Development of a Prognostic Tool for Predicting Prognosis in Early Stage Chronic Lymphocytic Leukemia Patients
Development of a Prognostic Tool for Predicting Prognosis in Early Stage Chronic Lymphocytic Leukemia Patients
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
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).
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Exclusion Criteria: