The National MDS Natural History Study: design of an integrated data and sample biorepository to promote research studies in myelodysplastic syndromes

Discordant pathologic diagnoses of myelodysplastic neoplasms and their implications for registries and therapies

Myelodysplastic neoplasms (MDS) are a collection of hematopoietic disorders with widely variable prognoses and treatment options. Accurate pathologic diagnoses present challenges because of interobserver variability in interpreting morphology and quantifying dysplasia. We compared local clinical site diagnoses with central, adjudicated review from 918 participants enrolled in the ongoing National Heart, Lung, and Blood Institute National MDS Natural History Study, a prospective observational cohort study of participants with suspected MDS or MDS/myeloproliferative neoplasms (MPNs). Locally, 264 (29%) were diagnosed as having MDS, 15 (2%) MDS/MPN overlap, 62 (7%) idiopathic cytopenia of undetermined significance (ICUS), 0 (0%) acute myeloid leukemia (AML) with <30% blasts, and 577 (63%) as other. Approximately one-third of cases were reclassified after central review, with 266 (29%) diagnosed as MDS, 45 (5%) MDS/MPN overlap, 49 (5%) ICUS, 15 (2%) AML with <30%, and 543 (59%) as other. Site miscoding errors accounted for more than half (53%) of the local misdiagnoses, leaving a true misdiagnosis rate of 15% overall, 21% for MDS. Therapies were reported in 37% of patients, including 43% of patients with MDS, 49% of patients with MDS/MPN, and 86% of patients with AML with <30% blasts. Treatment rates were lower (25%) in cases with true discordance in diagnosis compared with those for whom local and central diagnoses agreed (40%), and receipt of inappropriate therapy occurred in 7% of misdiagnosed cases. Discordant diagnoses were frequent, which has implications for the accuracy of study-related and national registries and can lead to inappropriate therapy. This trial was registered at www.clinicaltrials.gov as #NCT05074550.

Utility of targeted gene sequencing to differentiate myeloid malignancies from other cytopenic conditions

The National Heart, Lung, and Blood Institute-funded National MDS Natural History Study (NCT02775383) is a prospective cohort study enrolling patients with cytopenia with suspected myelodysplastic syndromes (MDS) to evaluate factors associated with disease. Here, we sequenced 53 genes in bone marrow samples harvested from 1298 patients diagnosed with myeloid malignancy, including MDS and non-MDS myeloid malignancy or alternative marrow conditions with cytopenia based on concordance between independent histopathologic reviews (local, centralized, and tertiary to adjudicate disagreements when needed). We developed a novel 2-stage diagnostic classifier based on mutational profiles in 18 of 53 sequenced genes that were sufficient to best predict a diagnosis of myeloid malignancy and among those with a predicted myeloid malignancy, predict whether they had MDS. The classifier achieved a positive predictive value (PPV) of 0.84 and negative predictive value (NPV) of 0.8 with an area under the receiver operating characteristic curve (AUROC) of 0.85 when classifying patients as having myeloid vs no myeloid malignancy based on variant allele frequencies (VAFs) in 17 genes and a PPV of 0.71 and NPV of 0.64 with an AUROC of 0.73 when classifying patients as having MDS vs non-MDS malignancy based on VAFs in 10 genes. We next assessed how this approach could complement histopathology to improve diagnostic accuracy. For 99 of 139 (71%) patients (PPV of 0.83 and NPV of 0.65) with local and centralized histopathologic disagreement in myeloid vs no myeloid malignancy, the classifier-predicted diagnosis agreed with the tertiary pathology review (considered the internal gold standard).

Health-related quality of life and vulnerability among people with myelodysplastic syndromes: a US national study

Health-related quality of life (HRQoL) and vulnerability are variably affected in patients with myelodysplastic syndromes (MDS) and other cytopenic states; however, the heterogeneity of these diseases has limited our understanding of these domains. The National Heart, Lung, and Blood Institute-sponsored MDS Natural History Study is a prospective cohort enrolling patients undergoing workup for suspected MDS in the setting of cytopenias. Untreated patients undergo bone marrow assessment with central histopathology review for assignment as MDS, MDS/myeloproliferative neoplasm (MPN), idiopathic cytopenia of undetermined significance (ICUS), acute myeloid leukemia (AML) with <30% blasts, or "At-Risk." HRQoL data are collected at enrollment, including the MDS-specific Quality of Life in Myelodysplasia Scale (QUALMS). Vulnerability is assessed with the Vulnerable Elders Survey. Baseline HRQoL scores from 449 patients with MDS, MDS/MPN, AML <30%, ICUS or At-Risk were similar among diagnoses. In MDS, HRQoL was worse for vulnerable participants (eg, mean Patent-Reported Outcomes Management Information Systems [PROMIS] Fatigue of 56.0 vs 49.5; P < .001) and those with worse prognosis (eg, mean Euroqol-5 Dimension-5 Level [EQ-5D-5L] of 73.4, 72.7, and 64.1 for low, intermediate, and high-risk disease; P = .005). Among vulnerable MDS participants, most had difficulty with prolonged physical activity (88%), such as walking a quarter mile (74%). These data suggest that cytopenias leading to MDS evaluation are associated with similar HRQoL, regardless of eventual diagnosis, but with worse HRQoL among the vulnerable. Among those with MDS, lower-risk disease was associated with better HRQoL, but the relationship was lost among the vulnerable, showing for the first time that vulnerability trumps disease risk in affecting HRQoL. This study is registered at www.clinicaltrials.gov as NCT02775383.

