Classification, risk stratification and response assessment in myelodysplastic syndromes/neoplasms (MDS): A state-of-the-art report on behalf of the International Consortium for MDS (icMDS).

The guidelines for classification, prognostication, and response assessment of myelodysplastic syndromes/neoplasms (MDS) have all recently been updated. In this report on behalf of the International Consortium for MDS (icMDS) we summarize these developments. We first critically examine the updated World Health Organization (WHO) classification and the International Consensus Classification (ICC) of MDS. We then compare traditional and molecularly based risk MDS risk assessment tools. Lastly, we discuss limitations of criteria in measuring therapeutic benefit and highlight how the International Working Group (IWG) 2018 and 2023 response criteria addressed these deficiencies and are endorsed by the icMDS. We also address the importance of patient centered care by discussing the value of quality-of-life assessment. We hope that the reader of this review will have a better understanding of how to classify MDS, predict clinical outcomes and evaluate therapeutic outcomes.

Quantitative assessment of macular and circumpapillary retinal vessel density across all stages of Leber hereditary optic neuropathy using swept source optical coherence tomography angiography.

PURPOSE: To investigate the macular and circumpapillary retinal microvasculature across all stages of Leber hereditary optic neuropathy (LHON) using swept source optical coherence tomography angiography (OCTA). METHODS: This prospective, multicentre, cross-sectional, observational study analysed a total of 119 eyes of 60 patients with molecularly confirmed LHON across all stages and 120 eyes of 60 control subjects. Optical coherence tomography angiography maps centred on the fovea and optic disc were obtained to measure vessel densities (VDs) in the macular superficial (SCP) and deep (DCP) capillary plexuses, and the radial peripapillary capillary plexus (RPCP) respectively. RESULTS: In asymptomatic eyes, only the SCP showed significant changes on average (B coefficient = -0.72, 95% CI = -1.34 to -0.10, p = 0.022) or in sectors representing the papillomacular bundle (PMB) (B coefficient = -1.17, 95% CI = -2.23 to -0.11, p = 0.031). However, in chronic eyes, the greatest magnitude of change was found in the temporal sector of the RPCP (B coefficient = -12.36, 95% CI = -14.49 to -10.23, p < 0.001). The RPCP showed the strongest correlations with visual acuity (VA, logarithm of the minimum angle of resolution; R = -0.677, p < 0.001) and structural parameters (R = 0.747, p < 0.001). CONCLUSIONS: Retinal VD changes in the circumpapillary region of the PMB appear later than in the macula but end up being more profound and correlate better with VA and structural parameters. Further studies are needed to assess the clinical utility of retinal VDs as potential LHON biomarkers.

Building a Healthcare Alliance for Resourceful Medicine Offensive Against Neoplasms in Hematology Added Value Framework for Hematologic Malignancies: A Comparative Analysis of Existing Tools.

OBJECTIVES: The Innovative Medicines Initiative-funded, multistakeholders project Healthcare Alliance for Resourceful Medicine Offensive Against Neoplasms in Hematology (HARMONY) created a task force involving patient organizations, medical associations, pharmaceutical companies, and health technology assessment/regulator agencies' representatives to evaluate the suitability of previously established value frameworks (VFs) for assessing the clinical and societal impact of new interventions for hematologic malignancies (HMs). METHODS: Since the HARMONY stakeholders identified the inclusion of patients' points of view on evaluating VFs as a priority, surveys were conducted with the patient organizations active in HMs and part of the HARMONY network, together with key opinion leaders, pharmaceutical companies, and regulators, to establish which outcomes were important for each HM. Next, to evaluate VFs against the sources of information taken into account (randomized clinical trials, registries, real-world data), structured questionnaires were created and filled by HARMONY health professionals to specify preferred data sources per malignancy. Finally, a framework evaluation module was built to analyze existing clinical VFs (American Society of Clinical Oncology, European Society of Medical Oncology, Magnitude of Clinical Benefit Scale, Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen, Institute for Clinical and Economic Review, National Comprehensive Cancer Network Evidence Blocks, and patient-perspective VF). RESULTS: The comparative analysis describes challenges and opportunities for the use of each framework in the context of HMs and drafts possible lines of action for creating or integrating a more specific, patient-focused clinical VF for HMs. CONCLUSIONS: None of the frameworks meets the HARMONY goals for a tool that applies to HMs and assesses in a transparent, reproducible, and systematic way the therapeutic value of innovative health technologies versus available alternatives, taking a patient-centered approach and using real-world evidence.

