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NOVEMBER 2018    A Monthly Review of Articles of Interest for the Clinical Community

..This Month's Clinical Focus:  BREAST CANCER..

 
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Latest Results from the I-SPY 2 Trial

New data from the trial shows that a subgroup of "Ultra-High Risk" patients identified by MammaPrint respond better to certain targeted therapies and treatment combinations

New data from the I-SPY 2 study was presented at the European Organization for Research and Treatment of Cancer (EORTC), the National Cancer Institute (NCI) and the American Association for Cancer Research (AACR) Symposium. The two presentations demonstrate both the prognostic, and the predictive role of the MammaPrint® 70-Gene Breast Cancer Risk of Recurrence and BluePrint® 80-Gene Molecular Subtyping tests in determining which patients are likely to respond to therapies.
 
MammaPrint High1/High2 risk class as a pre-specified biomarker of response to nine different targeted agents plus standard neoadjuvant therapy for ~1000 breast cancer patients in the I-SPY 2 TRIAL (Abstract 2).
DNA puzzle-2500333_1920 by qimomo PIXABAY Free Lic CC0
A new analysis from the I-SPY 2 trial showed that a subgroup of "Ultra-High Risk" patients identified by MammaPrint respond better to certain targeted therapies and treatment combinations. Patients were classified as either MammaPrint High Risk (MP1), indicating less aggressive disease, or MammaPrint Ultra-High Risk (MP2), indicating more aggressive disease. Nearly 50 percent of patients were classified as MP2 and had higher rates of pathological complete response (pCR) compared to MP1 patients.
 
In addition, MP2 patients had a higher chance of achieving pCR if they received veliparib/carboplatin, neratinib, ganitumab, TDM1/pertuzumab or pembrolizumab in addition to the standard paclitaxel treatment alone or in combination with trastuzumab. Together, these findings support the use of the MammaPrint High Risk or Ultra-High Risk result as a predictive biomarker of treatment response.
 
BluePrint basal subtype predicts neoadjuvant therapy response in ~400 HR+HER2- patients across 8 arms in the I-SPY 2 TRIAL (Abstract 3). A second analysis of the I-SPY 2 trial evaluated neoadjuvant chemotherapy response in different subgroups of patients with HR+/HER2- disease. Using the BluePrint Molecular Subtyping test, patients were classified as having either basal, luminal or HER2 subtypes. Patients with the basal subtype were four times more likely to achieve pCR with neoadjuvant therapy than patients with the luminal subtype, and this association was independent of the type of treatment they received. Additionally, more than three-quarters of patients with the HR+/HER2- basal subtype of cancer were classified as having MP2 Ultra-High Risk disease, suggesting that genetic and molecular risk signatures can be used to predict treatment response in similar subgroups of patients.

SOURCE: Used by Permission of PRNewswire

Newest AI Solution for Mammography

 
Current accuracy of screening mammography is at 32%; high recall cost estimated at $4B each year 
 
LUNIT AI Breast Cancer Detection
The AI software, Lunit INSIGHT for Mammography, is designed to solve this problem. It delivers high accuracy of 97% in detecting malignant lesions, which is expected to increase the cancer detection rate of radiologists by 10% when used as a second reader. The company also claims that its AI solution can enable general radiologists to perform at a specialist level, providing solutions to health facilities that experience strains with lack of specialists. It also aims to decrease recall rate and as a result, save medical costs that are being wasted every year.
 
The secret to the high accuracy level comes from the proprietary AI technology, trained with vast quality medical data. The AI has been trained with over 200,000 chest X-ray cases and 200,000 mammogram cases of which 50,000 cases were biopsy-proven malignant cases. The company's AI technology has been acknowledged at international competitions ImageNet (5th place, 2015), TUPAC 2016 (1st place), and Camelyon 2017 (1st place), surpassing top global companies like IBM, Google, and Microsoft. 

Lunit INSIGHT for Chest Radiography will also be showcased during this year's gathering at Radiological Society North America (RSNA), November 25-30 at McCormick Place, Chicago. Since being launched during last year's RSNA, it has been tested in more than 1.5 million cases from more than 70 countries. Boasting an unprecedented accuracy level of 97-99%, it detects major chest abnormalities including nodules, consolidation, pneumothorax, and etc. The CAD-based solution is also being integrated into the worklist for prioritization, in which positive cases may be read first in order to decrease turnaround time and increase overall reading productivity.

"While breast cancer takes up 25% of entire cancer cases, the accuracy of screening mammography is low by 32%," said Brandon Suh, CEO of Lunit. "False negative rates range from 10-30% and false positive rates are even higher at around 95%. This costs over 4 billion US dollars for unnecessary recalls in the United States alone."

SOURCE: Used by Permission of PRNewswire

Image credits: DNA Puzzle by qimono at Pixabay Free Lic CC0; Breast Cancer AI View courtesy of LUNIT 

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