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Risk-based Geriatric Assessment Driven Management Algorithm in Older Patients With Cancer Starting Chemotherapy: a Pilot Randomized Controlled Trial
Older patients with cancer are at increased risk of severe chemotherapy-related toxicities due to comorbidities, functional impairments, and geriatric syndromes. Comprehensive geriatric assessment (GA) can identify vulnerabilities and guide tailored management, but routine implementation is challenging due to time and resource constraints. This pilot randomized controlled trial evaluates the feasibility and preliminary efficacy of a patient self-report, risk-based geriatric assessment-driven management algorithm (GA-MA) compared with usual care in older patients starting chemotherapy. Participants aged 65 years or older who are initiating a new chemotherapy regimen are randomized in a 1:1 ratio to receive either GA-MA plus usual care or usual care alone. The primary outcome is the incidence of grade 3 or higher chemotherapy-related toxicities within three months of treatment initiation. Secondary outcomes include emergency department visits, unplanned hospitalizations, early chemotherapy termination, and changes in frailty and performance status. Feasibility outcomes include recruitment, retention, adherence to GA-driven recommendations, and time required to complete geriatric assessment.
This is a single-center, prospective, pilot randomized controlled trial evaluating the feasibility and preliminary effectiveness of a risk-based geriatric assessment-driven management algorithm (GA-MA) in older patients with cancer starting chemotherapy. Older adults receiving chemotherapy are at increased risk of severe treatment-related toxicities due to comorbidities, functional impairments, and geriatric syndromes that are not reliably identified by standard oncology assessments. Comprehensive geriatric assessment (GA) can identify these vulnerabilities and guide individualized supportive care, but routine implementation is challenging in busy oncology clinics. In this study, patients aged 65 years or older who are initiating a new chemotherapy regimen are randomized in a 1:1 ratio to receive either usual care or usual care plus GA-MA. In the intervention arm, patients complete a baseline geriatric assessment using validated self-report tools. Results are reviewed by oncology nurses and treating oncologists, who may apply a predefined risk-based management algorithm developed with multidisciplinary input. GA-driven recommendations may include medication review, nutritional support, physiotherapy or occupational therapy referral, caregiver education, and guidance on chemotherapy dose adjustment for higher-risk patients. Intervention cases are also reviewed in regular multidisciplinary meetings. Participants are followed for three months after chemotherapy initiation. Outcomes include the incidence of grade 3 or higher chemotherapy-related toxicities, emergency department visits, unplanned hospitalizations, early termination of chemotherapy, and changes in frailty and performance status. Feasibility outcomes include recruitment and retention rates, adherence to GA-MA recommendations, and time required to complete geriatric assessment. Results will inform the design of a future larger randomized trial and the feasibility of integrating GA-MA into routine oncology practice.
Age
65 - No limit years
Sex
ALL
Healthy Volunteers
No
Department of Clinical Oncology, School of Clinical Medicine, LKS Faculty of Medicine, the University of Hong Kong, Hong Kong SAR, Hong Kong,
Hong Kong, Hong Kong
Start Date
January 22, 2024
Primary Completion Date
June 30, 2026
Completion Date
October 31, 2026
Last Updated
March 20, 2026
70
ESTIMATED participants
Geriatric Assessment-Driven Management Algorithm (GA-MA)
OTHER
Lead Sponsor
The University of Hong Kong
NCT04235764
NCT04704661
Data Source & Attribution
This clinical trial information is sourced from ClinicalTrials.gov, a service of the U.S. National Institutes of Health.
Modifications: This data has been reformatted for display purposes. Eligibility criteria have been parsed into inclusion/exclusion sections. Location data has been geocoded to enable distance-based search. For the authoritative and most current information, please visit ClinicalTrials.gov.
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