hGLUTEN Tool: Measuring Its Social Impact Indicators.

hGLUTEN is a technological solution capable of detecting gluten and spoiled food. We measured the social impact of the hGLUTEN tool using two Likert scale surveys with two groups: professionals (engineers/chefs) and end-users. These data have been assessed in accordance with the social impact indicators defined for the Key Impact Pathways introduced by the European Commission for Horizon Europe and the criteria of the Social Impact Open Repository (SIOR). A total of 85% of users, 100% of engineers and 68% of professional chefs consider it very relevant to participate and give their opinion in research projects, which shows the increasingly high level of involvement of the general population. A total of 88% of users were unaware of other applications that detect gluten and were more dependent on guidelines provided by allergy associations and expiry dates of foodstuffs. In addition, only 5% of professional chefs said they were aware of other technology capable of detecting gluten in food, which may indicate a large economic market and good commercialisation possibilities for the tool in the future. Finally, the inclusion of tools to motivate users to promote it has been identified as an area for improvement, which could mean that it should be made more visible in the media to increase its impact and influence.

Classification and Personalized Prognostic Assessment on the Basis of Clinical and Genomic Features in Myelodysplastic Syndromes.

PURPOSE: Recurrently mutated genes and chromosomal abnormalities have been identified in myelodysplastic syndromes (MDS). We aim to integrate these genomic features into disease classification and prognostication. METHODS: We retrospectively enrolled 2,043 patients. Using Bayesian networks and Dirichlet processes, we combined mutations in 47 genes with cytogenetic abnormalities to identify genetic associations and subgroups. Random-effects Cox proportional hazards multistate modeling was used for developing prognostic models. An independent validation on 318 cases was performed. RESULTS: We identify eight MDS groups (clusters) according to specific genomic features. In five groups, dominant genomic features include splicing gene mutations (SF3B1, SRSF2, and U2AF1) that occur early in disease history, determine specific phenotypes, and drive disease evolution. These groups display different prognosis (groups with SF3B1 mutations being associated with better survival). Specific co-mutation patterns account for clinical heterogeneity within SF3B1- and SRSF2-related MDS. MDS with complex karyotype and/or TP53 gene abnormalities and MDS with acute leukemia-like mutations show poorest prognosis. MDS with 5q deletion are clustered into two distinct groups according to the number of mutated genes and/or presence of TP53 mutations. By integrating 63 clinical and genomic variables, we define a novel prognostic model that generates personally tailored predictions of survival. The predicted and observed outcomes correlate well in internal cross-validation and in an independent external cohort. This model substantially improves predictive accuracy of currently available prognostic tools. We have created a Web portal that allows outcome predictions to be generated for user-defined constellations of genomic and clinical features. CONCLUSION: Genomic landscape in MDS reveals distinct subgroups associated with specific clinical features and discrete patterns of evolution, providing a proof of concept for next-generation disease classification and prognosis.

Multidimensional assessment of patient condition and mutational analysis in peripheral blood, as tools to improve outcome prediction in myelodysplastic syndromes: A prospective study of the Spanish MDS group.

The International Prognostic Scoring System and its revised form (IPSS-R) are the most widely used indices for prognostic assessment of patients with myelodysplastic syndromes (MDS), but can only partially account for the observed variation in patient outcomes. This study aimed to evaluate the relative contribution of patient condition and mutational status in peripheral blood when added to the IPSS-R, for estimating overall survival and the risk of leukemic transformation in patients with MDS. A prospective cohort (2006-2015) of 200 consecutive patients with MDS were included in the study series and categorized according to the IPSS-R. Patients were further stratified according to patient condition (assessed using the multidimensional Lee index for older adults) and genetic mutations (peripheral blood samples screened using next-generation sequencing). The change in likelihood-ratio was tested in Cox models after adding individual covariates. The addition of the Lee index to the IPSS-R significantly improved prediction of overall survival [hazard ratio (HR) 3.02, 95% confidence interval (CI) 1.96-4.66, P < 0.001), and mutational analysis significantly improved prediction of leukemic evolution (HR 2.64, 1.56-4.46, P < 0.001). Non-leukemic death was strongly linked to patient condition (HR 2.71, 1.72-4.25, P < 0.001), but not to IPSS-R score (P = 0.35) or mutational status (P = 0.75). Adjustment for exposure to disease-modifying therapy, evaluated as a time-dependent covariate, had no effect on the proposed model's predictive ability. In conclusion, patient condition, assessed by the multidimensional Lee index and patient mutational status can improve the prediction of clinical outcomes of patients with MDS already stratified by IPSS-R.

