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Prognostication in myelofibrosis: Integrating genetics into routine practice
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One of the most exciting aspects of clinical research is translating lab-based discoveries into tests and treatments that can be used in daily clinical practice.
The last 2 decades have yielded an explosive amount of information about the genetics of hematologic malignancies, as well as targeted therapies based on this information.
Myeloproliferative neoplasms (MPNs) are no exception.
Prior to the 2005 discovery of the JAK2 V617F mutation in most patients, MPNs were classified as diseases rather than neoplasms.
This semantic difference may seem trivial, but it has tremendous implications on how patients are cared for. It is quite different to tell a patient he or she has a “disorder” than it is to say the person has a malignant neoplasm.
Understanding that patients with MPNs have a genetic marker of disease was the springboard that led to the discovery of additional genetic mutations, primarily in calreticulin (CALR) and MPL among most patients without JAK2 mutations.
In addition, we now know many patients have more than one mutation beyond JAK2, CALR or MPL mutations. Clinicians now routinely test for these three mutations, and many commonly test for dozens of other genes, as well.
More knowledge, more questions
Since the discovery of the JAK2 mutation, several important developments have occurred in the field of MPNs.
WHO has updated and refined how patients with MPNs are diagnosed. The National Comprehensive Cancer Network developed diagnosis and treatment guidelines for MPNs for the first time. In 2011, the FDA approved the first JAK inhibitor for the management of patients with myelofibrosis, a dramatic advance in patient care.
These advances highlight improved understanding of disease biology, diagnosis and treatment.
However, as happens often, more knowledge leads to more questions.
Outcomes for patients with myelofibrosis — arguably the most serious of the MPNs — vary significantly. Some patients live a few years from the time to diagnosis, and others live for several decades.
Risk-stratification models have existed for decades; however, until recently, they have not incorporated any genetic data. As clinicians, we often are left wondering how to integrate results from genetic testing into routine practice.
Several models for risk stratification exist for myelofibrosis. They include the International Prognostic Scoring System (IPSS), the dynamic IPSS (DIPSS) and DIPSS-plus.
These risk scores — the most common of which is DIPSS-plus — integrate clinical factors (eg, blood counts), symptoms, some biologic factors and cytogenetics; however, they do not include molecular data.
The ASH Annual Meeting and Exposition in December featured two key studies to help clinicians more accurately risk-stratify patients with myelofibrosis in a way that considers genetic data and updates risk stratification for myelofibrosis in line with our knowledge of the disease.
Enhanced prognostic score
Guglielmelli and colleagues presented results of a study — since published in Journal of Clinical Oncology — that included 805 patients with primary myelofibrosis. The patients, all of whom were aged younger than 70 years, were recruited from centers in Italy, as well as Mayo Clinic.
Investigators created two scores based on variables extracted from a Cox multivariable model that predicted OS. The first score — MIPSS70-plus — integrated clinical and genetic information. The second score, MIPSS70, was used for patients without cytogenetic data.
This new risk-stratification model confirmed the negative predictive value of many variables used in the DIPSS-plus model. However, for the first time, it added genetic variables to the mix.
More than 90% of patients with myelofibrosis will have a mutation in JAK2, CALR or MPL. This score incorporates those three variables, with calreticulin mutations being most favorable in the score.
In addition, more than 80% of patients with primary myelofibrosis harbor other mutations, such as ASXL1, TET2, EZH2, SRSF2, DNMT3A, U2AF1 and IDH1/IDH2.
Not only does the MIPSS70-plus score consider the presence or absence of additional genetic mutations, it is weighed differently whether a patient has more than one mutation. This is relevant, as studies have shown that more mutations are associated with worse outcomes.
Several points are worth mentioning about this score.
It is designed for individuals aged younger than 70 years — arbitrarily defined by this study as the upper age to go to transplant — to help make decisions about who should go to transplant. However, Guglielmelli and colleagues validated their score in patients aged older than 70 years, and it seemed to retain its validity.
A unique feature of MIPSS is that two systems were developed, one with cytogenetic data and one without. This is useful clinically, as many times it is difficult to get karyotype information from bone marrow of patients with myelofibrosis.
Like the DIPSS scores before it, it is only validated for people with primary myelofibrosis. It is not validated for secondary myelofibrosis, meaning myelofibrosis that developed from an underlying MPN, such as polycythemia vera or essential thrombocythemia.
An additional aspect of this score is that it includes patients with prefibrotic myelofibrosis, a small subpopulation of patients without overt myelofibrosis but with a higher risk of transformation to myelofibrosis than other MPNs. This score is helpful for risk stratifying this group, as well.
The score identified seven independent predictors of survival: hemoglobin, circulating blasts, constitutional symptoms, absence of a CALR type 1-like mutation, high molecular risk category, two or more high molecular risk mutations, and unfavorable karyotype.
