Reviews

Meta-analysis of the frequency of JAK2 in primary myelofibrosis according to the detection method used

Monica Mejía-Ochoa, Paola Andrea Acevedo-Toro, Jaiberth Antonio Cardona-Arias

Dra. Mónica Mejía-Ochoa: Bacterióloga, MSc(C) Microbiología y Bioanálisis-Énfasis Hematología. Grupo de Investigación Hematopatología Molecular, Escuela de Microbiología Universidad de Antioquia; Dra. Paola Andrea Acevedo-Toro: Microbióloga y Bioanalista, MSc Ciencias Básicas Biomédicas. Grupo de Investigación Hematopatología Molecular, Escuela de Microbiología Universidad de Antioquia; Dr. Jaiberth Antonio Cardona-Arias: MyB, MSc Epidemiología, MSc Economía Aplicada, PhD (candidato) Salud Pública. Escuela de Microbiología Universidad de Antioquia. Facultad de Medicina Universidad Cooperativa de Colombia. Medellín (Colombia).

Correspondencia: Dr. Jaiberth Antonio Cardona-Arias. Medellín (Colombia). E-mail jaiberthcardona@gmail.com

Received: 30/VIII/2019 Accepted: 07/X/2020

DOI: https://doi.org/10.36104/amc.2020.1462

Abstract

Background and objective: in the global scientific literature, the frequency of JAK2 is highly heterogenous in chronic myeloproliferative neoplasms. The objective of this study was to analyze the prevalence of the JAK2 mutation in primary myelofibrosis (PMF) and compare it according to the detection method used, from 2007-2018.

Materials and methods: a systematic review with meta-analysis, using 21 searches in three multidisciplinary databases. The PRISMA guideline phases of identification, screening, selection and inclusion were applied. Reproducibility and evaluation of the methodological quality were ensured. The analyses were based on frequencies and meta-analysis for the prevalence of the mutation with its 95% confidence interval.

Results: twenty-nine studies with 744 patients were included, mainly from Korea, Brazil and China. The most commonly used technique was AS-PCR, and the prevalence of JAK2 with this technique ranged from 33.3 to 71.4%; with real-time PCR ranging from 42.9 to 77.3%, sequencing from 14.3-57.4%, and ARMS from 36.4-83.3%. The prevalence of JAK2 showed no statistically significant differences according to the type of diagnostic test used.

Conclusion: high frequencies of the JAK2V617F mutation are seen in PMF, which shows that this entity should not be diagnosed solely based on clinical and hematological characteristics, but also on the patients' genetic screening. (Acta Med Colomb 2020; 45. DOI: https://doi.org/10.36104/amc.2020.1462).

Key words: prevalence; mutation; JAK2; primary myelofibrosis; meta-analysis.

Introduction

Primary myelofibrosis (PMF) is a Philadelphia-negative chronic myeloproliferative neoplasm (CMPN). The most recent World Health Organization classification has sub-classified it into prefibrotic and fibrotic states, given the need to differentiate it from essential thrombocythemia. The estimated annual incidence for this disease is 0.5-1.5 cases per 100,000 persons; its prevalence is increasing due to improved diagnosis and survival (1, 2).

Just like the rest of the CMPNs, PMF is characterized by clonal expansion of hematopoietic stem cells which leads to uncontrolled production of mature cells, mainly megakaryocytes and granuloctytes. A characteristic that differentiates this entity from the rest of those in this group is reactive bone marrow fibrosis, with clinical manifestations such as severe anemia, splenomegaly, thrombosis and bleeding (3). It is important to mention that bone marrow fibrosis may be caused by things other than PMF, including reactive states and hematological entities such as some acute leukemias; in these cases, myelofibrosis is termed "secondary" (4).

A diagnostic resource which has permitted the differentiation of the types of myelofibrosis and has elucidated the pathogenesis of CMPNs, has been the detection of various mutations (4), classified as "drivers" and "other mutations". The latter are related to disease prognosis and progression. The driver mutations are used as diagnostic markers; for PMF, the detection of JAK2, CALR and MPL is recommended, with the first being the most relevant (1, 4).

