Oncogeriatric Screening and Evaluation Program

NCT07805642 | Not Yet Recruiting

• 1 other identifier: LACOG 0325
• Study Type: observational
• Target: 412
• Locations: 1 country
• Sites: 2

Brief Summary

This study aims to develop, train, and validate a machine learning-based prediction model (PROTEGER) to provide treatment decision recommendations for older adults diagnosed with solid tumor cancers. The study has a two-phase observational design: a retrospective cohort using anonymized data from an oncogeriatric telecommittee to train the predictive model, followed by a prospective multicenter cohort across Chile, Peru, and Brazil. Information from Comprehensive Geriatric Assessments (CGA), treatment decisions, and 3- and 6-month clinical outcomes will be collected to evaluate and validate the decision-support platform's performance in assisting oncology teams.

Conditions

Solid Tumor Cancer

Keywords

Oncogeriatrics

Outcome Measures

Primary Outcomes (1)

• Predictive Accuracy of the PROTEGER Machine Learning Model

  Discrimination performance of the machine learning predictive model in recommending oncogeriatric treatment decisions (standard treatment, dose-adjusted treatment, or supportive care/no treatment) based on Comprehensive Geriatric Assessment (CGA) data, measured by the Area Under the Receiver Operating Characteristic Curve (AUC-ROC), with scores ranging from 0.5 (no discrimination/chance) to 1.0 (perfect discrimination).

  Up to 6 months post-enrollment.

Secondary Outcomes (6)

• Incidence of High-Grade Chemotherapy-Related Adverse Events

  At 3 and 6 months post-enrollment.

• General Quality of Life Score (EORTC QLQ-C30)

  Baseline, 3 months, and 6 months post-enrollment.

• Elderly-Specific Quality of Life Score (EORTC QLQ-ELD14)

  Baseline, 3 months, and 6 months post-enrollment.

• Incidence of Hospitalizations

  At 3 and 6 months post-enrollment.

• Treatment Discontinuation and Dose Reduction Rates

  At 3 and 6 months post-enrollment.

Study Arms (2)

Retrospective Training Cohort (Chile)

Anonymized data from cases submitted to the Oncogeriatrics Telecommittee from 2021 to the end of 2023, obtained from the Chilean Ministry of Health's Digital Hospital database, along with patient survival data, will be used to train and validate the predictive model using machine learning techniques.

Prospective Validation Cohort (Chile, Brasil, Peru)

Older adults with cancer receive a comprehensive geriatric assessment at their respective centers and are introduced to an oncogeriatric team. They will share their baseline characteristics, the results of their CGA, clinical data related to cancer treatment, and 3- and 6-month follow-up for the development and validation of a predictive model using machine learning techniques.

Eligibility Criteria

• Age: 65 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The study population consists of older adults (aged 65 years and older) diagnosed with solid tumor cancers who receive care in public and private health institutions in South America (Chile, Brazil, and Peru). The retrospective cohort includes anonymized historical data from patients evaluated by the Oncogeriatric Tele-Committee of the Chilean Ministry of Health. The prospective cohort comprises consecutive patients seen in routine oncological care who undergo a Comprehensive Geriatric Assessment (CGA) and are managed by local oncogeriatric teams.

You may qualify if:

• Age 65 years or older.
• Diagnosis of solid tumor cancer.
• Must have been evaluated and followed up by a local oncology team.
• Signed Informed Consent Form (ICF) applied in accordance with the local ethics committee.
• Must have undergone a Comprehensive Geriatric Assessment (CGA).

You may not qualify if:

• \- Patients who are unable or unwilling to consent to providing information will be excluded.

Sponsors & Collaborators

• Latin American Cooperative Oncology Group: lead
• ONCOGER SpA: collaborator

Study Sites (2)

BR192 HCOR - Hospital do Coração

São Paulo, São Paulo, 04004-060, Brazil

Location

HIAE - Hospital Israelita Albert Einstein

São Paulo, São Paulo, 05653-000, Brazil

Location

Study Officials

• Luciola Pontes Leite de Barros

  Hospital do Coração (HCOR)

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Project Manager

CONTACT

+55 51 3384 5334; lacog0325@lacog.group

Head of Clinical Operations

CONTACT

+55 (51) 3384.5334; laura.voelcker@lacog.group

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: OTHER
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: August 24, 2026
• First Posted: September 4, 2026
• Study Start: September 1, 2026
• Primary Completion (Estimated): January 1, 2027
• Study Completion (Estimated): July 1, 2027
• Last Updated: September 4, 2026

Record last verified: 2026-08

Locations

BR (2)