Page 68 - 2022_03-Haematologica-web
P. 68

J. Bloehdorn et al.
References
1. Fischer K, Bahlo J, Fink AM, et al. Long-term remissions after FCR chemoimmunotherapy in previously untreated patients with CLL: updated results of the CLL8 trial. Blood. 2016;127(2):208-215.
2. Keating MJ, O`Brien S, Albitar M, et al. Early results of a chemoimmunotherapy regimen of fludarabine, cyclophosphamide, and rit- uximab as initial therapy for chronic lym- phocytic leukemia. J Clin Oncol. 2005;23(18):4079-4088.
3. Rossi D, Rasi S, Fabbri G, et al. Mutations of NOTCH1 are an independent predictor of survival in chronic lymphocytic leukemia. Blood. 2012;119(2):521-529.
4. Döhner H, Stilgenbauer S, Benner A, et al. Genomic aberrations and survival in chronic lymphocytic leukemia. N Engl J Med. 2000;343(26):1910-1916.
5. Stilgenbauer S, Schnaiter A, Paschka P, et al. Gene mutations and treatment outcome in chronic lymphocytic leukemia: results from the CLL8 trial. Blood. 2014;123(21):3247- 3254.
6. Damle RN, Wasil T, Fais F, et al. Ig V gene mutation status and CD38 expression as novel prognostic indicators in chronic lym- phocytic leukemia. Blood. 1999;94(6):1840- 1847.
7. Hamblin TJ, Davis Z, Gardiner A, Oscier DG, Stevenson FK. Unmutated Ig V(H) genes are associated with a more aggressive form of chronic lymphocytic leukemia. Blood. 1999;94(6):1848-1854.
8. Woyach JA, Ruppert AS, Heerema NA, et al. Ibrutinib regimens versus chemoim- munotherapy in older patients with untreat- ed CLL. N Engl J Med. 2018;379(26):2517- 2528.
9. Moreno C, Greil R, Demirkan F, et al. Ibrutinib plus obinutuzumab versus chlo- rambucil plus obinutuzumab in first-line treatment of chronic lymphocytic leukaemia (iLLUMINATE): a multicentre, randomised, open-label, phase 3 trial. Lancet Oncol. 2019;20(1):43-56.
10. Roberts AW, Davids MS, Pagel JM, et al. Targeting BCL2 with Venetoclax in relapsed chronic lymphocytic leukemia. N Engl J Med. 2016;374(4):311-322.
11. Stilgenbauer S, Eichhorst B, Schetelig J, et al. Venetoclax in relapsed or refractory chronic lymphocytic leukaemia with 17p deletion: a
multicentre, open-label, phase 2 study.
Lancet Oncol. 2016;17(6):768-778.
12.Byrd JC, Furman RR, Coutre SE, et al. Targeting BTK with ibrutinib in relapsed chronic lymphocytic leukemia. N Engl J
Med. 2013;369(1):32-42.
13. Furman RR, Sharman JP, Coutre SE, et al.
Idelalisib and Rituximab in relapsed chronic lymphocytic leukemia. N Engl J Med. 2014;370(11):997-1007.
14. Shanafelt TD, Wang V, Kay NE, et al. A ran- domized phase III study of ibrutinib (PCI- 32765)-based therapy vs. standard fludara- bine, cyclophosphamide, and rituximab (FCR) chemoimmunotherapy in untreated younger patients with chronic lymphocytic leukemia (CLL): a trial of the ECOG-ACRIN cancer research group (E1912). Blood. 2018;132(Supplement 1):LBA-4.
15. Bengtsson H, Simpson K, Bullard J, Hansen K. aroma.affymetrix: A generic framework in R for analyzing small to very large Affymetrix data sets in bounded memory. Tech Reports. 2008;745:1-9.
16. van Buuren S, Groothuis-Oudshoorn K. MICE: multivariate imputation by chained equations in R. J Stat Software. 2011;45(3).
17. Fan J, Li R. Variable selection via nonconcave penalized likelihood and its oracle proper- ties. J Am Stat Assoc. 2001;96:1348-1360.
