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Study using artificial intelligence to examine microscope pictures of breast cancer tissue to identify risk of their breast cancer.

Deep Learning on Histopathological Images for Risk Stratification in Indian Breast Cancer Patients - Nil

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2025/12/099178
Enrollment
1000
Registered
2025-12-16
Start date
Unknown
Completion date
Unknown
Last updated
2026-01-12

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health Condition 1: C509- Malignant neoplasm of breast of unspecified site

Interventions

Sponsors

Tata Memorial Centre
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: Female patients diagnosed with invasive HRpositive, HER2-negative breast cancer. Histologically-confirmed invasive carcinoma of the breast, stage I to stage III Available archival H&E slide from diagnostic core biopsy or primary surgery. Must have the following recorded clinicopathologic variables, for eligibility and for applying the AI model: grade, age, ER, PR, HER2 at diagnosis. Recorded follow-up events and time to events, with a minimum of 5 years to last contact or or documented death before 5 years. Age at diagnosis more than 18 years To reduce bias, a consecutive patient data collection is important, where all eligible patients diagnosed within a fixed period of time will be included. i.e. all consecutively-diagnosed eligible patients diagnosed between 2014 to 2015, if required study will be extended to 2016.

Exclusion criteria

Exclusion criteria: Patients with distant metastases at diagnosis should be excluded. Patients with non-available or Poor quality pathology material will be excluded. Patients with no follow up update beyond 3 years will be excluded.

Design outcomes

Primary

MeasureTime frame
To determine the association of the AI-generated risk score (both as continuous and categorical variables) with 5-year patient outcomes. The primary endpoint is distant recurrence-free interval Protocol_Version__1.0 dated 22 Aug 2025 Page 4 of 7(DRFI). Secondary endpoints include recurrence-free interval (RFI), disease-free survival (DFS), and breast cancer-specific survivalTimepoint: 2 years

Secondary

MeasureTime frame
To perform a utility analysis to estimate the proportion of patients whose chemotherapy treatment decisions might potentially change based on the AI-derived risk classification.Timepoint: 2 year

Countries

India

Contacts

Public ContactYogesh Kembhavi

Tata Memorial Center

sudeepgupta04@yahoo.com8591555030

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Feb 4, 2026