4.4 Article

Integrative prognostic models predict long-term survival after immunochemotherapy in chronic lymphocytic leukemia patients

Journal

HAEMATOLOGICA
Volume 107, Issue 3, Pages 615-624

Publisher

FERRATA STORTI FOUNDATION
DOI: 10.3324/haematol.2020.251561

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Funding

  1. BMBF (PRECISE)
  2. European Commission/BMBF (FIRE CLL) [01KT160]
  3. Deutsche Forschungsgemeinschaft [Sonderforschungsbereich 1074]
  4. DJCLS [R 11/01]
  5. F. Hoffmann-La Roche

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Chemoimmunotherapy with fludarabine, cyclophosphamide, and rituximab has been found to induce long-term remissions in patients with chronic lymphocytic leukemia. By using gene expression profiling and other prognostic parameters, integrative models can be developed to identify patients who specifically benefit from this treatment.
Chemoimmunotherapy with fludarabine, cyclophosphamide and rituximab (FCR) can induce long-term remissions in patients with chronic lymphocytic leukemia. Treatment efficacy with Bruton's tyrosine kinase inhibitors was found similar to FCR in untreated chronic lymphocytic leukemia patients with a mutated immunoglobulin heavy chain variable (IGHV) gene. In order to identify patients who specifically benefit from FCR, we developed integrative models including established prognostic parameters and gene expression profiling (GEP). GEP 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 IGHV gene mutation status. Independent prognostic impact was confirmed for treatment, beta 2-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 GEP variables performed equal to models including only established non-GEP variables. GEP variables showed higher prognostic accuracy for patients with long progression-free survival compared to categorical variables like the IGHV gene mutation status and reliably predicted overall survival in CLL8 and an independent cohort. GEP-based prognostic models can help to identify patients who specifically benefit from FCR treatment.

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