Is sentinel lymph node biopsy alone accurate for breast cancer mastectomy? Results of a cohort study of 2423 patients.

Houvenaeghel, Gilles; Classe, Jean Marc; Blache, Guillaume; Mazouni, Chafika; Reyal, Fabien; Gimbergues, Pierre; Daraı̈, Émile; Azuar, A.-S.; Colombo, Pierre; Bannier, Marie; Lambaudie, Éric; Cohen, Monique

doi:10.21203/rs.2.14318/v1

Cited by 2 publications

(2 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In a previous publication, we reported results on paired numbers of patients with SN micro-metastases from the French cohort. The results were in favor of cALND compared to no cALND in patients undergoing mastectomy for BC with SN micro-metastases [ 21 ]. The results of the ongoing SERC and SENOMIC trials were therefore awaited in order to provide sufficient evidence to suggest the omission of cALND.…”

Section: Discussionmentioning

confidence: 99%

External Validation of the SERC Trial Population: Comparison with the Multicenter French Cohort, the Swedish and SENOMIC Trial Populations for Breast Cancer Patients with Sentinel Node Micro-Metastasis

Houvenaeghel

Hajj

Barrou

et al. 2020

Cancers

Self Cite

View full text Add to dashboard Cite

Many trials confirmed the safety of omitting axillary dissection in the selected patients treated for early breast cancer. The external validity of these trials is questionable. Our study aimed to evaluate the accuracy of the French population representativity in the SERC trial and the differences between these two populations as well as comparing the French and the Swedish populations (the SENOMIC trial population and the Swedish National Breast Cancer Registry (NKBC) cohort) of patients with sentinel node (SN) micro-metastasis. A higher rate of smaller tumors and grade 1 tumors was observed in the French cohort when compared to the SERC population. Our findings conclude that both French populations show similar characteristics. Positive non-sentinel node (NSN) rates at completion axillary lymph node dissection (ALND) were 10.28 % and 11.3 % in the SERC trial and French cohort, respectively (p = 0.5). The rate of grade 1 tumors was lower in the SENOMIC trial (16.2%) and in the NKBC cohort (17.4%) compared to the SERC trial population (27.3%) and the French cohort (34.4%). Our findings in addition to the previously demonstrated concordance between the SENOMIC trial and the NKBC populations imply that the results of both the SERC and the SENOMIC trials can be applied to both French and Swedish real populations.

show abstract

Section: Discussionmentioning

confidence: 99%

External Validation of the SERC Trial Population: Comparison with the Multicenter French Cohort, the Swedish and SENOMIC Trial Populations for Breast Cancer Patients with Sentinel Node Micro-Metastasis

Houvenaeghel

Hajj

Barrou

et al. 2020

Cancers

Self Cite

View full text Add to dashboard Cite

show abstract

“…Nevertheless, the reliability and/or distribution of data, such as multifocality, may change in the preoperative setting [40], which could change the prerequisites for predicting LVI status. Given the growing evidence on the significance of LVI status as a predictor of axillary N status [7,11,22,41], further evaluation of the presented LVI model is warranted.…”

Section: Comparison With Prior Studiesmentioning

confidence: 99%

Noninvasive Staging of Lymph Node Status (NILS) in Breast Cancer using Machine Learning: External Validation and Further Model Development

Hjärtström

Dihge

Bendahl

et al. 2023

Preprint

View full text Add to dashboard Cite

Background:Most patients diagnosed with breast cancer present with node–negative disease. Sentinel lymph node biopsy (SLNB) is routinely used to stage the axilla, leaving patients with healthy axillary lymph nodes without therapeutic effects but at risk of morbidities from the intervention. Numerous studies have developed nodal (N) status prediction models for noninvasive axillary staging using postoperative data or imaging features that are not part of the diagnostic workup. Lymphovascular invasion (LVI) is a top-ranked predictor of N metastasis; however, it is challenging to assess preoperatively.Objective:To externally validate a multilayer perceptron (MLP) model for noninvasive lymph node staging (NILS) in a large population-based register cohort (n=18 633) while developing a new N MLP in the same cohort. Data were extracted from the Swedish National Quality Register for Breast Cancer (NKBC), 2014–2017, comprising only routinely and preoperatively available documented clinicopathological variables. Furthermore, we aimed to develop and validate an LVI MLP to predict missing values of LVI status to increase the preoperative feasibility of the original NILS model.Methods:Three non-overlapping cohorts were used for model development and validation. Four N MLPs and one LVI MLP were developed using 11–12 routinely available predictors. Three N models were used to account for the different availabilities of LVI status in the cohorts and external validation in NKBC. The fourth N model was developed for 80% of NKBC cases (n=14 906) and validated in the remaining 20% (n=3727). Three alternatives for imputing missing values of the LVI status were compared using the LVI model. The discriminatory capacity was evaluated by validation area under the receiver operating characteristics curve (AUC) in three of the N models. The clinical feasibility of the models was evaluated using calibration and decision curve analyses.Results:External validation of the original NILS model was performed in NKBC (AUC 0.699, 95% CI: 0.690–0.708) with good calibration and the potential of sparing 16% of patients with node-negative disease from SLNB. The LVI model was externally validated (AUC 0.747, 95% CI: 0.694–0.799) with good calibration but did not improve the discriminatory performance of the N models. The new N model was developed in NKBC without information on LVI (AUC 0.709, 95% CI: 0.688–0.729) with excellent calibration in the hold-out internal validation cohort, resulting in the potential omission of 24% of patients from unnecessary SLNB.Conclusions:The NILS model was externally validated in NKBC, where the imputation of LVI status did not improve the model′s discriminatory performance. A new N model demonstrated the feasibility of using register data comprising only the variables available in the preoperative setting for NILS using machine learning. Future steps include ongoing preoperative validation of the NILS model and extending the model with, for example, mammography images.

show abstract

Is sentinel lymph node biopsy alone accurate for breast cancer mastectomy? Results of a cohort study of 2423 patients.

Cited by 2 publications

References 26 publications

External Validation of the SERC Trial Population: Comparison with the Multicenter French Cohort, the Swedish and SENOMIC Trial Populations for Breast Cancer Patients with Sentinel Node Micro-Metastasis

External Validation of the SERC Trial Population: Comparison with the Multicenter French Cohort, the Swedish and SENOMIC Trial Populations for Breast Cancer Patients with Sentinel Node Micro-Metastasis

Noninvasive Staging of Lymph Node Status (NILS) in Breast Cancer using Machine Learning: External Validation and Further Model Development

Contact Info

Product

Resources

About