The Effect of Incident Cancer, Depression and Pulmonary Disease Exacerbations on Type 2 Diabetes Control

Abstract

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.

Chronic Obstructive Pulmonary Disease and Diabetes Mellitus: A Systematic Review of the Literature

“…Interestingly, these mice developed impaired glucose tolerance over time, supporting a direct link between pulmonary inflammation and diabetes. Nevertheless, exposure to inflammation occurring during AECOPD has not been found to have effects on long-term glycemic control in patients with T2DM [75]. Therefore, future studies on the role of inflammation in the pathogenesis of diabetes should expand our understanding of the potential interaction of inflammatory processes that occur during COPD as well as the development and progression of diabetes.…”

Glycaemic control in people with type 2 diabetes mellitus during and after cancer treatment: A systematic review and meta-analysis

“…Papers described as being of moderate quality failed to provide sufficient detail on the patients’ cancer such as type and stage [30,35], details of how patients were selected and why [35], how missing data was dealt with [30], or did not appropriately deal with confounding variables [31]. …”

“…An explanation for this may be that little attention is paid to glycaemic control by cancer health professionals and/or poorer self-management by the patients themselves when also burdened with the added responsibilities and strains associated with other competing chronic conditions [30] including cancer self-management [13], however evidence to support this is extremely limited. It is also possible that there is a lack of integrated care and competing care priorities but again, evidence to support this is limited.…”

Association of Patient-Centered Outcomes With Patient-Reported and ICD-9-Based Morbidity Measures

“…For example, tools based on diagnosis codes from administrative data may be used to adjust for morbidity burden in investigations of quality-of-life outcomes or disease management behaviors-a method that may result in incomplete morbidity adjustment. 24,25 In particular, assessing self-reported morbidity burden may be underutilized because collecting selfreported data can be resource-intensive.…”

“…For example, tools based on diagnosis codes from administrative data may be used to adjust for morbidity burden in investigations of quality-of-life outcomes or disease management behaviors-a method that may result in incomplete morbidity adjustment. 24,25 In particular, assessing self-reported morbidity burden may be underutilized because collecting selfreported data can be resource-intensive.Self-reported morbidity assessments may incorporate biopsychosocial constructs not captured by other measures of morbidity and, therefore, may be particularly relevant for assessments using patient-reported outcomes. 20,26,27 In addition, there is evidence that any single morbidity measure may fail to capture the entire association between morbidity burden and a health outcome.…”