Direct comparison of three different mathematical models in two independent datasets of EUSOMA certified centers to predict recurrence and survival in estrogen receptor-positive breast cancer: impact on clinical practice

Iacuzzo, Cristiana; Giudici, Fabiola; Scomersi, Serena; Ceccherini, Rita; Zanconati, Fabrizio; Generali, Daniele; Bortul, Marina

doi:10.1007/s10549-021-06144-4

Cited by 2 publications

(4 citation statements)

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“…The estimated coefficients of the selected variables were used to derive an unscaled score which was further scaled 0–100 to obtain the final ALND-predict score. 30 , 31 A receiver operating characteristic (ROC) curve analysis was performed to evaluate the area under curve (AUC) with 95% CI of the model and the Youden Index was calculated to identify an optimal cutoff point. 30 , 31 The AUC gives an indication of the discriminatory performance of the model.…”

Section: Methodsmentioning

confidence: 99%

“… 30 , 31 A receiver operating characteristic (ROC) curve analysis was performed to evaluate the area under curve (AUC) with 95% CI of the model and the Youden Index was calculated to identify an optimal cutoff point. 30 , 31 The AUC gives an indication of the discriminatory performance of the model. An AUC of 0.5 indicates no discriminative performance, whereas an AUC of 1.0 indicates perfect discrimination.…”

Section: Methodsmentioning

confidence: 99%

“…An AUC of 0.5 indicates no discriminative performance, whereas an AUC of 1.0 indicates perfect discrimination. 31 A calibration of the ALND-predict continuous and dichotomic models was performed with the Hosmer–Lemershow test with g > p + 1. 32 Bootstrap analysis with calculation of bias-corrected and accelerated (BCa) 95% CI was undertaken to validate the predictors in artificial testing cohorts after 5000 resamplings.…”

Section: Methodsmentioning

confidence: 99%

Section: Study Objectives and Statistical Analysesmentioning

confidence: 99%

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Nonsentinel Axillary Lymph Node Status in Clinically Node-Negative Early Breast Cancer After Primary Systemic Therapy and Positive Sentinel Lymph Node: A Predictive Model Proposal

et al. 2023

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Background In clinically node-negative (cN0) early stage breast cancer (EBC) undergoing primary systemic treatment (PST), post-treatment positive sentinel lymph node (SLN+) directs axillary lymph node dissection (ALND), with uncertain impacts on outcomes and increased morbidities. Patients and Methods We conducted an observational study on imaging-confirmed cN0 EBC, who underwent PST and breast surgery that resulted in SLN+ and underwent ALND. The association among baseline/postsurgical clinic–pathological factors and positive nonsentinel additional axillary lymph nodes (non-SLN+) was analyzed with logistic regression. LASSO regression (LR) identified variables to include in a predictive score of non-SLN+ (ALND-predict). The accuracy and calibration were assessed, an optimal cut-point was then identified, and in silico validation with bootstrap was undertaken. Results Non-SLN+ were detected in 22.2% cases after ALND. Only progesterone receptor (PR) levels and macrometastatic SLN+ were independently associated to non-SLN+. LR identified PR, Ki67, and type and number of SLN+ as the most efficient covariates. The ALND-predict score was built based on their LR coefficients, showing an area under the curve (AUC) of 0.83 and an optimal cut-off of 63, with a negative predictive value (NPV) of 0.925. Continuous and dichotomic scores had a good fit (p = 0.876 and p = 1.00, respectively) and were independently associated to non-SLN+ [adjusted odds ratio (aOR): 1.06, p = 0.002 and aOR: 23.77, p < 0.001, respectively]. After 5000 bootstrap-adjusted retesting, the estimated bias-corrected and accelerated 95%CI included the aOR. Conclusions In cN0 EBC with post-PST SLN+, non-SLN+ at ALND are infrequent (~22%) and independently associated to PR levels and macrometastatic SLN. ALND-predict multiparametric score accurately predicted absence of non-SLN involvement, identifying most patients who could be safely spared unnecessary ALND. Prospective validation is required.

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