Your browser doesn't support javascript.
loading
Integrating clinical and biological prognostic biomarkers in patients with advanced NSCLC treated with immunotherapy: the DEMo score system.
Prelaj, Arsela; Proto, Claudia; Lo Russo, Giuseppe; Signorelli, Diego; Ferrara, Roberto; Mensah, Mavis; Galli, Giulia; De Toma, Alessandro; Viscardi, Giuseppe; Brambilla, Marta; Lobefaro, Riccardo; Trevisan, Benedetta; Trovò, Francesco; Torri, Valter; Sozzi, Gabriella; Garassino, Marina Chiara; Boeri, Mattia.
Afiliação
  • Prelaj A; Medical Oncology Department, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy.
  • Proto C; Department of Electronics, Information, and Bioengineering, Polytechnic University of Milan, Milano, Italy.
  • Lo Russo G; Medical Oncology Department, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy.
  • Signorelli D; Medical Oncology Department, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy.
  • Ferrara R; Medical Oncology Department, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy.
  • Mensah M; Medical Oncology Department, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy.
  • Galli G; Tumor Genomics Unit, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
  • De Toma A; Medical Oncology Department, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy.
  • Viscardi G; Medical Oncology Department, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy.
  • Brambilla M; Medical Oncology Department, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy.
  • Lobefaro R; Medical Oncology Department, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy.
  • Trevisan B; Medical Oncology Department, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy.
  • Trovò F; Medical Oncology Department, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy.
  • Torri V; Department of Electronics, Information, and Bioengineering, Polytechnic University of Milan, Milano, Italy.
  • Sozzi G; Pharmacological Research Institute IRCSS Mario Negri, Milano, Italy.
  • Garassino MC; Tumor Genomics Unit, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
  • Boeri M; Medical Oncology Department, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy.
Transl Lung Cancer Res ; 9(3): 617-628, 2020 Jun.
Article em En | MEDLINE | ID: mdl-32676324
BACKGROUND: Several biomarkers have been separately described to select patients for immunotherapy (IO), but few studies integrate these markers. Di Maio, EPSILoN and the plasma microRNA signature classifier (MSC), are three different clinico, biochemical and molecular markers able to independently predict prognosis in non-small cell lung cancer (NSCLC). METHODS: Complete data such as sex, histology, ECOG-PS, stage, smoking status, presence of liver metastasis, LDH and neutrophils-to-lymphocyte ratio were collected to generate Di Maio and EPSILoN. The MSC risk level was prospectively assessed in plasma samples collected at baseline IO. The 3 markers were integrated into the DEMo score system prospectively tested in a cohort of 200 advanced NSCLC patients treated with IO. Endpoints were overall survival (OS), progression-free survival (PFS) and overall response rate (ORR). RESULTS: DEMo separated patients in 7-risk groups whose median OS had a trend ranging from 29.7 to 1.5 months (P<0.0001). When comparing patients with the lowest (n=29) and the highest (n=35) DEMo scores ORR was 45% and 3%, respectively (P<0.0001). Considering the 53 PD-L1 ≥50% patients, DEMo identified a group of 13 (25%) patients who benefit less from IO in terms of both OS (HR: 8.81; 95% CI: 2.87-20.01) and PFS (HR: 6.82; 95% CI: 2.57-18.10). Twelve out of 111 (11%) patients who most benefit from IO according to OS (HR: 0.21; 95% CI: 0.07-0.62) and PFS (HR: 0.28; 95% CI: 0.12-0.65) were identified by DEMo in the PD-L1 <50% group. CONCLUSIONS: The DEMo prognostic score system stratified NSCLC patients treated with IO better than each single marker. The proper use of DEMo according to PD-L1 could improve selection in IO regimens.
Palavras-chave

Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Transl Lung Cancer Res Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Itália

Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Transl Lung Cancer Res Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Itália