The initial hormone receptor/HER2 subtype is the main determinator of subtype discordance in advanced breast cancer: a study of the SONABRE registry

Purpose The hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) are the main parameters in guiding systemic treatment choices in breast cancer, but can change during the disease course. This study aims to evaluate the biopsy rate and receptor subtype discordance rate in patients diagnosed with advanced breast cancer (ABC). Methods Patients diagnosed with ABC in seven hospitals in 2007–2018 were selected from the SOutheast Netherlands Advanced BREast cancer (SONABRE) registry. Multivariable logistic regression analyses were performed to identify factors influencing biopsy and discordance rates. Results Overall, 60% of 2854 patients had a biopsy of a metastatic site at diagnosis. One of the factors associated with a reduced biopsy rate was the HR + /HER2 + primary tumor subtype (versus HR + /HER2- subtype: OR = 0.68; 95% CI: 0.51–0.90). Among the 748 patients with a biopsy of the primary tumor and a metastatic site, the overall receptor discordance rate was 18%. This was the highest for the HR + /HER2 + primary tumor subtype, with 55%. In 624 patients with metachronous metastases, the HR + /HER2 + subtype remained the only predictor significantly related to a higher discordance rate, irrespective of prior (neo-)adjuvant therapies (OR = 7.49; 95% CI: 3.69–15.20). Conclusion The HR + /HER2 + subtype has the highest discordance rate, but the lowest biopsy rate of all four receptor subtypes. Prior systemic therapy was not independently related to subtype discordance. This study highlights the importance of obtaining a biopsy of metastatic disease, especially in the HR + /HER2 + subtype to determine the most optimal treatment strategy.

A Machine Learning Ensemble Based on Radiomics to Predict BI-RADS Category and Reduce the Biopsy Rate of Ultrasound-Detected Suspicious Breast Masses

We developed a machine learning model based on radiomics to predict the BI-RADS category of ultrasound-detected suspicious breast lesions and support medical decision-making towards short-interval follow-up versus tissue sampling. From a retrospective 2015–2019 series of ultrasound-guided core needle biopsies performed by four board-certified breast radiologists using six ultrasound systems from three vendors, we collected 821 images of 834 suspicious breast masses from 819 patients, 404 malignant and 430 benign according to histopathology. A balanced image set of biopsy-proven benign (n = 299) and malignant (n = 299) lesions was used for training and cross-validation of ensembles of machine learning algorithms supervised during learning by histopathological diagnosis as a reference standard. Based on a majority vote (over 80% of the votes to have a valid prediction of benign lesion), an ensemble of support vector machines showed an ability to reduce the biopsy rate of benign lesions by 15% to 18%, always keeping a sensitivity over 94%, when externally tested on 236 images from two image sets: (1) 123 lesions (51 malignant and 72 benign) obtained from two ultrasound systems used for training and from a different one, resulting in a positive predictive value (PPV) of 45.9% (95% confidence interval 36.3–55.7%) versus a radiologists’ PPV of 41.5% (p < 0.005), combined with a 98.0% sensitivity (89.6–99.9%); (2) 113 lesions (54 malignant and 59 benign) obtained from two ultrasound systems from vendors different from those used for training, resulting into a 50.5% PPV (40.4–60.6%) versus a radiologists’ PPV of 47.8% (p < 0.005), combined with a 94.4% sensitivity (84.6–98.8%). Errors in BI-RADS 3 category (i.e., assigned by the model as BI-RADS 4) were 0.8% and 2.7% in the Testing set I and II, respectively. The board-certified breast radiologist accepted the BI-RADS classes assigned by the model in 114 masses (92.7%) and modified the BI-RADS classes of 9 breast masses (7.3%). In six of nine cases, the model performed better than the radiologist did, since it assigned a BI-RADS 3 classification to histopathology-confirmed benign masses that were classified as BI-RADS 4 by the radiologist.

A Machine Learning Ensemble Based on Radiomics to Predict BI-RADS Category and Reduce the Biopsy Rate of Ultra-sound-Detected Suspicious Breast Masses

