Subgroups of patients with very large gastrointestinal stromal tumors with distinct prognoses: a multicenter study

J Surg Oncol. 2014 Feb;109(2):67-70. doi: 10.1002/jso.23471. Epub 2013 Oct 24.

Abstract

Background and objectives: Any gastrointestinal stromal tumors (GISTs) larger than 10 cm are classified as "high risk" according to the modified National Institutes of Health consensus criteria. We conducted a multicenter study to identify a subgroup with moderate prognosis even within the "high-risk" group.

Methods: We retrospectively collected data on 107 patients with tumors ≥10 cm from a multicenter database of GIST patients. Patients with macroscopic residual lesions or tumor rupture were excluded. The relationship between recurrence-free survival (RFS) and clinicopathological factors was analyzed.

Results: The median tumor size and mitotic count were 12.5 cm and 8/50 HPF. The RFS rate was 58.5% at 3 years, 52.1% at 5 years. Only mitotic count was an independent prognostic factor of RFS in the multivariate analysis (P = 0.001). The hazard ratio for recurrence in the subgroup with mitotic count >5/50 HPF was 2.91 (95% confidence interval, 1.53 to 5.56). The subgroup with mitotic count ≤5/50 HPF showed significantly better RFS than the mitotic count >5/50 HPF subgroup (P < 0.001).

Conclusions: Mitotic count is closely associated with outcome in patients with large GISTs. This suggests that the subset of large GISTs with low mitotic counts may be considered as "intermediate-risk" lesions.

Keywords: high risk; large GISTs; mitosis; mitotic count.

Publication types

  • Multicenter Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Disease-Free Survival
  • Female
  • Follow-Up Studies
  • Gastrointestinal Neoplasms / mortality*
  • Gastrointestinal Neoplasms / pathology*
  • Gastrointestinal Stromal Tumors / mortality*
  • Gastrointestinal Stromal Tumors / pathology*
  • Humans
  • Male
  • Middle Aged
  • Mitotic Index*
  • Neoplasm Recurrence, Local
  • Prognosis
  • Proportional Hazards Models
  • Retrospective Studies