Does establishing a preoperative nomogram including ultrasonographic findings help predict the likelihood of malignancy in patients with microcalcifications?

Abstract

Background Mammography (MG) is highly sensitive for detecting microcalcifications, but has low specificity. This study investigates whether establishing a preoperative nomogram including ultrasonographic findings can help predict the likelihood of malignancy in patients with mammographic microcalcification. Methods Between May 2012 and January 2017, 475 patients with suspicious microcalcifications detected on MG underwent ultrasonography (US). The χ 2 test was used to screen risk factors among the variables. Then, a multivariate logistic regression analysis was performed to identify independent predictors of malignant microcalcifications. A mammographic nomogram (M nomogram) and mammographic-ultrasonographic nomogram (M-U nomogram) were established based on multivariate logistic regression models. The discriminatory ability and clinical utility of both nomograms were compared by the receiver operating characteristics curve and decision curve analysis. The calibration ability was evaluated using a calibration curve. Results Among the cases, 68.2% (324/475) were pathologically diagnosed as breast cancer and 31.8% (151/475) were benign lesions. Based on multivariate logistic regression analysis, age, clinical manifestation, morphology and distribution of microcalcifications on MG and lesions associated with microcalcifications on US were confirmed as independent predictors of malignant microcalcifications. In terms of discrimination ability, the C-index of the M-U nomogram was significantly higher than that of the M nomogram (0.917 vs 0.897, p = 0.006). The bias-corrected curve was close to the ideal line in the calibration curve. Decision curve analysis suggested that the M-U nomogram was superior to M nomogram. Conclusions Combining mammographic parameters with ultrasonographic findings in a nomogram provided better performance than an M nomogram alone, especially for dense breasts, which suggests the value of ultrasonographic finding for individualized prediction of malignancy in patients with microcalcifications.

Malignancy Risk Stratification Prediction of Amorphous Calcifications Based on Clinical and Mammographic Features

“…Previous studies have demonstrated the importance of menopausal status and age in breast cancer assessment. 4,11,15 In our research, the malignancy rate of patients older than 60 years was higher than that of younger patients. Similar results were reported by Oligane et al, 4 who found that patients younger than 50 years had a lower malignancy rate.…”

“…Distribution and morphology are recognized as independent influencing factors of calcifications. 4,5,11,17 Generally, the malignancy rate of calcifications with only one pure morphology is lower than that of calcifications with more than one type of suspicious morphology. 14 Previous studies on the PPVs of morphology and distribution descriptors demonstrated an increasing trend toward malignancy from amorphous/coarse heterogeneous to fine pleomorphic/fine linear/fine-linear branching microcalcifications and from regional/grouped to segmental/linear distribution.…”

“…14 Previous studies on the PPVs of morphology and distribution descriptors demonstrated an increasing trend toward malignancy from amorphous/coarse heterogeneous to fine pleomorphic/fine linear/fine-linear branching microcalcifications and from regional/grouped to segmental/linear distribution. 5,11,17 Our study focused on only one suspicious amorphous morphology type, which has a lower PPV. For distribution, our result is similar to previous studies that grouped calcifications are the most common and have the lowest malignancy rate, while segmental distribution has the highest malignancy rate.…”

“…8 Previous studies have shown that this method could be used to predict malignant calcifications. [9][10][11] However, the above studies focused on all kinds of breast calcifications, and there was no specific discussion on amorphous calcifications. Thus, the objective of this study was to explore the potential influencing factors of the malignancy risk of amorphous calcifications and establish a nomogram for individualized malignancy risk stratification.…”

Nomogram Based on Ultrasonography and Clinical Features for Predicting Malignancy in Soft Tissue Tumors

“…[10][11][12] So far, nomograms have been established in the majority of cancer types. [10][11][12][13] For instance, Guo et al developed an USbased nomogram to improve the diagnostic accuracy of the identification of malignant thyroid nodules; 14 Qiu et al established and validated a nomogram to predict the probability of axillary lymph node metastasis as a preoperative tool to support clinical decision-making. 15 To the best of our knowledge, this study is the first attempt to develop and validate a nomogram based on US parameters as well as clinical risk factors to predict malignant STTs.…”