Page 42 - 2018_11-Haematologica-web
P. 42

J. Caers et al.
References
1. Kumar SK, Rajkumar V, Kyle RA, et al. Multiple myeloma. Nat Rev Dis Primers. 2017;3:17046.
2. Kumar SK, Dispenzieri A, Lacy MQ, et al. Continued improvement in survival in mul- tiple myeloma: changes in early mortality and outcomes in older patients. Leukemia. 2014;28(5):1122-1128.
3. RajkumarSV,DimopoulosMA,PalumboA, et al. International Myeloma Working Group updated criteria for the diagnosis of multiple myeloma. Lancet Oncol. 2014;15(12):e538-548.
4. Caers J, Fernández de Larrea C, Leleu X, et al. The changing landscape of smoldering multiple myeloma: a European perspective. Oncologist. 2016;21(3):333-342.
5. Guyatt G, Oxman AD, Akl EA, et al. GRADE guidelines: 1. Introduction-GRADE evidence profiles and summary of findings tables. J Clin Epidemiol. 2011;64(4):383-394.
6. KuhnemundA,LiebischP,BauchmullerK,et al. 'Light-chain escape-multiple myeloma'- an escape phenomenon from plateau phase: report of the largest patient series using LC- monitoring. J Cancer Res Clin Oncol. 2009;135(3):477-484.
7. Jenner E. Serum free light chains in clinical laboratory diagnostics. Clin Chim Acta. 2014;427:15-20.
8. Bradwell AR, Harding SJ, Fourrier NJ, et al. Assessment of monoclonal gammopathies by nephelometric measurement of individ- ual immunoglobulin κ/λ ratios. Clin Chem. 2009;55(9):1646-1655.
9. Ludwig H, Milosavljevic D, Berlanga O, et al. Suppression of the noninvolved pair of the myeloma isotype correlates with poor survival in newly diagnosed and relapsed/refractory patients with myeloma. Am J Hematol. 2016;91(3):295-301.
10. Greil C, Ihorst G, Gaiser F, et al. The serum heavy/light chain immunoassay: a valuable tool for sensitive paraprotein assessment, risk, and disease monitoring in monoclonal gammopathies. Eur J Haematol. 2017;99 (5):449-458.
11. Katzmann JA, Kyle RA, Benson J, et al. Screening panels for detection of monoclon- al gammopathies. Clin Chem. 2009;55(8): 1517-1522.
12. DejoieT,CorreJ,CaillonH,etal.Serumfree light chains, not urine specimens, should be used to evaluate response in light-chain mul- tiple myeloma. Blood. 2016;128(25):2941- 2948.
13. Heaney JLJ, Campbell JP, Griffin AE, et al. Diagnosis and monitoring for light chain only and oligosecretory myeloma using serum free light chain tests. Br J Haematol. 2017;178(2):220-230.
14. DispenzieriA,ZhangL,KatzmannJA,etal. Appraisal of immunoglobulin free light chain as a marker of response. Blood. 2008;111(10):4908-4915.
15. Dispenzieri A, Kyle R, Merlini G, et al. International Myeloma Working Group guidelines for serum-free light chain analysis in multiple myeloma and related disorders. Leukemia. 2008;23(2):215-224.
16. LeeN,MoonSY,LeeJh,etal.Discrepancies between the percentage of plasma cells in bone marrow aspiration and BM biopsy: impact on the revised IMWG diagnostic cri- teria of multiple myeloma. Blood Cancer J. 2017;7:e530.
17. Rawstron AC, Orfao A, Beksac M, et al. Report of the European Myeloma Network on multiparametric flow cytometry in mul-
tiple myeloma and related disorders.
Haematologica. 2008;93(3):431-438.
18. van Dongen JJM, Lhermitte L, Bottcher S, et al. EuroFlow antibody panels for standard- ized n-dimensional flow cytometric immunophenotyping of normal, reactive and malignant leukocytes. Leukemia.
2012;26(9):1908-1975.
19. Gonsalves WI, Rajkumar SV, Gupta V, et al.
Quantification of clonal circulating plasma cells in newly diagnosed multiple myeloma: implications for redefining high-risk myelo- ma. Leukemia. 2014;28(10):2060-2065.
20. Gonsalves WI, Morice WG, Rajkumar V, et al. Quantification of clonal circulating plas- ma cells in relapsed multiple myeloma. Br J Haematol. 2014;167(4):500-505.
21. Chakraborty R, Muchtar E, Kumar SK, et al. Serial measurements of circulating plasma cells before and after induction therapy has an independent prognostic impact in patients with multiple myeloma undergoing upfront autologous transplantation. Haematologica. 2017;102(8):1439-1445.
22. Robiou du Pont S, Cleynen A, Fontan C, et al. Genomics of multiple myeloma. J Clin Oncol. 2017;35(9):963-967.
23. Kuehl WM, Bergsagel PL. Molecular patho- genesis of multiple myeloma and its prema- lignant precursor. J Clin Invest. 2012;122(10):3456-3463.
24. Ross FM, Avet-Loiseau H, Ameye G, et al. Report from the European Myeloma Network on interphase FISH in multiple myeloma and related disorders. Haematologica. 2012;97(8):1272-1277.
25. Chretien M-L, Corre J, Lauwers-Cances V, et al. Understanding the role of hyperdiploidy in myeloma prognosis: which trisomies real- ly matter? Blood. 2015;126(25):2713-2719.
26. Billecke L, Murga Penas EM, May AM, et al. Cytogenetics of extramedullary manifesta- tions in multiple myeloma. Br J Haematol. 2013;161(1):87-94.
