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RESEARCH PRODUCT
Revised risk estimation and treatment stratification of low- and intermediate-risk neuroblastoma patients by integrating clinical and molecular prognostic markers.
Matthias FischerCarolina SterzAkira NakagawaraChunxuan ShaoIsaac YanivPaola ScaruffiRoland EilsAnne EngesserFranki SpelemanMiki OhiraRichard GrundyJo VandesompeleRene SchmidtAndré OberthuerJessica TheissenFrank BertholdThorsten SimonBenedikt BrorsGian Paolo ToniniRosa NogueraSmadar AvigadShahab AsgharzadehAndreas FaldumYvonne KahlertMonika OrtmannDilafruz JuraevaMarta PiquerasRobert C. SeegerIsabelle Janoueix-leroseyJean BénardRuth VollandFrank WestermannOlivier DelattreAlexander ValentGudrun SchleiermacherManfred SchwabBarbara Herosubject
OncologyMaleCancer ResearchMultivariate statisticsmedicine.medical_specialtyKaplan-Meier EstimateBioinformaticsRisk AssessmentNeuroblastomaText miningRisk FactorsInternal medicineNeuroblastomamedicineBiomarkers TumorCluster AnalysisHumansbusiness.industryProportional hazards modelGene Expression ProfilingReproducibility of ResultsRegression analysismedicine.diseasePrognosisClinical trialGene expression profilingGene Expression Regulation NeoplasticOncologyRegression AnalysisFemalebusinessRisk assessmentFollow-Up Studiesdescription
Abstract 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. 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. 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 < 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 < 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 < 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. 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. See related commentary by Attiyeh and Maris, p. 1782
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2014-04-07 | Clinical cancer research : an official journal of the American Association for Cancer Research |