The implementation of a noninvasive lymph node staging (NILS) preoperative prediction model is cost effective in primary breast cancer.

ABSTRACT:

Purpose

The need for sentinel lymph node biopsy (SLNB) in clinically node-negative (cN0) patients is currently questioned. Our objective was to investigate the cost-effectiveness of a preoperative noninvasive lymph node staging (NILS) model (an artificial neural network model) for predicting pathological nodal status in patients with cN0 breast cancer (BC).

Methods

A health-economic decision-analytic model was developed to evaluate the utility of the NILS model in reducing the proportion of cN0 patients with low predicted risk undergoing SLNB. The model used information from a national registry and published studies, and three sensitivity/specificity scenarios of the NILS model were evaluated. Subgroup analysis explored the outcomes of breast-conserving surgery (BCS) or mast

SUBMITTER: Skarping I 

PROVIDER: S-EPMC9287207 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature