Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
COMPLETED
20000 participants
OBSERVATIONAL
2018-07-01
2018-10-01
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
Usefulness of Blood Biomarkers for Overall Survival in NSCLC
NCT01936571
Rapid Learning for Lung Cancer
NCT01949259
Patient-Defined Treatment Success and Preferences in Stage IV Lung Cancer Patients
NCT02190864
Predictive Multimodal Signatures Associated With Response to Treatment and Prognosis of Patients With Stage IV Non-small Cell Lung Cancer
NCT04994795
Distress and Quality of Life During the Diagnostic Phase of a Suspected Serious Lung Disease
NCT02060877
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
The investigators hypothesize that sharing questions rather than sharing data is a better approach and can unlock orders of magnitude more data while limiting privacy and other concerns. An infrastructure to bring questions to the data has been demonstrated to work recently in project such as euroCAT(Lambin et al., 2013; Deist et al., 2017), Datashield (Gaye et al., 2014) and OHDSI (Hripcsak et al., 2015). However, the scale of the prior work has been limited in terms of the number of data subjects, number of data providers and global coverage.
In the experience of the investigators, the main challenges of scaling up the infrastructure are 1) the effort necessary to make data FAIR at each site ("stations"), 2) the technical and legal governance ("track") and 3) the mathematics and engineering of learning applications ("trains") - together called the Personal Health Train (PHT) infrastructure. Since multiple years a global consortium of healthcare providers, scientists and commercial parties called CORAL (Community in Oncology for RApid Learning) have worked on all three PHT challenges.
The aim of this study is to show that the PHT distributed learning infrastructure can be scaled to many 1000s of patients, specifically the investigators aim to machine learn a predictive model from more than 20.000 non-small cell lung cancer patients from more than 5 health care providers from more than 5 countries.
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
RETROSPECTIVE
Study Groups
Review each arm or cohort in the study, along with the interventions and objectives associated with them.
One group of 20.000 patients
No interventions will take place as this is an observational study
No interventions will take place (observational)
No interventions will take place (observational)
Interventions
Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.
No interventions will take place (observational)
No interventions will take place (observational)
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
* Treated in one of the participating hospitals
Exclusion Criteria
* Not treated in one of the participating centers
ALL
No
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
Radboud University Medical Center
OTHER
The Netherlands Cancer Institute
OTHER
Manchester Academic Health Science Centre
OTHER
Catholic University of the Sacred Heart
OTHER
Fudan University
OTHER
Velindre Cancer Center
UNKNOWN
University of Michigan
OTHER
Cardiff University
OTHER
Maastricht Radiation Oncology
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.
André Dekker, MD, PhD
Role: PRINCIPAL_INVESTIGATOR
Maastro Clinic, The Netherlands
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
MAASTRO clinic
Maastricht, , Netherlands
Countries
Review the countries where the study has at least one active or historical site.
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
20K Distributed Learning
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.