Age in combination with gender is a valuable parameter in differential diagnosis of solid pseudopapillary tumors and pancreatic neuroendocrine neoplasm

BMC Endocr Disord. 2022 Oct 21;22(1):255. doi: 10.1186/s12902-022-01164-7.

Abstract

Background: The clinicopathological characteristics of solid pseudopapillary tumor (SPT) and pancreatic neuroendocrine neoplasm (pNEN) are different. We, therefore, systematically investigated the performance of the clinicopathological characteristics in distinguishing SPT from pNEN.

Methods: We collected the cases from the Surveillance, Epidemiology, and End Results Program. The International Classification of Diseases for Oncology, third edition (ICD-O-3) for tumors was used to identify patients with pNEN or patients with SPT. To determine the performance of age in combination with gender in distinguishing SPT from pNEN, a nomogram was developed and the performance of this nomogram was evaluated by the receiver operating characteristic curve and the area under the curve (AUC).

Results: In the training cohort, 563 patients with pNENs and 30 patients with SPTs were recruited. The logistic regression and receiver operating characteristic curves suggest that age, gender, T-stage, N-stage, and M-stage could discriminate SPT and pNEN. The AUC of age, gender, T-stage, N-stage, and M-stage was 0.82, 0.75, 0.65, 0.69, and 0.70, respectively. Based on the nomogram, we observed that the AUC of age and gender is significantly high than that of the T-stage, N-stage, and M-stage.

Conclusions: The present study proposes a non-invasive nomogram that could aid in the differential diagnosis of pNEN and SPT. This might help the clinicians to distinguish SPT from pNEN and choose the appropriate treatments for the patients.

Keywords: Nomogram; Pancreatic neuroendocrine neoplasm; Solid pseudopapillary tumor.

MeSH terms

  • Diagnosis, Differential
  • Humans
  • Neuroendocrine Tumors* / diagnosis
  • Neuroendocrine Tumors* / pathology
  • Pancreatic Neoplasms* / diagnosis
  • Pancreatic Neoplasms* / pathology
  • ROC Curve