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Oberthuer, André; Juraeva, Dilafruz; Hero, Barbara; Volland, Ruth; Sterz, Carolina; Schmidt, Rene; Faldum, Andreas; Kahlert, Yvonne; Engesser, Anne; Asgharzadeh, Shahab; Seeger, Robert; Ohira, Miki; Nakagawara, Akira; Scaruffi, Paola; Tonini, Gian Paolo; Janoueix-Lerosey, Isabelle; Delattre, Olivier; Schleiermacher, Gudrun; Vandesompele, Jo; Speleman, Frank; Noguera, Rosa; Piqueras, Marta; Bénard, Jean; Valent, Alexander; [...]

Revised Risk Estimation and Treatment Stratification of Low- and Intermediate-Risk Neuroblastoma Patients by Integrating Clinical and Molecular Prognostic Markers

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  • Media type: E-Article
  • Title: Revised Risk Estimation and Treatment Stratification of Low- and Intermediate-Risk Neuroblastoma Patients by Integrating Clinical and Molecular Prognostic Markers
  • Contributor: Oberthuer, André; Juraeva, Dilafruz; Hero, Barbara; Volland, Ruth; Sterz, Carolina; Schmidt, Rene; Faldum, Andreas; Kahlert, Yvonne; Engesser, Anne; Asgharzadeh, Shahab; Seeger, Robert; Ohira, Miki; Nakagawara, Akira; Scaruffi, Paola; Tonini, Gian Paolo; Janoueix-Lerosey, Isabelle; Delattre, Olivier; Schleiermacher, Gudrun; Vandesompele, Jo; Speleman, Frank; Noguera, Rosa; Piqueras, Marta; Bénard, Jean; Valent, Alexander; [...]
  • imprint: American Association for Cancer Research (AACR), 2015
  • Published in: Clinical Cancer Research
  • Language: English
  • DOI: 10.1158/1078-0432.ccr-14-0817
  • ISSN: 1078-0432; 1557-3265
  • Keywords: Cancer Research ; Oncology
  • Origination:
  • Footnote:
  • Description: <jats:title>Abstract</jats:title> <jats:p>Purpose: To optimize neuroblastoma treatment stratification, we aimed at developing a novel risk estimation system by integrating gene expression–based classification and established prognostic markers.</jats:p> <jats:p>Experimental Design: Gene expression profiles were generated from 709 neuroblastoma specimens using customized 4 × 44 K microarrays. Classification models were built using 75 tumors with contrasting courses of disease. Validation was performed in an independent test set (n = 634) by Kaplan–Meier estimates and Cox regression analyses.</jats:p> <jats:p>Results: The best-performing classifier predicted patient outcome with an accuracy of 0.95 (sensitivity, 0.93; specificity, 0.97) in the validation cohort. The highest potential clinical value of this predictor was observed for current low-risk patients [5-year event-free survival (EFS), 0.84 ± 0.02 vs. 0.29 ± 0.10; 5-year overall survival (OS), 0.99 ± 0.01 vs. 0.76 ± 0.11; both P &amp;lt; 0.001] and intermediate-risk patients (5-year EFS, 0.88 ± 0.06 vs. 0.41 ± 0.10; 5-year OS, 1.0 vs. 0.70 ± 0.09; both P &amp;lt; 0.001). In multivariate Cox regression models for low-risk/intermediate-risk patients, the classifier outperformed risk assessment of the current German trial NB2004 [EFS: hazard ratio (HR), 5.07; 95% confidence interval (CI), 3.20–8.02; OS: HR, 25.54; 95% CI, 8.40–77.66; both P &amp;lt; 0.001]. On the basis of these findings, we propose to integrate the classifier into a revised risk stratification system for low-risk/intermediate-risk patients. According to this system, we identified novel subgroups with poor outcome (5-year EFS, 0.19 ± 0.08; 5-year OS, 0.59 ± 0.1), for whom we propose intensified treatment, and with beneficial outcome (5-year EFS, 0.87 ± 0.05; 5-year OS, 1.0), who may benefit from treatment de-escalation.</jats:p> <jats:p>Conclusions: Combination of gene expression–based classification and established prognostic markers improves risk estimation of patients with low-risk/intermediate-risk neuroblastoma. We propose to implement our revised treatment stratification system in a prospective clinical trial. Clin Cancer Res; 21(8); 1904–15. ©2014 AACR.</jats:p> <jats:p>See related commentary by Attiyeh and Maris, p. 1782</jats:p>
  • Access State: Open Access