Predictive ability of a drug-based score in patients with advanced non-small-cell lung cancer receiving first-line immunotherapy.
Adrenal Cortex Hormones
/ adverse effects
Aged
Anti-Bacterial Agents
/ adverse effects
Antibodies, Monoclonal, Humanized
/ adverse effects
Carcinoma, Non-Small-Cell Lung
/ drug therapy
Clinical Decision-Making
Decision Support Techniques
Drug Interactions
Female
Humans
Immune Checkpoint Inhibitors
/ adverse effects
Immunotherapy
/ adverse effects
Italy
Lung Neoplasms
/ drug therapy
Male
Patient Selection
Polypharmacy
Predictive Value of Tests
Progression-Free Survival
Proton Pump Inhibitors
/ adverse effects
Reproducibility of Results
Retrospective Studies
Risk Assessment
Risk Factors
Concomitant medications
First-line
Immunotherapy
Non–small-cell lung cancer
Pembrolizumab
Predictive score
Journal
European journal of cancer (Oxford, England : 1990)
ISSN: 1879-0852
Titre abrégé: Eur J Cancer
Pays: England
ID NLM: 9005373
Informations de publication
Date de publication:
06 2021
06 2021
Historique:
received:
04
03
2021
revised:
16
03
2021
accepted:
18
03
2021
pubmed:
3
5
2021
medline:
26
10
2021
entrez:
2
5
2021
Statut:
ppublish
Résumé
We previously demonstrated the cumulative poor prognostic role of concomitant medications on the clinical outcome of patients with advanced cancer treated with immune checkpoint inhibitors, creating and validating a drug-based prognostic score to be calculated before immunotherapy initiation in patients with advanced solid tumours. This 'drug score' was calculated assigning score 1 for each between proton-pump inhibitor and antibiotic administration until a month before cancer therapy initiation and score 2 in case of corticosteroid intake. The good risk group included patients with score 0, intermediate risk with score 1-2 and poor risk with score 3-4. Aiming at validating the prognostic and putative predictive ability depending on the anticancer therapy, we performed the present comparative analysis in two cohorts of advanced non-small-cell lung cancer (NSCLC), respectively, receiving first-line pembrolizumab or chemotherapy through a random case-control matching and through a pooled multivariable analysis including the interaction between the computed score and the therapeutic modality (pembrolizumab vs chemotherapy). Nine hundred fifty and 595 patients were included in the pembrolizumab and chemotherapy cohorts, respectively. After the case-control random matching, 589 patients from the pembrolizumab cohort and 589 from the chemotherapy cohort were paired, with no statistically significant differences between the characteristics of the matched subjects. Among the pembrolizumab-treated group, good, intermediate and poor risk evaluable patients achieved an objective response rate (ORR) of 50.0%, 37.7% and 23.4%, respectively, (p < 0.0001), whereas among the chemotherapy-treated group, patients achieved an ORR of 37.0%, 40.0% and 32.4%, respectively (p = 0.4346). The median progression-free survival (PFS) of good, intermediate and poor risk groups was 13.9 months, 6.3 months and 2.8 months, respectively, within the pembrolizumab cohort (p < 0.0001), and 6.2 months, 6.2 months and 4.3 months, respectively, within the chemotherapy cohort (p = 0.0280). Among the pembrolizumab-treated patients, the median overall survival (OS) for good, intermediate and poor risk patients was 31.4 months, 14.5 months and 5.8 months, respectively, (p < 0.0001), whereas among the chemotherapy-treated patients, it was 18.3 months, 16.8 months and 10.6 months, respectively (p = 0.0003). A similar trend was reported considering the two entire populations. At the pooled analysis, the interaction term between the score and the therapeutic modality was statistically significant with respect to ORR (p = 0.0052), PFS (p = 0.0003) and OS (p < 0.0001), confirming the significantly different effect of the score within the two cohorts. Our 'drug score' showed a predictive ability with respect to ORR in the immunotherapy cohort only, suggesting it might be a useful tool for identifying patients unlikely to benefit from first-line single-agent pembrolizumab. In addition, the prognostic stratification in terms of PFS and OS was significantly more pronounced among the pembrolizumab-treated patients.
Sections du résumé
BACKGROUND
We previously demonstrated the cumulative poor prognostic role of concomitant medications on the clinical outcome of patients with advanced cancer treated with immune checkpoint inhibitors, creating and validating a drug-based prognostic score to be calculated before immunotherapy initiation in patients with advanced solid tumours. This 'drug score' was calculated assigning score 1 for each between proton-pump inhibitor and antibiotic administration until a month before cancer therapy initiation and score 2 in case of corticosteroid intake. The good risk group included patients with score 0, intermediate risk with score 1-2 and poor risk with score 3-4.
METHODS
Aiming at validating the prognostic and putative predictive ability depending on the anticancer therapy, we performed the present comparative analysis in two cohorts of advanced non-small-cell lung cancer (NSCLC), respectively, receiving first-line pembrolizumab or chemotherapy through a random case-control matching and through a pooled multivariable analysis including the interaction between the computed score and the therapeutic modality (pembrolizumab vs chemotherapy).
