Publication
Impact of subtypes and comorbidities on breast cancer relapse and survival in population-based studies
Journal Paper/Review - Jul 30, 2018
Ess Silvia M, Mousavi Mohsen, Frick Harald, Rohrmann Sabine, Ortelli Laura, Bordoni Andrea, Konzelmann Isabelle, Rapiti Elisabetta, Neyroud Isabelle, Bouchardy Christine, Herrmann Christian, Thürlimann Beat
Units
PubMed
Doi
Citation
Type
Journal
Publication Date
Issn Electronic
Pages
Brief description/objective
OBJECTIVE
To study the impact of subtypes and comorbidities on breast cancer (BC) relapse and survival in the heterogeneous patients of the real world.
METHODS
We identified patients diagnosed with BC between January 2003 and December 2005 from six population-based Swiss cancer registries. Clinicopathologic data was completed with information on locoregional and distant relapse and date and cause of death for over 10-years. We approximated BC subtypes using grade and the immunohistochemical panel for oestrogen, progesterone and human epidermal growth factor 2 (HER2) receptor status. We studied factors affecting relapse and survival.
RESULTS
Luminal A-like subtype represented 46% of all newly diagnosed BC (N = 1831), followed by luminal B-like (N = 1504, 38%), triple negative (N = 436, 11%) and HER2 enriched (N = 204, 5%). We observed regional disparities in subtype prevalence that contribute to explain regional differences in survival formerly described. Disease relapse and BC specific mortality differed by subtype and were lower for luminal A like tumours than for other subtypes for any stage at diagnosis. After a median follow-up of 10.9 years, 1311 (33%) had died, half of them 647 (16%) due to another disease, showing the importance of comorbidities. Omission of systemic therapies in selected patients was not associated with poorer BC specific survival, BC subtype and life expectancy playing a role.
CONCLUSIONS
Information on tumour subtype is necessary for an adequate interpretation of population-based BC studies. Measures of comorbidity or frailty help in the evaluation of quality of care in the highly heterogeneous patients of the real world.