C R Lindsay1, F H Blackhall1, A Carmel2, F Fernandez-Gutierrez3, P Gazzaniga4, H J M Groen5, T J N Hiltermann5, M G Krebs1, S Loges6, R López-López7, L Muinelo-Romay7, K Pantel8, L Priest9, S Riethdorf8, E Rossi10, L Terstappen11, H Wikman8, J-C Soria12, F Farace13, A Renehan14, C Dive3, B Besse15, S Michiels16. 1. Division of Molecular and Clinical Cancer Sciences, University of Manchester, Manchester, UK; Department of Medical Oncology, The Christie NHS Foundation Trust, Wilmslow Road, Manchester, M20 4BX, UK; Cancer Research UK Lung Cancer Centre of Excellence, Manchester, UK. 2. Service de Biostatistique et d'Épidémiologie, Gustave Roussy, Université Paris-Saclay, 114, Rue Edouard Vaillant, Villejuif, 94805, France; INSERM U1018 OncoStat, CESP, Université Paris-Sud, Université Paris-Saclay, France; Ligue Nationale Contre le Cancer Meta-Analysis Platform, Gustave Roussy Cancer Campus, Villejuif, France. 3. Cancer Research UK Lung Cancer Centre of Excellence, Manchester, UK; Clinical and Experimental Pharmacology Group, Cancer Research UK Manchester Institute, University of Manchester, Manchester, UK. 4. Circulating Tumor Cells Unit, Dept Molecular Medicine, Sapienza, University of Rome, Italy. 5. Department of Pulmonary Diseases, University of Groningen and University Medical Center Groningen, Groningen, the Netherlands. 6. Department of Tumor Biology, University Medical Center Hamburg - Eppendorf, Hamburg, Germany; Department of Oncology, Hematology and Bone Marrow Transplantation with Section Pneumology, Hubertus Wald University Comprehensive Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. 7. Liquid Biopsy Analysis Unit, Oncomet, Health Research Institute of Santiago de Compostela (IDIS), CIBERONC, Santiago de Compostela, Spain. 8. Department of Tumor Biology, University Medical Center Hamburg - Eppendorf, Hamburg, Germany. 9. Department of Medical Oncology, The Christie NHS Foundation Trust, Wilmslow Road, Manchester, M20 4BX, UK. 10. Department of Surgery, Oncology and Gastroenterology, Oncology Section, University of Padova, Padova, Italy; Veneto Institute of Oncology IOV-IRCCS, Padua, Italy. 11. Department of Medical Cell BioPhysics, University of Twente, Enschede, the Netherlands. 12. Department of Cancer Medicine, Gustave Roussy Cancer Campus, Villejuif, France; INSERM, U981 "Predictive Biomarkers and New Therapeutics in Oncology", F-94805, Villejuif, France; Paris-Sud University, Orsay, France. 13. INSERM, U981 "Predictive Biomarkers and New Therapeutics in Oncology", F-94805, Villejuif, France; Gustave Roussy, Université Paris-Saclay. "Rare Circulating Cells" Translational Platform, CNRS UMS3655 - INSERM US23, AMMICA, F-94805, Villejuif, France. 14. Division of Molecular and Clinical Cancer Sciences, University of Manchester, Manchester, UK. 15. Department of Cancer Medicine, Gustave Roussy Cancer Campus, Villejuif, France; Paris-Sud University, Orsay, France. 16. Service de Biostatistique et d'Épidémiologie, Gustave Roussy, Université Paris-Saclay, 114, Rue Edouard Vaillant, Villejuif, 94805, France; INSERM U1018 OncoStat, CESP, Université Paris-Sud, Université Paris-Saclay, France; Ligue Nationale Contre le Cancer Meta-Analysis Platform, Gustave Roussy Cancer Campus, Villejuif, France. Electronic address: stefan.michiels@gustaveroussy.fr.
Abstract
INTRODUCTION: We assessed the clinical validity of circulating tumour cell (CTC) quantification for prognostication of patients with advanced non-small cell lung cancer (NSCLC) by undertaking a pooled analysis of individual patient data. METHODS: Nine European NSCLC CTC centres were asked to provide reported/unreported pseudo-anonymised data for patients with advanced NSCLC who participated in CellSearch CTC studies from January 2003 to March 2017. We used Cox regression models, stratified by centres, to establish the association between CTC count and survival. We assessed the added value of CTCs to prognostic clinicopathological models using likelihood ratio (LR) statistics and c-indices. RESULTS: Seven out of nine eligible centres provided data for 550 patients with prognostic information for overall survival. CTC counts of ≥2 and ≥ 5 per 7·5 mL were associated with reduced progression-free survival (≥2 CTCs: hazard ratio [HR] = 1.72, p < 0·001; ≥5 CTCs: HR = 2.21, p < 0·001) and overall survival (≥2 CTCs: HR = 2·18, p < 0·001; ≥5 CTCs: HR = 2·75, p < 0·001), respectively. Survival prediction was significantly improved by addition of baseline CTC count to LR clinicopathological models (log-transformed CTCs p < 0·001; ≥2 CTCs p < 0·001; ≥5 CTCs p ≤ 0·001 for both survival end-points), whereas moderate improvements were observed with the use of c-index models. There was some evidence of between-centre heterogeneity, especially when examining continuous counts of CTCs. CONCLUSIONS: These data confirm CTCs as an independent prognostic indicator of progression-free survival and overall survival in advanced NSCLC and also reveal some evidence of between-centre heterogeneity. CTC count improves prognostication when added to full clinicopathological predictive models.
INTRODUCTION: We assessed the clinical validity of circulating tumour cell (CTC) quantification for prognostication of patients with advanced non-small cell lung cancer (NSCLC) by undertaking a pooled analysis of individual patient data. METHODS: Nine European NSCLC CTC centres were asked to provide reported/unreported pseudo-anonymised data for patients with advanced NSCLC who participated in CellSearch CTC studies from January 2003 to March 2017. We used Cox regression models, stratified by centres, to establish the association between CTC count and survival. We assessed the added value of CTCs to prognostic clinicopathological models using likelihood ratio (LR) statistics and c-indices. RESULTS: Seven out of nine eligible centres provided data for 550 patients with prognostic information for overall survival. CTC counts of ≥2 and ≥ 5 per 7·5 mL were associated with reduced progression-free survival (≥2 CTCs: hazard ratio [HR] = 1.72, p < 0·001; ≥5 CTCs: HR = 2.21, p < 0·001) and overall survival (≥2 CTCs: HR = 2·18, p < 0·001; ≥5 CTCs: HR = 2·75, p < 0·001), respectively. Survival prediction was significantly improved by addition of baseline CTC count to LR clinicopathological models (log-transformed CTCs p < 0·001; ≥2 CTCs p < 0·001; ≥5 CTCs p ≤ 0·001 for both survival end-points), whereas moderate improvements were observed with the use of c-index models. There was some evidence of between-centre heterogeneity, especially when examining continuous counts of CTCs. CONCLUSIONS: These data confirm CTCs as an independent prognostic indicator of progression-free survival and overall survival in advanced NSCLC and also reveal some evidence of between-centre heterogeneity. CTC count improves prognostication when added to full clinicopathological predictive models.
Authors: Catherine Alix-Panabieres; Anthony Magliocco; Luis Enrique Cortes-Hernandez; Zahra Eslami-S; Daniel Franklin; Jane L Messina Journal: Clin Exp Metastasis Date: 2021-05-07 Impact factor: 5.150