JAK2 is a Janus kinase protein which participates in the JAK-STAT signaling pathway that regulates various cellular processes such as proliferation, differentiation, and apoptosis (5, 6). The JAK2 alteration identified in PMF is JAK2V617F, in which an amino acid substitution produces an altered protein product responsible for the pathogenesis of the disease (5, 6).

Ever since JAK2 was identified in PMF, the objective of several studies has been to determine its frequency, with highly heterogeneous results, probably attributable to the type of study population, as well as to variability in the diagnostic validity parameters of the tests used to detect the marker. To that effect, there are studies with frequencies as low as 14.3%, reported by Jaradat in 2015, and as high as 80.0 and 83.3%, reported by Suzuki in 2007 and Park in 2013, respectively (7-9).

Based on this research background, the objective of this systematic review is to meta-analyze the prevalence of the JAK2 mutation in PMF and compare it according to the detection technique.

Materials and methods

Type of study: a systematic literature review with meta-analysis of indirect measures.

Search protocol and study selection according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guide (10).

Identification: a search was performed without time limits in the Medline PubMed, Scielo and ScienceDirect multidisciplinary databases, using the terms primary myelofibrosis, JAK2, chromosome Ph, Philadelphia chromosome, Philadelphia -Ph- chromosome, Philadelphia translocation and BCR ABL Negative. It should be clarified that the restriction of the window of time to 2007 and later was done a posteriori, based on the oldest study found with the review protocol.

Screening: articles were included which contained the search terms in the title, abstract or key words; duplicate titles were eliminated. Subsequently, the inclusion criteria of studies related to the topic of interest (CMPN), studies reporting the frequency of the JAK2V617F mutation in PMF, and original articles and publications in humans or in vivo, were applied. Some of the syntaxes used were: on PubMed (((JAK2[Title/Abstract]) AND primary myelofibrosis[Title/Abstract]); chromosome ph[Title/Ab-stract]; BCR-ABL Negative[Title/Abstract]; on ScienceDirect: TITLE-ABSTR-KEY(BCR ABL Negative) or TITLE-ABSTR-KEY(Chromosome Ph OR Philadelphia chromosome OR Ph chromosome OR Philadelphia translocation); TITLE-ABSTR-KEY(BCR ABL Negative), and on Scielo: (ti:((ab:(JAK2primary myelofibrosis)))).

Selection: in the next phase, articles with a low number of patients (studies with 10 or fewer cases), studies with incomplete information which did not specify the type of diagnosis or did not report the frequency of mutation, experimental or clinical studies and studies which evaluated diagnostic tests were excluded.

Inclusion: the characterization of the studies was performed with extraction of the following variables: title, authors, type of study, main topic of the study, journal, publication year, first author, study country, number of patients evaluated, frequency of the JAK2V617F mutation, technique for detecting the mutation and description of the study subjects.

Analysis of reproducibility and assessment of methodological quality: the reproducibility of the study search and data extraction was evaluated using two researchers who applied the protocol independently, resolving discrepancies by consensus. The methodological quality was determined using the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) guideline, with the criteria being applied by two researchers, in order to ensure the reproducibility of this phase.

Data analysis

The study variables were described using absolute and relative frequencies. A meta-analysis of indirect measures by detection technique (a comparison of the prevalence of the mutation according to the diagnostic technique, but based on primary studies which do not make this comparison, but rather report the prevalence independently for each detection test analyzed) was used to analyze the frequency of the JAK2V617F mutation in PMF, through a proportion estimate with its 95% confidence interval and Z Test (confidence intervals for the difference in proportions).

Results

A total of 12,845 studies were obtained without applying limits. These were restricted to 1,909 results with the title, abstract and key word search; 253 duplicate articles, 1,482 articles that did not meet the inclusion criteria, and 145 that met the exclusion criteria were eliminated. In the end, 29 studies were selected for the qualitative and quantitative data synthesis (Figure 1).

