The Role of Alternative Lymph Node Classification Systems in Gastroenteropancreatic Neuroendocrine Neoplasms (GEP-NEN): Superiority of a LODDS Scheme Over N Category in Pancreatic NEN (pNEN).
Sarah KriegJohannes TunkSascha VaghiriDimitrios PrassasHenning JannRaphael MohrSven Heiko LoosenChristoph RoderburgSebastian MaasbergNehara BegumTom LueddeMatthias SchottFrederik GieselWolfram Trudo KnoefelAndreas Kriegnull nullPublished in: Hormone and metabolic research = Hormon- und Stoffwechselforschung = Hormones et metabolisme (2023)
Lymph node (LN) involvement in gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN) has been reported to have prognostic and therapeutic implications. Numerous novel LN classifications exist; however, no comparison of their prognostic performance for GEP-NEN has been done yet. Using a nationwide cohort from the German Neuroendocrine Tumor (NET) Registry, the prognostic and discriminatory power of different LN ratio (LNR) and log odds of metastatic LN (LODDS) classifications were investigated using multivariate Cox regression and C-statistics in 671 patients with resected GEP-NEN. An increase in positive LN (pLN), LNR, and LODDS was associated with advanced tumor stages, distant metastases, and hormonal functionality. However, none of the alternative LN classifications studied showed discriminatory superiority in predicting prognosis over the currently used N category. Interestingly, in a subgroup analysis, one LODDS classification was identified that might be most appropriate for patients with pancreatic NEN (pNEN). On this basis, a nomogram was constructed to estimate the prognosis of pNEN patients after surgery. In conclusion, a more accurate classification of LN status may allow a more precise prediction of overall survival and provide the basis for individualized strategies for postoperative treatment and surveillance especially for patients with pNEN.
Keyphrases
- lymph node
- machine learning
- deep learning
- end stage renal disease
- neoadjuvant chemotherapy
- sentinel lymph node
- squamous cell carcinoma
- prognostic factors
- chronic kidney disease
- ejection fraction
- newly diagnosed
- small cell lung cancer
- public health
- high resolution
- randomized controlled trial
- patients undergoing
- adipose tissue
- wastewater treatment
- peritoneal dialysis
- metabolic syndrome
- data analysis
- open label
- replacement therapy
- solid state