A Markovian decision model of adaptive cancer treatment and quality of life

Peter Bayer, Joel Steven Brown, Johan Dubbeldam and Mark Broom

Working Papers from HAL

Abstract: This paperdevelopsandanalyzesaMarkovchainmodelforthetreatmentofcancer. Cancer therapyismodeledasthepatient'sMarkovDecisionProblem,withtheobjectiveof maximizing thepatient'sdiscountedexpectedqualityoflifeyears.Patientsmakedecisions on thedurationoftherapybasedontheprogressionofthediseaseaswellastheirown preferences. Weobtainapowerfulanalyticdecisiontoolthroughwhichpatientsmay select theirpreferredtreatmentstrategy.Weillustratethetradeo spatientsarefacing in anumericalexampleandcalculatethevaluelosttoacohortwhochoosesuboptimal strategies. Inasecondmodelpatientsmaymakechoicestoincludedrugholidays.By delayingtherapy,thepatienttemporarilyforgoesthegainsoftherapyinordertodelay its sidee ects.Weobtainananalytictoolthatallowsnumericalapproximationsofthe optimal timesofdelay.

Date: 2022-01
Note: View the original document on HAL open archive server: https://hal.science/hal-03542494v1
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Working Paper: A Markovian decision model of adaptive cancer treatment and quality of life (2022)
Working Paper: A Markovian decision model of adaptive cancer treatment and quality of life (2022)
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