Validation of the molecular international prognostic scoring system in patients with myelodysplastic syndromes defined by international consensus classification.
Wan-Hsuan LeeMing-Tao TsaiCheng-Hong TsaiFeng-Ming TienMin-Yen LoMei-Hsuan TsengYuan-Yeh KuoMing-Chih LiuYi-Tsung YangJui-Che ChenJih-Luh TangHsun-I SunYi-Kuang ChuangLiang-In LinWen-Chien ChouChien-Chin LinHsin-An HouHwei-Fang TienPublished in: Blood cancer journal (2023)
Myelodysplastic syndromes (MDS) have varied prognoses and require a risk-adapted treatment strategy for treatment optimization. Recently, a molecular prognostic model (Molecular International Prognostic Scoring System [IPSS-M]) that combines clinical parameters, cytogenetic abnormalities, and mutation topography was proposed. This study validated the IPSS-M in 649 patients with primary MDS (based on the 2022 International Consensus Classification [ICC]) and compared its prognostic power to those of the IPSS and revised IPSS (IPSS-R). Overall, 42.5% of the patients were reclassified and 29.3% were up-staged from the IPSS-R. After the reclassification, 16.9% of the patients may receive different treatment strategies. The IPSS-M had greater discriminative potential than the IPSS-R and IPSS. Patients with high, or very high-risk IPSS-M might benefit from allogeneic hematopoietic stem cell transplantation. IPSS-M, age, ferritin level, and the 2022 ICC categorization predicted outcomes independently. After analyzing demographic and genetic features, complementary genetic analyses, including KMT2A-PTD, were suggested for accurate IPSS-M categorization of patients with ASXL1, TET2, STAG2, RUNX1, SF3B1, SRSF2, DNMT3A, U2AF1, and BCOR mutations and those classified as MDS, not otherwise specified with single lineage dysplasia/multi-lineage dysplasia based on the 2022 ICC. This study confirmed that the IPSS-M can better risk-stratified MDS patients for optimized therapeutic decision-making.
Keyphrases
- end stage renal disease
- newly diagnosed
- ejection fraction
- chronic kidney disease
- allogeneic hematopoietic stem cell transplantation
- peritoneal dialysis
- prognostic factors
- machine learning
- type diabetes
- gene expression
- decision making
- metabolic syndrome
- acute lymphoblastic leukemia
- deep learning
- acute myeloid leukemia
- skeletal muscle
- genome wide
- dna methylation
- transcription factor
- weight loss
- mass spectrometry
- clinical practice
- smoking cessation
- patient reported
- human health