A Predictive Nomogram for Small Intestine Neuroendocrine Tumors

Susheian Kelly, Jeffrey Aalberg, Michelle Kang Kim, Celia M. Divino

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Objective There is a scarcity of prognostic tools for small intestine neuroendocrine tumors (SI-NETs) and inconsistencies in currently available grading and staging systems. Nomograms are being proposed to address these limitations. However, none is specific to the US population. This study proposed a concise nomogram for SI-NETs using US population-based data. Methods Patients with SI-NETs (2004-2015) were selected from the Surveillance, Epidemiology, and End Results database. Variables selected were age, sex, race, tumor grade, primary tumor size, and TNM staging. Cox regression parameter estimates were used to generate nomogram scores. Results A total of 2734 patients were selected: 2050 for nomogram development and 684 for internal validation. Prognosticators, age (P < 0.0001), primary tumor size >3 cm (P < 0.0022), tumor grade (P < 0.0001), depth of invasion ≥T3 (P < 0.0280), and distant metastasis (P < 0.0001) were used to develop the nomogram. Nomogram scores ranges from 10 to 80 points with an area under the curve of 0.76, which remained consistently high during internal validation (area under the curve, 0.75). Conclusions This Surveillance, Epidemiology, and End Results database nomorgram is a concise prognostic tool that demonstrated high predictive accuracy.

Original languageEnglish
Pages (from-to)524-528
Number of pages5
Issue number4
StatePublished - 1 Apr 2020


  • neuroendocrine tumor
  • nomogram
  • prognostication
  • small intestine


Dive into the research topics of 'A Predictive Nomogram for Small Intestine Neuroendocrine Tumors'. Together they form a unique fingerprint.

Cite this