We developed a machine learning model based on radiomics to predict the BI-RADS category of ultrasound-detected suspicious breast lesions and support medical decision making towards short-interval follow-up versus tissue sampling. From a retrospective 2015-2019 series of ultrasound-guided core needle biopsies performed by four board-certified breast radiologists using six ultrasound systems from three vendors, we collected 821 images of 834 suspicious breast masses from 819 patients, 404 malignant and 430 benign according to histopathology. A balanced image set of biopsy-proven benign (n = 299) and malignant (n = 299) lesions were used for training and cross-validation of ensembles of machine learning algorithms supervised during learning by histopathological diagnosis as a reference standard. Based on a majority vote (over 80% of the votes to have a valid prediction of benign lesion), an ensemble of support vector machines showed an ability to reduce the biopsy rate of benign lesions by 15% to 18%, always keeping a sensitivity over 94%, when externally tested on 236 images from two image sets: 1) 123 lesions (51 malignant and 72 benign) obtained from the same four ultrasound systems used for training, resulting into a positive predictive value (PPV) of 45.9% (95% confidence interval 36.3-55.7%) versus a radiologists' PPV of 41.5% (p < 0.005), combined with a 98.0% sensitivity (89.6-99.9%); 2) 113 lesions (54 malignant and 59 benign) obtained from two ultrasound systems from vendors different from those used for training, resulting into a 50.5% PPV (40.4-60.6%) versus a radiologists' PPV of 47.8% (p < 0.005), combined with a 94.4% sensitivity (84.6-98.8%). Errors in BI-RADS 3 category (i.e., assigned by the model as BI-RADS 4) were 0.8% and 2.7% in the Testing set I and II, respectively. The board-certified breast radiologist accepted the BI-RADS classes assigned by the model in 114 masses (92.7%) and modified the BI-RADS classes of 9 breast masses (7.3%). In 6 of 9 cases the model performed better than the radiologist, since it assigned a BI-RADS 3 classification to histopathology-confirmed benign masses that were classified as BI-RADS 4 by the radiologist.

Diagnostic Performance Improvement with Combined use of Proteomics Biomarker Assay and Breast Ultrasound

Purpose: To investigate the combined use of blood-based 3-protein signature and breast ultrasound (US) for validating US detected lesions.Methods: From July 2011 to April 2020, women who underwent whole-breast US within at least 6 months from sampling period were retrospectively included. Blood-based 3-protein signature (Mastocheck®) value and US findings were evaluated. Following outcome measures were compared between US alone and the combination of Mastocheck® value with US: sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), area under the receiver operating characteristic curve (AUC), and biopsy rate. Results: Among the 237 women included, 59 (24.9%) were healthy individuals and 178 (75.1%) cancer patients. Mean size of cancers was 1.2±0.8 cm. Median value of Mastocheck® was significantly different between non-malignant (-0.24, interquartile range [IQR], -0.48, -0.03) and malignant lesions (0.55, IQR, -0.03, 1.42) (P < .001). Utilizing Mastocheck® value with US increased the AUC from 0.67 (95% confidence interval [CI], 0.61, 0.73) to 0.81 (95% CI: 0.75, 0.88; P < .001), specificity from 35.6% (95% CI: 23.4, 47.8) to 64.4% (95% CI: 52.2, 76.6; P < .001) without loss in sensitivity. PPV was increased from 82.2% (95% CI: 77.1, 87.3) to 89.3% (95% CI: 85.0, 93.6; P < .001), and biopsy rate was significantly decreased from 79.3% (188/237) to 72.1% (171/237) (P < .001). Consistent improvements in specificity, PPV, and AUC were observed in asymptomatic women and in those with normal/benign mammographic findings. Conclusion: Mastocheck® is an effective tool that can be used with US to improve diagnostic specificity and reduce false-positive findings and unnecessary biopsies.

Kidney biopsy-based epidemiologic analysis shows growing biopsy rate among the elderly

Systematic registration and examination of biopsy-related data in Central and Eastern Europe are scarce, while the health condition of the population is worse compared to other more developed countries. We aim to create a database and analyze the distribution and temporal variation of the renal biopsy diagnoses in Hungary, including the effect of the recent coronavirus pandemic. The diagnoses were standardized according to the recommendation of the European Renal Association. Native biopsy samples processed between January 1, 2006, and December 31, 2020, were analyzed. During the 15 years, 2140 native kidney biopsies were performed. The number of samples increased from 24.5 to 57.9 per million person-years and the median age from 37 to 51 years (p < 0.0001). The predominance of glomerular diseases was stable. The most frequent glomerulopathy was IgA nephropathy (21.5%), followed by focal segmental glomerulosclerosis (17.7%), and membranous nephropathy (15.7%). Trends showed the rise of ANCA-associated vasculitis. During the coronavirus pandemic, there was a decrease in the number of kidney biopsies and the proportion of membranous nephropathies. The diagnostic trends in our database showed increasing biopsy rates among the elderly and the growing frequencies of age-related diseases, which emphasizes the importance of altering medical focus according to demographic changes in this area.

