Breast Cancer, Early Breast Cancer, ER-Positive HER2-Negative Breast Cancer
Conditions
Keywords
digital pathology, artificial intelligence, prognostic assay, distant recurrence, ABCSG-8, ABCSG-16, endocrine therapy, whole slide imaging
Brief summary
This retrospective observational study evaluates the prognostic performance of a locked Artificial Intelligence (AI)-based assay in patients with Estrogen Receptor (ER)-positive, Human Epidermal Growth Factor Receptor 2 (HER2)-negative early breast cancer (EBC) from Austrian Breast & Colorectal Cancer Study Group (ABCSG)-8, with extended follow-up from ABCSG-16 where available. ABCSG will provide digitized hematoxylin and eosin (H&E) slides and required baseline clinicopathologic variables to Spotlight Medical without outcome data for blinded assay inference. ABCSG will then perform the prespecified statistical analyses linking assay outputs to clinical outcomes.
Detailed description
This is an independent, external, blinded, retrospective validation study of a locked AI-based prognostic assay in ER-positive/HER2-negative EBC. The source population consists of eligible patients from ABCSG-8 with available archived tumor material suitable for H&E slide digitization, with extended follow-up from ABCSG-16 where available. Primary analyses will be conducted in patients with slides that pass prespecified quality control and with required baseline clinicopathologic variables available or derivable according to the prespecified statistical analysis plan. The assay generates a continuous prognostic score and predefined risk categories using one digitized H&E-stained surgical resection slide together with routine baseline clinicopathologic variables. Spotlight Medical will generate assay predictions while blinded to clinical outcomes. ABCSG will conduct the statistical analyses according to a prespecified protocol and statistical analysis plan. The primary objective is validation of the association of the assay with time to distant recurrence. Secondary objectives are validation of the association of the assay with disease-free survival and overall survival.
Interventions
A locked AI-based assay applied to one digitized H\&E-stained surgical resection slide and routine baseline clinicopathologic variables to generate a continuous prognostic score and predefined risk categories.
Sponsors
Study design
Eligibility
Inclusion criteria
* Female patients enrolled in ABCSG-8 * Postmenopausal patients with ER-positive/HER2-negative early invasive breast cancer * Available archived primary tumor material suitable for H\&E slide digitization * Available required baseline clinicopathologic variables or variables derivable according to the prespecified statistical analysis plan * Patients with permission for inclusion in this retrospective translational research study
Exclusion criteria
* No suitable archived primary tumor material for H\&E slide digitization * Missing required baseline clinicopathologic variables not recoverable according to the prespecified statistical analysis plan * No analyzable follow-up for the endpoint of interest
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Time to distant recurrence | From ABCSG-8 randomization to distant recurrence, assessed up to 15 years. | Association of the continuous assay score and predefined risk categories with time to distant recurrence. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Disease-free survival | From ABCSG-8 randomization to first disease-free survival event, assessed up to 15 years. | Association of the continuous assay score and predefined risk categories with disease-free survival. |
| Overall survival | From ABCSG-8 randomization to death from any cause, assessed up to 15 years. | Association of the continuous assay score and predefined risk categories with overall survival. |
Countries
Austria
Contacts
Medical University of Vienna
Medical University of Vienna