Milena A Gianfrancesco1,2, Laura Trupin3,4, Stephen Shiboski3,4, Mark van der Laan3,4, Jonathan Graf3,4, John Imboden3,4, Jinoos Yazdany3,4, Gabriela Schmajuk3,4. 1. From the Division of Rheumatology, Department of Medicine, University of California, San Francisco, California, USA. Milena.Gianfrancesco@ucsf.edu. 2. M.A. Gianfrancesco, PhD, MPH, Division of Rheumatology, Department of Medicine, University of California, San Francisco; L. Trupin, MPH, Division of Rheumatology, Department of Medicine, University of California, San Francisco; S. Shiboski, PhD, Department of Epidemiology and Biostatistics, University of California, San Francisco; M. van der Laan, PhD, Division of Biostatistics, School of Public Health, University of California, Berkeley; J. Graf, MD, Division of Rheumatology, Department of Medicine, University of California, San Francisco; J. Imboden, MD, Division of Rheumatology, Department of Medicine, University of California, San Francisco; J. Yazdany, MD, MPH, Division of Rheumatology, Department of Medicine, University of California, San Francisco; G. Schmajuk, MD, MS, Division of Rheumatology, Department of Medicine, University of California, San Francisco, and Veterans Affairs Medical Center, San Francisco, California, USA. Milena.Gianfrancesco@ucsf.edu. 3. From the Division of Rheumatology, Department of Medicine, University of California, San Francisco, California, USA. 4. M.A. Gianfrancesco, PhD, MPH, Division of Rheumatology, Department of Medicine, University of California, San Francisco; L. Trupin, MPH, Division of Rheumatology, Department of Medicine, University of California, San Francisco; S. Shiboski, PhD, Department of Epidemiology and Biostatistics, University of California, San Francisco; M. van der Laan, PhD, Division of Biostatistics, School of Public Health, University of California, Berkeley; J. Graf, MD, Division of Rheumatology, Department of Medicine, University of California, San Francisco; J. Imboden, MD, Division of Rheumatology, Department of Medicine, University of California, San Francisco; J. Yazdany, MD, MPH, Division of Rheumatology, Department of Medicine, University of California, San Francisco; G. Schmajuk, MD, MS, Division of Rheumatology, Department of Medicine, University of California, San Francisco, and Veterans Affairs Medical Center, San Francisco, California, USA.
Abstract
OBJECTIVE: Prior studies around the relationship between smoking and rheumatoid arthritis (RA) disease activity have reported inconsistent findings, which may be ascribed to heterogeneous study designs or biases in statistical analyses. We examined the association between smoking and RA outcomes using statistical methods that account for time-varying confounding and loss to followup. METHODS: We included 282 individuals with an RA diagnosis using electronic health record data collected at a public hospital between 2013 and 2017. Current smoking status and disease activity were assessed at each visit; covariates included sex, race/ethnicity, age, obesity, and medication use. We used longitudinal targeted maximum likelihood estimation to estimate the causal effect of smoking on disease activity measures at 27 months, and compared results to conventional longitudinal methods. RESULTS: Smoking was associated with an increase of 0.64 units in the patient global score compared to nonsmoking (p = 0.01), and with 2.58 more swollen joints (p < 0.001). While smoking was associated with a higher clinical disease activity score (2.11), the difference was not statistically significant (p = 0.22). We found no association between smoking and physician global score, or C-reactive protein levels, and an inverse association between smoking and tender joint count (p = 0.05). Analyses using conventional methods showed a null relationship for all outcomes. CONCLUSION: Smoking is associated with higher levels of disease activity in RA. Causal methods may be useful for investigations of additional exposures on longitudinal outcome measures in rheumatologic disease.
OBJECTIVE: Prior studies around the relationship between smoking and rheumatoid arthritis (RA) disease activity have reported inconsistent findings, which may be ascribed to heterogeneous study designs or biases in statistical analyses. We examined the association between smoking and RA outcomes using statistical methods that account for time-varying confounding and loss to followup. METHODS: We included 282 individuals with an RA diagnosis using electronic health record data collected at a public hospital between 2013 and 2017. Current smoking status and disease activity were assessed at each visit; covariates included sex, race/ethnicity, age, obesity, and medication use. We used longitudinal targeted maximum likelihood estimation to estimate the causal effect of smoking on disease activity measures at 27 months, and compared results to conventional longitudinal methods. RESULTS: Smoking was associated with an increase of 0.64 units in the patient global score compared to nonsmoking (p = 0.01), and with 2.58 more swollen joints (p < 0.001). While smoking was associated with a higher clinical disease activity score (2.11), the difference was not statistically significant (p = 0.22). We found no association between smoking and physician global score, or C-reactive protein levels, and an inverse association between smoking and tender joint count (p = 0.05). Analyses using conventional methods showed a null relationship for all outcomes. CONCLUSION: Smoking is associated with higher levels of disease activity in RA. Causal methods may be useful for investigations of additional exposures on longitudinal outcome measures in rheumatologic disease.
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