Prognostic scoring systems and risk stratification in myelodysplastic syndrome: focus on integration of molecular profile

Background : Unrecognized myocardial infarction (UMI), as diagnosed by surveillance electrocardiography (ECG), has the same poor prognosis as recognized (RMI), independent of ejection fraction or ischemia. The value of post UMI risk stratification by infarct size is unknown. Methods : The study group consisted of 5430 patients who underwent 2 day stress (exercise n = 191, pharmacologic n = 155) and rest Tc-99m sestamibi SPECT studies. UMI was diagnosed if ECG showed Q wave MI in the absence of history of MI. SPECT infarct size was quantitated based on a 60% of peak counts threshold method and was expressed as a percentage of the left ventricle (% LV). The association between infarct size and mortality was adjusted for clinical and exercise test prognostic scoring systems. Results : The population consisted of 346 UMI, 628 RMI, and 4456 patients without MI (No MI). Compared to No MI, mortality risk was increased in UMI (RR 1.7, 95% CI 1.6–1.9; p < 0.001) and RMI (RR 1.6, 95% CI 1.4–1.9; p < 0.001) patients. In the UMI group, infarct size was significantly associated with mortality ( p < 0.001), which persisted after adjustment for Mayo prognostic score alone (available in all patients) ( p < 0.001) and for Mayo prognostic score, Framingham risk score, and Duke treadmill score (data available in 137 patients) ( p < 0.001). For every 10% LV increase in infarct size, mortality risk increased 30% (RR = 1.3, 95% CI 1.2–1.5) (see figure ). Conclusions: In patients with UMI, larger quantitated SPECT infarct size predicts increased mortality independent of clinical and exercise test prognostic scoring systems. This finding supports the use of infarct size imaging for risk stratification of UMI patients.

Download Full-text

Lower risk but high risk

Hematology ◽

10.1182/hematology.2021000277 ◽

2021 ◽

Vol 2021 (1) ◽

pp. 428-434

Author(s):

Amy E. DeZern

Keyword(s):

High Risk ◽

Risk Stratification ◽

Myelodysplastic Syndromes ◽

Genetic Information ◽

Lower Risk ◽

Molecular Genetic ◽

Scoring Systems ◽

International Prognostic Scoring System ◽

Disease Characteristics ◽

Prognostic Scoring Systems

Abstract Risk stratification is crucial to the appropriate management of most cancers, but in patients with myelodysplastic syndromes (MDS), for whom expected survival can vary from a few months to more than a decade, accurate disease prognostication is especially important. Currently, patients with MDS are often grouped into higher-risk (HR) vs lower-risk (LR) disease using clinical prognostic scoring systems, but these systems have limitations. Factors such as molecular genetic information or disease characteristics not captured in the International Prognostic Scoring System–Revised (IPSS-R) can alter risk stratification and identify a subset of patients with LR-MDS who actually behave more like those with HR-MDS. This review describes the current identification and management of patients with LR-MDS whose condition is likely to behave in a less favorable manner than predicted by the IPSS-R.

Download Full-text

Prognostic models in myelodysplastic syndromes

Hematology ◽

10.1182/asheducation-2013.1.504 ◽

2013 ◽

Vol 2013 (1) ◽

pp. 504-510 ◽

Cited By ~ 18

Author(s):

Rafael Bejar

Keyword(s):

Risk Stratification ◽

Myelodysplastic Syndromes ◽

Somatic Mutations ◽

Scoring Systems ◽

Accurate Estimate ◽

Prognostic Models ◽

International Prognostic Scoring System ◽

Clinical Predictors ◽

Molecular Abnormalities ◽

Prognostic Scoring Systems

Abstract Establishing the prognosis for patients with myelodysplastic syndromes (MDS) is a key element of their care. It helps patients understand the severity of their disease and set expectations for their future. For physicians, an accurate estimate of prognosis drives decisions about the timing and choice of therapeutic options to consider. The International Prognostic Scoring System (IPSS) has been the standard tool for MDS risk stratification since it was released in 1997. It has been used to describe patients in pivotal clinical trials and is a key element of practice guidelines. Subsequent changes to the classification scheme for MDS and an underestimation of risk in some patients from the low and intermediate-1 categories have led to the development of several newer prognostic models. The most recent is the revised IPSS (IPSS-R), which addresses several of the perceived deficiencies of its predecessor. Despite their utility, none of the available prognostic systems incorporates disease-related molecular abnormalities such as somatic mutations. These lesions are present in the nearly all cases and many have been shown to improve upon existing prognostic models. However, the interpretation of somatic mutations can be challenging and it is not yet clear how best to combine them with clinical predictors of outcome. Here I review several prognostic scoring systems developed after the IPSS and describe the emerging use of molecular markers to refine risk stratification in the MDS patient population.

