Decision Impact Study of PreciseDx Breast

NCT06309615 | Not Yet Recruiting DMC

• 1 other identifier: PDX-001_2
• Study Type: observational
• Target: 300
• Locations: 0 countries
• Sites: N/A

Brief 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.

Conditions

Breast Cancer

Outcome Measures

Primary Outcomes (2)

• 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

• 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 Outcomes (1)

• Decision Impact on long term outcomes

  2-5 years

Study Arms (2)

Standard of Care

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.

Other: Standard of Care

Standard of Care plus PreciseDx Breast test

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.

Other: Standard of Care

Interventions

Standard of Care OTHER

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,

Standard of Care; Standard of Care plus PreciseDx Breast test

Eligibility Criteria

• Age: 23 Years+
• Sex: female
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Accepting all patients newly diagnosed with early stage breast cancer and scheduled for a resection.

You may qualify if:

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

You may not qualify if:

• Prior history of invasive breast cancer
• Neoadjuvant therapy

Sponsors & Collaborators

• Precise Dx, Inc.: lead
• Mount Sinai Hospital, New York: collaborator

Related Publications (2)

• 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.

  PMID: 38114366 BACKGROUND

• 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 assay to predict early-stage breast cancer recurrence within 6 years. Breast Cancer Res. 2022 Dec 20;24(1):93. doi: 10.1186/s13058-022-01592-2.

  PMID: 36539895 RESULT

MeSH Terms

Conditions

Breast Neoplasms

Interventions

Standard of Care

Condition Hierarchy (Ancestors)

Neoplasms by Site; Neoplasms; Breast Diseases; Skin Diseases; Skin and Connective Tissue Diseases

Intervention Hierarchy (Ancestors)

Quality Indicators, Health Care; Quality of Health Care; Health Services Administration; Health Care Quality, Access, and Evaluation

Study Officials

• Gregory S Henderson, MD, PhD

  MOUNT SINAI HOSPITAL

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Kristian Cruz

CONTACT

6468189330; kcruz@precisedx.ai

Michael J Donovan, PhD, MD

CONTACT

6468189330; mdonovan@precisedx.ai

Study Design

• Study Type: observational
• Observational Model: CASE CROSSOVER
• Time Perspective: PROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: February 20, 2024
• First Posted: March 13, 2024
• Study Start: August 1, 2025
• Primary Completion (Estimated): August 1, 2026
• Study Completion (Estimated): May 30, 2029
• Last Updated: May 29, 2025

Record last verified: 2025-05