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Lung Cancer. 2019 Jan;127:122-129. doi: 10.1016/j.lungcan.2018.11.030. Epub 2018 Nov 24.

Assessing the lung cancer comorbidome: An analysis of German claims data.

Author information

1
Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Institute of Health Economics and Health Care Management, Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Ingolstaedter Landstrasse 1, D-85764 Neuherberg, Germany; Department of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-University Munich, Marchioninistr.15, D-81377 Munich, Germany. Electronic address: monika.murawski@helmholtz-muenchen.de.
2
Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Institute of Health Economics and Health Care Management, Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Ingolstaedter Landstrasse 1, D-85764 Neuherberg, Germany. Electronic address: Julia.Walter@helmholtz-muenchen.de.
3
Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Institute of Health Economics and Health Care Management, Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Ingolstaedter Landstrasse 1, D-85764 Neuherberg, Germany. Electronic address: L.Schwarzkopf@helmholtz-muenchen.de.

Abstract

OBJECTIVES:

In presence of lung cancer, the additional impact of comorbidity on survival is often neglected, although comorbidities are likely to be prevalent. Our study examines the comorbidity profile and the impact of distinct conditions on survival in German lung cancer patients.

MATERIAL AND METHODS:

We investigated claims data from a large nationwide statutory health insurance fund of 16,202 patients initially diagnosed with lung cancer in 2009. We calculated the prevalence of comorbidities grouped according to an extension of the Elixhauser Comorbidity Index (EI). Effects of distinct comorbidities on 5-year survival were examined using multivariate Cox proportional hazards models, adjusted for sex, age and metastases at baseline. All analyses were stratified by initial lung cancer-related treatment regimen (Surgery, Chemotherapy/Radiotherapy, No treatment). Findings were visualized in the form of a comorbidome.

RESULTS:

Our study population was predominantly male (70.6%) with a mean age of 68.6 years, and a mean EI score of 3.94. Patients without treatment were older (74.4 years), and their comorbidity burden was higher (mean EI = 4.59). Median survival varied by subgroup (Surgery: 24.4 months, Chemotherapy/Radiotherapy: 8.8 months, No treatment: 2.0 months), and so did the comorbidity profile and the impact of distinct conditions on survival. Generally, the effect of comorbidities on survival was detrimental and the negative association was most pronounced for 'Weight Loss' and' Paralysis'. In contrast, 'Lipid Metabolism Disorders' and 'Obesity' were positively associated with survival. Noteworthily, highly prevalent conditions tended not to show any significant association.

CONCLUSION:

We found specific comorbidity profiles within the distinct treatment regimens. Moreover, there were negative but also some positive associations with survival, and the strength of these effects varied by stratum. Particularly the positive effects of 'Obesity" and 'Lipid Metabolism Disorders' which were robust across strata need to be further investigated to elucidate potential biomedical explanations.

KEYWORDS:

Administrative data; Bronchial carcinoma; Comorbidity; Elixhauser Comorbidity Index; Mortality; Statutory health insurance

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