Dataset Information

Medico-economic impact of MSKCC non-sentinel node prediction nomogram for ER-positive HER2-negative breast cancers.

ABSTRACT:

Background

Avoiding axillary lymph node dissection (ALND) for invasive breast cancers with isolated tumor cells or micrometastatic sentinel node biopsy (SNB) could decrease morbidity with minimal clinical significance.

Purpose

The aim of this study is to simulate the medico-economic impact of the routine use of the MSKCC non-sentinel node (NSN) prediction nomogram for ER+ HER2- breast cancer patients.

Methods

We studied 1036 ER+ HER2- breast cancer patients with a metastatic SNB. All had a complementary ALND. For each patient, we calculated the probability of the NSN positivity using the MSKCC nomogram. After validation of this nomogram in the population, we described how the patients' characteristics spread as the threshold value changed. Then, we performed an economic simulation study to estimate the total cost of caring for patients treated according to the MSKCC predictive nomogram results.

Results

A 0.3 threshold discriminate the type of sentinel node (SN) metastases: 98.8% of patients with pN0(i+) and 91.6% of patients with pN1(mic) had a MSKCC score under 0.3 (false negative rate = 6.4%). If we use the 0.3 threshold for economic simulation, 43% of ALND could be avoided, reducing the costs of caring by 1 051 980 EUROS among the 1036 patients.

Conclusion

We demonstrated the cost-effectiveness of using the MSKCC NSN prediction nomogram by avoiding ALND for the pN0(i+) or pN1(mic) ER+ HER2- breast cancer patients with a MSKCC score of less than or equal to 0.3.

SUBMITTER: Bonsang-Kitzis H

PROVIDER: S-EPMC5328272 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Medico-economic impact of MSKCC non-sentinel node prediction nomogram for ER-positive HER2-negative breast cancers.

Bonsang-Kitzis Hélène H Mouttet-Boizat Delphine D Guillot Eugénie E Feron Jean-Guillaume JG Fourchotte Virginie V Alran Séverine S Pierga Jean-Yves JY Cottu Paul P Lerebours Florence F Stevens Denise D Vincent-Salomon Anne A Sigal-Zafrani Brigitte B Campana François F Rouzier Roman R Reyal Fabien F

PloS one 20170227 2

<h4>Background</h4>Avoiding axillary lymph node dissection (ALND) for invasive breast cancers with isolated tumor cells or micrometastatic sentinel node biopsy (SNB) could decrease morbidity with minimal clinical significance.<h4>Purpose</h4>The aim of this study is to simulate the medico-economic impact of the routine use of the MSKCC non-sentinel node (NSN) prediction nomogram for ER+ HER2- breast cancer patients.<h4>Methods</h4>We studied 1036 ER+ HER2- breast cancer patients with a metastati ...[more]

PMID: 28241044

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Project description:BackgroundDual-targeted therapy is currently the standard adjuvant treatment for human epidermal growth factor receptor 2-positive (HER2+) and lymph node-positive (LN+) breast cancer. However, the optimal therapeutic strategy for patients with HER2+ and lymph node-negative (LN-) breast cancer remains unclear. This population-based study aimed to explore the factors associated with survival in patients with HER2+ and LN- breast cancer, and develop a survival-predicting nomogram in the era of trastuzumab-based single-targeted therapy.MethodsWe collected the clinicopathological information of HER2+ and LN- breast cancer patients who underwent chemotherapy and surgery from The Surveillance, Epidemiology, and End Results (SEER) database (2010-2016, the Trastuzumab-based single-targeted therapy era). We subsequently explored the risk factors for breast cancer-specific survival (BCSS) and overall survival (OS) using a Cox proportional hazards regression model, aiming to identify subgroups with worse prognosis, which would indicate potential demand for dual-targeted therapy. Three- and 5-year survival probability-predictive nomograms were established and subjected to bootstrap internal validation. The concordance index (C-index) and calibration curve were applied to evaluate the performance of the model.ResultsAfter data cleansing, a total of 13,755 patients were included in the current analysis. Using univariate and multivariate Cox proportional hazards regression, higher clinical T stage, hormone receptors-negative (HR-), and partial mastectomy without radiotherapy were identified as independent risk factors for BCSS and OS in patients with HER2+ and LN- breast cancer. Nomograms for 3- and 5-year BCSS and OS incorporating the selected prognostic factors were established. Calibration curves verified good consistency between the actual and nomogram-predicted survival probability. The C-index values of the BCSS and OS predictions and 95% confidence interval (CI) were 0.773 (0.740-0.806) and 0.764 (0.737-0.791), respectively.ConclusionsHigher clinical T stage, HR-, and partial mastectomy without radiotherapy predicted worse prognosis in patients with HER2+ and LN- breast cancer. In clinical practice, patients can be recommended for single-targeted or dual-targeted therapy according to the individualized factors.

Project description:BackgroundTreatment strategies for various subtypes of breast cancer (BC) are different based on their distinct molecular characteristics. Therefore, it is very important to identify key differentially expressed genes (DEGs) between ER-positive/HER2-negative BC and ER-negative/HER2-negative BC.MethodsGene expression profiles of GSE22093 and GSE23988 were obtained from the Gene Expression Omnibus database. There were 74 ER-positive/HER2-negative BC tissues and 85 ER-negative/HER2-negative BC tissues in the two profile datasets. DEGs between ER-positive/HER2-negative tissues and ER-negative/HER2-negative BC tissues were identified by the GEO2R tool. The common DEGs among the two datasets were detected with Venn software online. Next, we made use of the Database for Annotation, Visualization and Integrated Discovery to analyze enriched Kyoto Encyclopedia of Gene and Genome (KEGG) pathways and gene ontology terms. Then, the protein-protein interactions (PPIs) of these DEGs were visualized by Cytoscape with the Search Tool for the Retrieval of Interacting Genes. Of the proteins in the PPI network, Molecular Complex Detection plug-in analysis identified nine core upregulated genes and one core downregulated gene. UALCAN and Gene Expression Profiling Interactive Analysis were applied to determine the expression of these 10 genes in BC. Furthermore, for the analysis of overall survival among those genes, the Kaplan-Meier method was implemented.ResultsNinety-three common DEGs (63 upregulated and 30 downregulated) were identified. KEGG pathway enrichment analysis showed that upregulated DEGs were particularly enriched in the progesterone-mediated oocyte maturation pathway. In addition, PGR might be a prognostic biomarker for ER-positive/HER2-negative BC. CCND1 is a poor prognostic biomarker for ER-positive/HER2-negative BC and ER-negative/HER2-negative BC. Moreover, TFF1, AGR2 and EGFR might be predictive biomarkers of node metastasis in ER-positive/HER2-negative BC and ER-negative/HER2-negative BC.ConclusionsCCND1, AGR2, PGR, TFF1 and EGFR are the key DEGs between ER-positive/HER2-negative BC and ER-negative/HER2-negative BC. Further studies are required to confirm the functions of the identified genes.

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Dataset Information

Medico-economic impact of MSKCC non-sentinel node prediction nomogram for ER-positive HER2-negative breast cancers.

Background

Purpose

Methods

Results

Conclusion

Publications

Medico-economic impact of MSKCC non-sentinel node prediction nomogram for ER-positive HER2-negative breast cancers.

Similar Datasets

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