MPNs are a gaggle of persistent illnesses of the hematopoietic stem cell leading to overproduction of myeloid progenitor cells, together with white blood cells, pink blood cells or platelets within the bone marrow. Credit score: Karolinska Institutet (2024). DOI: 10.69622/26983783.v1
A brand new thesis from Karolinska Institutet reveals the effectiveness of versatile parametric survival fashions in modeling a number of time-scales, offering a sturdy software for advanced time-to-event information evaluation. The fashions have been examined within the context of myeloproliferative neoplasms, a gaggle of persistent hematologic malignancies through which the bone marrow makes too many pink blood cells, white blood cells, or platelets.
This overproduction can result in varied problems, together with blood clots (thrombosis), bleeding issues, transformation to acute myeloid leukemia and myelodysplastic syndromes.
In her thesis, doctoral pupil Nurgul Batyrbekova on the Division of Medical Epidemiology and Biostatistics, describes a novel technique to modeling a number of time-scales in time-to-event evaluation through the use of versatile parametric survival fashions (FPM) that may seamlessly incorporate a number of time-scales with out requiring information splitting. She additionally explores whether or not conventional survival fashions that depend on a single time-scale result in bias and inaccuracies in sure eventualities.
In two of her research, utilizing the novel technique, Nürgul investigates clinically related questions for MPN, particularly, how the speed of thrombosis and the speed of transformation to AML/MDS are affected by age and length of MPN illness.
General, her thesis may present that the brand new means to make use of a number of time-scales in survival fashions was higher and supplies solutions to clinically related analysis questions within the discipline of MPN.
Extra info:
Nurgul Batyrbekova, Modelling a number of time-scales with versatile parametric survival fashions : with purposes to myeloproliferative neoplasms, (2024). DOI: 10.69622/26983783.v1
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A sturdy software for advanced time-to-event information evaluation within the context of myeloproliferative neoplasms (2024, November 25)
retrieved 25 November 2024
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