Predictors of nodal metastases in early stage HER2+ breast cancer: Deciding on treatment approach with neoadjuvant chemotherapy vs. upfront surgery

Faleh, Sohayb; Prakash, Ipshita; Eisenberg, Elisheva; Basik, Mark; Boileau, Jean François; Tejera, David; Panet, François; Buhlaiga, Najwa; Meterissian, Sarkis; Wong, Stéphanie

doi:10.1016/j.ejso.2023.03.226

Cited by 3 publications

(2 citation statements)

References 27 publications

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“…In the present study, the incidence of LNM was 48.1%, and age, CA19-9, and tumour diameter can be used as predictive factors for LNM in pCCA. In breast cancer, Faleh S et al [ 27 ] indicated that the proportion of axillary lymph node metastasis increases with younger age at diagnosis, and the highest proportion occurs when the age is less than 40. A SEER data-based study found that age ≤ 70 was an independent risk factor for LNM in gastric cancer [ 28 ].…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a novel preoperative clinical model for predicting lymph node metastasis in perihilar cholangiocarcinoma

Mao,

Shan,

et al. 2024

BMC Cancer

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Backgroud We aimed to develop a novel preoperative nomogram to predict lymph node metastasis (LNM) in perihilar cholangiocarcinoma (pCCA) patients. Methods 160 pCCA patients were enrolled at Lihuili Hospital from July 2006 to May 2022. A novel nomogram model was established to predict LNM in pCCA patients based on the independent predictive factors selected by the multivariate logistic regression model. The precision of the nomogram model was evaluated through internal and external validation with calibration curve statistics and the concordance index (C-index). Receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to evaluate and determine the clinical utility of the nomogram. Results Multivariate logistic regression demonstrated that age (OR = 0.963, 95% CI: 0.930–0.996, P = 0.030), CA19-9 level (> 559.8 U/mL vs. ≤559.8 U/mL: OR = 3.162, 95% CI: 1.519–6.582, P = 0.002) and tumour diameter (OR = 1.388, 95% CI: 1.083–1.778, P = 0.010) were independent predictive factors of LNM in pCCA patients. The C-index was 0.763 (95% CI: 0.667–0.860) and 0.677 (95% CI: 0.580–0.773) in training cohort and validation cohort, respectively. ROC curve analysis indicated the comparative stability and adequate discriminative ability of nomogram. The sensitivity and specificity were 0.820 and 0.652 in training cohort and 0.704 and 0.649 in validation cohort, respectively. DCA revealed that the nomogram model could augment net benefits in the prediction of LNM in pCCA patients. Conclusions The novel prediction model is useful for predicting LNM in pCCA patients and showed adequate discriminative ability and high predictive accuracy.

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Section: Discussionmentioning

confidence: 99%

Development and validation of a novel preoperative clinical model for predicting lymph node metastasis in perihilar cholangiocarcinoma

Mao,

Shan,

et al. 2024

BMC Cancer

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“…However, lymph nodes are still considered to be key players in the process of metastasis [1]. Lymph node status is a critical event that can affect staging, treatment, survival, and prognostic factors in patients with breast cancer [2][3][4]. Intraoperative histologic examination of the axillary lymph nodes is considered to be the gold standard for node staging [5].…”

Section: Introductionmentioning

confidence: 99%

Ability of dynamic contrast-enhanced magnetic resonance imaging to determine axillary sentinel lymph node status in patients with breast cancer

Xiao,

Wang,

Jin

et al. 2023

Preprint

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Purpose Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been confirmed to be a useful technique for identification of lymph node metastasis in patients with breast cancer. However, the value of DCE-MRI for the determination of sentinel lymph node (SLN) status [pN0, pN0(i+), pN1mi, or pN1] is unknown. The aim of this study was to investigate the ability of DCE-MRI to determine SLN status in patients with breast cancer. Methods Fifty-four women with breast cancer (mean age 50.30 ± 11.41 years) who underwent SLN biopsy, DCE-MRI, and axillary lymph node dissection between 2019 and 2021 were enrolled in the study. DCE-MRI kinetic parameters were investigated according to SLN status. Univariable and ordered logistic regression was used to identify risk factors according to SLN status. The diagnostic performance of the kinetic parameters was quantified by the area under the receiver-operating characteristic curve (AUC). Results The findings for DCE-MRI kinetic parameters according to SLN status were statistically significant. Ktrans was the strongest predictor of SLN status. The AUC of Ktrans for distinguishing between metastatic and nonmetastatic SLNs was 0.942 (95% confidence interval [CI] 0.887–0.997, P < 0.001), 0.937 (95% CI 0.874–1.000, P < 0.001) for distinguishing between pN0 to pN1mi and pN1, and 0.928 (95% CI 0.855–1.000, P < 0.001) for distinguishing between pN0 to pN0(i+) and pN1mi to pN1. Conclusion DCE-MRI is a useful diagnostic modality for detection of SLN metastasis. Ktrans is the best single parameter for determination of SLN status.

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Preoperative factors that predict pathologic nodal involvement in early-stage HER2+ breast cancer: selecting cT1cN0 patients for treatment with neoadjuvant chemotherapy versus upfront surgery

Faleh,

Prakash,

Salehi

et al. 2024

Breast Cancer Res Treat

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Predictors of nodal metastases in early stage HER2+ breast cancer: Deciding on treatment approach with neoadjuvant chemotherapy vs. upfront surgery

Cited by 3 publications

References 27 publications

Development and validation of a novel preoperative clinical model for predicting lymph node metastasis in perihilar cholangiocarcinoma

Development and validation of a novel preoperative clinical model for predicting lymph node metastasis in perihilar cholangiocarcinoma

Ability of dynamic contrast-enhanced magnetic resonance imaging to determine axillary sentinel lymph node status in patients with breast cancer

Preoperative factors that predict pathologic nodal involvement in early-stage HER2+ breast cancer: selecting cT1cN0 patients for treatment with neoadjuvant chemotherapy versus upfront surgery

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