Accuracy of clinical breast examination's abnormalities for breast cancer screening: cross-sectional study

Development and Validation of a Diagnostic Model for Enhancing Lesions on Breast MRI: Based on Kaiser Score

RATIONALE AND OBJECTIVES

This study aims to develop and validate a new diagnostic model based on the Kaiser score for preoperative diagnosis of the malignancy probability of enhancing lesions on breast MRI.

MATERIALS AND METHODS

This study collected consecutive inpatient data (including imaging data, clinical data, and pathological data) from two different institutions. All patients underwent preoperative breast Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) examinations and were found to have enhancing lesions. These lesions were confirmed as benign or malignant by surgical resection or biopsy pathology (all carcinomas in situ were confirmed by pathology after surgical resection). Data from one institution were used as the training set(284 cases), and data from the other institution were used as the validation set(107 cases). The Kaiser score was directly incorporated into the diagnostic model as a single predictive variable. Other predictive variables were screened using Least Absolute Shrinkage and Selection Operator (LASSO) regression. Multivariate logistic regression was employed to integrate the Kaiser score and other selected predictive variables to construct a new diagnostic model, presented in the form of a nomogram. Receiver operating characteristic (ROC) curve, DeLong test, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were adopted to evaluate and compare the discrimination of the diagnostic model for breast enhancing lesions based on Kaiser score (hereinafter referred to as the "breast lesion diagnostic model") and the Kaiser score alone. Calibration curves were used to assess the calibration of the breast lesion diagnostic model, and decision curve analysis (DCA) was used to evaluate the clinical efficacy of the diagnostic model and the Kaiser score.

RESULTS

LASSO regression indicated that, besides the indicators already included in the Kaiser score system, "age", "MIP sign", "associated imaging features", and "clinical breast examination (CBE) results" were other valuable diagnostic parameters for breast enhancing lesions. In the training set, the AUCs of the breast lesion diagnostic model and the Kaiser score were 0.948 and 0.869, respectively, with a statistically significant difference (p < 0.05). In the validation set, the AUCs of the breast lesion diagnostic model and the Kaiser score were 0.956 and 0.879, respectively, with a statistically significant difference (p < 0.05). The DeLong test, NRI, and IDI showed that the breast lesion diagnostic model had a higher discrimination ability for breast enhancing lesions compared to the Kaiser score alone, with statistically significant differences (p < 0.05). The calibration curves indicated good calibration of the breast lesion diagnostic model. DCA demonstrated that the breast lesion diagnostic model had higher clinical application value, with greater net clinical benefit over a wide range of diagnostic thresholds compared to the Kaiser score.

CONCLUSION

The Kaiser score-based breast lesion diagnostic model, which integrates "age," "MIP sign", "associated imaging features", and "CBE results", can be used for the preoperative diagnosis of the malignancy probability of breast enhancing lesions, and it outperforms the classic Kaiser score in terms of diagnostic performance for such lesions.

The role of clinical breast examination and fine needle aspiration cytology in early detection of breast cancer: A cross-sectional study nested in a cohort in a low-resource setting

BACKGROUND

Breast cancer is prevalent worldwide, with disparities in screening, diagnosis, treatment outcomes, and survival. In Africa, the majority of women are diagnosed at advanced stages, affecting treatment outcomes. Screening is one of the best strategies to reduce mortality rates caused by this cancer. Yet in a resource-constrained setting, there is limited access to screening and early detection services, which are available only at a few referral hospitals.

OBJECTIVES

We aimed to evaluate the prevalence and screening results of breast cancer using clinical breast examination coupled with fine needle aspiration cytology in a resource-constraint setting.

DESIGN

A combined cross-sectional and cohort study.

METHODS

Women at risk of developing breast cancer in the Kilimanjaro region of Tanzania were invited, through public announcements, to their primary healthcare facilities. A questionnaire was used to assess the participants' characteristics. The women received a clinical breast examination, and detectable lesions were subjected to a confirmatory fine needle aspiration cytology or an excisional biopsy. Preliminary data from this ongoing breast cancer control program were extracted and analyzed for this study.

RESULTS

A total of 3577 women were screened for breast cancer; their mean age was 47 ± 7.53 years. About a third of them (1145, 32%) were practicing self-breast examination at least once a month. Of 200 (5.6%) with abnormal clinical breast examination, 18 (9%) were confirmed to be breast cancer, making the prevalence to be 0.5%. The vast majority of participants with breast cancer (13, 72.2%) had early disease stages, and infiltrating ductal carcinoma, no special type, was the most common (15, 83.3%) histopathology subtype. Hormonal receptor status determination results indicated that 11 (61.1%), 7 (38.9%), and 5 (27.8%) of the tumors overexpressed estrogen receptor, progesterone receptor, and human epidermal receptor-2, respectively.

