Dataset Information

ICUS, IDUS, CHIP and CCUS: Diagnostic Criteria, Separation from MDS and Clinical Implications.

ABSTRACT: Various myeloid neoplasms, including the myelodysplastic syndromes (MDS), bear a certain risk of progression to secondary acute myeloid leukemia (sAML). The evolution from low-risk to high-risk MDS and finally to sAML suggests that leukemogenesis is a multistep process. However, even before an overt neoplasm, such as an MDS, develops, "prediagnostic" clonal conditions may be identified. With the advent of large-scale genomic screens, such conditions may be detected quite frequently and early in apparently healthy individuals. Recent data suggest that these conditions increase with age and are indeed associated with an increased risk of the occurrence of MDS or another myeloid neoplasm. In other patients, unexplained cytopenia may be detected and may precede MDS. More recently, diagnostic criteria for potential pre-MDS conditions, including idiopathic cytopenia of uncertain significance and clonal hematopoiesis with indeterminate potential, have been proposed. The current article provides an overview of pre-MDS states and related criteria through which these conditions can be discriminated from each other and from MDS. In addition, the clinical implications and management of pre-MDS states are discussed.

SUBMITTER: Valent P

PROVIDER: S-EPMC7115849 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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ICUS, IDUS, CHIP and CCUS: Diagnostic Criteria, Separation from MDS and Clinical Implications.

Valent Peter P

Pathobiology : journal of immunopathology, molecular and cellular biology 20180601 1

Various myeloid neoplasms, including the myelodysplastic syndromes (MDS), bear a certain risk of progression to secondary acute myeloid leukemia (sAML). The evolution from low-risk to high-risk MDS and finally to sAML suggests that leukemogenesis is a multistep process. However, even before an overt neoplasm, such as an MDS, develops, "prediagnostic" clonal conditions may be identified. With the advent of large-scale genomic screens, such conditions may be detected quite frequently and early in ...[more]

PMID: 29860246

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Project description:Background[18F]FDG-PET hypometabolism patterns are indicative of different neurodegenerative conditions, even from the earliest disease phase. This makes [18F]FDG-PET a valuable tool in the diagnostic workup of neurodegenerative diseases. The utility of [18F]FDG-PET in dementia with Lewy bodies (DLB) needs further validation by considering large samples of patients and disease comparisons and applying state-of-the-art statistical methods. Here, we aimed to provide an extensive validation of the [18F]FDG-PET metabolic signatures in supporting DLB diagnosis near the first clinical assessment, which is characterized by high diagnostic uncertainty, at the single-subject level.MethodsIn this retrospective study, we included N = 72 patients with heterogeneous clinical classification at entry (mild cognitive impairment, atypical parkinsonisms, possible DLB, probable DLB, and other dementias) and an established diagnosis of DLB at a later follow-up. We generated patterns of [18F]FDG-PET hypometabolism in single cases by using a validated voxel-wise analysis (p < 0.05, FWE-corrected). The hypometabolism patterns were independently classified by expert raters blinded to any clinical information. The final clinical diagnosis at follow-up (2.94 ± 1.39 [0.34-6.04] years) was considered as the diagnostic reference and compared with clinical classification at entry and with [18F]FDG-PET classification alone. In addition, we calculated the diagnostic accuracy of [18F]FDG-PET maps in the differential diagnosis of DLB with Alzheimer's disease dementia (ADD) (N = 60) and Parkinson's disease (PD) (N = 36).ResultsThe single-subject [18F]FDG-PET hypometabolism pattern, showing temporo-parietal and occipital involvement, was highly consistent across DLB cases. Clinical classification at entry produced several misclassifications with an agreement of only 61.1% with the diagnostic reference. On the contrary, [18F]FDG-PET hypometabolism maps alone accurately predicted diagnosis of DLB at follow-up (88.9%). The high power of the [18F]FDG-PET hypometabolism signature in predicting the final clinical diagnosis allowed a ≈ 50% increase in accuracy compared to the first clinical assessment alone. Finally, [18F]FDG-PET hypometabolism maps yielded extremely high discriminative power, distinguishing DLB from ADD and PD conditions with an accuracy of > 90%.ConclusionThe present validation of the diagnostic and prognostic accuracy of the disease-specific brain metabolic signature in DLB at the single-subject level argues for the consideration of [18F]FDG-PET in the early phase of the DLB diagnostic flowchart. The assessment of the [18F]FDG-PET hypometabolism pattern at entry may shorten the diagnostic time, resulting in benefits for treatment options and management of patients.

Dataset Information

ICUS, IDUS, CHIP and CCUS: Diagnostic Criteria, Separation from MDS and Clinical Implications.

Publications

ICUS, IDUS, CHIP and CCUS: Diagnostic Criteria, Separation from MDS and Clinical Implications.

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