A cohort study of mammography screening finds that comorbidity measures are insufficient for controlling selection bias
Autor: | Franziska Heinze, Klaus Giersiepen, Ulrike Haug, Hans-Werner Hense, Heinz Rothgang, Hajo Zeeb, Ingo Langner, Dirk Enders, Jonas Czwikla |
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Rok vydání: | 2018 |
Předmět: |
Epidemiology
media_common.quotation_subject Breast Neoplasms Comorbidity Cohort Studies Insurance Claim Review 03 medical and health sciences 0302 clinical medicine Cause of Death Humans Medicine 030212 general & internal medicine Selection Bias Aged Retrospective Studies media_common Selection bias business.industry Proportional hazards model Mortality rate Hazard ratio Middle Aged medicine.disease Confidence interval Observational Studies as Topic 030220 oncology & carcinogenesis Female Observational study business Mammography Demography Cohort study |
Zdroj: | Journal of Clinical Epidemiology. 104:1-7 |
ISSN: | 0895-4356 |
Popis: | Objective To examine the potential of claims-based comorbidity measures for controlling selection bias in observational studies of mammography screening. Study Design and Setting Based on claims data of a large German Statutory Health Insurance fund, the single comorbidities considered by the Charlson, Elixhauser, Multipurpose Australian Comorbidity Scoring System, and M3 comorbidity measures were identified for mammography screening participants and nonparticipants. Total death rates within 4 years after screening invitation were compared. Cox proportional hazards regressions were performed unadjusted and adjusted for age, federal state of residence, and comorbidity. Results Among 1,247,919 insured women aged 50–68 years (56.2% participants), 10,311 participants (death rate 375.8/100,000 person-years) and 18,113 nonparticipants (death rate 854.8/100,000 person-years) died from any cause during the follow-up. The unadjusted hazard ratio (HR) for death from any cause for participants vs. nonparticipants was 0.44 (99.9% confidence interval 0.42–0.46). Adjustments attenuated the HR to a maximum of 0.52 (0.50–0.54). Conclusion The lower short-term all-cause mortality among participants cannot be explained by mammography screening effects and should be interpreted as selection bias. Adjusting for comorbidities only slightly attenuated this bias. Future studies should examine whether claims data include further information that is beneficial to adequately control selection bias in observational studies of mammography screening. |
Databáze: | OpenAIRE |
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