A Prognostic Scoring System for the Prediction of Metastatic Recurrence Following Curative Resection of Pancreatic Neuroendocrine Tumors.
Neoplasm recurrence
Neuroendocrine tumors
Pancreas
Surgical oncology
Journal
Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
ISSN: 1873-4626
Titre abrégé: J Gastrointest Surg
Pays: United States
ID NLM: 9706084
Informations de publication
Date de publication:
07 2019
07 2019
Historique:
received:
03
08
2018
accepted:
10
10
2018
pubmed:
26
10
2018
medline:
22
7
2020
entrez:
25
10
2018
Statut:
ppublish
Résumé
Patients with early-stage pancreatic neuroendocrine tumors (PNETs) may develop metastatic recurrences despite undergoing potentially curative pancreas resections. We sought to identify factors predictive of metastatic recurrences and develop a prognostication strategy to predict recurrence-free survival (RFS) in resected PNETs. Patients with localized PNETs undergoing surgical resection between 1989 and 2015 were identified. Univariate and multivariate analysis were used to identify potential predictors of post-resection metastasis. A score-based prognostication system was devised using the identified factors. The bootstrap model validation methodology was utilized to estimate the external validity of the proposed prognostication strategy. Of the 140 patients with completely resected early-stage PNETs, overall 5- and 10-year RFS were 84.6% and 67.1%, respectively. The median follow-up was 56 months. Multivariate analysis identified tumor size > 5 cm, Ki-67 index 8-20%, lymph node involvement, and high histologic grade (G3, or Ki-67 > 20%) as independent predictors of post-resection metastatic recurrence. A scoring system based on these factors stratified patients into three prognostic categories with distinct 5-year RFS: 96.9%, 54.8%, and 33.3% (P < 0.0001). The bootstrap model validation methodology projected our proposed prognostication strategy to retain a high predictive accuracy even when applied in an external dataset (validated c-index of 0.81). The combination of tumor size, LN status, grade, and Ki-67 was identified as the most highly predictive indicators of metastatic recurrences in resected PNETs. The proposed prognostication strategy may help stratify patients for adjuvant therapies, enhanced surveillance protocols and future clinical trials.
Sections du résumé
BACKGROUND
Patients with early-stage pancreatic neuroendocrine tumors (PNETs) may develop metastatic recurrences despite undergoing potentially curative pancreas resections. We sought to identify factors predictive of metastatic recurrences and develop a prognostication strategy to predict recurrence-free survival (RFS) in resected PNETs.
METHODS
Patients with localized PNETs undergoing surgical resection between 1989 and 2015 were identified. Univariate and multivariate analysis were used to identify potential predictors of post-resection metastasis. A score-based prognostication system was devised using the identified factors. The bootstrap model validation methodology was utilized to estimate the external validity of the proposed prognostication strategy.
RESULTS
Of the 140 patients with completely resected early-stage PNETs, overall 5- and 10-year RFS were 84.6% and 67.1%, respectively. The median follow-up was 56 months. Multivariate analysis identified tumor size > 5 cm, Ki-67 index 8-20%, lymph node involvement, and high histologic grade (G3, or Ki-67 > 20%) as independent predictors of post-resection metastatic recurrence. A scoring system based on these factors stratified patients into three prognostic categories with distinct 5-year RFS: 96.9%, 54.8%, and 33.3% (P < 0.0001). The bootstrap model validation methodology projected our proposed prognostication strategy to retain a high predictive accuracy even when applied in an external dataset (validated c-index of 0.81).
CONCLUSIONS
The combination of tumor size, LN status, grade, and Ki-67 was identified as the most highly predictive indicators of metastatic recurrences in resected PNETs. The proposed prognostication strategy may help stratify patients for adjuvant therapies, enhanced surveillance protocols and future clinical trials.
Identifiants
pubmed: 30353489
doi: 10.1007/s11605-018-4011-7
pii: 10.1007/s11605-018-4011-7
pmc: PMC6736531
mid: NIHMS1046630
doi:
Substances chimiques
Ki-67 Antigen
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1392-1400Subventions
Organisme : RRD VA
ID : I01 RX000194
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA016042
Pays : United States
Organisme : NIDDK NIH HHS
ID : P30 DK041301
Pays : United States
Organisme : NIDDK NIH HHS
ID : T32 DK007180
Pays : United States
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