Geriatric Core Dataset (G-CODE) for Clinical Research in Elderly Cancer Patients
NCT ID: NCT03976531
Last Updated: 2021-01-20
Study Results
Outcome measurements, participant flow, baseline characteristics, and adverse events have been published for this study.
View full resultsBasic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
COMPLETED
42 participants
OBSERVATIONAL
2015-01-01
2017-01-01
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
The objective of this project is to develop a set of geriatric data, the Geriatric Core Dataset (G-CODE), to be collected in cancer trials of older patients. The methods rely on a consensus process involving international experts in the field of oncology and geriatrics.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
Multicenter Prospective Cohort of Informal Caregivers in Burgundy and Franche-Comté
NCT02626377
Improving Quality of Life in Frail, Older Patients with Hematological Cancer Through Geriatric Assessment and Treatment - a Pilot Study
NCT06689332
Development of General Practitioners Screening Tool of Frail Older Old Community
NCT02087982
MoCA vs. MMS: Which Tool to Detect Cognitive Disorders in Oncogeriatric?
NCT03299855
Opposition to Diagnostic or Therapeutic Procedures by Aged Hospitalized Patient
NCT03373838
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
Ageing is a heterogeneous process that stresses the clinical need to identify comorbid conditions and ageing-related physiologic changes, both well-known factors increasing the risk of treatment side-effects and poor outcomes.
Geriatric assessment (GA) is defined by geriatricians as a multidimensional interdisciplinary assessment of the general health stat us of the older patient, reviewing the medical, psychosocial, functional and environmental domains. For each domain, several tools are available, but consensus is lacking on which tool to use and the optimal cut-offs or threshold scores. The literature supports the prognostic value of the GA and its utility in weighing the benefits and risks of cancer treatments in older adults. However, GA has not been implemented in routine oncology practice or in cancer clinical trials.
In 2011, after a workshop on clinical trial methodology in older adults with cancer, the Elderly Task Force of the European Organization for Research and Treatment of Cancer (EORTC) recommended the use of a standardised minimum data set (minDS) for assessing the global health and functional status of older populations. This minDS consisted of the G8 screening tool, the Instrumental Activities of Daily Living Following a consensus approach, a panel of 14 geriatricians from oncology clinics identified seven domains of importance in geriatric assessment. Based on the international recommendations, geriatricians selected the mostly commonly used tools/items for geriatric assessment by domain. The Geriatric Core Dataset (G-CODE) was progressively developed according to RAND appropriateness ratings and feedback during three successive Delphi rounds. The face validity of the G-CODE was assessed with two large panels of health professionals (55 national and 42 international experts) involved both in clinical practice and cancer trials.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
COHORT
PROSPECTIVE
Study Groups
Review each arm or cohort in the study, along with the interventions and objectives associated with them.
Elderly cancer patients included in randomized controlled trials
No interventions assigned to this group
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
* clinical research associates
* nurses.
18 Years
ALL
No
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
Plate-forme PACAN (Elderly and Cancer Platform)
OTHER
European Georges Pompidou Hospital
OTHER
Hospital Ambroise Paré Paris
OTHER
Institut Curie
OTHER
Centre Leon Berard
OTHER
Institut Claudius Regaud
OTHER
Saint-Louis Hospital, Paris, France
OTHER
Hospital Avicenne
OTHER
Göteborg University
OTHER
Oslo University Hospital
OTHER
City of Hope Comprehensive Cancer Center
OTHER
Institut Bergonié
OTHER
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Principal Investigators
Learn about the lead researchers overseeing the trial and their institutional affiliations.
Simone Mathoulin-Pélissier, MD/PhD
Role: PRINCIPAL_INVESTIGATOR
Institut Bergonié
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
Institut Bergonié, Comprehensive Cancer Center
Bordeaux, , France
Countries
Review the countries where the study has at least one active or historical site.
References
Explore related publications, articles, or registry entries linked to this study.
Paillaud E, Soubeyran P, Caillet P, Cudennec T, Brain E, Terret C, Etchepare F, Mourey L, Aparicio T, Pamoukdjian F, Audisio RA, Rostoft S, Hurria A, Bellera C, Mathoulin-Pelissier S; G-CODE collaborators. Multidisciplinary development of the Geriatric Core Dataset for clinical research in older patients with cancer: A French initiative with international survey. Eur J Cancer. 2018 Nov;103:61-68. doi: 10.1016/j.ejca.2018.07.137. Epub 2018 Sep 11.
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
IB2017-GCODE
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.