1460 Spot the difference? Suspected Skin Cancer Referral Clinic 2020 Impact Audit

Introduction According to the 2018 WHO statistics nearly 18,000 people were diagnosed with melanoma in the UK and nearly 3000 died from this. We did this audit to study our skin cancer detection rates in the department of plastic surgery in Salisbury hospital before and during COVID. During COVID, our practise included telephone consultations, image reviews and some face-to-face consultations. Method We did two snapshot audits in January and May 2020. Based on Cancer Waiting time guidelines our hospital operational standard for patient to be seen in 2WW was 93% and Time for definitive treatment target is 96% (where the clock stops) Result There was significant drop in the number of patients presenting overall but the case load for plastics remained similar in both cycles. Audit showed compliance with 2WW waiting time except in 1 case in January owing to patient factors. 2% increase in biopsy rate. 24% of biopsied patient had cancer in January compared to 16% in May. Majority were squamous cell carcinomas. Average wait time to biopsy was longer in May by a week. Conclusions Although there has been a drastic reduction in the number of presentations there was no significant variation in the cancer detection rates. Biopsy rate was 2% higher, likely owing to a more cautious approach when using visual/ telephone consultations and image review. The audit highlights the pros and cons of using non face to face consultations in clinical practice.

Rate of breast biopsy referrals in BRCA mutation carriers: a retrospective comparative study and matched analysis

Purpose To evaluate the total biopsy and positive biopsy rates in women at high risk of breast cancer compared to the general population. Methods The study group consisted of 330 BRCA mutation carriers attending the dedicated multidisciplinary breast cancer clinic of a tertiary medical center in Israel. Clinical, genetic, and biopsy data were retrieved from the central healthcare database and the medical files. Patients who were at age 50 years or older during follow-up were matched 1:10 to women in the general population referred for routine breast cancer screening at the same age, as recommended in the international guidelines. The groups were compared for rate of biopsy studies performed and percentage of positive biopsy results. Matched analysis was performed to correct for confounders. Results The matched analysis revealed that the total biopsy rate per 1000 follow-up-years was 61.7 in the study group and 22.7 in the control group (p < 0.001). The positive biopsy rates per 1000 follow-up-years were 26.4 and 2.0, correspondingly (p < 0.001), and the positive biopsy percentages were 42.9% and 8.7% correspondingly (p < 0.0001). Conclusions BRCA mutation carriers who attend a dedicated clinic, have a 2.7 times higher biopsy rate per 1000 follow-up-years, a 13.2 times higher positive biopsy rate per 1000 follow-up-years, and a 4.9 times higher positive biopsy percentage compared with women in the general population.

The Added Value of Supplemental Breast Ultrasound Screening for Women With Dense Breasts: A Single Center Canadian Experience

Purpose: We evaluated the contribution to cancer detection of supplemental breast ultrasound screening in women with dense breasts based on a single center experience by comparing our results with similar programs elsewhere. Methods: We performed a retrospective review of handheld sonographer-performed screening ultrasound exams at our academic breast imaging center, from January 1st to December 31st, 2019. Breast density, breast cancer risk factors, BI-RADS assessment, and lesion pathology were reviewed and tallied, followed by derivation of the biopsy rate, breast cancer detection rate, PPV3 and average tumor size. These values were compared to published results of breast screening programs elsewhere. Results: 695 screening breast ultrasounds for women with dense breasts and negative mammograms were performed in 2019. The biopsy rate was 1.3%, breast cancer detection rate was 7 in 1000, PPV3 was 42%, and the average tumor size was 9.0 ± 1.4 mm. Conclusions: The first-year data of the breast screening ultrasound program at our practice are promising, demonstrating comparable cancer detection rate, higher PPV3, and similar biopsy rate in those with dense breasts compared with similar programs elsewhere. Longitudinal analysis and larger sample size are required for validation. Comparison of incidence and prevalence screening data is also warranted to elucidate the true value of this program.

Application of a second opinion ultrasound in Breast Imaging Reporting and Data System 4A cases: can immediate biopsy be avoided?

Objective The probability of malignancy in women who are diagnosed with a Breast Imaging Reporting and Data System (BI-RADS) 4A score is low. Application of a second opinion ultrasound (SOUS), which is low in cost and minimally invasive, may lower the biopsy rate for patients who fall into this category. This study aimed to apply SOUS to patients with a BI-RADS score of 4A and predict the pathological results of a biopsy. Methods One hundred seventy-eight patients were analyzed. Univariate and multivariate analyses were performed to screen for predictive factors that are associated with malignancy. Categorical alteration of downgraded, unchanged, or upgraded was made after SOUS results. Changes in category were compared with biopsies to determine their predictive value of benignancy or malignancy. Results Independent factors associated with malignancy were age (>50 years), tumor size (≥20 mm), margin (not circumscribed), orientation (not parallel), and peripheral location, and an upgraded categorical alteration from SOUS. Downgraded categorical alterations were associated with benignancy. Conclusions In BI-RADS 4A cases, a biopsy is recommended when independent factors are associated with malignancy. A downgraded result from an SOUS examination is a protective factor, supporting the likelihood of benignancy in these patients.