. Marginal structural models are a new class of causal models the parameters of which are estimated through inverse-probability-of-treatment weighting; these models allow for appropriate adjustment for confounding. We describe the marginal structural Cox proportional hazards model and use it to estimate the causal effect of zidovudine on the survival of human immunodeficiency virus-positive men participating in the Multicenter AIDS Cohort Study. In this study, CD4 lymphocyte count is both a time-dependent confounder of the causal effect of zidovudine on survival and is affected by past zidovudine treatment. The crude mortality rate ratio (95% confidence interval) for zidovudine was 3.6 (3.0-4.3), which reflects the presence of confounding. After controlling for baseline CD4 count and other baseline covariates using standard methods, the mortality rate ratio decreased to 2.3 (1.9-2.8). Using a marginal structural Cox model to control further for time-dependent confounding due to CD4 count and other time-dependent covariates, the mortality rate ratio was 0.7 (95% conservative confidence interval = 0.6-1.0). We compare marginal structural models with previously proposed causal methods.
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            Handling time varying confounding in observational research

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              Marginal Structural Models to Estimate the Joint Causal Effect of Nonrandomized Treatments

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                Author and article information

                Journal
                Pragmat Obs Res
                Pragmat Obs Res
                POR
                por
                Pragmatic and Observational Research
                Dove
                1179-7266
                18 April 2019
                2019
                : 10
                : 23-28
                Affiliations
                [1 ]Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences , Tehran, Iran
                [2 ]Rheumatic Diseases Research Center (RDRC), Mashhad University of Medical Sciences , Mashhad, Iran
                Author notes
                Correspondence: Hojjat ZeraatiDepartment of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences , Pour sina street, Tehran1417613151, IranTel +98 216 649 9713Fax +98 216 649 5936Email zeraatih@ 123456tums.ac.ir
                Article
                194408
                10.2147/POR.S194408
                6503221
                df49d07c-aca5-445a-b5e4-4543d60d4e21
                © 2019 Akhlaghi et al.

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                History
                : 15 November 2018
                : 23 January 2019
                Page count
                Figures: 1, Tables: 2, References: 30, Pages: 6
                Categories
                Original Research

                survival,biologics,iptw,propensity score,time-dependent confounder,marginal structural models,piece-wise constant baseline hazard model

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