Xie Yamie, Zhu Ying, Chai Weimin, Zong Shaoyun, Xu Shangyan, Zhan Weiwei, Zhang Xiaoxiao
Department of Ultrasound, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
College of Medicine, Kunming University of Science and Technology, Department of Ultrasound, The First People's Hospital of Yunnan Province, Kunming, China.
Front Oncol. 2022 Jan 27;12:807402. doi: 10.3389/fonc.2022.807402. eCollection 2022.
To downgrade BI-RADS 4A patients by constructing a nomogram using R software.
A total of 1,717 patients were retrospectively analyzed who underwent preoperative ultrasound, mammography, and magnetic resonance examinations in our hospital from August 2019 to September 2020, and a total of 458 patients of category BI-RADS 4A (mean age, 47 years; range 18-84 years; all women) were included. Multivariable logistic regression was used to screen out the independent influencing parameters that affect the benign and malignant tumors, and the nomogram was constructed by R language to downgrade BI-RADS 4A patients to eligible category.
Of 458 BI-RADS 4A patients, 273 (59.6%) were degraded to category 3. The malignancy rate of these 273 lesions is 1.5% (4/273) (<2%), and the sensitivity reduced to 99.6%, the specificity increased from 4.41% to 45.3%, and the accuracy increased from 63.4% to 78.8%.
By constructing a nomogram, some patients can be downgraded to avoid unnecessary biopsy.
使用R软件构建列线图，对乳腺影像报告和数据系统（BI-RADS）4A类患者进行降级。
回顾性分析2019年8月至2020年9月在我院接受术前超声、乳腺X线摄影和磁共振检查的1717例患者，纳入458例BI-RADS 4A类患者（平均年龄47岁；范围18 - 84岁；均为女性）。采用多变量逻辑回归筛选出影响肿瘤良恶性的独立影响参数，并用R语言构建列线图，将BI-RADS 4A类患者降级至合适类别。
458例BI-RADS 4A类患者中，273例（59.6%）降级为3类。这273个病灶的恶性率为1.5%（4/273）（<2%），敏感性降至99.6%，特异性从4.41%提高到45.3%，准确性从63.4%提高到78.8%。
通过构建列线图，部分患者可实现降级，避免不必要的活检。
