title: Cost modeling of preoperative axillary ultrasound and fine-needle aspiration to guide surgery for invasive breast cancer.
abstract: OBJECTIVE
  Preoperative axillary lymph node ultrasound (US) and fine-needle aspiration (FNA) biopsy can identify a proportion of node-positive patients and avoid sentinel lymph node (SLN) surgery and direct surgical treatment. We compared the costs with preoperative US/FNA to without US/FNA (standard of care) for invasive breast cancer.
  
  
  METHODS
  Using decision-analytic software we constructed a model to assess the costs associated with the two preoperative strategies. Diagnostic test sensitivities and specificities were obtained from literature review. Costs were derived from Medicare payment rates and actual resource utilization. Base-case results were fully probabilistic to capture parameter uncertainty in economic results.
  
  
  RESULTS
  Base-case results estimate total mean costs per patient of $10,947 ("$" indicates US dollars throughout) with the US/FNA strategy and $10,983 with standard of care, an incremental cost savings of $36, on average, per patient [95% confidence interval (CI) of cost difference: -$248 to $179]. Most (63%) of the simulations resulted in cost saving with axillary US/FNA. One-way sensitivity analyses suggest that results are sensitive to assumed diagnostic and surgical costs and selected diagnostic test parameters. US/FNA approach was similar in costs or cost saving relative to the standard of care for all tumor stages.
  
  
  CONCLUSIONS
  The additional cost of performing axillary US with possible FNA in every patient is balanced, on average, by the savings from avoiding SLN in cases where metastasis can be documented preoperatively. Routine use of preoperative axillary US with FNA to guide surgical planning can decrease the overall cost of patient care for invasive breast cancer.
authors.affiliation: Department of Surgery, Mayo Clinic, Rochester, Minnesota, USA. boughey.judy@mayo.edu
authors.forename: Judy C
authors.initials: JC
authors.lastname: Boughey
authors.forename: James P
authors.initials: JP
authors.lastname: Moriarty
authors.forename: Amy C
authors.initials: AC
authors.lastname: Degnim
authors.forename: Melissa S
authors.initials: MS
authors.lastname: Gregg
authors.forename: Jason S
authors.initials: JS
authors.lastname: Egginton
authors.forename: Kirsten Hall
authors.initials: KH
authors.lastname: Long
mesh_terms: D001365:Axilla; D044963:Biopsy, Fine-Needle / Q000191:economics*; D001943:Breast Neoplasms / Q000191:economics* / Q000473:pathology; D018270:Carcinoma, Ductal, Breast / Q000191:economics* / Q000556:secondary; D003198:Computer Simulation; D003365:Costs and Cost Analysis; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D008198:Lymph Nodes / Q000000981:diagnostic imaging / Q000473:pathology; D008207:Lymphatic Metastasis; D009010:Monte Carlo Method; D009362:Neoplasm Metastasis; D011300:Preoperative Care; D012680:Sensitivity and Specificity; D016217:Ultrasonography, Mammary / Q000191:economics*