Personalized Prediction Model to Risk Stratify Patients With Myelodysplastic Syndromes

Nazha, Aziz; Komrokji, Rami; Meggendorfer, Manja; Jia, Xuefei; Radakovich, Nathan; Shreve, Jacob; Hilton, Cameron Beau; Nagata, Yasunubo; Hamilton, Betty K.; Mukherjee, Sudipto; Ali, Najla Al; Walter, Wencke; Hütter, Stephan; Padron, Eric; Sallman, David A.; Kuzmanovic, Teodora; Kerr, Cassandra M; Ademà, Vera; Steensma, David P.; DeZern, Amy E.; Roboz, Gail J.; Garcia‐Manero, Guillermo; Erba, Harry P.; Haferlach, Claudia; Maciejewski, Jaroslaw P.; Haferlach, Torsten; Sekeres, Mikkael A.

doi:10.1200/jco.20.02810

Cited by 119 publications

(88 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A critical deficiency of these predictive models is the absence of somatic mutations in the models; because of this, some patients deemed LR-MDS by the IPSS-R score may progress more rapidly than predicted. A recent paper by Nazha et al aimed to create a personalized prediction model to help predict survival and leukemia transformation to help guide management in such patients (25). Somatic mutations in seven genes were prognostically significant, and mutations in multiple genes led to worse outcomes.…”

Section: Prognostic Modelsmentioning

confidence: 99%

“…A recent paper by Nazha et al. aimed to create a personalized prediction model to help predict survival and leukemia transformation to help guide management in such patients ( 25 ). Somatic mutations in seven genes were prognostically significant, and mutations in multiple genes led to worse outcomes.…”

Section: Clinical and Laboratory Featuresmentioning

confidence: 99%

“…In regards to prognostication, studies identifying the role of new prognostic models and somatic mutations, such as the new personalized prediction model by Nazha et al., on alloBMT are warranted ( 25 ). Specifically, the implementation of these models for identifying patients in need of transplant is not well defined.…”

Section: Future Perspectivesmentioning

confidence: 99%

See 2 more Smart Citations

BMT for Myelodysplastic Syndrome: When and Where and How

Jain

Elmariah

2022

Front. Oncol.

View full text Add to dashboard Cite

Myelodysplastic syndromes (MDS) are a diverse group of hematological malignancies distinguished by a combination of dysplasia in the bone marrow, cytopenias and the risk of leukemic transformation. The hallmark of MDS is bone marrow failure which occurs due to selective growth of somatically mutated clonal hematopoietic stem cells. Multiple prognostic models have been developed to help predict survival and leukemic transformation, including the international prognostic scoring system (IPSS), revised international prognostic scoring system (IPSS-R), WHO prognostic scoring system (WPSS) and MD Anderson prognostic scoring system (MDAPSS). This risk stratification informs management as low risk (LR)-MDS treatment focuses on improving quality of life and cytopenias, while the treatment of high risk (HR)-MDS focuses on delaying disease progression and improving survival. While therapies such as erythropoiesis stimulating agents (ESAs), erythroid maturation agents (EMAs), immunomodulatory imide drugs (IMIDs), and hypomethylating agents (HMAs) may provide benefit, allogeneic blood or marrow transplant (alloBMT) is the only treatment that can offer cure for MDS. However, this therapy is marred, historically, by high rates of toxicity and transplant related mortality (TRM). Because of this, alloBMT is considered in a minority of MDS patients. With modern techniques, alloBMT has become a suitable option even for patients of advanced age or with significant comorbidities, many of whom who would not have been considered for transplant in prior years. Hence, a formal transplant evaluation to weigh the complex balance of patient and disease related factors and determine the potential benefit of transplant should be considered early in the disease course for most MDS patients. Once alloBMT is recommended, timing is a crucial consideration since delaying transplant can lead to disease progression and development of other comorbidities that may preclude transplant. Despite the success of alloBMT, relapse remains a major barrier to success and novel approaches are necessary to mitigate this risk and improve long term cure rates. This review describes various factors that should be considered when choosing patients with MDS who should pursue transplant, approaches and timing of transplant, and future directions of the field.

show abstract

Section: Prognostic Modelsmentioning

confidence: 99%

Section: Clinical and Laboratory Featuresmentioning

confidence: 99%

See 1 more Smart Citation

BMT for Myelodysplastic Syndrome: When and Where and How

Jain

Elmariah

2022

Front. Oncol.

