Which prediction models best identify additional axillary disease after a positive sentinel node biopsy for breast cancer?

• Published in: Breast cancer research and treatment Vol. 133; no. 2; pp. 695 - 702
• Main Authors: Berrang, Tanya S., Lesperance, Mary, Truong, Pauline T., Walter, Caroline, Hayashi, Allen H., Olivotto, Ivo A.
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01-06-2012; Springer; Springer Nature B.V
• Subjects: Adult; Aged; Aged, 80 and over; Analysis; Axilla; Biological and medical sciences; Biopsy; Breast cancer; Breast Neoplasms - diagnosis; Breast Neoplasms - pathology; Cancer research; Cancer therapies; Clinical Trial; Clinical trials; Cohort Studies; Computer Simulation; Female; Gynecology. Andrology. Obstetrics; Humans; Internet; Lymph Nodes - pathology; Lymphatic Metastasis - diagnosis; Lymphatic system; Mammary gland diseases; Medical sciences; Medicine; Medicine & Public Health; Middle Aged; Models, Statistical; Neoplasm Grading; Neoplasm Staging; Oncology; Reproducibility of Results; Risk factors; ROC Curve; Sensitivity and Specificity; Sentinel Lymph Node Biopsy; Tumors; Validation; Breast cancer; Prediction; Sentinel lymph node biopsy; Breast disease; Disease; Sentinel lymph node; Node; Malignant tumor; Mammary gland diseases; Anatomic pathology; Biopsy; Models; Predictive factor; Cancer; Axillary
• ISSN: 0167-6806; 1573-7217
• DOI: 10.1007/s10549-012-1991-y

To determine which web-based model best identifies women at low risk of further axillary disease after a positive sentinel lymph node (SLN+) biopsy. 673 women with T1-2cN0M0 SNB+ breast cancer who underwent completion axillary dissection (AxD) were identified. A subgroup not eligible to avoid AxD as part of the Z0011 study was defined (Z0011 exclusion group). Predicted risk of further axillary disease was generated using seven web-based models. “Low risk” was defined as a ≤10% risk of further axillary disease. False negative (“low risk” prediction but AxD+) rates (FNRs), area under the receiver operating characteristic curve (AUC), and Brier score were determined for each model. 6 of 7 models identified “low risk” patients but FNRs ranged from 14 to 30%. The Stanford and Memorial Sloan-Kettering (MSKCC) models had the best FNRs. FNRs were lower with SLN micrometastasis (7–15%) and higher in the Z0011 exclusion group (21–41%). All models under-predicted further nodal disease in low risk patients and over-predicted in higher-risk patients. The Stanford and MSKCC models were able to identify women with SLN micrometastasis with a ≤10% FNR. Models were not able to accurately identify low risk women from a cohort that would have been excluded from Z0011.