Annals of surgical oncology · 2018
A Predictive Model for Axillary Node Pathologic Complete Response after Neoadjuvant Chemotherapy for Breast Cancer.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Kantor Olga, Sipsy Lynn McNulty, Yao Katharine, James Ted A
Аннотация
BACKGROUND: Recent trials have suggested the feasibility of performing a sentinel lymph node biopsy (SNB) following neoadjuvant chemotherapy (NAC). The selection of suitable patients for this approach remains controversial. We developed a predictive model to identify patients most likely to benefit from SNB following NAC.
METHODS: The National Cancer Data Base was used to identify patients with clinically node positive (cN+) breast cancer undergoing NAC followed by breast surgery and axillary lymph node dissection (ALND). Patients were randomly assigned to a 70% testing or 30% validation cohort for model development. A predictive model was built based on significant factors associated with pathologic nodal response (pN0) and breast response.
RESULTS: Using the testing cohort (n = 13,396), multivariate regression was used to identify predictors of pN0 based on preoperative factors. Younger age, hormone receptor (HR)-negative/Her2-negative, HR-positive/Her2-positive, HR-negative/Her2-positive, high-grade, ductal histology, cN1 versus cN2, and extent of breast response were all significant independent predictors of pN0 on adjusted analysis. The odds ratios translated into a 10-point scale correlating to a stepwise increase in pN0 response. The area under the curve for the ROC curves for the testing and validation cohorts was 0.781 and 0.788, respectively (p < 0.01).
CONCLUSIONS: Our model incorporates known preoperative factors to predict the likelihood of pN0 response in patients with cN+ disease who undergo NAC. For patients with high scores, SNB should be considered over ALND, because these patients have a greater likelihood of having negative nodes at final pathology.
METHODS: The National Cancer Data Base was used to identify patients with clinically node positive (cN+) breast cancer undergoing NAC followed by breast surgery and axillary lymph node dissection (ALND). Patients were randomly assigned to a 70% testing or 30% validation cohort for model development. A predictive model was built based on significant factors associated with pathologic nodal response (pN0) and breast response.
RESULTS: Using the testing cohort (n = 13,396), multivariate regression was used to identify predictors of pN0 based on preoperative factors. Younger age, hormone receptor (HR)-negative/Her2-negative, HR-positive/Her2-positive, HR-negative/Her2-positive, high-grade, ductal histology, cN1 versus cN2, and extent of breast response were all significant independent predictors of pN0 on adjusted analysis. The odds ratios translated into a 10-point scale correlating to a stepwise increase in pN0 response. The area under the curve for the ROC curves for the testing and validation cohorts was 0.781 and 0.788, respectively (p < 0.01).
CONCLUSIONS: Our model incorporates known preoperative factors to predict the likelihood of pN0 response in patients with cN+ disease who undergo NAC. For patients with high scores, SNB should be considered over ALND, because these patients have a greater likelihood of having negative nodes at final pathology.
Предметные рубрики MeSH
Age FactorsAgedArea Under CurveAxillaBreast NeoplasmsCarcinoma, Ductal, BreastCarcinoma, LobularChemotherapy, AdjuvantDatabases, FactualFemaleHumansLymph Node ExcisionLymphatic MetastasisMiddle AgedModels, BiologicalNeoadjuvant TherapyNeoplasm GradingPatient SelectionROC CurveErb-b2 Receptor Tyrosine KinasesReceptors, EstrogenReceptors, ProgesteroneSentinel Lymph NodeSentinel Lymph Node BiopsyTreatment Outcome