EPAC-lung: European pooled analysis of the prognostic value of circulating tumour cells in small cell lung cancer.
Small cell lung cancer (SCLC)
biomarker
circulating tumour cells (CTCs)
liquid biopsies
meta-analysis
prognostic models
Journal
Translational lung cancer research
ISSN: 2218-6751
Titre abrégé: Transl Lung Cancer Res
Pays: China
ID NLM: 101646875
Informations de publication
Date de publication:
Apr 2021
Apr 2021
Historique:
entrez:
20
5
2021
pubmed:
21
5
2021
medline:
21
5
2021
Statut:
ppublish
Résumé
Circulating tumour cell (CTC) number is an independent prognostic factor in patients with small cell lung cancer (SCLC) but there is no consensus on the CTC threshold for prognostic significance. We undertook a pooled analysis of individual patient data to clinically validate CTC enumeration and threshold for prognostication. Four European cancer centres, experienced in CellSearch CTC enumeration for SCLC provided pseudo anonymised data for patients who had undergone pre-treatment CTC count. Data was collated, and Cox regression models, stratified by centre, explored the relationship between CTC count and survival. The added value of incorporating CTCs into clinico-pathological models was investigated using likelihood ratio tests. A total of 367 patient records were evaluated. A one-unit increase in log-transformed CTC counts corresponded to an estimated hazard ratio (HR) of 1.24 (95% CI: 1.19-1.29, P<0.0001) for progression free survival (PFS) and 1.23 (95% CI: 1.18-1.28, P<0.0001) for overall survival (OS). CTC count of ≥15 or ≥50 was significantly associated with an increased risk of progression (CTC ≥15: HR 3.20, 95% CI: 2.50-4.09, P<0.001; CTC ≥50: HR 2.56, 95% CI: 2.01-3.25, P<0.001) and an increased risk of death (CTC ≥15: HR 2.90, 95% CI: 2.28-3.70, P<0.001; CTC ≥50: HR 2.47, 95% CI: 1.95-3.13, P<0.001). There was no significant inter-centre heterogeneity observed. Addition of CTC count to clinico-pathological models as a continuous log-transformed variable, offers further prognostic value (both likelihood ratio P<0.001 for OS and PFS). Higher pre-treatment CTC counts are a negative independent prognostic factor in SCLC when considered as a continuous variable or dichotomised counts of ≥15 or ≥50. Incorporating CTC counts, as a continuous variable, improves clinic-pathological prognostic models.
Sections du résumé
BACKGROUND
BACKGROUND
Circulating tumour cell (CTC) number is an independent prognostic factor in patients with small cell lung cancer (SCLC) but there is no consensus on the CTC threshold for prognostic significance. We undertook a pooled analysis of individual patient data to clinically validate CTC enumeration and threshold for prognostication.
METHODS
METHODS
Four European cancer centres, experienced in CellSearch CTC enumeration for SCLC provided pseudo anonymised data for patients who had undergone pre-treatment CTC count. Data was collated, and Cox regression models, stratified by centre, explored the relationship between CTC count and survival. The added value of incorporating CTCs into clinico-pathological models was investigated using likelihood ratio tests.
RESULTS
RESULTS
A total of 367 patient records were evaluated. A one-unit increase in log-transformed CTC counts corresponded to an estimated hazard ratio (HR) of 1.24 (95% CI: 1.19-1.29, P<0.0001) for progression free survival (PFS) and 1.23 (95% CI: 1.18-1.28, P<0.0001) for overall survival (OS). CTC count of ≥15 or ≥50 was significantly associated with an increased risk of progression (CTC ≥15: HR 3.20, 95% CI: 2.50-4.09, P<0.001; CTC ≥50: HR 2.56, 95% CI: 2.01-3.25, P<0.001) and an increased risk of death (CTC ≥15: HR 2.90, 95% CI: 2.28-3.70, P<0.001; CTC ≥50: HR 2.47, 95% CI: 1.95-3.13, P<0.001). There was no significant inter-centre heterogeneity observed. Addition of CTC count to clinico-pathological models as a continuous log-transformed variable, offers further prognostic value (both likelihood ratio P<0.001 for OS and PFS).