Computational analysis of peripheral blood smears detects disease-associated cytomorphologies

Many hematological diseases are characterized by altered abundance and morphology of blood cells and their progenitors. Myelodysplastic syndromes (MDS), for example, are a group of blood cancers characterised by cytopenias, dysplasia of hematopoietic cells and blast expansion. Examination of peripheral blood slides (PBS) in MDS often reveals changes such as abnormal granulocyte lobulation or granularity and altered red blood cell (RBC) morphology; however, some of these features are shared with conditions such as haematinic deficiency anemias. Definitive diagnosis of MDS requires expert cytomorphology analysis of bone marrow smears and complementary information such as blood counts, karyotype and molecular genetics testing. Here, we present Haemorasis, a computational method that detects and characterizes white blood cells (WBC) and RBC in PBS. Applied to over 300 individuals with different conditions (SF3B1-mutant and SF3B1-wildtype MDS, megaloblastic anemia, and iron deficiency anemia), Haemorasis detected over half a million WBC and millions of RBC and characterized their morphology. These large sets of cell morphologies can be used in diagnosis and disease subtyping, while identifying novel associations between computational morphotypes and disease. We find that hypolobulated neutrophils and large RBC are characteristic of SF3B1-mutant MDS. Additionally, while prevalent in both iron deficiency and megaloblastic anemia, hyperlobulated neutrophils are larger in the latter. By integrating cytomorphological features using machine learning, Haemorasis was able to distinguish SF3B1-mutant MDS from other MDS using cytomorphology and blood counts alone, with high predictive performance. We validate our findings externally, showing that they generalize to other centers and scanners. Collectively, our work reveals the potential for the large-scale incorporation of automated cytomorphology into routine diagnostic workflows.

Raising the standards of patient‐centered outcomes research in myelodysplastic syndromes: Clinical utility and validation of the subscales of the QUALMS from the MDS‐RIGHT project

BACKGROUND

Clinical decision-making for patients with myelodysplastic syndromes (MDS) is challenging, and both disease and treatment effects heavily impact health-related quality of life (HRQoL) of these patients. Therefore, disease-specific HRQoL measures can be critical to harness the patient voice in MDS research.

METHODS

We report a prospective international validation study of the Quality of Life in Myelodysplasia Scale (QUALMS) with a main focus on providing information on the psychometric characteristics of its three subscales: physical burden (QUALMS-P), emotional burden (QUALMS-E), and benefit finding (QUALMS-BF). The analysis is based on patients enrolled from three European countries and Israel, participating to the MDS-RIGHT Project. The scale structure and psychometric properties of the QUALMS were assessed.

RESULTS

Overall, 270 patients with a median age of 74 years were analyzed and the majority of them (60.3%) had a low MDS-Comorbidity Index score. Results of the confirmatory factor analysis supported the underlying scale structure of the QUALMS, which, in addition to a total score, includes three subscales: QUALMS-P, QUALMS-E, and the QUALMS-BF. The QUALMS-P exhibited the highest Cronbach's alpha coefficients. Discriminant validity analysis indicated good results with the QUALMS-P and QUALMS-E distinguishing between patients with different performance status, comorbidity, anemia, and transfusion dependency status. No floor and ceiling effects were observed. Responsiveness to change analysis supported the validity of the measure. Patients with a hemoglobin (Hb) level of <11 g/dL at study entry, who subsequently showed an improvement in their Hb levels, also reported a mean score change of 9 and 8 points (scales ranging between 0 and 100) in the expected direction of the QUALMS-E and QUALMS-P, respectively.

CONCLUSIONS

Our study provides additional validation data on the QUALMS from the international MDS-RIGHT Project. The use of this disease-specific HRQoL measure may contribute to raise quality standards of patient-centered outcomes research in MDS.

