Dynamic Bayesian networks for prediction of health status and treatment effect in patients with chronic lymphocytic leukemia.

Chronic lymphocytic leukemia (CLL) is the most common blood cancer in adults. The course of CLL and patients' response to treatment are varied. This variability makes it difficult to select the most appropriate treatment regimen and predict the progression of the disease.

A network meta-analysis of progression free survival and overall survival in first-line treatment of chronic lymphocytic leukemia.

Background: A limited evidence exists regarding comparisons of clinical effectiveness of available therapies for first-line treatment of chronic lymphocytic leukemia (CLL).

Methods: We compared available therapies for treatment-naïve, symptomatic CLL regarding progression free survival (PFS) and overall survival (OS) in all the identified random control trials and in subgroups composed of younger/fit and older/unfit patients, using a Bayesian network meta-analysis.

Results: In younger/fit patients we obtained median of projected mean PFS of: 19, 26, 31, 43, 51 and 75months for chlorambucil, fludarabine, alemtuzumab, fludarabine with cyclophosphamide (FC), bendamustine and fludarabine with cyclophosphamide and rituximab (FCR), respectively.

Area of the diabetic ulcers estimated applying a foot scanner-based home telecare system and three reference methods.

Background: Diabetic foot ulcer area is a basic parameter used for monitoring the wound healing and effectiveness of the treatment applied. TeleDiaFoS (developed earlier in collaboration with the Department and Clinic of Gastroenterology and Metabolic Diseases, Medical University of Warsaw, Warsaw, Poland) is one of just a few systems available that make possible monitoring of the wound size remotely based on the foot scans transmitted to the physician from a patient's home. The aim of this study was to compare the diabetic foot ulcer areas measured using TeleDiaFoS with the results obtained using three reference methods.