Ann Lab Med.  2025 Jan;45(1):36-43. 10.3343/alm.2024.0079.

Reclassification of Myelodysplastic Neoplasms According to the 2022 World Health Organization Classification and the 2022 International Consensus Classification Using Open-Source Data: Focus on SF3B1- and TP53-Mutated Myelodysplastic Neoplasms

• Yun J
• Kim HR

• KMID: 2563853
• DOI: http://doi.org/10.3343/alm.2024.0079

Abstract

Background
In 2022, the WHO and International Consensus Classification (ICC) published diagnostic criteria for myelodysplastic neoplasms (MDSs). We examined the influence of the revised diagnostic criteria on classifying MDSs in a large population.
Methods
We retrieved an open-source pre-existing dataset from cBioPortal and included 2,454 patients with MDS in this study. Patients were reclassified based on the new diagnostic 2022 WHO and ICC criteria. Survival analysis was performed using Cox regression to validate the new criteria and to assess risk factors.
Results
Based on the 2022 WHO criteria, 1.4% of patients were reclassified as having AML. The 2022 WHO criteria provide a superior prognostic/diagnostic model to the 2017 WHO criteria (Akaike information criterion, 14,152 vs. 14,516; concordance index, 0.705 vs. 0.681). For classifying MDS with low blast counts and SF3B1 mutation, a variant allele frequency cut-off of 5% (2022 WHO criteria) and the absence of RUNX1 co-mutation (2022 ICC criteria) are diagnostically relevant. For classifying MDSs with mutated TP53, a blast count cut-off of 10% (2022 ICC criteria) and multi-hit TP53 (2022 WHO criteria) are independent risk factors in cases with ≥ 10% blasts.
Conclusions
Our findings support the refinements of the new WHO criteria. We recommend the complementary use of the new WHO and ICC criteria in classifying SF3B1 - and TP53-mutated MDSs for better survival prediction.

Keyword

Information sources; International Consensus Classification; Myelodysplastic syndromes; SF3B1; TP53; WHO Classification

Figure

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  Fig. 1 Subgroup analyses in MDS-SF3B1WHO. Kaplan–Meier curves of overall survival were plotted according to (A) type of SF3B1 variants (K700E alone vs. others), (B) VAF of SF3B1 variants (5%≤VAF<10% vs. VAF≥10%), and (C) RUNX1 co-mutation (wild-type vs. mutated). HRs and 95% CIs were calculated using Cox proportional-hazards models adjusted for sex, age, ontogeny, treatment, type of SF3B1 variants, VAF of SF3B1 variants, and RUNX1 co-mutation. The HR is shown with the 95% CI in parentheses. Abbreviations: VAF, variant allele frequency; HR, hazard ratio; CI, confidence interval.

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  Fig. 2 Relationship between the 2022 WHO and ICC classifications focused on MDSs with mutated TP53. Abbreviations: ICC, International Consensus Classification; VAF, variant allele frequency; -biTP53, with biallelic TP53 inactivation; -IB, with increased blasts; NOS, not otherwise specified; -EB, with excess blasts.

• 

  Fig. 3 Subgroup analyses of MDSs with mutated TP53. (A) Kaplan–Meier curves of overall survival were plotted for MDS with mutated TP53ICC and MDS/AML with mutated TP53ICC. The HR and 95% CI were calculated using a multivariate Cox regression model adjusted for sex, age, ontogeny, diagnosis, and treatment. Within MDS-biTP53WHO, Kaplan–Meier curves of overall survival were plotted according to (B) the type of biallelic TP53 inactivation and (C) VAF of TP53 mutations (whether the ICC diagnoses are MNs with mutated TP53 or not). The HR and 95% CI were calculated using a multivariate Cox regression model adjusted for sex, age, ontogeny, treatment, type of biallelic TP53 inactivation, and VAF of TP53 mutations. (D) Within MDS cases with ≥10% blasts, Kaplan–Meier curves of overall survival were plotted in MDS-IB2WHO|MDS/AMLICC, MDS-IB2WHO|MDS/AML with mutated TP53ICC, and MDS-biTP53WHO|MDS/AML with mutated TP53ICC. The HR and 95% CI were calculated using a multivariate Cox regression model adjusted for sex, age, ontogeny, treatment, and diagnosis. The HR is shown with the 95% CI in parentheses. Abbreviations: ICC, International Consensus Classification; cnLOH, copy-neutral loss of heterozygosity; TP53mut, TP53 mutations; VAF, variant allele frequency; MNs, myeloid neoplasms;. -IB2, with increased blasts-2, -biTP53, with biallelic TP53 inactivation; HR, hazard ratio; CI, confidence interval.

Reference

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