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SUMMARY:Statistical Approaches to Personalised Medicine in Breast Cancer -
  Dr Oscar Rueda (CRUK - CI)
DTSTART:20190306T140000Z
DTEND:20190306T150000Z
UID:TALK116308@talks.cam.ac.uk
CONTACT:46925
DESCRIPTION:Abstract:\nBreast cancer is the leading cause of cancer in wom
 en\, with roughly 1.4 million new cases diagnosed each year worldwide. We 
 have previously shown that\, as a result of different molecular processes\
 , breast cancer is a collection of at least ten distinct diseases that hav
 e diverse prognoses. \nWe present here a statistical model that accounts f
 or different types of relapse (loco-regional and distant)\, competing caus
 es of death (cancer death or other causes)\, clinical covariates\, and spe
 cific baseline hazards for different molecular subgroups.\nWe show that a 
 multistate model for breast cancer recurrence combined with proper patient
  stratification can be very useful to make informed decisions about clinic
 al management of the patients. In particular\, intermediate events like lo
 co-regional relapse change completely the pattern of disease-specific surv
 ival and suggest different courses of action for each breast cancer subtyp
 e.\nUsing the complete patient history of recurrences\, we show that every
  disease subtype can metastasise into any organ\, although there are some 
 preferences for specific sites. Finally\, we study the pattern of consecut
 ive recurrences in each subtype\, the number and speed of each metastasis 
 site\, the risk of death for each of them. \nWe show that our model produc
 es baseline risks that can be used to measure the prognostic power of biom
 arkers or to predict the additional benefit of chemotherapy. We also comme
 nt on the integration of different layers of molecular information in the 
 context of a personalised breast cancer program.
LOCATION:MR4\, Centre for Mathematical Sciences\, Wilberforce Road\, Cambr
 idge
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