{"title":"Development and validation of a preoperative nomogram for predicting residual tumor risk in breast cancer patients undergoing excisional biopsy.","authors":"Yangfan Fan, Yiwei Wu, Fangfang Chen, Fang Wan, Dianlei Liu, Jingpei Long, Tao Zhang","doi":"10.21037/tcr-2025-850","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Current research on breast-conserving surgery (BCS) focuses on recurrence and survival but overlooks the issue of residual tumors post-excisional biopsy. These remnants, crucial for surgical planning, often necessitate additional excisions, impacting BCS success. Our 5-year study of excisional biopsy patients identifies risk factors for residual tumors, offering insights to improve surgical decisions.</p><p><strong>Methods: </strong>This study examined 233 breast cancer patients split into training and validation groups (2:1 ratio). Logistic regression models identified predictors of post-biopsy residual tumors status, leading to the creation and validation of a preoperative nomogram for residual risk.</p><p><strong>Results: </strong>In this study of 233 patients, 23.9% with BCS had residual tumors after biopsy, significantly less than those in the non-BCS group (P<0.001). Tumor size, biopsy method, and histopathological subtype were crucial in predicting residual tumors and were used to develop a nomogram, which showed strong predictive accuracy for preoperative residual tumor status. This tool enhances preoperative risk stratification and aids in the formulation of personalized surgical strategies by providing visual quantification of the probabilities associated with oncological clearance parameters.</p><p><strong>Conclusions: </strong>We developed a clinically practical nomogram for predicting residual tumor status following excisional biopsy, facilitating preoperative risk stratification and personalized surgical strategy. Further prospective studies are necessary to evaluate its generalizability and accuracy.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"4965-4975"},"PeriodicalIF":1.7000,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432765/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational cancer research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.21037/tcr-2025-850","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/8/27 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Current research on breast-conserving surgery (BCS) focuses on recurrence and survival but overlooks the issue of residual tumors post-excisional biopsy. These remnants, crucial for surgical planning, often necessitate additional excisions, impacting BCS success. Our 5-year study of excisional biopsy patients identifies risk factors for residual tumors, offering insights to improve surgical decisions.
Methods: This study examined 233 breast cancer patients split into training and validation groups (2:1 ratio). Logistic regression models identified predictors of post-biopsy residual tumors status, leading to the creation and validation of a preoperative nomogram for residual risk.
Results: In this study of 233 patients, 23.9% with BCS had residual tumors after biopsy, significantly less than those in the non-BCS group (P<0.001). Tumor size, biopsy method, and histopathological subtype were crucial in predicting residual tumors and were used to develop a nomogram, which showed strong predictive accuracy for preoperative residual tumor status. This tool enhances preoperative risk stratification and aids in the formulation of personalized surgical strategies by providing visual quantification of the probabilities associated with oncological clearance parameters.
Conclusions: We developed a clinically practical nomogram for predicting residual tumor status following excisional biopsy, facilitating preoperative risk stratification and personalized surgical strategy. Further prospective studies are necessary to evaluate its generalizability and accuracy.
期刊介绍:
Translational Cancer Research (Transl Cancer Res TCR; Print ISSN: 2218-676X; Online ISSN 2219-6803; http://tcr.amegroups.com/) is an Open Access, peer-reviewed journal, indexed in Science Citation Index Expanded (SCIE). TCR publishes laboratory studies of novel therapeutic interventions as well as clinical trials which evaluate new treatment paradigms for cancer; results of novel research investigations which bridge the laboratory and clinical settings including risk assessment, cellular and molecular characterization, prevention, detection, diagnosis and treatment of human cancers with the overall goal of improving the clinical care of cancer patients. The focus of TCR is original, peer-reviewed, science-based research that successfully advances clinical medicine toward the goal of improving patients'' quality of life. The editors and an international advisory group of scientists and clinician-scientists as well as other experts will hold TCR articles to the high-quality standards. We accept Original Articles as well as Review Articles, Editorials and Brief Articles.