CONCLUSION

Our study demonstrates 5.6% of Tanzanian women have abnormal clinical breast examination findings, with 9% having breast cancer. Nearly three-quarters (72.2%) of breast cancer screened for early disease were detected in the early disease stages. This finding suggests that organized screening with clinical breast examination coupled with fine needle aspiration cytology, which is a simple and cost-effective screening method, has the potential to improve early detection and outcomes for breast cancer patients in a resource-constraint setting.

Application of SHAP for Explainable Machine Learning on Age-Based Subgrouping Mammography Questionnaire Data for Positive Mammography Prediction and Risk Factor Identification

Mammography is considered the gold standard for breast cancer screening. Multiple risk factors that affect breast cancer development have been identified; however, there is an ongoing debate regarding the significance of these factors. Machine learning (ML) models and Shapley Additive Explanation (SHAP) methodology can rank risk factors and provide explanatory model results. This study used ML algorithms with SHAP to analyze the risk factors between two different age groups and evaluate the impact of each factor in predicting positive mammography. The ML model was built using data from the risk factor questionnaires of women participating in a breast cancer screening program from 2017 to 2021. Three ML models, least absolute shrinkage and selection operator (lasso) logistic regression, extreme gradient boosting (XGBoost), and random forest (RF), were applied. RF generated the best performance. The SHAP values were then applied to the RF model for further analysis. The model identified age at menarche, education level, parity, breast self-examination, and BMI as the top five significant risk factors affecting mammography outcomes. The differences between age groups ranked by reproductive lifespan and BMI were higher in the younger and older age groups, respectively. The use of SHAP frameworks allows us to understand the relationships between risk factors and generate individualized risk factor rankings. This study provides avenues for further research and individualized medicine.

The iBreastExam versus clinical breast examination for breast evaluation in high risk and symptomatic Nigerian women: a prospective study

BACKGROUND

The iBreastExam electronically palpates the breast to identify possible abnormalities. We assessed the iBreastExam performance compared with clinical breast examination for breast lesion detection in high risk and symptomatic Nigerian women.

METHODS

This prospective study was done at the Obafemi Awolowo University Teaching Hospital Complex (OAUTHC) in Nigeria. Participants were Nigerian women aged 40 years or older who were symptomatic and presented with breast cancer symptoms or those at high risk with a first-degree relative who had a history of breast cancer. Participants underwent four breast examinations: clinical breast examination (by an experienced surgeon), the iBreastExam (performed by recent nursing school graduates, who finished nursing school within the previous year), ultrasound, and mammography. Sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV) of the iBreastExam and clinical breast examination for detecting any breast lesion and suspicious breast lesions were calculated, using mammography and ultrasound as the reference standard.

FINDINGS

Between June 19 and Dec 5, 2019, 424 Nigerian women were enrolled (151 [36%] at high risk of breast cancer and 273 [64%] symptomatic women). The median age of participants was 46 years (IQR 42-52). 419 (99%) women had a breast imaging-reporting and data system (BI-RADS) assessment and were included in the analysis. For any breast finding, the iBreastExam showed significantly better sensitivity than clinical breast examination (63%, 95% CI 57-69 vs 31%, 25-37; p<0·0001), and clinical breast examination showed significantly better specificity (94%, 90-97 vs 59%, 52-66; p<0·0001). For suspicious breast findings, the iBreastExam showed similar sensitivity to clinical breast examination (86%, 95% CI 70-95 vs 83%, 67-94; p=0·65), and clinical breast examination showed significantly better specificity (50%, 45-55 vs 86%, 83-90; p<0·0001). The iBreastExam and clinical breast examination showed similar NPVs for any breast finding (56%, 49-63 vs 52%, 46-57; p=0·080) and suspicious findings (98%, 94-99 vs 98%, 96-99; p=0·42), whereas the PPV was significantly higher for clinical breast examination in any breast finding (87%, 77-93 vs 66%, 59-72; p<0·0001) and suspicious findings (37%, 26-48 vs 14%, 10-19; p=0·0020). Of 15 biopsy-confirmed cancers, clinical breast examination and the iBreastExam detected an ipsilateral breast abnormality in 13 (87%) women and missed the same two cancers (both <2 cm).

INTERPRETATION

The iBreastExam by nurses showed a high sensitivity and NPV, but lower specificity than surgeon's clinical breast examination for identifying suspicious breast lesions. In locations with few experienced practitioners, the iBreastExam might provide a high sensitivity breast evaluation tool. Further research into improved specificity with device updates and cost feasibility in low-resource settings is warranted.

