New York State Approves AI-Driven PDxBr Breast Test for Cancer Risk Categorization

The New York State Department of Health has approved the use of PreciseDx’s Lab Developed Test (LDT), PDxBr, for breast cancer grading and risk categorization. This AI-driven, patient-specific disease analysis process has the potential to revolutionize the way breast cancer is managed, and New York patients can now access this innovative testing through PreciseDx’s CLIA certified laboratory. The New York State Department of Health requires every LDT to be reviewed for its analytical and clinical performance, as well as its reproducibility, by going through the comprehensive and rigorous Clinical Laboratory Evaluation Program (CLEP) Assay Validation Review. This review is considered to be one of the most important levels of validation for LDTs.

“We are pleased to receive the approval from the New York State Department of Health for our PDxBr breast test. This approval marks a significant regulatory milestone for our company and is a key step on our journey to commercialization,” said Wayne Brinster, CEO of PreciseDx.

The histopathologic characterization of all solid tumors is a crucial first step for diagnostic identification (i.e. organ/cell type) and the determination of the tumor’s histologic grade or state of differentiation. Surgical pathologists often refer to differentiation, or histologic grade, as a marker of the tumor’s aggressiveness and the risk of spread. However, current tumor grading systems have several shortcomings, such as being subjective, interpretive, semiquantitative, skill-dependent, and oftentimes inconsistent and variable. These problems are particularly noticeable in cancers, like prostate and breast cancer, that use complex decision-based scoring systems in order to compute a patient’s clinical risk. To address this problem, the researchers developed the AI-driven Morphology Feature Array by utilizing the PreciseDx Platform. 

“Consistent with our mission of improving healthcare, PDxBr has shown to be an effective prognostic tool to further improve risk stratification over current histopathology methods.”

In December 2022, a study was published in Breast Cancer Research that aimed to evaluate the effectiveness of the PDxBr in enriching breast cancer grading and enhancing risk categorization in order to predict recurrence in patients with early-stage breast cancer. The researchers concluded that the assay was both accurate and reproducible, incorporating machine-learning algorithms alongside standard-of-care attributes such as age, tumor size, and extent of disease, as well as tissue and cellular features such as tumor-stromal ratios and lymphocytic content. As a result, it is able to provide a more comprehensive understanding of the cancer’s biology. Therefore, the study was approved, and future studies are being conducted to explore the potential of this approach in improving treatment decision-making, gene expression assays, and overall disease management. The submission to New York State included this data, which is more detailed in regards to the patient’s disease status and is the cutting edge of pathology analysis.

“The recent clinical validation of the PDx breast test has provided a significant advancement in the characterization of invasive breast cancer through the use of AI,” said Michael J. Donovan, PhD MD CMO and Co-Founder of PreciseDx. “Now, with the recent approval from the New York State Department of Health, the testing platform will soon be available to providers and patients throughout the state.”

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Stan Martin

Stan Martin

Stan Martin is a journalist writing about all aspects of the healthcare sector. Stan's reporting spans a wide array of topics within healthcare, from medical advancements and health policy to patient care and the economic aspects of the healthcare industry. Stan has contributed hundreds of news articles to Healthcare IT Journal, demonstrating a commitment to delivering factual, comprehensive news.

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