Decision Impact Study of PreciseDx Breast (PDxBRUTILITY)

Precise Dx

Status: Begins enrollment this month

Conditions: Breast Cancer

Treatments: Other: Standard of Care

Study type: Observational

Funder types: Other; Industry

Identifiers

NCT06309615

PDX-001_2

Details and patient eligibility

About

The investigator's developed a digital LDT to predict invasive breast cancer (IBC) recurrence within 6 years by combining histologic features extracted from an H&E image of the patients IBC with clinical data including the patients age, tumor size, stage and number of positive lymph nodes. The development of an artificial-intelligent (AI)-grade provides not only an objective, quantitative advancement of classical breast cancer grading but also improves upon the accuracy and utility of clinical risk. The investigator's sought to understand how such a PreciseDx Breast would be used in clinical practice post-surgical resection for women with early-stage IBC.

Full description

Female breast cancer (BC) has surpassed lung cancer as the most commonly diagnosed cancer worldwide, which translates into 24.5% of all cancer diagnoses and 15.5% of all cancer death. In the United States, it is estimated that 290,560 Americans will be diagnosed with breast cancer in 2022 and 43,780 will die of disease. Given these statistics, the 2022 National Comprehensive Cancer Network (NCCN), American Society of Clinical Oncology (ASCO), and College of American Pathologists (CAP) clinical practice guidelines continue to stress the critical importance of the pathology assessment at diagnosis to establish extent of disease and features that reflect a biological potential for recurrence such as histologic grade and stage.

Precise Dx Breast Assay (PDxBR™) is an in vitro prognostic clinically approved test by the NYSDOH to predict breast cancer recurrence for patients diagnosed with early-stage IBC. The test utilizes a digital scan of a representative H&E-stained resection specimen from the patient. Using advances in applied artificial intelligence (AI) outcome-based image analysis, selected features of the invasive cancer are acquired and combined with clinical variables to produce a risk score predicting likelihood of having breast cancer recurrence within 6-years. With the advent of computational methods, the investigator's investigated whether AI interrogation of whole slide images (WSI) could be used to improve on the characterization and accuracy of IBC histopathology. The approach was based on the generation of quantitative, discreet morphology features within a tissue section (Morphology Feature Array, MFA) and the use of machine learning to create AI models that predict risk of recurrence in early-stage disease. The investigator's developed a test that improves risk stratification of IBC relative to the use of clinical features as well as re-classification of standard breast histologic grade into low- and high-risk groups using MFA-enabled AI models.

Enrollment: 300 estimated patients

Sex: Female

Ages: 23+ years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• Invasive breast cancer (ductal / mixed ductal-lobular)

Exclusion criteria

• Prior history of invasive breast cancer
• Neoadjuvant therapy

Trial design

300 participants in 2 patient groups

Standard of Care

Description:

Patients with a diagnosis of early-stage invasive breast cancer, post-surgery, in the process of developing a treatment plan. After a period of 2-4 weeks, patient and provider will receive the PreciseDx breast test results with follow up questionnaires to assess change in care path.

Treatment:

Other: Standard of Care

Standard of Care plus PreciseDx Breast test

Description:

Patients with a diagnosis of early-stage invasive breast cancer, post-surgery, in the process of developing a treatment plan. In addition to standard of care the patient and their provider will also receive the results from the PreciseDx breast test. Questionnaires will be utilized to assess impact on decision making and planned care path.

Treatment:

Other: Standard of Care