English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Aims and Background   Bayesian survival analysis was applied to assess the long-term survival and probability of death due to breast cancer (BC) in Girona, the Spanish region with the highest BC incidence.Methods   A Bayesian autoregressive model was implemented to compare survival indicators between the periods 1985–1994 and 1995–2004. We assessed the long-term excess hazard of death, relative survival (RS), and crude probability of death due to BC (P BC ) up to 20 years after BC diagnosis, reporting the 95% credible intervals (CI) of these indicators.Results   Patients diagnosed from 1995 onwards showed lower 20-year excess hazards of death than those diagnosed earlier (RS during 1985–1994: local stage: 76.6%; regional stage: 44.9%; RS during 1995–2004: local stage: 85.2%; regional stage: 57.0%). The P BC  after 20 years of BC diagnosis for patients diagnosed in 1995 and after might reach 14.4% (95% CI: 8.9%–21.2%) in local stage and 41.0% (95% CI: 36.1%–47.1%) in regional stage.Conclusions   The method presented could be useful when dealing with population-based survival data from a small region. Better survival prospects were found in patients diagnosed after 1994, although we detected a non-decreasing long-term excess hazard of death, suggesting that these patients have higher mortality than the general population even 10 years after the diagnosis of BC.

Estimating Long-Term Crude Probability of Death among Young Breast Cancer Patients: A Bayesian Approach