Development of a Prognostic Tool for Predicting Prognosis in Early Stage Chronic Lymphocytic Leukemia Patients
Trial Snapshot
- Phase
- Not Applicable
- Status
- Completed
- Sponsor
- Enrollment
- 4,933
- Locations
- 1
- Primary Endpoint
- Discrimination capacity of the study model (per c-index)
Study Overview
Brief Summary
The study aims at developing a model for the prediction of time to first treatment in chronic lymphocytic leukemia patients presenting with asymptomatic early stage disease
Detailed Description
Already existing and coded health-related personal data will be retrospectively collected from the CLL databases of the Institute of Oncology Research and of the Division of Hematology of the University of Eastern Piedmont.
The adjusted association between exposure variables and time to first treatment will be estimated by Cox regression. This approach will provide the covariates independently associated with progression free survival that will be utilized in the development of a model to predict time to first treatment.
Model performance (c-index and net reclassification improvement) in discriminating patients who will eventually be treated vs patients who will not be eventually treated will be compared with that of already existing prognostic model that have been validated to predict overall survival but not time to first treatment in CLL (i.e. CLL-IPI, MDACC score, Barcelona-Brno score).
Study Design
- Study Type
- Observational
- Observational Model
- Cohort
- Time Perspective
- Retrospective
Eligibility Criteria
- Ages
- 18 Years to — (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- •Male or female adults 18 years or older
- •Diagnosis of chronic lymphocytic leukemia
- •Binet A stage at presentation
- •No treatment need at presentation
- •Availability of the baseline and follow-up annotations
Exclusion Criteria
- Not provided
Outcomes
Primary Outcomes
Discrimination capacity of the study model (per c-index)
Time Frame: Time to first treatment: interval between diagnosis and first line therapy (event), death without treatment (censoring), or last follow up without treatment (censoring), up to 20 years
Primary endpoint of the study model ability in discriminating patients who will be eventually treated vs patients who will not be eventually treated. The discrimination capacity of the model will be assessed by calculating the c-index. This approach will allow to estimate the model accuracy and its capacity of discriminating outcome at the individual patient level. Model performance (net reclassification improvement) in discriminating patients who will be eventually treated vs patients who will not be eventually treated will be compared with that of already existing prognostic models that have been validated to predict overall survival but not time to first treatment in CLL (i.e. CLL-IPI, MDACC score, Barcelona-Brno score).
Secondary Outcomes
No secondary outcomes reported
Investigators
Davide Rossi
MD, PhD, Principal investigator
Oncology Institute of Southern Switzerland