Assessment of late cardiomyopathy by magnetic resonance imaging in patients with acute promyelocytic leukaemia treated with all-trans retinoic acid and idarubicin.

Late cardiomyopathy CMP is regarded as a potential severe long-term complication after anthracycline-based regimens for acute promyelocitic leukaemia (APL). We assess by MRI the incidence and severity of clinical and subclinical long-term CMP in a cohort of adult APL patients in first complete remission with PETHEMA trials. Adult patients diagnosed with APL in first complete remission lasting ≥2 years underwent anamnesis and physical examination and were asked to perform a cardiac MRI. Clinical CMP was defined as radiographic and physical signs of heart failure accompanied by symptoms or by left ventricle ejection fraction (LVEF) <45% by MRI with or without symptoms. Subclinical CMP was defined as the following MRI abnormalities: LVEF 45-50% or late gadolinium enhancement or two or more of LVEF ≤55%, left ventricle end-diastolic volume index ≥98 ml/m2, left ventricle end-systolic volume index ≥38 ml/m2, right ventricle end-diastolic volume index ≥106 ml/m2 and regional wall motion abnormalities. Of the 82 patients enrolled in the study, median cumulative dose of anthracyclines (doxorubicin equivalence) was 650 mg/m2, and median time from APL diagnosis to the study was 87 months (range, 24-195). Seven out of 57 patients with available MRI (12%) had subclinical CMP (all of them showed late gadolinium enhancement in MRI), and none had clinical CMP. Among the 25 patients without MRI, none had CMP by chest X-ray and physical assessment. In summary, we found 12% of subclinical and no clinical late CMP assessed by MRI in APL patients treated with PETHEMA protocols. Due to the low number of patients, we must interpret our results cautiously.

Integrating clinical features and genetic lesions in the risk assessment of patients with chronic myelomonocytic leukemia.

Chronic myelomonocytic leukemia (CMML) is a myelodysplastic/myeloproliferative neoplasm with variable clinical course. To predict the clinical outcome, we previously developed a CMML-specific prognostic scoring system (CPSS) based on clinical parameters and cytogenetics. In this work, we tested the hypothesis that accounting for gene mutations would further improve risk stratification of CMML patients. We therefore sequenced 38 genes to explore the role of somatic mutations in disease phenotype and clinical outcome. Overall, 199 of 214 (93%) CMML patients carried at least 1 somatic mutation. Stepwise linear regression models showed that these mutations accounted for 15% to 24% of variability of clinical phenotype. Based on multivariable Cox regression analyses, cytogenetic abnormalities and mutations in RUNX1, NRAS, SETBP1, and ASXL1 were independently associated with overall survival (OS). Using these parameters, we defined a genetic score that identified 4 categories with significantly different OS and cumulative incidence of leukemic evolution. In multivariable analyses, genetic score, red blood cell transfusion dependency, white blood cell count, and marrow blasts retained independent prognostic value. These parameters were included into a clinical/molecular CPSS (CPSS-Mol) model that identified 4 risk groups with markedly different median OS (from >144 to 18 months, hazard ratio [HR] = 2.69) and cumulative incidence of leukemic evolution (from 0% to 48% at 4 years, HR = 3.84) (P < .001). The CPSS-Mol fully retained its ability to risk stratify in an independent validation cohort of 260 CMML patients. In conclusion, integrating conventional parameters and gene mutations significantly improves risk stratification of CMML patients, providing a robust basis for clinical decision-making and a reliable tool for clinical trials.