27. Avet-Loiseau H, Leleu X, Roussel M, et al. Bortezomib plus dexamethasone induction improves outcome of patients with t(4;14) myeloma but not outcome of patients with del(17p). J Clin Oncol. 2010;28(30):4630- 4634.
28. Neben K, Lokhorst HM, Jauch A, et al. Administration of bortezomib before and after autologous stem cell transplantation improves outcome in multiple myeloma patients with deletion 17p. Blood. 2012;119(4):940-948.
29. Merz M, Hielscher T, Seckinger A, et al. Baseline characteristics, chromosomal alter- ations, and treatment affecting prognosis of deletion 17p in newly diagnosed myeloma. Am J Hematol. 2016;91(11):E473-E477.
30. Thanendrarajan S, Tian E, Qu P, et al. The level of deletion 17p and bi-allelic inactiva- tion of TP53 has a significant impact on clin- ical outcome in multiple myeloma. Haematologica. 2017;102(9):e364-e367.
31. Avet-Loiseau H, Attal M, Campion L, et al. Long-term analysis of the IFM 99 trials for myeloma: cytogenetic abnormalities [t(4;14), del(17p), 1q gains] play a major role in defining long-term survival. J Clin Oncol. 2012;30(16):1949-1952.
32. Boyd KD, Ross FM, Chiecchio L, et al. A novel prognostic model in myeloma based on co-segregating adverse FISH lesions and the ISS: analysis of patients treated in the MRC Myeloma IX trial. Leukemia. 2012;26(2):349-355.
33. Hebraud B, Magrangeas F, Cleynen A, et al. Role of additional chromosomal changes in the prognostic value of t(4;14) and del(17p)
in multiple myeloma: the IFM experience.
Blood. 2015;125(13):2095-2100.
34. Keats JJ, Chesi M, Egan JB, et al. Clonal com-
petition with alternating dominance in mul- tiple myeloma. Blood. 2012;120(5):1067- 1076.
35. Egan JB, Shi C-X, Tembe W, et al. Whole- genome sequencing of multiple myeloma from diagnosis to plasma cell leukemia reveals genomic initiating events, evolution, and clonal tides. Blood. 2012;120(5):1060- 1066.
36. Melchor L, Brioli A, Wardell CP, et al. Single- cell genetic analysis reveals the composition of initiating clones and phylogenetic pat- terns of branching and parallel evolution in myeloma. Leukemia. 2014;28(8):1705-1715.
37. Lohr Jens G, Stojanov P, Carter Scott L, et al. Widespread genetic heterogeneity in multi- ple myeloma: implications for targeted ther- apy. Cancer Cell. 25(1):91-101.
38. Bolli N, Avet-Loiseau H, Wedge DC, et al. Heterogeneity of genomic evolution and mutational profiles in multiple myeloma. Nat Commun. 2014;5:2997.
39. Bolli N, Li Y, Sathiaseelan V, et al. A DNA target-enrichment approach to detect muta- tions, copy number changes and immunoglobulin translocations in multiple myeloma. Blood Canc J. 2016;6:e467.
40. Johnson DC, Weinhold N, Mitchell JS, et al. Genome-wide association study identifies variation at 6q25.1 associated with survival in multiple myeloma. Nat Commun. 2016;7:10290.
41. Shaughnessy JD, Zhan F, Burington BE, et al. A validated gene expression model of high- risk multiple myeloma is defined by deregu- lated expression of genes mapping to chro- mosome 1. Blood. 2007;109(6):2276-2284.
42. Kuiper R, Broyl A, de Knegt Y, et al. A gene expression signature for high-risk multiple myeloma. Leukemia. 2012;26(11):2406- 2413.
43. Kuiper R, van Duin M, van Vliet MH, et al. Prediction of high- and low-risk multiple myeloma based on gene expression and the International Staging System. Blood. 2015;126(17):1996-2004.
44. Decaux O, Lodé L, Magrangeas F, et al. Prediction of survival in multiple myeloma based on gene expression profiles reveals cell cycle and chromosomal instability signa- tures in high-risk patients and hyperdiploid signatures in low-risk patients: a study of the Intergroupe Francophone du Myélome. J Clin Oncol. 2008;26(29):4798-4805.
45. Dickens NJ, Walker BA, Leone PE, et al. Homozygous deletion mapping in myeloma samples identifies genes and an expression signature relevant to pathogenesis and out- come. Clin Cancer Res. 2010;16(6):1856- 1864.
46. Terpos E, Kleber M, Engelhardt M, et al. European Myeloma Network guidelines for the management of multiple myeloma-relat- ed complications. Haematologica. 2015;100 (10):1254-1266.
47. Hillengass J, Moulopoulos LA, Delorme S, et al. Whole-body computed tomography ver- sus conventional skeletal survey in patients with multiple myeloma: a study of the International Myeloma Working Group. Blood Canc J. 2017;7:e599.
48. Excellence NIfHaC. Myeloma: diagnosis and management 2016 [cited; Available from: https://www.nice.org.uk/guidance/ ng35/resources/myeloma-diagnosis-and- management-pdf-1837394042821
49. Moreau P, San Miguel J, Sonneveld P, et al. Multiple myeloma: ESMO clinical practice
1782
haematologica | 2018; 103(11)


































































































   40   41   42   43   44