Myelodysplastic Syndromes: Where Do We Go From Here?

Publication
Article
OncologyONCOLOGY Vol 25 No 6
Volume 25
Issue 6

The review by Dr. Akhtari outlines the diagnosis, prognosis, and treatment options for patients with myelodysplastic syndromes (MDS), and touches on the current challenges in treating patients suffering from MDS.

The review by Dr. Akhtari outlines the diagnosis, prognosis, and treatment options for patients with myelodysplastic syndromes (MDS), and touches on the current challenges in treating patients suffering from MDS. Specifically, his review highlights the difficulty in treating MDS patients, many of whom are elderly and have multiple co-morbidities. In such patients, treatment options are associated with significant morbidity and mortality; physicians are thus often limited to palliative approaches. Given our aging population and the increasing incidence of MDS, it is essential to improve our ability to identify which patients should be offered treatment as well as to establish realistic outcomes for each individual patient.

The diagnosis of MDS can be challenging since several entities demonstrate overlap between MDS and myeloproliferative disorders (MPD). Advances in current tools, such as flow cytometry, help define specific cell populations/markers unique to MDS for diagnostic as well as prognostic purposes (ie, identification of minimal residual disease [MRD]).[1-3] Molecular studies to evaluate the mutational status of FLT3, NPM1, TET2, CEBPα, IDH1, and IDH2 are useful in assessing the prognosis of patients with acute myeloid leukemia (AML), and these studies (or other novel molecular markers) may be useful in improving our ability to estimate the prognosis of patients with MDS.[4-5] Molecular tests like JAK2 mutation analysis are examples in which these advances have been helpful in the classification of the patient’s disease state as well as establishment of the prognosis.[6]

The most commonly used prognostic classification system is the International Prognostic Scoring System (IPSS). The inclusion of additional factors, such as age, performance status, and degree of cytopenia, as in the MD Anderson risk model, has been proposed with the hope of improving the prognostic accuracy.[7] Unfortunately, the added complexity can be cumbersome and thus is less likely to be utilized by the community. However, it is precisely these “upgrades” that serve to categorize patients more accurately with regard to the need for therapy and help to best identify who might benefit most from each type of therapy.[8] In particular, the WHO classification–based prognostic scoring system (WPSS)[9] score, which incorporates red cell transfusion use into the clinical parameters in the IPSS, can be used to assess prognosis at any time during a patient’s illness-in contrast to the IPSS, which was statistically modeled based only on the initial diagnostic data. Accordingly, the WPSS is the most appropriate score to be used in monitoring for disease progression in patients with MDS.

Improvements in biotechnology are helping to tailor and monitor therapy in patients diagnosed with MDS. Specifically, we have a better handle on the biology of the disease (WPSS score/pace of progression to AML) as well as on the biology of MDS patients (responsiveness to treatment/ability to tolerate therapy). As Dr. Akhtari points out, the decision to treat a patient should be based on his or her age, performance status, and IPSS score. Furthermore, prognostic factors and co-morbidities also impact this decision. For example, allogeneic hematopoietic stem cell transplantation (HSCT) is currently recommended for younger patients with higher-risk MDS, but alternative transplants are now being offered to the elderly population, with advances such as non-myeloablative options and alternative donor transplants. Data on quality of life will need to be collected in order to truly evaluate the success of such modalities.

Treatment decisions for patients with MDS are becoming more complex for physicians. DNA methyltransferase inhibitors such as azacitidine (Vidaza) and decitabine (Dacogen) seem to be well tolerated and to have clinical impact, even in elderly patients. Azacitidine has been shown to double two-year survival in high-risk MDS patients, compared with comparator arms that included best supportive care, low-dose cytarabine, and cytarabine-plus-anthracycline induction chemotherapy.[10] Improving on these responses by combining them with other agents, such as histone deacetylase inhibitors or lenalidomide (Revlimid), is being explored.

As is well described in the Akhtari review, the treatment of patients with MDS is complex and the decision making can be complicated. Given the challenging patient population, it is important to balance attempts to cure the disease (or achieve a long remission state) against the patient’s quality of life. Our ability to monitor this disorder is improving, with established flow cytometry techniques now able to identify MRD. Future studies will have the opportunity to learn from minimal disease states and will potentially offer earlier and more effective treatments tailored to individual patients. Additionally, the role of bone marrow transplant may become more important as the targeted agents delay progression and allow for transplantation, even in an elderly population.

Financial Disclosure:Dr. Carraway has no significant financial interest or other relationship with the manufacturers of any products or providers of any service mentioned in this article. Dr. Gore is a consultant for and receives research support from Celgene. He also has equity ownership in Celgene. 

References:

References:

1. Wells DA, Benesch M, Loken MR, et al. Myeloid and monocytic dyspoiesis as determined by flow cytometric scoring in myelodysplastic syndrome correlates with the IPSS and with outcome after hemopoietic stem cell transplantation. Blood. 2003;102:394-403.

2. Scott B, Wells D, Deeg J, et al. Validation of a flow cytometric scoring system as a prognostic indicator for posttransplanation outcome in patients with myelodysplastic syndrome. Blood. 2008;112:2681-6.

3. Alhan C, Westers T, Van de Loosdrecht A, et al. Flow cytometric score correlates with clinical response to azacitidine in intermediate 2 and high risk myelodysplastic syndrome patients [abstract 441]. American Society of Hematology Annual Meeting and Exposition; 2010 Dec 4-7; Orlando, Fla.

4. Itzykson R, Kosmider O, Fenaux P, et al. Presence of TET2 mutation predicts a higher response rate to azacitidine in MDS and AML post MDS [abstract 439]. American Society of Hematology Annual Meeting and Exposition; 2010 Dec 4-7; Orlando, Fla.

5. Paschka P, Schlenk R, Dohner K, et al. IDH1 and IDH2 mutations are frequently genetic alterations in acute myeloid leukemia and confer adverse prognosis in cytogenetically normal acute myeloid leukemia with NPM1 mutation without FLT3 internal tandem duplication. J Clin Oncol. 2010;28:XX.

6. De Renzis B, Wattel E, Fenaux P, et al. Prognostic Impact of JAK2V617F mutation in MDS: a matched case control study [abstract 440]. American Society of Hematology Annual Meeting and Exposition; 2010 Dec 4-7; Orlando, Fla.

7. Kantarjian H, O’Brien S, Garcia-Manero G, et al. Proposal for a new risk model in myelodysplastic syndrome that accounts for events not considered in the original International Prognostic Scoring System. Cancer. 2008;113:1351-61.

8. Corrales-Yepez M, Lancet J, Komrokji R, et al. Validation of the newly proposed MD Anderson prognostic risk model for patients with myelodysplastic syndromes [abstract 444]. American Society of Hematology Annual Meeting and Exposition; 2010 Dec 4-7; Orlando, Fla.

9. Malcovati L, Germing U, Kuendgen A, et al. Time-dependent prognostic scoring system for predictiong survival and leukemic evolution in myelodysplastic syndromes. J Clin Oncol. 2007;25:3503-10.

10. Fenaux P, Mufti GJ, Silverman LR, et al. Efficacy of azacitidine compared with that of conventional care regimens in the treatment of higher-risk myelodysplastic syndromes: a randomized, open label, phase III study. Lancet Oncol. 2009:10:223-32.

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