Modeling risk stratification in human cancer.

Abstract : MOTIVATION: Despite huge prognostic promises, gene expression-based survival assessment is rarely used in clinical routine. Main reasons include difficulties in performing and reporting analyses and restriction in most methods to one high-risk group with the vast majority of patients being unassessed. The present study aims at limiting these difficulties by (i) mathematically defining the number of risk groups without any a priori assumption; (ii) computing the risk of an independent cohort by considering each patient as a new patient incorporated to the validation cohort and (iii) providing an open-access Web site to freely compute risk for every new patient. RESULTS: Using the gene expression profiles of 551 patients with multiple myeloma, 602 with breast-cancer and 460 with glioma, we developed a model combining running log-rank tests under controlled chi-square conditions and multiple testing corrections to build a risk score and a classification algorithm using simultaneous global and between-group log-rank chi-square maximization. For each cancer entity, we provide a statistically significant three-group risk prediction model, which is corroborated with publicly available validation cohorts. CONCLUSION: In constraining between-group significances, the risk score compares favorably with previous risk classifications. AVAILABILITY: Risk assessment is freely available on the Web at https://gliserv.montp.inserm.fr/PrognoWeb/ for personal or test data files. Web site implementation in Perl, R and Apache.
Type de document :
Article dans une revue
Bioinformatics, Oxford University Press (OUP), 2013, 29 (9), pp.1149-57. 〈10.1093/bioinformatics/btt124〉
Liste complète des métadonnées

Littérature citée [43 références]  Voir  Masquer  Télécharger

http://www.hal.inserm.fr/inserm-00806666
Contributeur : Monique Frei <>
Soumis le : mardi 2 avril 2013 - 10:42:08
Dernière modification le : lundi 8 janvier 2018 - 17:11:38
Document(s) archivé(s) le : dimanche 2 avril 2017 - 23:08:51

Fichier

 Accès restreint
Fichier visible le : jamais

Connectez-vous pour demander l'accès au fichier

Identifiants

Citation

Thierry Rème, Dirk Hose, Charles Theillet, Bernard Klein. Modeling risk stratification in human cancer.. Bioinformatics, Oxford University Press (OUP), 2013, 29 (9), pp.1149-57. 〈10.1093/bioinformatics/btt124〉. 〈inserm-00806666〉

Partager

Métriques

Consultations de la notice

131