The association of mood disorders with breast cancer survival: an investigation of linked cancer registration and hospital admission data for South East England
- PMID: 26619290
- PMCID: PMC5096051
- DOI: 10.1002/pon.4037
The association of mood disorders with breast cancer survival: an investigation of linked cancer registration and hospital admission data for South East England
Abstract
Background: Data linkage studies find that depression before or after a breast cancer diagnosis predicts reduced survival. This study aimed to determine whether depression or bipolar recorded in routine hospital admission data independently predicts survival in English breast cancer patients and whether onset in relation to cancer diagnosis is significant.
Methods: Data on 77,173 women diagnosed with breast cancer (ICD-10 C50) in South East England, 2000-2009, were included. Of these, 131 women had a diagnosis of bipolar affective disorder (ICD-10 F31) and 955 of depression (either depressive episodes (ICD-10 F32) or depressive disorder (ICD-10 F33)) recorded in Hospital Episode Statistics between 3 years before and a year following cancer diagnosis. Kaplan-Meier plots were used to examine overall survival. Cox regression analyses were carried out overall and separately for mood disorder diagnoses before and after the cancer diagnosis and adjusted for confounding variables.
Results: A record of depression was a predictor of worse overall survival in breast cancer patients (adjusted HR = 1.33, 95% CI: 1.20-1.48, p < 0.001), while the effect of bipolar was not statistically significant (adjusted HR = 1.33, 95% CI: 0.97-1.82, p = 0.079). New recordings of depression and bipolar diagnoses following a cancer diagnosis appeared better predictors of overall survival than a prior history of either.
Conclusions: There is evidence that English breast cancer patients with depression and bipolar recorded in routine hospital data have worse overall survival than those without these mood disorders. Further work exploring the concordance of records within administrative health data with clinical diagnosis and cause-specific death within these patient groups is needed.
Copyright © 2015 John Wiley & Sons, Ltd.
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