The studies were published between 2007 and 2018; the countries with the most studies were Korea (n=5), Brazil (n=3) and China (n=3). An analysis by continent shows that the largest number of studies come from Europe and Asia, with 38% each, followed by America with 21% and, finally, Africa with 3%. In the studies which reported the subjects' average age, it was over 45 years, and most used the WHO diagnostic criteria (Table 1).

All the studies had excellent methodological quality, as they met more than 70% of the STROBE guideline criteria. However, most did not explicitly state the parameters used to estimate the sample size, nor discuss the limitations or possibility of generalizing the results (Figure 2).

Based on the use of AS-PCR, the prevalence of JAK2 ranged from 33.3 to 71.4%; with real-time PCR, the range was from 42.9 to 77.3%; with sequencing, it was 14.3-57.4%; and with ARMS, it was 36.4-83.3% (Figure 3). Two studies that used PCR-RFLP reported a prevalence of 72.7 and 40% (32, 32); in Takata' s study with SNP it was 36.4%, for Vytrva with DHPLC it was 63.6%, for Wu Z with HRM it was 58.0%, and for Misawa with ABC-PCR it was 53.8% (34-37).

There was no statistically significant difference in the prevalence of JAK2 by type of diagnostic test; there was a prevalence of 64.6% (95%CI=54.7-74,6) using ARMS in 99 patients; 57.3% (95%CI=47.2-67.3) with real-time PCR in 103 patients; 51.2% (95%CI=44.1-58.3) in 205 patients evaluated with AS-PCR, and 51.0% (95%CI=40.6-61.4) in 98 patients analyzed by sequencing (Figure 4). However, it should be clarified that a comparison of the groups with the highest and lowest prevalence had a statistical power of 77.5%, which would indicate a high |3 error, evidencing the need to increase the number of studies, and patients per study, of this disease.

Discussion

The results of this review with 29 studies and 744 patients show that the main technique used was AS-PCR; the prevalence of JAK2 with this technique ranged from 33.3 to 71.4%. The prevalence with real-time PCR was between 42.9 and 77.3%, with sequencing it was 14.3-57.4%, and with ARMS it was 36.4-83.3%.

Most of the studies were carried out in Korea, Brazil and China, countries with significant development and research policy budget allocations (38). South America showed insufficient development in the search for mutations at the various hematological centers, despite JAK2 being included as a major diagnostic criterion in the 2016 WHO update. This prevents an accurate diagnosis of the disease which could keep it from being confused with other causes of medullary fibrosis, and at the same time prevents a comprehensive study of the disease (1, 39).

The high frequencies of JAK2 mutation found in this study evidence the need to migrate from the conventional prognostic systems based mainly on clinical characteristics, such as the International Prognostic Scoring System (IPSS) and Dynamic International Prognostic Scoring System (DIPSS), towards new systems which stratify patients' risk based on their genetic profile, mainly the detection of the JAK2 mutation (40-45).

In this vein, the low number of studies in Latin American countries could suggest a lack of adherence to the prognostic scoring criteria of the new international systems based on genetic and molecular characteristics, such as the Genetically Inspired Prognostic Scoring System for Primary Myelofibrosis (GIPSS) and Mutation-Enhanced International Prognostic Scoring System (MIPSS), which provide accurate stratification of patients' risk, both at diagnosis as well as during follow-up, in terms of survival and risk of progression to leukemia (44, 45).

The prevalence of JAK2 mutations showed no statistically significant difference according to the technique used. These results could be affected by a low statistical power (77.5%) caused by a low number of studies and patients analyzed per each of the techniques. In fact, in an evaluation of methodological quality, only 17% describe how they reached the sample size, which affects the estimation of prevalence. This could be explained by the difficulty in including patients with PMF due to its low occurrence and the active search for cases worldwide (46). This situation could be improved by carrying out multicenter studies which would allow the inclusion of more patients and, in this way, improve the estimate of prevalence or increase the statistical power of the comparisons in different subgroups.