Download Full-text

Microarray-based classifiers and prognosis models identify subgroups with distinct clinical outcomes and high risk of AML transformation of myelodysplastic syndrome

Blood ◽

10.1182/blood-2008-10-187203 ◽

2009 ◽

Vol 114 (5) ◽

pp. 1063-1072 ◽

Cited By ~ 104

Author(s):

Ken I. Mills ◽

Alexander Kohlmann ◽

P. Mickey Williams ◽

Lothar Wieczorek ◽

Wei-min Liu ◽

...

Keyword(s):

Myelodysplastic Syndrome ◽

Scoring Systems ◽

Molecular Classification ◽

Classification Model ◽

Diagnostic Classification ◽

Diagnostic Classification Model ◽

Indolent Disease ◽

Adult Leukemia ◽

Prognostic Scoring Systems ◽

Rapid Transformation

The diagnosis of myelodysplastic syndrome (MDS) currently relies primarily on the morphologic assessment of the patient's bone marrow and peripheral blood cells. Moreover, prognostic scoring systems rely on observer-dependent assessments of blast percentage and dysplasia. Gene expression profiling could enhance current diagnostic and prognostic systems by providing a set of standardized, objective gene signatures. Within the Microarray Innovations in LEukemia study, a diagnostic classification model was investigated to distinguish the distinct subclasses of pediatric and adult leukemia, as well as MDS. Overall, the accuracy of the diagnostic classification model for subtyping leukemia was approximately 93%, but this was not reflected for the MDS samples giving only approximately 50% accuracy. Discordant samples of MDS were classified either into acute myeloid leukemia (AML) or “none-of-the-targets” (neither leukemia nor MDS) categories. To clarify the discordant results, all submitted 174 MDS samples were externally reviewed, although this did not improve the molecular classification results. However, a significant correlation was noted between the AML and “none-of-the-targets” categories and prognosis, leading to a prognostic classification model to predict for time-dependent probability of leukemic transformation. The prognostic classification model accurately discriminated patients with a rapid transformation to AML within 18 months from those with more indolent disease.

Download Full-text

Is dynamic thiol/disulfide homeostasis associated with the prognosis of myelodysplastic syndrome?

Journal of Medical Biochemistry ◽

10.2478/jomb-2019-0050 ◽

2019 ◽

Vol 0 (0) ◽

Author(s):

Mehmet Ali Ucar ◽

Anıl Tombak ◽

Simten Dagdas ◽

Aydan Akdeniz ◽

Funda Ceran ◽

...

Keyword(s):

Risk Factors ◽

Myelodysplastic Syndrome ◽

Cox Regression ◽

Bone Marrow Aspiration ◽

Scoring Systems ◽

Control Group ◽

Total Thiol ◽

Healthy Control ◽

Prognostic Scoring Systems ◽

Relationship Of

Summary Background This study planned to investigate the relationship of dynamic thiol/disulfide homeostasis with the prognosis of myelodysplastic syndrome (MDS). Methods 80 patients who had been diagnosed with MDS between 2012 and 2017 and who were older than 18 were included in the study together with 80 healthy control subjects. The MDS diagnosis was confirmed using bone marrow aspiration-biopsy immunostaining. Dynamic thiol/disulfide homeostasis and ischemia-modified albumin (IMA) levels were examined. Results The average IMA (0.71±0.08 vs. 0.67±0.09; p=0.002), median disulfide (18.0 vs. 11.6; p<0.001), median disulfide/native thiol (6 vs. 3; p<0.001), and median disulfide/total thiol (5.4 vs. 2.9; p<0.001) were found higher in the MDS patients compared to control group, and the median hemoglobin, median white blood cell count, median neutrophil count, median lymphocyte count, average native thiol (290.7±48.5 vs. 371.5±103.8; p<0.001), average total thiol (328.2±48.9 vs. 393±105.5; p<0.001), and average native thiol/total thiol (%) (88.3±4.3 vs. 94.2±2.1; p<0.001) were found to be low. Risk factors such as collagen tissue disease (HR:9.17; p=0.005), MDS-EB-1 (HR:10.14; p=0.032), MDS-EB-2 (HR:18.2; p=0.043), and disulfide/native thiol (HR:1.17; p=0.023) were found as the independent predictors anticipating progression to acute myeloid leukemia. In the Cox regression model, risk factors such as age (HR:1.05; p=0.002), MDS-EB-1 (HR:12.58; p<0.001), MDS-EB-2 (HR:5.75; p=0.033), disulfide/native thiol (HR:1.14; p=0.040), and hemoglobin (HR:0.64; p=0.007) were found as predictors anticipating for mortality. Conclusions We can argue that dynamic thiol/disulfide homeostasis could have significant effects on both the etiopathogenesis and the survival of patients with MDS, and it could be included in new prognostic scoring systems.

Download Full-text