Failure to Detect Mutations in U2AF1 due to Changes in the GRCh38 Reference Sequence

The U2AF1 gene is a core part of mRNA splicing machinery and frequently contains somatic mutations that contribute to oncogenesis in myelodysplastic syndrome, acute myeloid leukemia, and other cancers. A change introduced in the GRCh38 version of the human reference build prevents detection of mutations in this gene, and others, by variant calling pipelines. This study describes the problem in detail and shows that a modified GRCh38 reference build with unchanged coordinates can be used to ameliorate the issue.

What You Need to Know Before Implementing a Clinical Research Data Warehouse: Comparative Review of Integrated Data Repositories in Health Care Institutions

Background

Integrated data repositories (IDRs), also referred to as clinical data warehouses, are platforms used for the integration of several data sources through specialized analytical tools that facilitate data processing and analysis. IDRs offer several opportunities for clinical data reuse, and the number of institutions implementing an IDR has grown steadily in the past decade.

Objective

The architectural choices of major IDRs are highly diverse and determining their differences can be overwhelming. This review aims to explore the underlying models and common features of IDRs, provide a high-level overview for those entering the field, and propose a set of guiding principles for small- to medium-sized health institutions embarking on IDR implementation.

Methods

We reviewed manuscripts published in peer-reviewed scientific literature between 2008 and 2020, and selected those that specifically describe IDR architectures. Of 255 shortlisted articles, we found 34 articles describing 29 different architectures. The different IDRs were analyzed for common features and classified according to their data processing and integration solution choices.

Results

Despite common trends in the selection of standard terminologies and data models, the IDRs examined showed heterogeneity in the underlying architecture design. We identified 4 common architecture models that use different approaches for data processing and integration. These different approaches were driven by a variety of features such as data sources, whether the IDR was for a single institution or a collaborative project, the intended primary data user, and purpose (research-only or including clinical or operational decision making).

Conclusions

IDR implementations are diverse and complex undertakings, which benefit from being preceded by an evaluation of requirements and definition of scope in the early planning stage. Factors such as data source diversity and intended users of the IDR influence data flow and synchronization, both of which are crucial factors in IDR architecture planning.

The IPSS-R more accurately captures fatigue severity of newly diagnosed patients with myelodysplastic syndromes compared with the IPSS index

We aimed to compare fatigue of newly diagnosed patients with myelodysplastic syndromes (MDS) with that of the general population (GP). We also investigated the ability of the IPSS and IPSS-R to capture severity of patient-reported fatigue at diagnostic workup. A sample of 927 newly diagnosed patients with MDS was consecutively enrolled in a large international observational study and all patients completed the FACIT-Fatigue questionnaire at baseline. Fatigue was compared with that of the GP (N = 1075) and a 3-point difference in mean scores was considered as clinically meaningful. Fatigue of MDS patients was on average 4.6 points below the mean of the GP (95% CI, -5.9 to -3.2, p < 0.001), reflecting clinically meaningful worse fatigue. Unlike the IPSS, the IPSS-R identified clearly distinct subgroups with regard to burden of fatigue. Mean scores differences compared with GP ranged from nonclinically relevant for very low risk (Δ = -1.8, 95% CI, -4.0 to 0.5, p = 0.119) to large clinically meaningful differences for very high-risk IPSS-R patients (Δ = -8.2, 95% CI, -10.3 to -6.2, p < 0.001). At diagnostic workup, fatigue of MDS is clinically meaningful worse than that reported by the GP. Compared with the IPSS classification, the IPSS-R provides a better stratification of patients with regard to fatigue severity.

Assessing clonal haematopoiesis: clinical burdens and benefits of diagnosing myelodysplastic syndrome precursor states

Diagnosing, surveilling, and understanding the biological consequences of clonal haematopoiesis poses a clinical challenge for both patients and clinicians. The relationship between peripheral blood cytopenias and myeloid neoplasms-such as myelodysplastic syndrome-is an area of active research, and understanding of clonal haematopoiesis has developed markedly on the basis of findings concerning somatic mutations in genes known to be associated with myelodysplastic syndrome. These findings have raised the conundrum of how to appropriately define and follow myelodysplastic syndrome precursor states, such as clonal haematopoiesis of indeterminate potential (CHIP) and clonal cytopenias of undetermined significance (CCUS). Identifying these conditions could allow earlier diagnosis of myelodysplastic syndrome, modify surveillance for myelodysplastic syndrome, and possibly guide therapies, but this information also comes at a cost to patients that might or might not be justified by our present understanding of clonal haematopoiesis. When faced with a diagnosis of clonal haematopoiesis, some patients and providers might be content to let the events unfold naturally, whereas others may insist on intense follow-up and early interventions. This Viewpoint assesses recent developments in clonal haematopoiesis and the related implications for affected patients and their providers.