S'abonner

Predictive value of a proteomic signature in patients with non-small-cell lung cancer treated with second-line erlotinib or chemotherapy (PROSE): a biomarker-stratified, randomised phase 3 trial - 27/05/14

Doi : 10.1016/S1470-2045(14)70162-7 
Vanesa Gregorc, DrMD a, , Silvia Novello, MD b, Chiara Lazzari, MD a, Sandro Barni, MD c, Michele Aieta, MD d, Manlio Mencoboni, MD e, Francesco Grossi, MD f, Tommaso De Pas, MD g, Filippo de Marinis, MD g, h, Alessandra Bearz, MD i, Irene Floriani, PhD j, Valter Torri, MD j, Alessandra Bulotta, MD a, Angela Cattaneo a, Julia Grigorieva, PhD k, Maxim Tsypin, PhD k, Joanna Roder, PhD k, Claudio Doglioni, ProfMD l, Matteo Giaj Levra, MD b, Fausto Petrelli, MD c, Silvia Foti, MD a, Mariagrazia Viganò, MD a, Angela Bachi, PhD a, Heinrich Roder, PhD k
a Department of Medical Oncology, Istituto di Ricovero e Cura a Carattere Scientifico, Ospedale San Raffaele, Milan, Italy 
b Department of Oncology, University of Turin, Azienda Ospedaliera Universitaria San Luigi Orbassano, Turin, Italy 
c Division of Medical Oncology, Department of Medical Oncology, Azienda Ospedaliera Treviglio, Treviglio, Italy 
d Division of Medical Oncology, Centro di Riferimento Oncologico di Basilicata, Istituto di Ricovero e Cura a Carattere Scientifico, Rionero in Vulture, Italy 
e Oncology Unit, Villa Scassi Hospital, Azienda Sanitaria Locale 3, Genoa, Italy 
f Lung Cancer Unit, Istituto di Ricovero e Cura a Carattere Scientifico, Azienda Ospedaliera Universitaria San Martino, Istituto Nazionale per la Ricerca sul Cancro, Genoa, Italy 
g Division of Thoracic Oncology, European Institute of Oncology, Milan, Italy 
h 1st Oncological Pulmonary Unit, San Camillo, High Specialization Hospital, Rome, Italy 
i Department of Medical Oncology, National Cancer Institute of Aviano, Aviano, Italy 
j Department of Oncology, Istituto di Ricovero e Cura a Carattere Scientifico–Istituto di Richerche Farmacologiche Mario Negri, Milan, Italy 
k Biodesix, Boulder, CO, USA 
l Università Vita-Salute San Raffaele, School of Medicine, Department of Pathology, Istituto di Ricovero e Cura a Carattere Scientifico, Ospedale San Raffaele, Milan, Italy 

* Correspondence to: Dr Vanesa Gregorc, Department of Medical Oncology, Istituto di Ricovero e Cura a Carattere Scientifico, Ospedale San Raffaele, Via Olgettina 60, Milan 20123, Italy

Summary

Background

An established multivariate serum protein test can be used to classify patients according to whether they are likely to have a good or poor outcome after treatment with EGFR tyrosine-kinase inhibitors. We assessed the predictive power of this test in the comparison of erlotinib and chemotherapy in patients with non-small-cell lung cancer.

Methods

From Feb 26, 2008, to April 11, 2012, patients (aged ≥18 years) with histologically or cytologically confirmed, second-line, stage IIIB or IV non-small-cell lung cancer were enrolled in 14 centres in Italy. Patients were stratified according to a minimisation algorithm by Eastern Cooperative Oncology Group performance status, smoking history, centre, and masked pretreatment serum protein test classification, and randomly assigned centrally in a 1:1 ratio to receive erlotinib (150 mg/day, orally) or chemotherapy (pemetrexed 500 mg/m2, intravenously, every 21 days, or docetaxel 75 mg/m2, intravenously, every 21 days). The proteomic test classification was masked for patients and investigators who gave treatments, and treatment allocation was masked for investigators who generated the proteomic classification. The primary endpoint was overall survival and the primary hypothesis was the existence of a significant interaction between the serum protein test classification and treatment. Analyses were done on the per-protocol population. This trial is registered with ClinicalTrials.gov, number NCT00989690.

