OBJECTIVE: Research in immune-mediated inflammatory disorders (IMIDs) suggests that several diseases share disruptions in key cytokines. A common pathogenesis may present as similar patterns of disease co-occurrence and comorbidity, which could be observed through the analysis of healthcare claims datasets. METHODS: Adult patients continuously enrolled from 2001-2002 were identified in two US healthcare datasets containing medical and drug claims from health plans and self-insured employers. Patients with treatment records indicating an IMID were selected (e.g., rheumatoid arthritis, psoriasis, Crohn's disease); controls for each disorder were matched 3:1 based on age, gender, region, and previous insurance coverage. IMID cohorts and comorbidities were identified using International Classification of Diseases, 9th revision codes. Prevalence relative risk was used to assess co-occurrence and comorbidity rates in IMID cohorts and controls. Medical and drug utilization patterns were also explored. RESULTS: Findings were similar across the two datasets. IMID patients represented about 4% of the population; specific IMID prevalence matched the epidemiology literature. Patients with at least one IMID had a higher risk for another IMID when compared to controls. The risk for infectious, renal, liver, and ulcerative comorbidities was also elevated. Selected drug utilization patterns confirmed comorbidity findings. IMID patients used more healthcare resources compared to controls; findings were robust under sensitivity analyses. CONCLUSIONS: IMID patients were generally more likely than controls to have another IMID, supporting the concept that the diseases are related. These patients also had higher comorbidity rates. Findings may be limited by the nature of claims datasets and the confounding effect of current treatments. Prospective studies are needed to determine whether IMIDs have a common pathogenesis.
OBJECTIVE: Research in immune-mediated inflammatory disorders (IMIDs) suggests that several diseases share disruptions in key cytokines. A common pathogenesis may present as similar patterns of disease co-occurrence and comorbidity, which could be observed through the analysis of healthcare claims datasets. METHODS: Adult patients continuously enrolled from 2001-2002 were identified in two US healthcare datasets containing medical and drug claims from health plans and self-insured employers. Patients with treatment records indicating an IMID were selected (e.g., rheumatoid arthritis, psoriasis, Crohn's disease); controls for each disorder were matched 3:1 based on age, gender, region, and previous insurance coverage. IMID cohorts and comorbidities were identified using International Classification of Diseases, 9th revision codes. Prevalence relative risk was used to assess co-occurrence and comorbidity rates in IMID cohorts and controls. Medical and drug utilization patterns were also explored. RESULTS: Findings were similar across the two datasets. IMID patients represented about 4% of the population; specific IMID prevalence matched the epidemiology literature. Patients with at least one IMID had a higher risk for another IMID when compared to controls. The risk for infectious, renal, liver, and ulcerative comorbidities was also elevated. Selected drug utilization patterns confirmed comorbidity findings. IMID patients used more healthcare resources compared to controls; findings were robust under sensitivity analyses. CONCLUSIONS: IMID patients were generally more likely than controls to have another IMID, supporting the concept that the diseases are related. These patients also had higher comorbidity rates. Findings may be limited by the nature of claims datasets and the confounding effect of current treatments. Prospective studies are needed to determine whether IMIDs have a common pathogenesis.
Authors: Raghda Ghonimy Elsheikh; Tarek El-Sayed Amin; Amal Ahmad El-Ashmawy; Samah Ibrahim Abd El-Fttah Abdalla Journal: J Saudi Heart Assoc Date: 2013-12-18
Authors: Alexa B Kimball; Dafna Gladman; Joel M Gelfand; Kenneth Gordon; Elizabeth J Horn; Neil J Korman; Gretchen Korver; Gerald G Krueger; Bruce E Strober; Mark G Lebwohl Journal: J Am Acad Dermatol Date: 2008-03-04 Impact factor: 11.527
Authors: Maryam M Asgari; Jashin J Wu; Joel M Gelfand; Craig Salman; Jeffrey R Curtis; Leslie R Harrold; Lisa J Herrinton Journal: Pharmacoepidemiol Drug Saf Date: 2013-05-02 Impact factor: 2.890