CONCLUSIONS
CONCLUSIONS
Higher pre-treatment CTC counts are a negative independent prognostic factor in SCLC when considered as a continuous variable or dichotomised counts of ≥15 or ≥50. Incorporating CTC counts, as a continuous variable, improves clinic-pathological prognostic models.
Identifiants
pubmed: 34012782
doi: 10.21037/tlcr-20-1061
pii: tlcr-10-04-1653
pmc: PMC8107738
doi:
Types de publication
Journal Article
Langues
eng
Pagination
1653-1665Informations de copyright
2021 Translational Lung Cancer Research. All rights reserved.
Déclaration de conflit d'intérêts
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure forms (available at http://dx.doi.org/10.21037/tlcr-20-1061). Dr. CRL reports personal fees from Amgen, personal fees from copartners, outside the submitted work. Dr. CRL was supported by the European Society for Medical Oncology (translational research fellowship – no grant number applicable) with the aid of a grant from Hoffman-La Roche and the International Association for the Study of Lung Cancer (no grant number applicable). CRL also received support as a recipient of the grant DUERTECC/EURONCO (Diplome Universitaire Européen de Recherche Translationelle et Clinique en Cancerologie - no grant number applicable). Dr. VF was funded via a Clinical Pharmacology Fellowship educational grant from CRUK and AstraZeneca (C147/A12328). Dr. MGK reports personal fees from Janssen, personal fees from Roche, personal fees from Bayer, personal fees from Seattle Genetics, outside the submitted work. Dr. Groen reports grants from Cancer-ID project, outside the submitted work. Dr. BB reports grants from Abbvie, grants from Amgen, grants from AstraZeneca, grants from Biogen, grants from Blueprint Medicines, grants from BMS, grants from Celgène, grants from Eli-Lilly, grants from GSK, grants from Ignyta, grants from ISPEN, grants from Merck KGaA, grants from MSD, grants from Nektar, grants from Onxeo, grants from Pfizer, grants from Pharma Mar, grants from Sanofi, grants from Spectrum Pharmaceuticals, grants from Takeda, grants from Tiziana Pharma, outside the submitted work. Dr. AM reports personal fees from ROCHE, personal fees from ASTRAZENECA, personal fees from BOEHRINGER, from Pfizer, from BMS, from MSD, from TAKEDA, outside the submitted work. Dr. FP reports grants, personal fees and non-financial support from Bayer, personal fees from Sandoz, grants and personal fees from Incyte, personal fees from Celgene, grants and personal fees from Astra Zeneca, personal fees from Pierre Fabre, personal fees from Janssen Cilag, grants from Roche, grants from Pfizer, outside the submitted work. Dr. CFF reports grants and other from AstraZeneca, grants and other from Elekta, outside the submitted work. Dr. CD reports grants from AstraZeneca, grants from NIHR Manchester Biomedical Research Centre, during the conduct of the study; grants and personal fees from AstraZeneca, grants from Amgen, grants from Angle PLC, grants from Astex Pharmaceuticals, grants from Bayer, grants and personal fees from Biocartis, grants from Bioven, grants from BMS, grants from Boehringer Ingelheim, grants from Celgene, grants and non-financial support from Clearbridge Biomedics, grants from GSK, grants from Menarini Diagnostics, grants and personal fees from Merck KGaA, grants from Novartis, grants from Roche, grants from Taiho Oncology, non-financial support from Thermofisher, outside the submitted work. Dr. SM reports personal fees from Statistical advice: IDDI, Janssen CilagÐ personal fees from Independent Data Monitoring Committee member: Hexal, Steba, IQVIA, Roche, Sensorion, Biophytis, Servier, Yuhan, outside the submitted work. Dr. NN serves as an unpaid editorial board member of the Translational Lung Cancer Research from Sep 2019 to Sep 2021. The authors have no other conflicts of interest to declare.
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