Introduction: Little is known about how the development of a new chronic health condition affects management of existing chronic conditions over time. New conditions might worsen management of existing conditions because of competing demands or improve management of existing conditions because of increased engagement with heath care. We assessed the effect of incident stage 0, 1, 2 or 3 breast, colon or prostate cancer; incident depression; or an exacerbation of chronic pulmonary disease on control of type 2 diabetes (DM2).
Methods: We conducted a longitudinal, historical cohort study within an integrated, not-for-profit HMO. Of a cohort of persons with diagnoses of DM2 between 1998 and 2008, 582, 2,959 and 2,332 developed incident cancer, depression or pulmonary disease exacerbation, respectively. We assessed change in hemoglobin A1c (A1c) as a function of the occurrence of the incident comorbidity in each subcohort for a period of 1 to 5 years after the occurrence of the incident comorbidity. Secondary outcomes were systolic blood pressure (SBP) and low density lipoprotein (LDL) levels. Multivariate linear regression was adjusted for demographics, morbidity level, BMI, numbers of primary and specialty visits, and continuity of primary care. Latent class analyses assessed post-comorbidity outcome trajectories. All time-varying covariates were calculated for a 24-month pre-diagnosis period and 0 to 24- and 24 to 60-month post-diagnosis periods.
Results: For each condition, A1c did not change significantly from before to after the incident comorbidity. This was confirmed by latent class growth curve analyses that grouped patients by their A1c trajectories. SBP and LDL were also not significantly changed pre- and post-diagnosis of the incident comorbidities.
Discussion: Although incident comorbidities inevitably will affect patients' and clinicians' care priorities, we did not observe changes in these particular outcomes. Additional investigation of interactions between diseases will inform changes in care that benefit complex patient populations.