The amplification resistant mutation system (ARMS) and allele-specific PCR (AS-PCR) are simple methods for detecting mutations which involve changes in a single base or small deletions. Both can have a high sensitivity, even with a very small number of mutated cells. However, this parameter may be affected by the type of mutation and correct primer design (47). On the other hand, real-time PCR is highly sensitive and specific, with very short processing times. Unlike the described methods, it allows a reproducible quantification of the genetic material; however, this technique may produce a large quantity of inaccurate data when there is not a strict control of the quality of the analytical variables, such as the quality of the standards and the correct selection of the housekeeping gene (48).

Sequencing is a molecular technique which enables the specific modifications in gene sequences to be pinpointed exactly. However, unlike the previous techniques, its main limitation, when Sanger sequencing is used, is its low analytical sensitivity and the high concentration of DNA required (49).

In line with these characteristics, and despite the fact that this study did not find differences between the techniques employed due to the low statistical power of the comparisons, the use of sequencing methods other than Sanger must be recommended, in order to achieve greater sensitivity in the genetic screening of PMF patients.

The limitations of the current study include a low sample size in the included studies, which shows the need to carry out new studies on the topic. In addition, due to the number of studies and patients in each technique, a robust meta-analysis was not carried out in the statistical evaluation of heterogeneity, publication bias or the sensitivity of the summary measures. This could be related to the language restrictions used and the search strategies in each of the sources consulted. In this vein, subsequent studies should improve the comprehensiveness of article selection in this field by increasing the search languages, and broadening the number of terms and sources consulted, among other strategies to minimize potential selection bias.

With regard to the techniques employed in the various studies, most have high sensitivity: however, according to the GEMFIN group and Sociedad Española de Hematología y Hemoterapia recommendations, the use of methods such as Sanger sequencing, pyrosequencing and PCR-RFLP is not recommended, as they have low sensitivity which is limited to a high number of mutated clones (50).

Conclusion

A high frequency of JAK2 mutations was seen, showing that the diagnosis of PMF should not be made only by clinical and hematological characteristics, but also by the search for specific molecular markers.

Referencias

1. Arber DA, Orazi A, Hasserjian R, Borowitz MJ, Beau MM Le, Bloomfield CD, et al. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood. 2016;127(20):2391-406.

2. Swerdlow S, Campo E, Harris N et al. World Health Organization Classification of Tumours of haematopoietic and lymphoid Tissues. 2017

3. Tefferi A. Primary myelofibrosis: 2017 update on diagnosis, risk-stratification, and management. Am J Hematol. 2016;91(12): 1262-71.

4. Vainchenker W, Kralovics R. Genetic basis and molecular pathophysiology of classical myeloproliferative neoplasms. Blood. 2017;129(6):667-79.

5. Kralovics R, Passamonti F, Buser AS, Teo S-S, Tiedt R, Passweg JR, et al. A gain-of-function mutation of JAK2 in myeloproliferative disorders. N Engl J Med. 2005;352(17): 1779-90.

6. Levine RL, Wadleigh M, Cools J, Ebert BL, Wernig G, Huntly BJP, et al. Activating mutation in the tyrosine kinase JAK2 in polycythemia vera, essential thrombocythemia, and myeloid metaplasia with myelofibrosis. Cancer Cell. 2005;7(4):387-97.

7. Jaradat SA, Khasawneh R, Kamal N, Matalka I, Al-Bishtawi M, Al-Sweedan S, et al. Analysis of JAK2V617F mutation in Jordanian patients with myeloproliferative neoplasms. Hematol Oncol Stem Cell Ther. 2015;8(4): 160-6.

8. Suzuki R, Onizuka M, Kojima M, Shimada M, Tsuboi K, Ogawa Y, et al. Infrequent hypermethylation of WIF-1 promoter in BCR/ABL-negative myeloproliferative disorders. Tokai J Exp Clin Med. 2007;32(4): 131-5.

