Women with short survival after diagnosis of metastatic breast cancer: a population-based registry study

Abstract

Abstract Purpose Despite therapeutic advances, overall survival of metastatic breast cancer (MBC) at the population level has seen little improvement over the past decades. Aggressive tumor biology or delay in access to cancer care might be contributing factors. With this retrospective population-based study we aimed to quantify and characterize patients with very short survival time following MBC diagnosis. Methods Women diagnosed with MBC between Jan 1st, 2005 and Dec 31st, 2016 were identified using the population-based Stockholm–Gotland breast cancer registry. Data regarding demographic and clinicopathological characteristics, survival, and treatment were extracted retrospectively from the registry and from patient charts. Patients who died within 90 days following diagnosis of MBC were identified and their characteristics were compared with all other patients diagnosed with MBC during the same period. Results Between 2005 and 2016, 3124 patients were diagnosed with MBC, of whom 498 (16.2%) died within 90 days of diagnosis. Nearly half (N = 233) did not receive any antitumoral treatment. Patients with short survival were older (p < 0.001), had higher primary tumor grade (p < 0.001), higher clinical stage at primary diagnosis (p = 0.002), and more often estrogen receptor (ER)-negative breast cancer (p < 0.001). Visceral metastases were more frequent (p < 0.001) and patients with short survival received adjuvant chemotherapy (p < 0.001) to a lesser extent compared to patients with a better prognosis. In multivariable analysis older age, time period of diagnosis, metastasis site, adjuvant chemotherapy, and primary tumor grade were independent predictors for short survival, whereas ER status was not. Conclusion Nearly one out of six patients with MBC survive less than 3 months after diagnosis. Our findings demonstrate a different spectrum of MBC at population level and can potentially inform on individualized follow-up strategies and treatment algorithms.