FUNDING

Prevent Cancer Foundation Global Community Grant Award with additional support from the P30 Cancer Center Support Grant (P30 CA008748).

Use of Palpation Imaging in Diagnosis of Breast Diseases: A Way to Improve the Detection Rate

Background

Breast diseases pose increasing threat to women health as peoples lifestyle changes. The aim of this study was to investigate the clinical application value of Palpation Imaging (PI) in the diagnosis of breast diseases.

Material/Methods

From October 2019 to February 2020, 184 patients with 225 breast lesions were examined by using PI, ultrasound, and mammography in the department of Breast Surgery, the First Affiliated Hospital of Anhui Medical University. All cases were confirmed pathologically by core-needle biopsy or excisional biopsy. The cut-off value of the PI tests was determined by receiver operating characteristic (ROC) curve. We compared the examination results of PI with ultrasound and mammography to analyze the diagnostic value of PI.

Results

Pathological examination revealed that 186/225(82.67%) lesions were benign, while 39 were malignant. All 8 parameters of PI were significantly correlated with pathological findings (P<0.05). The best cut-off value for the PI score was 19.5 and the area under the curve (AUC) for the PI was 0.921 (95% CI: 0.874–0.968, P<0.001) with 89.7% sensitivity and 86.0% specificity. PI showed greater sensitivity (89.7%) and its specificity (86.0% vs. 86.4%, P=0.931) and accuracy (86.7% vs. 84.6%, P=0.604) were similar to those of mammography. The combination of 3 types of test is superior to a single examination. The sensitivity was 100% and the specificity was 98.8%.

Conclusions

PI has high clinical value in differentiation of benign and malignant breast lesions. Combination examination has the potential to improve the detection of breast cancer in screening and diagnostic capacities and can be used as a supplement to ultrasound and mammography.

Comparison of mammography results from individual and organized screening for breast cancer

BACKGROUND

In France, the coexistence of individual screening (IS) and organized screening (OS) for breast cancer induces difficulties for primary care practitioners to position themselves. This study assessed whether the risk of having a mammography with a high risk of malignancy (BI-RADS 4 or 5) was different between patients aged from 50 to 74year performing it as part of an IS or of the OS.

METHOD

This cross-sectional multicenter study included women aged 50-74, with no personal history of breast cancer, performing mammography in radiology centers in Paris (France). The nature of the screening (OS or IS), breast cancer risk (high risk: BI-RADS 4 or 5), risk factors and clinical breast examination (CBE) abnormalities were collected. Patients in the IS and OS group were matched on age, breast density, history of benign lesions and family history of breast cancer using a propensity score. The association between the nature of screening and the risk of malignancy was evaluated by conditional logistic regression.

RESULTS

Among 2190 included patients, 77 % performed a mammography with the IS and had more CBE abnormalities (23 % vs 11 %, p<0,001), a history of benign lesion (15 % vs 11 %, p=0.01) and a family history of breast cancer (42 % vs 29 %, p<0,001). After matching 503 OS patients with 941 IS patients, the risk of malignancy and the nature of the screening were not associated (OR=0.72 [0.35-1.47], p=0.50).

CONCLUSION

The risk of malignancy was not different whether the mammography was performed as part of the OS or IS.

Peripheral blood transcriptome identifies high-risk benign and malignant breast lesions

Background

Peripheral blood transcriptome profiling is a potentially important tool for disease detection. We utilize this technique in a case-control study to identify candidate transcriptomic biomarkers able to differentiate women with breast lesions from normal controls.

Methods

Whole blood samples were collected from 50 women with high-risk breast lesions, 57 with breast cancers and 44 controls (151 samples). Blood gene expression profiling was carried out using microarray hybridization. We identified blood gene expression signatures using AdaBoost, and constructed a predictive model differentiating breast lesions from controls. Model performance was then characterized by AUC sensitivity, specificity and accuracy. Biomarker biological processes and functions were analyzed for clues to the pathogenesis of breast lesions.

Results

Ten gene biomarkers were identified (YWHAQ, BCLAF1, WSB1, PBX2, DDIT4, LUC7L3, FKBP1A, APP, HERC2P2, FAM126B). A ten-gene panel predictive model showed discriminatory power in the test set (sensitivity: 100%, specificity: 84.2%, accuracy: 93.5%, AUC: 0.99). These biomarkers were involved in apoptosis, TGF-beta signaling, adaptive immune system regulation, gene transcription and post-transcriptional protein modification.

Conclusion

A promising method for the detection of breast lesions is reported. This study also sheds light on breast cancer/immune system interactions, providing clues to new targets for breast cancer immune therapy.