Background: Systematic evaluation and validation of new prognostic and predictive markers, technologies and interventions for colorectal cancer (CRC) is crucial for optimizing patients' outcomes. With only 5-15% of patients participating in clinical trials, generalizability of results is poor. Moreover, current trials often lack the capacity for post-hoc subgroup analyses. For this purpose, a large observational cohort study, serving as a multiple trial and biobanking facility, was set up by the Dutch Colorectal Cancer Group (DCCG).Methods/design: The Prospective Dutch ColoRectal Cancer cohort is a prospective multidisciplinary nationwide observational cohort study in the Netherlands (yearly CRC incidence of 15 500). All CRC patients (stage...
Real-world data (RWD) sources are important to advance clinical oncology research and evaluate treat...
Real-world data (RWD) sources are important to advance clinical oncology research and evaluate treat...
Introduction The COLO-COHORT study aims to produce a multi-factorial risk prediction model for colo...
Background: Systematic evaluation and validation of new prognostic and predictive markers, technolog...
Background: Systematic evaluation and validation of new prognostic and predictive markers, technolog...
Background: Systematic evaluation and validation of new prognostic and predictive markers, technolog...
Background: Systematic evaluation and validation of new prognostic and predictive markers, technolog...
Background: Systematic evaluation and validation of new prognostic and predictive markers, technolog...
BACKGROUND: Systematic evaluation and validation of new prognostic and predictive markers, technolog...
BACKGROUND: Systematic evaluation and validation of new prognostic and predictive markers, technolog...
BACKGROUND: Systematic evaluation and validation of new prognostic and predictive markers, technolog...
Systematic evaluation and validation of new prognostic and predictive markers, technologies and inte...
Contains fulltext : 171289.pdf (publisher's version ) (Open Access)BACKGROUND: Sys...
Real-world data (RWD) sources are important to advance clinical oncology research and evaluate treat...
Real-world data (RWD) sources are important to advance clinical oncology research and evaluate treat...
Real-world data (RWD) sources are important to advance clinical oncology research and evaluate treat...
Real-world data (RWD) sources are important to advance clinical oncology research and evaluate treat...
Introduction The COLO-COHORT study aims to produce a multi-factorial risk prediction model for colo...
Background: Systematic evaluation and validation of new prognostic and predictive markers, technolog...
Background: Systematic evaluation and validation of new prognostic and predictive markers, technolog...
Background: Systematic evaluation and validation of new prognostic and predictive markers, technolog...
Background: Systematic evaluation and validation of new prognostic and predictive markers, technolog...
Background: Systematic evaluation and validation of new prognostic and predictive markers, technolog...
BACKGROUND: Systematic evaluation and validation of new prognostic and predictive markers, technolog...
BACKGROUND: Systematic evaluation and validation of new prognostic and predictive markers, technolog...
BACKGROUND: Systematic evaluation and validation of new prognostic and predictive markers, technolog...
Systematic evaluation and validation of new prognostic and predictive markers, technologies and inte...
Contains fulltext : 171289.pdf (publisher's version ) (Open Access)BACKGROUND: Sys...
Real-world data (RWD) sources are important to advance clinical oncology research and evaluate treat...
Real-world data (RWD) sources are important to advance clinical oncology research and evaluate treat...
Real-world data (RWD) sources are important to advance clinical oncology research and evaluate treat...
Real-world data (RWD) sources are important to advance clinical oncology research and evaluate treat...
Introduction The COLO-COHORT study aims to produce a multi-factorial risk prediction model for colo...