9. Park SH, Chi H-S, Cho Y-U, Jang S, Park C-J. The allele burden of JAK2 V617F can aid in differential diagnosis of Philadelphia Chromosome-Negative Myeloproliferative Neoplasm. Blood Res. 2013;48(2): 128-32.

10. Moher D, Liberati A, Tetzlaff J, Altman DG, Group TP. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. 2009;6(7).

11. Speletas M, Katodritou E, Daiou C, Mandala E, Papadakis E, Kioumi A, et al. Correlations of JAK2-V617F mutation with clinical and laboratory findings in patients with myeloproliferative disorders. Leuk Res. 2007;31(8): 1053-62.

12. Lucia E, Martino B, Mammi C, Vigna E, Mazzone C, Gentile M, et al. The incidence of JAK2 V617F mutation in bcr/abl-negative chronic myeloproliferative disorders: assessment by two different detection methods. Leuk Lymphoma. 2008;49(10): 1907-15.

13. Pardanani A, Fridley BL, Lasho TL, Gilliland DG, Tefferi A. Host genetic variation contributes to phenotypic diversity in myeloproliferative disorders. Blood. 2008;111(5):2785-9.

14. Xu W, Li J-Y, Xia J, Zhang S-J, Fan L, Qiao C. MPL W515L mutation in Chinese patients with myeloproliferative diseases. Leuk Lymphoma. 2008;49(5): 955-8.

15. Bang S-M, Lee J-S, Ahn JY, Lee JH, Hyun MS, Kim BS, et al. Vascular events in Korean patients with myeloproliferative neoplasms and their relationship to JAK2 mutation. Thromb Haemost. 2009;101(3):547-51.

16. Medinger M, Skoda R, Gratwohl A, Theocharides A, Buser A, Heim D, et al. Angiogenesis and vascular endothelial growth factor-/receptor expression in myeloproliferative neoplasms: correlation with clinical parameters and JAK2-V617F mutational status. Br J Haematol 2009; 146(2): 150-7.

17. Kim JT, Cho YG, Choi SI, Lee YJ, Kim HR, Jang SJ, et al. JAK2 V617F and exon 12 genetic variations in Korean patients with BCR/ABL1-negative myeloproliferative neoplasms. Korean J Lab Med. 2010;30(6): 567-74.

18. Benmoussa A, Dehbi H, Fehri S, Quessar A, Nadifi S. JAK2-V617F mutation in Moroccan patients with myeloproliferative disorders: contribution, diagnosis and therapeutic prospects. Pathol Biol (Paris). 2011;59(4):e89-92.

19. Vadikolia CM, Tsatalas C, Anagnostopoulos K, Trypsianis G, Pantelidou D, Bazdiara I, et al. Proteolytic matrix metallopeptidases and inhibitors in BCR-ABL1-negative myeloproliferative neoplasms: correlation with JAK2 mutation status. Acta Haematol. 2011; 126(1): 54-62.

20. Ha J-S, Kim Y-K, Jung S-I, Jung H-R, Chung I-S. Correlations between Janus kinase 2 V617F allele burdens and clinicohematologic parameters in myeloproliferative neoplasms. Ann Lab Med. 2012;32(6):385-91.

21. Zhang X, Maimaitili Y, Li Y, An L, Mao M, Fu L, et al. Detection and clinical significance of JAK2 V617F mutation in Chinese and Uyghur patients with chronic myeloproliferative in Xinjiang. Zhonghua Xue Ye Xue Za Zhi. 2012;33(12):1020-3.

22. Boveri E, Passamonti F, Rumi E, Pietra D, Elena C, Arcaini L, et al. Bone marrow microvessel density in chronic myeloproliferative disorders: a study of 115 patients with clinicopathological and molecular correlations. Br J Haematol. 2008;140(2): 162-8.

23. Dos Santos LC, Ribeiro JC da C, Silva NP, Cerutti J, da Silva MRR, Chauffaille M de LLF. Cytogenetics, JAK2 and MPL mutations in polycythemia vera, primary myelofibrosis and essential thrombocythemia. Rev Bras Hematol Hemoter. 2011;33(6):417-24.

