Decision Impact Study of PreciseDx Breast

Breast Cancer Clinical Trial

— PDxBRUTILITY  

Official title:

Prospective Clinical Utility / Decision Support Study of an AI-enabled Digital Breast Cancer Test (Precise Dx Breast, PDxBRTM) to Predict Early-stage Breast Cancer Recurrence Within 6 Years

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT06309615
• Other study ID #: PDX-001_2
• Status: Not yet recruiting
• Start date: March 30, 2024
• Est. completion date: May 30, 2029

Study information

• Verified date: March 2024
• Source: Precise Dx, Inc.
• Contact: Kristian Cruz
• Phone: 6468189330
• Email: kcruz[@]precisedx.ai
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

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.

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.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 300
• Est. completion date: May 30, 2029
• Est. primary completion date: May 30, 2025
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: Female
• Age group: 23 Years and older

Eligibility

Inclusion Criteria:

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

Exclusion Criteria:

• Prior history of invasive breast cancer

• Neoadjuvant therapy

Related Conditions & MeSH terms

• Breast Cancer
• Breast Neoplasms

Intervention

Other:
• Standard of Care
To use the patients age, tumor size, grade, and lymph node status and any genomic tests (i.e. OncotypeDx, MammaPrint etc to determine risk of recurrence,

Locations

Country	Name	City	State
n/a

Sponsors (2)

Lead Sponsor	Collaborator
Precise Dx, Inc.	The Cleveland Clinic

References & Publications (2)

Fernandez G, Prastawa M, Madduri AS, Scott R, Marami B, Shpalensky N, Cascetta K, Sawyer M, Chan M, Koll G, Shtabsky A, Feliz A, Hansen T, Veremis B, Cordon-Cardo C, Zeineh J, Donovan MJ. Development and validation of an AI-enabled digital breast cancer a — View Citation

Fernandez G, Zeineh J, Prastawa M, Scott R, Madduri AS, Shtabsky A, Jaffer S, Feliz A, Veremis B, Mejias JC, Charytonowicz E, Gladoun N, Koll G, Cruz K, Malinowski D, Donovan MJ. Analytical Validation of the PreciseDx Digital Prognostic Breast Cancer Test in Early-Stage Breast Cancer. Clin Breast Cancer. 2024 Feb;24(2):93-102.e6. doi: 10.1016/j.clbc.2023.10.008. Epub 2023 Nov 2. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Decision Impact Study of PreciseDx Breast on treating Oncologist	Proportion (target; 20%) of medical oncologists who utilized the PDxBR results in their management of patients with IBC including any of the following decisions / actions: i. overall confirmation or adjustment of original management plan, ii. order / defer genomic testing, iii. adjust type, dose, or regimen of endocrine therapy, iv. introduction of chemotherapy in addition to endocrine treatment, v. use radiotherapy etc.	6-12 months
Primary	Decision Impact Study of PreciseDx Breast on Diagnostic Pathologist	Proportion (target: 20%) of pathologists who utilized the PDxBR results in their routine diagnostic assessment of IBC including any of the following: i. supported and or changed their diagnostic histologic grade (based on the AI-grade provided by the PDxBR assay), ii. provided additional useful information in the histologic assessment of the IBC including the presence of lymphocytes, stromal content etc. iii. found the interactive smart phone accessible digital feature display tool helpful in their understanding and use of the test results in their assessment process.	6-12 months
Secondary	Decision Impact on long term outcomes	Use of NPV, PPV, Sensitivity, Specificity, HR for predicting local-regional, distant metastasis or overall survival.	2-5 years