IEEE J Biomed Health Inform - A MDP model for breast and ovarian cancer intervention strategies for BRCA1/2 mutation carriers.

Tópicos

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Resumo

RPOSE: Women with BRCA1/2 mutations have higher risk for breast and ovarian cancers. Available intervention actions include prophylactic surgeries and breast screening, which vary significantly in cost, cancer prevention, and in resulting death from other causes. We present a model designed to yield optimal intervention strategies for mutation carriers between the ages of 30 and 65 and any prior intervention history.METHODS: A Markov decision process (MDP) model is developed that considers yearly state transitions for the mutation carriers and state dependent intervention actions. State is defined as a vector comprising mutation type, health states, prior intervention actions, and age. A discounted value iteration algorithm is used to obtain optimal strategies from the MDP model using both cost and quality-adjusted life years (QALYs) as rewards.RESULTS: The results from MDP model show that for 30-year-old women with BRCA1 mutation and no prior intervention history, the cost-optimal strategy is a combination of prophylactic mastectomy (PM) and prophylactic oophorectomy (PO) at age 30 with no screening afterwards. Whereas, the QALYs-optimal strategy suggests PO at age 30 and PM at age 50 with screening afterwards. For BRCA2 mutation carriers at age 30, the cost-optimal strategy is PO at age 30, PM at age 40, and yearly screening only after age 56. Corresponding QALYs-optimal strategy is PM at age 40 with screening. Strategies for all other ages (31 to 65) are obtained and presented. It is also demonstrated that the cost-optimal strategies offer near maximum survival rate and near minimum cancer incidence rates by age 70, when compared to other ad hoc strategies.

Resumo Limpo

rpose women brca mutat higher risk breast ovarian cancer avail intervent action includ prophylact surgeri breast screen vari signific cost cancer prevent result death caus present model design yield optim intervent strategi mutat carrier age prior intervent historymethod markov decis process mdp model develop consid year state transit mutat carrier state depend intervent action state defin vector compris mutat type health state prior intervent action age discount valu iter algorithm use obtain optim strategi mdp model use cost qualityadjust life year qali rewardsresult result mdp model show yearold women brca mutat prior intervent histori costoptim strategi combin prophylact mastectomi pm prophylact oophorectomi po age screen afterward wherea qalysoptim strategi suggest po age pm age screen afterward brca mutat carrier age costoptim strategi po age pm age year screen age correspond qalysoptim strategi pm age screen strategi age obtain present also demonstr costoptim strategi offer near maximum surviv rate near minimum cancer incid rate age compar ad hoc strategi

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