In:
Neuroendocrinology, S. Karger AG, Vol. 112, No. 6 ( 2022), p. 571-579
Abstract:
〈 b 〉 〈 i 〉 Background: 〈 /i 〉 〈 /b 〉 Despite the low recurrence rate of resected nonfunctional pancreatic neuroendocrine tumors (NF-pNETs), nearly all patients undergo long-term surveillance. A prediction model for recurrence may help select patients for less intensive surveillance or identify patients for adjuvant therapy. The objective of this study was to assess the external validity of a recently published model predicting recurrence within 5 years after surgery for NF-pNET in an international cohort. This prediction model includes tumor grade, lymph node status and perineural invasion as predictors. 〈 b 〉 〈 i 〉 Methods: 〈 /i 〉 〈 /b 〉 Retrospectively, data were collected from 7 international referral centers on patients who underwent resection for a grade 1–2 NF-pNET between 1992 and 2018. Model performance was evaluated by calibration statistics, Harrel’s C-statistic, and area under the curve (AUC) of the receiver operating characteristic curve for 5-year recurrence-free survival (RFS). A sub-analysis was performed in pNETs & #x3e;2 cm. The model was improved to stratify patients into 3 risk groups (low, medium, high) for recurrence. 〈 b 〉 〈 i 〉 Results: 〈 /i 〉 〈 /b 〉 Overall, 342 patients were included in the validation cohort with a 5-year RFS of 83% (95% confidence interval [CI]: 78–88%). Fifty-eight patients (17%) developed a recurrence. Calibration showed an intercept of 0 and a slope of 0.74. The C-statistic was 0.77 (95% CI: 0.70–0.83), and the AUC for the prediction of 5-year RFS was 0.74. The prediction model had a better performance in tumors & #x3e;2 cm (C-statistic 0.80). 〈 b 〉 〈 i 〉 Conclusions: 〈 /i 〉 〈 /b 〉 External validity of this prediction model for recurrence after curative surgery for grade 1–2 NF-pNET showed accurate overall performance using 3 easily accessible parameters. This model is available via www.pancreascalculator.com.
Type of Medium:
Online Resource
ISSN:
0028-3835
,
1423-0194
Language:
English
Publisher:
S. Karger AG
Publication Date:
2022
detail.hit.zdb_id:
1483028-0
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