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

Skarping, Ida LU orcid ; Nilsson, Kristoffer ; Dihge, Looket LU ; Fridhammar, Adam ; Ohlsson, Mattias LU orcid ; Huss, Linnea LU ; Bendahl, Pär Ola LU ; Steen Carlsson, Katarina LU orcid and Rydén, Lisa LU orcid (2022) In Breast Cancer Research and Treatment 194(3). p.577-586
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... (More)

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 mastectomy. The results are presented as cost (€) and quality-adjusted life years (QALYs) per 1000 patients. Results: All three scenarios of the NILS model reduced total costs (–€93,244 to –€398,941 per 1000 patients). The overall health benefit allowing for the impact of SLNB complications was a net health gain (7.0–26.9 QALYs per 1000 patients). Sensitivity analyses disregarding reduced quality of life from lymphedema showed a small loss in total health benefits (0.4–4.0 QALYs per 1000 patients) because of the reduction in total life years (0.6–6.5 life years per 1000 patients) after reduced adjuvant treatment. Subgroup analyses showed greater cost reductions and QALY gains in patients undergoing BCS. Conclusion: Implementing the NILS model to identify patients with low risk for nodal metastases was associated with substantial cost reductions and likely overall health gains, especially in patients undergoing BCS.

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author
; ; ; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Artificial neural network, Axillary lymph nodes, Breast neoplasm, Cost-effectiveness, Staging
in
Breast Cancer Research and Treatment
volume
194
issue
3
pages
10 pages
publisher
Springer
external identifiers
  • scopus:85133495096
  • pmid:35790694
ISSN
0167-6806
DOI
10.1007/s10549-022-06636-x
language
English
LU publication?
yes
id
abef86f2-b108-4117-bbac-63af2e8cc122
date added to LUP
2022-09-23 15:12:22
date last changed
2024-04-15 19:35:36
@article{abef86f2-b108-4117-bbac-63af2e8cc122,
  abstract     = {{<p>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 mastectomy. The results are presented as cost (€) and quality-adjusted life years (QALYs) per 1000 patients. Results: All three scenarios of the NILS model reduced total costs (–€93,244 to –€398,941 per 1000 patients). The overall health benefit allowing for the impact of SLNB complications was a net health gain (7.0–26.9 QALYs per 1000 patients). Sensitivity analyses disregarding reduced quality of life from lymphedema showed a small loss in total health benefits (0.4–4.0 QALYs per 1000 patients) because of the reduction in total life years (0.6–6.5 life years per 1000 patients) after reduced adjuvant treatment. Subgroup analyses showed greater cost reductions and QALY gains in patients undergoing BCS. Conclusion: Implementing the NILS model to identify patients with low risk for nodal metastases was associated with substantial cost reductions and likely overall health gains, especially in patients undergoing BCS.</p>}},
  author       = {{Skarping, Ida and Nilsson, Kristoffer and Dihge, Looket and Fridhammar, Adam and Ohlsson, Mattias and Huss, Linnea and Bendahl, Pär Ola and Steen Carlsson, Katarina and Rydén, Lisa}},
  issn         = {{0167-6806}},
  keywords     = {{Artificial neural network; Axillary lymph nodes; Breast neoplasm; Cost-effectiveness; Staging}},
  language     = {{eng}},
  number       = {{3}},
  pages        = {{577--586}},
  publisher    = {{Springer}},
  series       = {{Breast Cancer Research and Treatment}},
  title        = {{The implementation of a noninvasive lymph node staging (NILS) preoperative prediction model is cost effective in primary breast cancer}},
  url          = {{http://dx.doi.org/10.1007/s10549-022-06636-x}},
  doi          = {{10.1007/s10549-022-06636-x}},
  volume       = {{194}},
  year         = {{2022}},
}