Estimating long-term crude probability of death among young breast cancer patients: a Bayesian approach.

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 (PBC) 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 PBC 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.