24. Payzin KB, Savasoglu K, Alacacioglu I, Ozdemirkiran F, Mutlu BB, Bener S, et al. JAK2 V617F mutation status of 232 patients diagnosed with chronic myeloproliferative neoplasms. Clin Lymphoma Myeloma Leuk. 2014;14(6):525-33.

25. Azevedo AP, Silva SN, Reichert A, Lima F, Junior E, Rueff J. Prevalence of the Janus kinase 2 V617F mutation in Philadelphia-negative myeloproliferative neoplasms in a Portuguese population. Biomed reports. 2017;7(4):370-6.

26. Kim SY, Im K, Park SN, Kwon J, Kim J-A, Lee DS. CALR, JAK2, and MPL mutation profiles in patients with four different subtypes of myeloproliferative neoplasms: primary myelofibrosis, essential thrombocythemia, polycythemia vera, and myeloproliferative neoplasm, unclassifiable. Am J Clin Pathol. 2015;143(5):635-44.

27. Lekovic D, Gotic M, Skoda R, Beleslin-Cokic B, Milic N, Mitrovic-Ajtic O, et al. Bone marrow microvessel density and plasma angiogenic factors in myeloproliferative neoplasms: clinicopathological and molecular correlations. Ann Hematol. 2017;96(3):393-404.

28. Trifa AP, Cucuianu A, Petrov L, Urian L, Militaru MS, Dima D, et al. The G allele of the JAK2 rs10974944 SNP, part of JAK2 46/1 haplotype, is strongly associated with JAK2 V617F-positive myeloproliferative neoplasms. Ann Hematol. 2010;89(10):979-83.

29. Borowczyk M, Wojtaszewska M, Lewandowski K, Gil L, Lewandowska M, Lehmann-Kopydlowska A, et al. The JAK2 V617F mutational status and allele burden may be related with the risk of venous thromboembolic events in patients with Philadelphia-negative myeloproliferative neoplasms. Thromb Res. 2015;135(2):272-80.

30. Ojeda MJ, Bragos IM, Calvo KL, Williams GM, Carbonell MM, Pratti AF. CALR, JAK2 and MPL mutation status in Argentinean patients with BCR-ABL1-negative myeloproliferative neoplasms. Hematology. 2018;23(4):208-11.

31. da Silva RR, Domingues Hatzlhofer BL, Machado CG de F, Lima AS de M, de Albuquerque DM, dos Santos MNN, et al. JAK2 V617F mutation prevalence in myeloproliferative neoplasms in Pernambuco, Brazil. Genet Test Mol Biomarkers. 2012;16(7):802-5.

32. Didone A, Nardinelli L, Marchiani M, Ruiz ARL, de Lima Costa AL, Lima IS, et al. Comparative study of different methodologies to detect the JAK2 V617F mutation in chronic BCR-ABL1 negative myeloproliferative neoplasms. Pract Lab Med. 2016;4: 30-7.

33. Tefferi A, Pardanani A, Lim K-H, Abdel-Wahab O, Lasho TL, Patel J, et al. TET2 mutations and their clinical correlates in polycythemia vera, essential thrombocythemia and myelofibrosis. Leukemia. 2009;23(5):905-11.

34. Takata Y, Seki R, Kanajii T, Nohara M, Koteda S, Kawaguchi K, et al. Association between thromboembolic events and the JAK2 V617F mutation in myeloproliferative neoplasms. Kurume Med J. 2014;60(3-4):89-97.

35. Vytrva N, Stacher E, Regitnig P, Zinke-Cerwenka W, Hojas S, Hubmann E, et al. Megakaryocytic morphology and clinical parameters in essential thrombocythemia, polycythemia vera, and primary myelofibrosis with and without JAK2 V617F. Arch Pathol Lab Med. 2014;138(9): 1203-9.

