Assessment of the Risk of Nodal Involvement in Rectal Neuroendocrine Neoplasms: The NOVARA Score, a Multicentre Retrospective Study.
Angela Dalia RicciSara PuscedduFrancesco PanzutoFabio GelsominoSara MassironiClaudio Giovanni De AngelisRoberta ModicaGianluca RiccoMartina TorchioMaria RinzivilloNatalie PrinziFelice RizziGiuseppe LambertiDavide CampanaPublished in: Journal of clinical medicine (2022)
Rectal neuroendocrine tumors (r-NETs) are rare tumors with overall good prognosis after complete resection. However, there is no consensus on the extension of lymphadenectomy or regarding contraindications to extensive resection. In this study, we aim to identify predictive factors that correlate with nodal metastasis in patients affected by G1-G2 r-NETs. A retrospective analysis of G1-G2 r-NETs patients from eight tertiary Italian centers was performed. From January 1990 to January 2020, 210 patients were considered and 199 were included in the analysis. The data for nodal status were available for 159 cases. The nodal involvement rate was 9%. A receiver operating characteristic (ROC) curve analysis was performed to identify the diameter (>11.5 mm) and Ki-67 (3.5%), respectively, as cutoff values to predict nodal involvement. In a multivariate analysis, diameter > 11.5 mm and vascular infiltration were independently correlated with nodal involvement. A risk scoring system was constructed using these two predictive factors. Tumor size and vascular invasion are predictors of nodal involvement. In addition, tumor size > 11.5 mm is used as a driving parameter of better-tailored treatment during pre-operative assessment. Data from prospective studies are needed to validate these results and to guide decision-making in r-NETs patients in clinical practice.
Keyphrases
- end stage renal disease
- lymph node
- newly diagnosed
- ejection fraction
- chronic kidney disease
- prognostic factors
- clinical practice
- early stage
- randomized controlled trial
- electronic health record
- deep learning
- minimally invasive
- wastewater treatment
- artificial intelligence
- patient reported
- smoking cessation
- cell migration