title: Outcomes and cost analysis of pyeloplasty for antenatally diagnosed ureteropelvic junction obstruction using Markov models.
abstract: OBJECTIVE
  The optimal timing of pyeloplasty for children diagnosed with ureteropelvic junction obstruction (UPJO) after workup for antenatal hydronephrosis is disputed. We sought to examine the potential costs and clinical outcomes of treatment protocols featuring different indications for pediatric pyeloplasty using Markov models.
  
  
  METHODS
  Cost and outcomes analysis using Markov modeling was performed for three treatment algorithms: medical management, immediate pyeloplasty (during the first year of life), and pyeloplasty after no improvement on imaging. The costs were determined from the perspective of the medical institution. The variables tracked during Markov model simulation included age at resolution of UPJO, the proportion of patients with worsened hydronephrosis, the number of pyeloplasties, the number of pyelonephritis episodes, and costs. Sensitivity analyses were performed to determine which elements affected the model and to determine threshold values.
  
  
  RESULTS
  Immediate pyeloplasty and pyeloplasty after no improvement on imaging resulted in rapid resolution of UPJO (mean age at resolution younger than 2 years) with lower rates of worsened hydronephrosis and pyelonephritis compared with observation alone. For the surgical protocols, the costs per resolved case of UPJO were greater than those for medical management alone at the probability values tested in the Markov models. The sensitivity analysis of all variables over realistic ranges demonstrated that the costs of surgery, annual antibiotics and imaging, and the rate of pyelonephritis were critical in determining the costs.
  
  
  CONCLUSIONS
  Pediatric urologists should include practice-specific features such as the costs of surgery, annual antibiotics and imaging, and pyelonephritis rates when considering efficacious, yet less costly, treatment protocols for UPJO.
authors.affiliation: Department of Urology, Baylor College of Medicine, Houston, Texas, USA. mhhsieh@stanfordalumni.org
authors.forename: Michael H
authors.initials: MH
authors.lastname: Hsieh
authors.forename: Maxwell V
authors.initials: MV
authors.lastname: Meng
authors.forename: Laurence S
authors.initials: LS
authors.lastname: Baskin
mesh_terms: D000465:Algorithms; D003365:Costs and Cost Analysis; D006801:Humans; D007223:Infant; D007682:Kidney Pelvis / Q000601:surgery*; D008390:Markov Chains; D015233:Models, Statistical; D011296:Prenatal Diagnosis; D016896:Treatment Outcome; D014517:Ureteral Obstruction / Q000175:diagnosis / Q000191:economics* / Q000601:surgery*; D013520:Urologic Surgical Procedures / Q000379:methods