36. Wu Z, Zhang X, Xu X, Chen Y, Hu T, Kang Z, et al. The mutation profile of JAK2 and CALR in Chinese Han patients with Philadelphia chromosome-negative myeloproliferative neoplasms. J Hematol Oncol. 2014;7:48.

37. Misawa K, Yasuda H, Araki M, Ochiai T, Morishita S, Shirane S, et al. Mutational subtypes of JAK2 and CALR correlate with different clinical features in Japanese patients with myeloproliferative neoplasms. Int J Hematol. 2018;107(6):673-80.

38. Grupo Banco mundial: Gasto en investigación y desarrollo (% del PIB) [internet]. n.d [consultado 10 de julio 2018]. Disponible en: https://datos.bancomundial.org/indicador/GB.XPD.RSDV.GD.ZS?view=map&year_high_desc=false.

39. Abello V, Quintero G, Espinosa D, Solano M, Casas C, D Saavedra. Descripción de las características clínicas de las neoplasias mieloproliferativas crónicas (NMPC) Description of the clinical characteristics of chronic myeloproliferative neoplasms (MPNs) First report of the colombian registry of MPNs. 2017;35-41.

40. Passamonti F, Cervantes F, Vannucchi AM, Morra E, Rumi E, Cazzola M, et al. Dynamic International Prognostic Scoring System (DIPSS) predicts progression to acute myeloid leukemia in primary myelofibrosis. Vol. 116, Blood. United States; 2010. p. 2857-8.

41. Gangat N, Caramazza D, Vaidya R, George G, Begna K, Schwager S, et al. DIPSS plus: a refined Dynamic International Prognostic Scoring System for primary myelofibrosis that incorporates prognostic information from karyotype, platelet count, and transfusion status. J Clin Oncol. 2011;29(4):392-7.

42. Cervantes F, Dupriez B, Pereira A, Passamonti F, Reilly JT, Morra E, et al. New prognostic scoring system for primary myelofibrosis based on a study of the International Working Group for Myelofibrosis Research and Treatment. Blood. 2009;113(13):2895-901.

43. Mesa RA, Passamonti F. Individualizing Care for Patients With Myeloproliferative Neoplasms: Integrating Genetics, Evolving Therapies, and Patient-Specific Disease Burden. Am Soc Clin Oncol Educ book Am Soc Clin Oncol Annu Meet. 2016;35:e324-35.

44. Tefferi A, Guglielmelli P, Nicolosi M, Mannelli F, Mudireddy M, Bartalucci N, et al. GIPSS: genetically inspired prognostic scoring system for primary myelofibrosis. Leukemia [Internet]. 2018;32(7): 1631-42.

45. Tefferi A, Guglielmelli P, Lasho TL, Gangat N, Ketterling RP, Pardanani A, et al. MIPSS70+ Version 2.0: Mutation and Karyotype-Enhanced International Prognostic Scoring System for Primary Myelofibrosis. J Clin Oncol. 2018; 36(17): 1769-70.

46. Titmarsh GJ, Duncombe AS, Mcmullin MF, O'Rorke M, Mesa R, De Vocht F, et al. How common are myeloproliferative neoplasms? A systematic review and meta-analysis. Am J Hematol. 2014;89(6):581-7.

47. Little S. Amplification-refractory mutation system (ARMS) analysis of point mutations. Curr Protoc Hum Genet. 2001; Chapter 9:Unit 9.8.

48. Arya M, Shergill IS, Williamson M, Gommersall L, Arya N, Patel HRH. Basic principles of real-time quantitative PCR. Expert Rev Mol Diagn. 2005 Mar;5(2):209-19.

49. Tipu HN, Shabbir A. Evolution of DNA sequencing. J Coll Physicians Surg Pak. 2015;25(3):210-5.

50. Blessés C, Cervantes F. Manual de recomendaciones en Neoplasias Mieloproliferativas Crónicas Filadelfia Negativas. Grupo Español de Neoplasias Filadelfia Negativas (GEMFIN). 2014; Available from: http://www.sehh.es/images/stories/recursos/2014/documentos/guias/GUIA_GEMFIN.pdf