Dealing With Treatment-Confounder Feedback and Sparse Follow-up in Longitudinal Studies: Application of a Marginal Structural Model in a Multiple Sclerosis Cohort
| العنوان: | Dealing With Treatment-Confounder Feedback and Sparse Follow-up in Longitudinal Studies: Application of a Marginal Structural Model in a Multiple Sclerosis Cohort |
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| المؤلفون: | Helen Tremlett, Feng Zhu, Elaine Kingwell, John Petkau, Mohammad Ehsanul Karim |
| المصدر: | American Journal of Epidemiology. 190:908-917 |
| بيانات النشر: | Oxford University Press (OUP), 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | Adult, Male, Multiple Sclerosis, Epidemiology, Marginal structural model, Effect Modifier, Epidemiologic, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Bias, Humans, Medicine, Longitudinal Studies, 030212 general & internal medicine, Imputation (statistics), British Columbia, business.industry, Inverse probability weighting, Hazard ratio, Confounding, Confounding Factors, Epidemiologic, Interferon-beta, medicine.disease, Survival Analysis, Comorbidity, Confidence interval, 3. Good health, Cohort, Disease Progression, Female, business, 030217 neurology & neurosurgery, Follow-Up Studies, Demography |
| الوصف: | The beta-interferons are widely prescribed platform therapies for patients with multiple sclerosis (MS). We accessed a cohort of patients with relapsing-onset MS from British Columbia, Canada (1995–2013), to examine the potential survival advantage associated with beta-interferon exposure using a marginal structural model. Accounting for potential treatment-confounder feedback between comorbidity, MS disease progression, and beta-interferon exposure, we found an association between beta-interferon exposure of at least 6 contiguous months and improved survival (hazard ratio (HR) = 0.63, 95% confidence interval 0.47, 0.86). We also assessed potential effect modifications by sex, baseline age, or baseline disease duration, and found these factors to be important effect modifiers. Sparse follow-up due to variability in patient contact with the health system is one of the biggest challenges in longitudinal analyses. We considered several single-level and multilevel multiple imputation approaches to deal with sparse follow-up and disease progression information; both types of approach produced similar estimates. Compared to ad hoc imputation approaches, such as linear interpolation (HR = 0.63), and last observation carried forward (HR = 0.65), all multiple imputation approaches produced a smaller hazard ratio (HR = 0.53), although the direction of effect and conclusions drawn concerning the survival advantage remained the same. |
| تدمد: | 1476-6256 0002-9262 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c9e08e05f44aac991aa4b52481ab959aTest https://doi.org/10.1093/aje/kwaa243Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....c9e08e05f44aac991aa4b52481ab959a |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 14766256 00029262 |
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