Different weights are given based on the HR calculated for each variable. A four-category MIPSS70-plus risk model was created: low (score of 0 to 2), intermediate (score of 3), high (score of 4 to 6) and very high (score of 7 or higher).
To facilitate its use in clinical practice, the authors developed an online calculator, available at www.mipss70score.it.
Prognostic model for secondary myelofibrosis
In general, risk-stratification models have been developed and validated only for primary myelofibrosis. Although these scores are applied to patients with secondary myelofibrosis in clinical practice, they were not developed for these patients.
At ASH, Masarova and colleagues from The University of Texas MD Anderson Cancer Center presented results of a study designed to validate a prognostic model for patients with myelofibrosis secondary to polycythemia vera or essential thrombocythemia.
This presentation built upon work by Passamonti and colleagues, published last year in Leukemia.
This initial publication — based on a study of 685 patients — developed a risk score for patients with secondary myelofibrosis.
This score, termed MYSEC-PM, identified similar risk factors to those used in DIPSS-plus, with the addition of genetic mutations as part of risk stratification.
Specifically, the score assigns 2 points to a hemoglobin less than 11 g/dL (similar to DIPSS-plus), circulating blasts of greater than 3%, and to CALR-unmutated genotype. One point is assigned for platelets less than 150 x 109/l and to constitutional symptoms. Finally, 0.15 points are assigned for each year of age.
The MYSEC-PM divided patients into four categories: low, intermediate-1, intermediate 2 and high risk.
Masarova and colleagues applied this score to 178 newly diagnosed patients and 244 patients at the time of referral to their center between 1984 and 2015.
Investigators compared the MYSEC-PM to the IPSS and DIPSS. They determined the MYSEC-PM model better classified patients into prognostic categories.
Of note, the MYSEC-PM’s prognostic value was validated only at time of diagnosis, similarly to IPSS and DIPSS, specifically for patients with intermediate-risk DIPSS.
This risk score and its validation represent an important step in the care of patients with secondary myelofibrosis, and it supports the understanding that clinical behavior of secondary myelofibrosis may be different from primary myelofibrosis.
Practically, it allows clinicians to more accurately risk stratify patients with secondary myelofibrosis to better care for them.
From a research perspective, more work needs to be done to create a score that is dynamic and allows for risk stratification during treatment, similarly to the DIPSS-plus.
In addition, although the MYSEC-PM includes CALR, JAK2 and MPL, it does not include other genetic mutations, such as ASXL1, TET2 and others, that likely affect prognosis.
Conclusion
Accurate risk stratification is a critical first step in the care of patients with either primary or secondary myelofibrosis, as this helps to better inform patients about their disease and to determine treatment.
These two new risk stratification models represent an important step toward more accurately risk stratifying patients.
For patients with primary myelofibrosis, the MIPSS70 score provides a comprehensive tool that includes clinical and molecular data to more precisely prognosticate outcomes. The score immediately translates into clinical care, as it allows clinicians to better assess which patients should be considered for an allogeneic transplant.
It is worth noting that many centers will take patients to transplant even if they are aged older than 70 years; however, the score is still relevant for this population, as the authors validated the score in these older patients, as well.
The MYSEC-PM represents a recognition in the field that secondary myelofibrosis may not behave the same as primary myelofibrosis. Although the variables in the score are similar to other risk prediction tools, more accurately predicting outcomes for this patient population with a tailored tool is critical.
Risk stratification not only helps clinicians talk to patients more honestly about prognosis, it helps to enroll and follow patients more accurately in clinical trials. Ultimately, if we define our patients more accurately, we will be better equipped to identify subgroups of patients that respond well to therapies.
Additional work remains to be done to develop therapies that apply to the needs of each subtype and effectively modify disease biology.
References:
Guglielmelli P, et al. J Clin Oncol. 2018;doi:10.1200/JCO.2017.76.4886.
Masarova L, et al. Abstract 4205. Presented at: ASH Annual Meeting and Exposition; Dec. 9-12, 2017; Atlanta.
Passamonti F, et al. Leukemia. 2017;doi:10.1038/leu.2017.169.
Vannucchi AM, et al. Abstract 200. Presented at: ASH Annual Meeting and Exposition; Dec. 9-12, 2017; Atlanta.
For more information:
Gabriela Hobbs, MD, is instructor in medicine at Harvard Medical School and clinical director of the leukemia service at Massachusetts General Hospital Cancer Center. She also is a HemOnc Today Next Gen Innovator. She can be reached at 100 Blossom St., Boston, MA 02114; email: ghobbs@partners.org.
Disclosure: Hobbs reports no relevant financial disclosures.