View full text Add to dashboard Cite

show abstract

“…The inclusion of genetic mutations, mutational patterns, and demographic features allowed researchers to overcome the IPSS-R limitations, as evidenced by the improved prognostication power (C-index 0.74) [ 70 ]. The prognostic value of these features is further demonstrated by the dynamic ML-based genoclinical model described by Nazha et al [ 71 ]. The proposed multicenter-validated model has a C-index of 0.74 and 0.81 for OS and leukemic transformation, respectively, overpowering the IPSS, IPSS-R, and even the models previously described by the same group [ 29 , 71 ].…”

Section: Recent Applications Of Machine Learning Tools In Myelodyspla...mentioning

confidence: 99%

“…The prognostic value of these features is further demonstrated by the dynamic ML-based genoclinical model described by Nazha et al [ 71 ]. The proposed multicenter-validated model has a C-index of 0.74 and 0.81 for OS and leukemic transformation, respectively, overpowering the IPSS, IPSS-R, and even the models previously described by the same group [ 29 , 71 ].…”

Section: Recent Applications Of Machine Learning Tools In Myelodyspla...mentioning

confidence: 99%

Personalized Risk Schemes and Machine Learning to Empower Genomic Prognostication Models in Myelodysplastic Syndromes

Awada

Gurnari

Durmaz

et al. 2022

IJMS

View full text Add to dashboard Cite

Myelodysplastic syndromes (MDS) are characterized by variable clinical manifestations and outcomes. Several prognostic systems relying on clinical factors and cytogenetic abnormalities have been developed to help stratify MDS patients into different risk categories of distinct prognoses and therapeutic implications. The current abundance of molecular information poses the challenges of precisely defining patients’ molecular profiles and their incorporation in clinically established diagnostic and prognostic schemes. Perhaps the prognostic power of the current systems can be boosted by incorporating molecular features. Machine learning (ML) algorithms can be helpful in developing more precise prognostication models that integrate complex genomic interactions at a higher dimensional level. These techniques can potentially generate automated diagnostic and prognostic models and assist in advancing personalized therapies. This review highlights the current prognostication models used in MDS while shedding light on the latest achievements in ML-based research.

show abstract

Diagnosis and Treatment of Myelodysplastic Syndromes

Sekeres

Taylor

2022

JAMA

Self Cite

View full text Add to dashboard Cite

he myelodysplastic neoplasms (MDS), formerly known as myelodysplastic syndromes, are a group of cancers characterized by failure of bone marrow stem cells to mature into normal-functioning blood cells. MDS are characterized by reduced numbers of peripheral blood cells, an increased risk of acute myeloid leukemia transformation, and reduced survival, with a 5-year survival rate of approximately 37%. 1,2 The yearly incidence of MDS is approximately 4 per 100 000 people. 3 MDS are more common in men (with yearly incidence rates of approxi-mately 5.4 per 100 000 vs 2.9 per 100 000 for women) and are more common among people who are White compared with people who are Asian/Pacific Islander (4.0 per 100 000), Black (2.7 per 100 000), or Hispanic (2.9 per 100 000), and among people who are older. 3 The median age of diagnosis is approximately 70 years, and the yearly incidence rate increases to 25 per 100 000 in people aged 65 years and older. 3 Older age is associated with clonal hematopoiesis of indeterminate potential, which is considered a precursor to MDS. 4 Additional risk factors IMPORTANCE Myelodysplastic neoplasms (MDS), formerly known as myelodysplastic syndromes, are clonal hematopoietic malignancies that cause morphologic bone marrow dysplasia along with anemia, neutropenia, or thrombocytopenia. MDS are associated with an increased risk of acute myeloid leukemia (AML). The yearly incidence of MDS is approximately 4 per 100 000 people in the United States and is higher among patients with advanced age.OBSERVATIONS MDS are characterized by reduced numbers of peripheral blood cells, an increased risk of acute myeloid leukemia transformation, and reduced survival. The median age at diagnosis is approximately 70 years, and the yearly incidence rate increases to 25 per 100 000 in people aged 65 years and older. Risk factors associated with MDS include older age and prior exposures to toxins such as chemotherapy or radiation therapy. MDS are more common in men compared with women (with yearly incidence rates of approximately 5.4 vs 2.9 per 100 000). MDS typically has an insidious presentation, consisting of signs and symptoms associated with anemia, thrombocytopenia, and neutropenia. MDS can be categorized into subtypes that are associated with lower or higher risk for acute myeloid leukemia transformation and that help with therapy selection. Patients with lower-risk MDS have a median survival of approximately 3 to 10 years, whereas patients with higher-risk disease have a median survival of less than 3 years. Therapy for lower-risk MDS is selected based on whether the primary clinical characteristic is anemia, thrombocytopenia, or neutropenia. Management focuses on treating symptoms and reducing the number of required transfusions in patients with low-risk disease. For patients with lower-risk MDS, erythropoiesis stimulating agents, such as recombinant humanized erythropoietin or the longer-acting erythropoietin, darbepoetin alfa, can improve anemia in 15% to 40% of patients for a median of 8 to 23 months. For th...

show abstract

Personalized Prediction Model to Risk Stratify Patients With Myelodysplastic Syndromes

Cited by 119 publications

References 14 publications

BMT for Myelodysplastic Syndrome: When and Where and How

BMT for Myelodysplastic Syndrome: When and Where and How

Personalized Risk Schemes and Machine Learning to Empower Genomic Prognostication Models in Myelodysplastic Syndromes

Diagnosis and Treatment of Myelodysplastic Syndromes

Contact Info

Product

Resources

About