Findings

142 patients were randomly assigned to chemotherapy and 143 to erlotinib, and 129 (91%) and 134 (94%), respectively, were included in the per-protocol analysis. 88 (68%) patients in the chemotherapy group and 96 (72%) in the erlotinib group had a proteomic test classification of good. Median overall survival was 9·0 months (95% CI 6·8–10·9) in the chemotherapy group and 7·7 months (5·9–10·4) in the erlotinib group. We noted a significant interaction between treatment and proteomic classification (pinteraction=0·017 when adjusted for stratification factors; pinteraction=0·031 when unadjusted for stratification factors). Patients with a proteomic test classification of poor had worse survival on erlotinib than on chemotherapy (hazard ratio 1·72 [95% CI 1·08–2·74], p=0·022). There was no significant difference in overall survival between treatments for patients with a proteomic test classification of good (adjusted HR 1·06 [0·77–1·46], p=0·714). In the group of patients who received chemotherapy, the most common grade 3 or 4 toxic effect was neutropenia (19 [15%] vs one [<1%] in the erlotinib group), whereas skin toxicity (one [<1%] vs 22 [16%]) was the most frequent in the erlotinib group.

Interpretation

Our findings indicate that serum protein test status is predictive of differential benefit in overall survival for erlotinib versus chemotherapy in the second-line setting. Patients classified as likely to have a poor outcome have better outcomes on chemotherapy than on erlotinib.

Funding

Italian Ministry of Health, Italian Association of Cancer Research, and Biodesix.

Le texte complet de cet article est disponible en PDF.

Plan


© 2014  Elsevier Ltd. Tous droits réservés.
Ajouter à ma bibliothèque Retirer de ma bibliothèque Imprimer
Export

    Export citations

  • Fichier

  • Contenu

Vol 15 - N° 7

P. 713-721 - juin 2014 Retour au numéro
Article précédent Article précédent
  • Ipilimumab versus placebo after radiotherapy in patients with metastatic castration-resistant prostate cancer that had progressed after docetaxel chemotherapy (CA184-043): a multicentre, randomised, double-blind, phase 3 trial
  • Eugene D Kwon, Charles G Drake, Howard I Scher, Karim Fizazi, Alberto Bossi, Alfons J M van den Eertwegh, Michael Krainer, Nadine Houede, Ricardo Santos, Hakim Mahammedi, Siobhan Ng, Michele Maio, Fabio A Franke, Santhanam Sundar, Neeraj Agarwal, Andries M Bergman, Tudor E Ciuleanu, Ernesto Korbenfeld, Lisa Sengeløv, Steinbjorn Hansen, Christopher Logothetis, Tomasz M Beer, M Brent McHenry, Paul Gagnier, David Liu, Winald R Gerritsen, for the CA184-043 Investigators †
| Article suivant Article suivant
  • Validity of Adjuvant! Online program in older patients with breast cancer: a population-based study
  • Nienke A de Glas, Willemien van de Water, Ellen G Engelhardt, Esther Bastiaannet, Anton J M de Craen, Judith R Kroep, Hein Putter, Anne M Stiggelbout, Nir I Weijl, Cornelis J H van de Velde, Johanneke E A Portielje, Gerrit-Jan Liefers

Bienvenue sur EM-consulte, la référence des professionnels de santé.
L’accès au texte intégral de cet article nécessite un abonnement.

Déjà abonné à cette revue ?

Mon compte


Plateformes Elsevier Masson

Déclaration CNIL

EM-CONSULTE.COM est déclaré à la CNIL, déclaration n° 1286925.

En application de la loi nº78-17 du 6 janvier 1978 relative à l'informatique, aux fichiers et aux libertés, vous disposez des droits d'opposition (art.26 de la loi), d'accès (art.34 à 38 de la loi), et de rectification (art.36 de la loi) des données vous concernant. Ainsi, vous pouvez exiger que soient rectifiées, complétées, clarifiées, mises à jour ou effacées les informations vous concernant qui sont inexactes, incomplètes, équivoques, périmées ou dont la collecte ou l'utilisation ou la conservation est interdite.
Les informations personnelles concernant les visiteurs de notre site, y compris leur identité, sont confidentielles.
Le responsable du site s'engage sur l'honneur à respecter les conditions légales de confidentialité applicables en France et à ne pas divulguer ces informations à des tiers.


Tout le contenu de ce site: Copyright © 2024 Elsevier, ses concédants de licence et ses contributeurs. Tout les droits sont réservés, y compris ceux relatifs à l'exploration de textes et de données, a la formation en IA et aux technologies similaires. Pour tout contenu en libre accès, les conditions de licence Creative Commons s'appliquent.