Review Article

Prognostic Parameters in Myeloid Malignancies in a Historical Context – From Microscopy to Individualized Medicine

Author(s): Paul Jäger*, Sören Twarock and Rainer Haas

Volume 22 , Issue 2 , 2021

Published on: 01 October, 2020

Page: [202 - 213] Pages: 12

DOI: 10.2174/1389450121666201001122816

Price: $65


With this article, we would like to take the reader on a journey into the world of molecular medicine as it has evolved over the past decades, enabled by advances in genomics. These findings advanced both the development of prognostic parameters and the evolvement of therapy strategies. In this manuscript, we will present haematopoietic diseases as a prime example of this progress because they are relevant not only for their frequency but also for the evident diagnostic and therapeutic progress. The growing understanding of the underlying pathophysiology originates from the cellular pathology as it was described by, e.g., Rudolf Virchow (1821-1902). The identification of specific genomic changes in haematological malignancies and solid tumour diseases provided us with very sensitive tools for diagnostics and prediction of prognosis. Thus, it paved the way for individualized or personalized therapy. In particular, the rapid development of sequencing techniques for the human genome using Next Generation Sequencing (NGS) has contributed to this progress. Recently, artificial intelligence provided us with the tools to analyze the complex interactions of genomic alterations, course of the disease, and further factors of as yet unknown significance. With all these indisputable improvements, we should not neglect the holistic treatment mandate of personalized therapy, i.e., therapy appropriate to the individual. In this context, the treating physician should address relevant co-morbidities, the psychosocial embedding of the patient and his desire for treatment.

Keywords: Myeloid malignancies, next generation sequencing, diagnostic, targeted therapies, prognosis, artificial intelligence, allogeneic stem cell transplantation.

Graphical Abstract

Rights & Permissions Print Export Cite as
© 2022 Bentham Science Publishers | Privacy Policy