A nomogram to predict disease-free survival after surgical resection of GIST.

Published

Journal Article

BACKGROUND: Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumors of the gastrointestinal tract. Adjuvant imatinib therapy has resulted in improved disease-free survival (DFS) following resection of primary GIST. The aim of our study was to create a nomogram to predict DFS following resection of GIST. METHOD: Using a multi-institutional cohort of patients who underwent surgery for primary GIST at 7 academic hospitals in the USA and Canada between January 1998 and December 2012, a multivariable Cox proportional hazards model predicting DFS was created using backward stepwise selection. A nomogram to predict DFS following surgical resection of GIST was constructed with the variables selected in the multivariable model. We tested nomogram discrimination by calculating the C-statistic and compared the nomogram to four existing GIST prognostic stratification systems. RESULTS: A total of 365 patients who underwent surgery for primary GIST was included in the study. Using backward stepwise selection, sex, tumor size, tumor site, and mitotic rate were selected for incorporation into the nomogram. The nomogram demonstrated superior discrimination compared to the NIH criteria, modified NIH criteria, and Memorial Sloan-Kettering Nomogram and had similar discrimination to the Miettinen criteria (C-statistic 0.77 vs 0.73, 0.71, 0.71, and 0.78, respectively). CONCLUSION: Four independent predictors of recurrence following surgery for primary GIST were used to create a nomogram to predict DFS. The nomogram stratified patients into prognostic groups and performed well on internal validation.

Full Text

Cited Authors

  • Bischof, DA; Kim, Y; Behman, R; Karanicolas, PJ; Quereshy, FA; Blazer, DG; Maithel, SK; Gamblin, TC; Bauer, TW; Pawlik, TM

Published Date

  • December 2014

Published In

Volume / Issue

  • 18 / 12

Start / End Page

  • 2123 - 2129

PubMed ID

  • 25245766

Pubmed Central ID

  • 25245766

Electronic International Standard Serial Number (EISSN)

  • 1873-4626

Digital Object Identifier (DOI)

  • 10.1007/s11605-014-2658-2

Language

  • eng

Conference Location

  • United States