Is There a Role for Surgery in Patients with Neuroendocrine Tumors of the Esophagus? A Contemporary View from the NCDB.
Journal
Annals of surgical oncology
ISSN: 1534-4681
Titre abrégé: Ann Surg Oncol
Pays: United States
ID NLM: 9420840
Informations de publication
Date de publication:
Mar 2020
Mar 2020
Historique:
received:
31
03
2019
pubmed:
13
10
2019
medline:
20
11
2020
entrez:
13
10
2019
Statut:
ppublish
Résumé
Esophageal neuroendocrine tumors (eNETs) are exceedingly rare, aggressive and have a poor prognosis. Treatment guidelines are ill-defined and mainly based on evidence from case reports and analogous experiences drawn from similar disease sites. The NCDB was reviewed for histologically confirmed stage I-III, primary eNETs from 2006 to 2014. Patients were grouped into whether or not they underwent primary tumor resection. Univariate, multivariable, and full bipartite propensity score (PS) adjusted Cox regression analyses were used to assess overall and relative survival differences. A total of 250 patients were identified. Mean age was 65.0 (standard deviation [SD] 11.9) years, and 174 (69.6%) patients were male. Most patients had stage III disease (n = 136, 54.4%), and the most common type of NET was small cell eNET (n = 111, 44.4%). Chemotherapy was used in 186 (74.4%), radiation therapy in 178 (71.2%), and oncological resection was performed in 69 (27.6%) patients. Crude 2-year survival rates were higher in the operated (57.3%) compared with the nonoperated group (35.2%; p < 0.001). The survival benefit held true after multivariable adjustment (hazard ratio [HR] 0.47, 95% confidence interval [CI] 0.32-0.69, p < 0.001). After full bipartite PS adjustment analysis, survival was longer for patients who received a surgical resection compared with those who did not (HR 0.48, 95% CI 0.31-0.75, p = 0.003) with a corresponding 2-year overall survival rate of 63.3% (95% CI 52.0-77.2) versus 38.8% (95% CI 30.9-48.8), respectively. Multimodal treatment that includes surgery is associated with better overall survival for eNETs. Additional research is needed to more definitively identify patients who benefit from esophagectomy and to establish an appropriate treatment algorithm.
Sections du résumé
BACKGROUND
BACKGROUND
Esophageal neuroendocrine tumors (eNETs) are exceedingly rare, aggressive and have a poor prognosis. Treatment guidelines are ill-defined and mainly based on evidence from case reports and analogous experiences drawn from similar disease sites.
METHODS
METHODS
The NCDB was reviewed for histologically confirmed stage I-III, primary eNETs from 2006 to 2014. Patients were grouped into whether or not they underwent primary tumor resection. Univariate, multivariable, and full bipartite propensity score (PS) adjusted Cox regression analyses were used to assess overall and relative survival differences.
RESULTS
RESULTS
A total of 250 patients were identified. Mean age was 65.0 (standard deviation [SD] 11.9) years, and 174 (69.6%) patients were male. Most patients had stage III disease (n = 136, 54.4%), and the most common type of NET was small cell eNET (n = 111, 44.4%). Chemotherapy was used in 186 (74.4%), radiation therapy in 178 (71.2%), and oncological resection was performed in 69 (27.6%) patients. Crude 2-year survival rates were higher in the operated (57.3%) compared with the nonoperated group (35.2%; p < 0.001). The survival benefit held true after multivariable adjustment (hazard ratio [HR] 0.47, 95% confidence interval [CI] 0.32-0.69, p < 0.001). After full bipartite PS adjustment analysis, survival was longer for patients who received a surgical resection compared with those who did not (HR 0.48, 95% CI 0.31-0.75, p = 0.003) with a corresponding 2-year overall survival rate of 63.3% (95% CI 52.0-77.2) versus 38.8% (95% CI 30.9-48.8), respectively.
CONCLUSIONS
CONCLUSIONS
Multimodal treatment that includes surgery is associated with better overall survival for eNETs. Additional research is needed to more definitively identify patients who benefit from esophagectomy and to establish an appropriate treatment algorithm.
Identifiants
pubmed: 31605338
doi: 10.1245/s10434-019-07847-1
pii: 10.1245/s10434-019-07847-1
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM