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@ARTICLE{Bloehdorn:167949,
      author       = {J. Bloehdorn and J. Krzykalla$^*$ and K. Holzmann and A.
                      Gerhardinger and B. M. C. Jebaraj and J. Bahlo and K.
                      Humphrey and E. Tausch and S. Robrecht and D. Mertens$^*$
                      and C. Schneider and K. Fischer and M. Hallek and H. Döhner
                      and A. Benner$^*$ and S. Stilgenbauer},
      title        = {{I}ntegrative prognostic models predict long-term survival
                      after immunochemotherapy in chronic lymphocytic leukemia
                      patients.},
      journal      = {Haematologica},
      volume       = {107},
      number       = {3},
      issn         = {1592-8721},
      address      = {Pavia},
      publisher    = {Ferrata Storti Foundation64433},
      reportid     = {DKFZ-2021-00660},
      pages        = {615-624},
      year         = {2022},
      note         = {2022Volume 107(3):615-624 / #LA:C060#},
      abstract     = {Chemoimmunotherapy with fludarabine, cyclophosphamide and
                      rituximab can induce longterm remissions in patients with
                      chronic lymphocytic leukemia. Treatment efficacy with
                      Bruton's tyrosine kinase inhibitors was found similar to
                      fludarabine, cyclophosphamide and rituximab in untreated
                      chronic lymphocytic leukemia patients with a mutated
                      immunoglobulin heavy chain variable gene. To identify
                      patients who specifically benefit from fludarabine,
                      cyclophosphamide and rituximab, we developed integrative
                      models including established prognostic parameters and gene
                      expression profiling. Gene expression profiling was
                      conducted on n=337 CLL8 trial samples, 'core' probe sets
                      were summarized on gene levels and RMA normalized.
                      Prognostic models were built using penalized Cox
                      proportional hazards models with the smoothly clipped
                      absolute deviation penalty. We identified a prognostic
                      signature of less than a dozen genes, which substituted for
                      established prognostic factors, including TP53 and
                      immunoglobulin heavy chain variable gene mutation status.
                      Independent prognostic impact was confirmed for treatment,
                      β2-microglobulin and del(17p) regarding overall survival
                      and for treatment, del(11q), del(17p) and SF3B1 mutation for
                      progression-free survival. The combination of independent
                      prognostic and gene expression profiling variables performed
                      equal to models including only established non-gene
                      expression profiling variables. Gene expression profiling
                      variables showed higher prognostic accuracy for patients
                      with long progression-free survival compared to categorical
                      variables like the immunoglobulin heavy chain variable gene
                      mutation status and reliably predicted overall survival in
                      CLL8 and an independent cohort. Gene expression profiling
                      based prognostic models can help to identify patients who
                      specifically benefit from fludarabine, cyclophosphamide and
                      rituximab treatment. The CLL8 trial is registered under
                      EUDRACT- 2004-004938-14 and ClinicalTrials.gov Identifier
                      NCT00281918.},
      cin          = {C060 / B061},
      ddc          = {610},
      cid          = {I:(DE-He78)C060-20160331 / I:(DE-He78)B061-20160331},
      pnm          = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
      pid          = {G:(DE-HGF)POF4-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:33730841},
      doi          = {10.3324/haematol.2020.251561},
      url          = {https://inrepo02.dkfz.de/record/167949},
}