18. Willi Sauerbrei, Buchholz A, Boulesteix AL, Binder H. On stability issues in deriving multivariable regression models. Biom J. 2015;57(4):531-555.
19. Mogensen UB, Ishwaran H, Gerds TA. Evaluating random forests for survival analy- sis using prediction error curves. J Stat Softw. 2012;50(11):1-23.
20. Beran R. Nonparametric regression with randomly censored survival data. Tech Report. 1981 University of California, Berkeley.
21. Gerds TA. Prodlim: Product-limit estimation for censored event history analysis 2014. URL https//CRAN. R-project. org/package= prodlim. R Packag. version 1, 460 (2016).
22. Herold T, Jurinovic V, Metzeler KH, et al. An eight-gene expression signature for the pre- diction of survival and time to treatment in chronic lymphocytic leukemia. Leukemia. 2011;25(10):1639-1645.
23. Duzkale H, Schweighofer CD, Coombes KR, et al. LDOC1 mRNA is differentially expressed in chronic lymphocytic leukemia and predicts overall survival in untreated patients. Blood. 2011;117(15):4076-4084.
24.Morabito F, Cutrona G, Mosca L, et al. Surrogate molecular markers for IGHV mutational status in chronic lymphocytic leukemia for predicting time to first treat- ment. Leuk Res. 2015;39(8):840-845.
25. Rosenwald A, Alizadeh AA, Widhopf G, et al. Relation of gene expression phenotype to immunoglobulin mutation genotype in B cell chronic lymphocytic leukemia. J Exp Med. 2001;194(11):1639-1647.
26. Rassenti LZ, Huynh L, Toy TL, et al. ZAP-70 compared with immunoglobulin heavy- chain gene mutation status as a predictor of disease progression in chronic lymphocytic leukemia. N Engl J Med. 2004;351(9):893- 901.
27. Klein U, Tu Y, Stolovitzky GA, et al. Gene expression profiling of B cell chronic lym- phocytic leukemia reveals a homogeneous phenotype related to memory B cells. J Exp Med. 2001;194(11):1625-1638.
28. International CLL-IPI working group. An international prognostic index for patients with chronic lymphocytic leukaemia (CLL- IPI): a meta-analysis of individual patient data. Lancet Oncol. 2016;17(6):779-790.
29. Kulis M, Heath S, Bibikova M, et al. Epigenomic analysis detects widespread gene-body DNA hypomethylation in chron- ic lymphocytic leukemia. Nat Genet. 2012;44(11):1236-1242.
30. Oakes CC, Seifert M, Assenov Y, et al. DNA methylation dynamics during B cell matura- tion underlie a continuum of disease pheno- types in chronic lymphocytic leukemia. Nat Genet. 2016;48(3):253-264.
31. Wojdacz TK, Amarasinghe HE, Kadalayil L, et al. Clinical significance of DNA methyla- tion in chronic lymphocytic leukemia patients: results from 3 UK clinical trials. Blood Adv. 2019;3(16):2474-2481.
32. Dvinge H, Ries RE, Ilagan JO, Stirewalt DL, Meshinchi S, Bradley RK. Sample processing obscures cancer-specific alterations in leukemic transcriptomes. Proc Natl Acad Sc. U S A. 2014;111(47):16802-16807.
33. Chen Q, Jain N, Ayer T, et al. Economic bur- den of chronic lymphocytic leukemia in the era of oral targeted therapies in the United States. J Clin Oncol. 2017;35(2):166-174.
34. Zhang W, Yu Y, Hertwig F, et al. Comparison of RNA-seq and microarray-based models for clinical endpoint prediction. Genome Biol. 2015;16(1):133.
624
haematologica | 2022; 107(3)


































































































   66   67   68   69   70