title: Quantitative assessment of lymph vascular space invasion (LVSI) provides important prognostic information in node-negative breast cancer.
abstract: BACKGROUND
  Some studies investigating the prognostic value of lymph vascular space invasion (LVSI) have shown an association between LVSI and disease-free survival. Definitive criteria and optimal determination of this parameter remain unclear, however, especially regarding the clinical relevance of LVSI quantification.
  
  
  METHODS
  A subset of node-negative breast carcinomas from premenopausal patients from the European Organization for the Research and Treatment of Cancer trial 10854 (assessing efficacy of perioperative chemotherapy patients with T1-T3, N0-2, and M0 breast cancer (BC) was selected and scored for LVSI. In 358 evaluable breast carcinomas, the number of LVSI foci and tumor cells was determined in the largest tumor embolus within the lymph vessels. These two parameters were multiplied to calculate the LVSI tumor burden (LVSI TB). The optimal cutoff for this parameter was calculated in a test set (N = 120), tested in a validation set (N = 238), and compared with simple quantitation of the number of LVSI foci.
  
  
  RESULTS
  Tumors with a single LVSI focus are not associated with increased risk for relapse [hazard ratio (HR) 1.423, 95% confidence interval (CI) 0.762-2.656]. The LVSI TB had higher sensitivity and specificity compared with simple determination of the number of LVSI foci. LVSI TB was independently associated with disease-free survival in the validation set (HR 2.366, 95% CI 1.369-4.090, P = 0.002) in multivariate analysis and provided prognostic information in both the low- and high-risk node-negative BC groups (P < 0.001 and P = 0.007, respectively).
  
  
  CONCLUSIONS
  The determination of the number of LVSI foci multiplied by the number of tumor cells gives the most reliable quantitative assessment of this parameter, which can provide prognostic information in node-negative BC.
authors.affiliation: Department of Clinical Oncology.
authors.forename: T J A
authors.initials: TJ
authors.lastname: Dekker
authors.forename: C J H
authors.initials: CJ
authors.lastname: van de Velde
authors.forename: D
authors.initials: D
authors.lastname: van Bruggen
authors.forename: W E
authors.initials: WE
authors.lastname: Mesker
authors.forename: J J M
authors.initials: JJ
authors.lastname: van der Hoeven
authors.forename: J R
authors.initials: JR
authors.lastname: Kroep
authors.forename: R A E M
authors.initials: RA
authors.lastname: Tollenaar
authors.forename: V T H B M
authors.initials: VT
authors.lastname: Smit
mesh_terms: D000328:Adult; D001943:Breast Neoplasms / Q000473:pathology* / Q000628:therapy; D018270:Carcinoma, Ductal, Breast / Q000473:pathology* / Q000628:therapy; D018572:Disease-Free Survival; D005260:Female; D006801:Humans; D053208:Kaplan-Meier Estimate; D042601:Lymphatic Vessels / Q000473:pathology*; D008875:Middle Aged; D009361:Neoplasm Invasiveness; D011379:Prognosis; D016016:Proportional Hazards Models; D012306:Risk; D016896:Treatment Outcome; D055815:Young Adult
keywords: breast cancer; lvsi; lymph vessel invasion; prognosis; risk stratification