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• W2966567327 abstract "Background: Histologic subtypes of appendiceal cancer vary in their propensity for metastases to regional lymph nodes (LN). A predictive model would help direct subsequent surgical therapy. Methods: The National Cancer Database was queried for patients with appendiceal cancer undergoing surgery between 1998 and 2012. Multivariable logistic regression was used to develop a predictive model of LN metastases which was internally validated using Brier score and Area under the Curve (AUC). Results: A total of 21,647 patients were identified, of whom 9079 (41.9%) had node negative disease, 4575 (21.1%) node positive disease, and 7993 (36.9%) unknown LN status. The strongest predictors of LN positivity were histology (carcinoid tumors OR 12.78, 95% CI 9.01–18.12), increasing T Stage (T3 OR 3.36, 95% CI 2.52–4.50, T4 OR 6.30, 95% CI 4.71–8.42), and tumor grade (G3 OR 5.55, 95% CI 4.78–6.45, G4 OR 5.98, 95% CI 4.30–8.31). The coefficients from the regression analysis were used to construct a calculator that generated predicted probabilities of LN metastases given certain inputs. Internal validation of the overall model showed an AUC of 0.75 (95% CI 0.74–0.76) and Brier score of 0.188. Histology-specific predictive models were also constructed with an AUC that varied from 0.669 for signet cell to 0.75 for goblet cell tumors. Conclusions: The risk for nodal metastases in patients with appendiceal cancers can be quantified with reasonable accuracy using a predictive model incorporating patient age, sex, tumor histology, T-stage, and grade. This can help inform clinical decision making regarding the need for a right hemicolectomy following appendectomy." @default.
• W2966567327 created "2019-08-13" @default.
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• W2966567327 date "2019-07-29" @default.
• W2966567327 modified "2023-09-24" @default.
• W2966567327 title "A Predictive Model for Nodal Metastases in Patients With Appendiceal Cancers" @default.
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• W2966567327 doi "https://doi.org/10.1097/sla.0000000000003501" @default.
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