Dataset Information

Smoking Is Associated with Higher Disease Activity in Rheumatoid Arthritis: A Longitudinal Study Controlling for Time-varying Covariates.

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.

SUBMITTER: Gianfrancesco MA

PROVIDER: S-EPMC6445683 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Smoking Is Associated with Higher Disease Activity in Rheumatoid Arthritis: A Longitudinal Study Controlling for Time-varying Covariates.

Gianfrancesco Milena A MA Trupin Laura L Shiboski Stephen S van der Laan Mark M Graf Jonathan J Imboden John J Yazdany Jinoos J Schmajuk Gabriela G

The Journal of rheumatology 20181201 4

<h4>Objective</h4>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.<h4>Methods</h4>We included 282 individuals with an RA diagnosis using electronic health record data collec ...[more]

PMID: 30504507

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Project description:ObjectiveInsufficient engagement is a critical barrier impacting the utility of digital interventions and mobile health assessments. As a result, engagement itself is increasingly becoming a target of studies and interventions. The purpose of this study is to investigate the dynamics of engagement in mobile health data collection by exploring whether, how, and why response to digital self-report prompts change over time in smoking cessation studies.MethodData from two ecological momentary assessment (EMA) studies of smoking cessation among diverse smokers attempting to quit (N = 573) with a total of 65,974 digital self-report prompts. We operationalize engagement with self-reporting in term of prompts delivered and prompt response to capture both broad and more granular engagement in self-reporting, respectively. The data were analyzed to describe trends in prompt delivered and prompt response over time. Time-varying effect modeling (TVEM) was employed to investigate the time-varying effects of response to previous prompt and the average response rate on the likelihood of current prompt response.ResultsAlthough prompt response rates were relatively stable over days in both studies, the proportion of participants with prompts delivered declined steadily over time in one of the studies, indicating that over time, fewer participants charged the device and kept it turned on (necessary to receive at least one prompt per day). Among those who did receive prompts, response rates were relatively stable. In both studies, there is a significant, positive and stable relationship between response to previous prompt and the likelihood of response to current prompt throughout all days of the study. The relationship between the average response rate prior to current prompt and the likelihood of responding to the current prompt was also positive, and increasing with time.ConclusionOur study highlights the importance of integrating various indicators to measure engagement in digital self-reporting. Both average response rate and response to previous prompt were highly predictive of response to the next prompt across days in the study. Dynamic patterns of engagement in digital self-reporting can inform the design of new strategies to promote and optimize engagement in digital interventions and mobile health studies.

Dataset Information

Smoking Is Associated with Higher Disease Activity in Rheumatoid Arthritis: A Longitudinal Study Controlling for Time-varying Covariates.

Publications

Smoking Is Associated with Higher Disease Activity in Rheumatoid Arthritis: A Longitudinal Study Controlling for Time-varying Covariates.

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