Validation of a Novel Nomogram for Prediction of Local Relapse after Surgery for Invasive Breast Carcinoma

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Abstract

Background: Around 7% of women who undergo breast-conserving surgery (BCS) or mastectomy are at risk of developing ipsilateral breast tumor recurrence (IBTR). When assessing risks that, like that of IBTR, depend on multiple clinicopathological variables, nomograms are the predictive tools of choice. In this study, two independent nomograms were constructed to estimate the individualized risk of IBTR after breast surgery. Patients and Methods: In this retrospective study, 18,717 consecutive patients with primary invasive breast cancer were enrolled. The training set used for building the nomograms comprised 15,124 patients (11,627 treated with BCS and 3497 with mastectomy), while the validation set included 3593 women (2565 BCS and 1028 mastectomy). Median follow-up time was 8 years in the training set and 6 years in the validation set. Multivariable Cox proportional hazards regression was used to identify independent factors for IBTR. Two separated nomograms were constructed on multivariate models for BCS and mastectomy. Results: The factors that associated with IBTR after either BCS or mastectomy were identified. The two multivariable models were used to build nomograms for the prediction of IBTR 1 year, 5 years, and 10 years after BCS or after mastectomy. Five-year and 10-year IBTR rates in the BCS training set were equal to 3.50% and 7.00%, respectively, and to 5.39% and 7.94% in the mastectomy training set. The nomograms were subsequently validated with c-index values of 0.77 and 0.69 in the BCS and mastectomy validation sets, respectively. Conclusions: The nomograms presented in this study provide clinicians and patients with a valuable decision-making tool for choosing between different treatment options for invasive breast cancer.

Original languageEnglish
JournalAnnals of Surgical Oncology
DOIs
Publication statusAccepted/In press - Jan 1 2020

ASJC Scopus subject areas

  • Surgery
  • Oncology

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