4.3 Article

Re-excision or wait and watch-a prediction model in breast phyllodes tumors after surgery

期刊

ANNALS OF TRANSLATIONAL MEDICINE
卷 8, 期 6, 页码 -

出版社

AME PUBL CO
DOI: 10.21037/atm.2020.02.26

关键词

Breast phyllodes tumor; clinical prediction model; nomogram; recurrence

资金

  1. National Science and Technology Major Project [2020ZX09201021]
  2. National Natural Science Foundation of China [81872158, 81572596, 81972471, U1601223]
  3. Natural Science Foundation of Guangdong Province [2017A030313828]
  4. Elite Young Scholars Program of Sun Yat-Sen Memorial Hospital [Y201703]
  5. Guangzhou Science and Technology Major Program [201704020131]
  6. Sun Yat-Sen University Clinical Research 5010 Program [2018007]
  7. Sun Yat-Sen Clinical Research Cultivating Program [SYS-C-201801]
  8. Guangdong Science and Technology Department [2017B030314026]
  9. Medical Artificial Intelligence Project of Sun Yat-Sen Memorial Hospital [YXRGZN201902]
  10. Key Laboratory of Malignant Tumor Gene Regulation and Target Therapy of Guangdong Higher Education Institutes, Sun Yat-Sen University [KLB09001]
  11. Key Laboratory of Malignant Tumor Molecular Mechanism and Translational Medicine of Guangzhou Bureau of Science and Information Technology [[2013]163]
  12. Yat-Sen Scholarship for Young Scientist

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Background: The prognosis of breast phyllodes tumors (PTs) largely depending on the pathological grading, which lacks objectivity. This study aimed to develop a nomogram based on clinicopathological features to evaluate the recurrence probability of PTs following surgery. Methods: Data from 334 patients with breast PTs, who underwent surgical treatment at Sun Yat-sen Memorial Hospital from January 2005 to December 2014, were used to develop a prediction model. Additionally, data of 36 patients from Peking University Shenzhen Hospital (cohort 1) and data of 140 patients from Sun Yat-sen University Cancer Center (cohort 2) during the same period were used to validate the model. The medical records and tumor slides were retrospectively reviewed. The log-rank and Cox regression tests were used to develop a clinical prediction model of breast PTs. All statistical analyses were performed using R and STATA. Results: Of all 334 patients included in the primary cohort, 224 had benign, 91 had borderline, and 19 had malignant tumors. The 1-, 3-, and 5-year recurrence-free survival was 98.5%, 97.9%, and 96.8%, respectively. Ultrasound-guided vacuum-assisted biopsy (UGVAB) is a non-inferior treatment application in benign PTs compared with open surgery [hazard ratio (HR), 2.38; 95% confidence interval (CI), 0.59-9.58]. Width of surgical margin, mitoses, and tumor border were identified as independent risk factors for breast PTs. A nomogram was developed based on these three variables. The C-index of internal and external validation was 0.71, 0.67 (cohort 1) and 0.73 (cohort 2), respectively. Conclusions: The study model presented more concise and objective variables to evaluate the recurrence-free survival of patients after surgery, which can help deciding whether to do a re-excision or wait and watch.

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