Sandra Söhler

Systematic Analysis of Self-Reported Comorbidities in Large Cohort Studies - A Novel Stepwise Approach by Evaluation of Medication.

Objective In large cohort studies comorbidities are usually self-reported by the patients. This way to collect health information only represents conditions known, memorized and openly reported by the patients. Several studies addressed the relationship between self-reported comorbidities and medical records or pharmacy data, but none of them provided a structured, documented method of evaluation. We thus developed a detailed procedure to compare self-reported comorbidities with information on comorbidities derived from medication inspection. This was applied to the data of the German COPD cohort COSYCONET. Methods Approach I was based solely on ICD10-Codes for the diseases and the indications of medications. To overcome the limitations due to potential non-specificity of medications, Approach II was developed using more detailed information, such as ATC-Codes specific for one disease. The relationship between reported comorbidities and medication was expressed by a four-level concordance score. Results Approaches I and II demonstrated that the patterns of concordance scores markedly differed between comorbidities in the COSYCONET data. On average, Approach I resulted in more than 50% concordance of all reported diseases to at least one medication. The more specific Approach II showed larger differences in the matching with medications, due to large differences in the disease-specificity of drugs. The highest concordance was achieved for diabetes and three combined cardiovascular disorders, while it was substantial for dyslipidemia and hyperuricemia, and low for asthma. Conclusion Both approaches represent feasible strategies to confirm self-reported diagnoses via medication. Approach I covers a broad spectrum of diseases and medications but is limited regarding disease-specificity. Approach II uses the information from medications specific for a single disease and therefore can reach higher concordance scores. The strategies described in a detailed and reproducible manner are generally applicable in large studies and might be useful to extract as much information as possible from the available data.

Relationship of hyperlipidemia to comorbidities and lung function in COPD: Results of the COSYCONET cohort

Although hyperlipidemia is common in COPD, its relationship to comorbidities, risk factors and lung function in COPD has not been studied in detail. Using the baseline data of the COSYCONET cohort we addressed this question. Data from 1746 COPD patients (GOLD stage 1–4; mean age 64.6 y, mean FEV1%pred 57%) were evaluated, focusing on the comorbidities hyperlipidemia, diabetes and cardiovascular complex (CVC; including arterial hypertension, cardiac failure, ischemic heart disease). Risk factors comprised age, gender, BMI, and packyears of smoking. The results of linear and logistic regression analyses were implemented into a path analysis model describing the multiple relationships between parameters. Hyperlipidemia (prevalence 42.9%) was associated with lower intrathoracic gas volume (ITGV) and higher forced expiratory volume in 1 second (FEV1) when adjusting for its multiple relationships to risk factors and other comorbidities. These findings were robust in various statistical analyses. The associations between comorbidities and risk factors were in accordance with previous findings, thereby underlining the validity of our data. In conclusion, hyperlipidemia was associated with less hyperinflation and airway obstruction in patients with COPD. This surprising result might be due to different COPD phenotypes in these patients or related to effects of medication.

Transfer factor for carbon monoxide in patients with COPD and diabetes: results from the German COSYCONET cohort

BackgroundAn impairment of CO diffusing capacity has been shown in diabetic patients without lung disease. We analyzed how diffusing capacity in patients with COPD is affected by the concurrent diagnosis of diabetes.MethodsData from the initial visit of the German COPD cohort COSYCONET were used for analysis. 2575 patients with complete lung function data were included, among them 358 defined as diabetics with a reported physician diagnosis of diabetes and/or specific medication. Pairwise comparisons between groups and multivariate regression models were used to identify variables predicting the CO transfer factor (TLCO%pred) and the transfer coefficient (KCO%pred).ResultsCOPD patients with diabetes differed from those without diabetes regarding lung function, anthropometric, clinical and laboratory parameters. Moreover, gender was an important covariate. After correction for lung function, gender and body mass index (BMI), TLCO%pred did not significantly differ between patients with and without diabetes. The results for the transfer coefficient KCO were similar, demonstrating an important role of the confounding factors RV%pred, TLC%pred, ITGV%pred, FEV1%pred, FEV1/FVC, age, packyears, creatinine and BMI. There was not even a tendency towards lower values in diabetes.ConclusionThe analysis of data from a COPD cohort showed no significant differences of CO transport parameters between COPD patients with and without diabetes, if BMI, gender and the reduction in lung volumes were taken into account. This result is in contrast to observations in lung-healthy subjects with diabetes and raises the question which factors, among them potential anti-inflammatory effects of anti-diabetes medication are responsible for this finding.