Publicación:
CURE RATE MODELS FOR HETEROGENEOUS COMPETING CAUSES

dc.creatorDIEGO IGNACIO GALLARDO MATELUNA
dc.date2023
dc.date.accessioned2025-01-10T15:41:45Z
dc.date.available2025-01-10T15:41:45Z
dc.date.issued2023
dc.description.abstractCURE RATE MODELS HAVE BEEN WIDELY STUDIED TO ANALYZE TIME-TO-EVENT DATA WITH A CURED FRACTION OF PATIENTS. IN THIS TYPE OF MODEL, THE NUMBER OF CONCURRENT CAUSES IS ASSUMED TO BE A RANDOM VARIABLE. HOWEVER, IN PRACTICE, IT IS NATURAL TO ADMIT THAT THE DISTRIBUTION OF THE NUMBER OF COMPETING CAUSES IS DIFFERENT FROM INDIVIDUAL TO INDIVIDUAL. OUR PROPOSAL IS TO ASSUME THAT THE NUMBER OF COMPETING CAUSES BELONGS TO A CLASS OF A FINITE MIXTURE OF COMPETING CAUSES DISTRIBUTIONS. WE ASSUME THE NUMBER OF MALIGNANT CELLS FOLLOW A MIXTURE OF TWO POWER SERIES DISTRIBUTIONS AND SUPPOSE THAT THE TIME TO THE EVENT OF INTEREST FOLLOWS A WEIBULL DISTRIBUTION. WE CONSIDER THE PROPORTION OF THE CURED NUMBER OF COMPETING CAUSES DEPENDING ON COVARIATES, ALLOWING DIRECT MODELING OF THE CURE RATE. THE PROPOSED MODEL INCLUDES SEVERAL WELL-KNOWN MODELS AS SPECIAL CASES AND DEFINES MANY NEW SPECIAL MODELS. AN EXPECTATION-MAXIMIZATION ALGORITHM IS PROPOSED FOR PARAMETER ESTIMATION, WHERE THE EXPECTATION STEP INVOLVES THE COMPUTATION OF THE EXPECTED NUMBER OF CONCURRENT CAUSES FOR EACH INDIVIDUAL. A MONTE CARLO SIMULATION IS PERFORMED TO ASSESS THE BEHAVIOR OF THE ESTIMATION METHOD. IN ORDER TO SHOW THE POTENTIAL FOR THE PRACTICE OF OUR MODEL, WE APPLY IT TO THE REAL MEDICAL DATA SET FROM A POPULATION-BASED STUDY OF INCIDENT CASES OF CUTANEOUS MELANOMA DIAGNOSED IN THE STATE OF SÃO PAULO, BRAZIL, ILLUSTRATING THAT THE MODEL PROPOSED CAN OUTPERFORM TRADITIONAL MODELS IN TERMS OF MODEL FITTING.
dc.formatapplication/pdf
dc.identifier.doiDOI: 10.1177/09622802231188514
dc.identifier.issn1477-0334
dc.identifier.issn0962-2802
dc.identifier.urihttps://repositorio.ubiobio.cl/handle/123456789/13228
dc.languagespa
dc.publisherSTATISTICAL METHODS IN MEDICAL RESEARCH
dc.relation.uriDOI: 10.1177/09622802231188514
dc.rightsPUBLICADA
dc.subjectpower series distribution.
dc.subjectmixtures
dc.subjectmelanoma data set
dc.subjectexpectation?maximization algorithm
dc.subjectConcurrent causes
dc.titleCURE RATE MODELS FOR HETEROGENEOUS COMPETING CAUSES
dc.typeARTÍCULO
dspace.entity.typePublication
ubb.EstadoPUBLICADA
ubb.Otra ReparticionDEPARTAMENTO DE ESTADISTICA
ubb.SedeCONCEPCIÓN
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