RESULTS
Nine hundred fifty and 595 patients were included in the pembrolizumab and chemotherapy cohorts, respectively. After the case-control random matching, 589 patients from the pembrolizumab cohort and 589 from the chemotherapy cohort were paired, with no statistically significant differences between the characteristics of the matched subjects. Among the pembrolizumab-treated group, good, intermediate and poor risk evaluable patients achieved an objective response rate (ORR) of 50.0%, 37.7% and 23.4%, respectively, (p < 0.0001), whereas among the chemotherapy-treated group, patients achieved an ORR of 37.0%, 40.0% and 32.4%, respectively (p = 0.4346). The median progression-free survival (PFS) of good, intermediate and poor risk groups was 13.9 months, 6.3 months and 2.8 months, respectively, within the pembrolizumab cohort (p < 0.0001), and 6.2 months, 6.2 months and 4.3 months, respectively, within the chemotherapy cohort (p = 0.0280). Among the pembrolizumab-treated patients, the median overall survival (OS) for good, intermediate and poor risk patients was 31.4 months, 14.5 months and 5.8 months, respectively, (p < 0.0001), whereas among the chemotherapy-treated patients, it was 18.3 months, 16.8 months and 10.6 months, respectively (p = 0.0003). A similar trend was reported considering the two entire populations. At the pooled analysis, the interaction term between the score and the therapeutic modality was statistically significant with respect to ORR (p = 0.0052), PFS (p = 0.0003) and OS (p < 0.0001), confirming the significantly different effect of the score within the two cohorts.
CONCLUSION
Our 'drug score' showed a predictive ability with respect to ORR in the immunotherapy cohort only, suggesting it might be a useful tool for identifying patients unlikely to benefit from first-line single-agent pembrolizumab. In addition, the prognostic stratification in terms of PFS and OS was significantly more pronounced among the pembrolizumab-treated patients.
Identifiants
pubmed: 33934059
pii: S0959-8049(21)00208-2
doi: 10.1016/j.ejca.2021.03.041
pii:
doi:
Substances chimiques
Adrenal Cortex Hormones
0
Anti-Bacterial Agents
0
Antibodies, Monoclonal, Humanized
0
Immune Checkpoint Inhibitors
0
Proton Pump Inhibitors
0
pembrolizumab
DPT0O3T46P
Types de publication
Journal Article
Multicenter Study
Validation Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
224-231Commentaires et corrections
Type : CommentIn
Type : CommentIn
Informations de copyright
Copyright © 2021 Elsevier Ltd. All rights reserved.
Déclaration de conflit d'intérêts
Conflict of interest statement S.B. received honoraria as a speaker at scientific events and for the advisory role from Bristol Myers Squibb (BMS), Pfizer, MSD, Ipsen, Roche, Eli Lilly, AstraZeneca and Novartis. M.B. received honoraria as a speaker at scientific events from Bristol Myers Squibb (BMS), Novartis, AstraZeneca and Pfizer and as a consultant for the advisory role from Novartis, BMS and Pfizer; she also received fees for copyright transfer from Sciclone Pharmaceuticals and research funding from Seqirus UK, Pfizer, Novartis, BMS, AstraZeneca, Roche S.p.A. and Sanofi Genzyme. R.G. received speaker fees and grant consultancies from AstraZeneca and Roche. J.G.J.V.A. reports receiving commercial research grants from Amphera and Roche, holds ownership interest (including patents) in Amphera BV and is a consultant/advisory board member for Amphera, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, MSD and Roche. A.F. received grant consultancies from Roche, Pfizer, Astellas and BMS. F.M. received grant consultancies from MSD and Takeda. R.C. received speaker fees from BMS, MSD, Takeda, Pfizer, Roche and AstraZeneca. C.G. received speaker fees/grant consultancies from AstraZeneca, BMS, Boehringer Ingelheim, Roche and MSD. M.R. received honoraria for scientific events from Roche, AstraZeneca, BMS, MSD and Boehringer Ingelheim. E.B. received speaker and travel fees from MSD, AstraZeneca, Pfizer, Helsinn, Eli Lilly, BMS, Novartis and Roche and grant consultancies from Roche and Pfizer. M.C.G. received grants from MSD, AstraZeneca, Novartis, Roche, Pfizer, Celgene, Tiziana Sciences, Clovis, Merck, Bayer, GSK, Spectrum and Blueprint; personal fees from Eli Lilly, Boehringer Ingelheim, Otsuka Pharma, AstraZeneca, Novartis, BMS, Roche, Pfizer, Celgene, Incyte, Inivata, Takeda, Bayer, MSD, Sanofi, Seattle Genetics and Daiichi Sankyo and other financial supports from Eli Lilly, AstraZeneca, Novartis, BMS, Roche, Pfizer, Celgene, Tiziana Sciences, Clovis, Merck Serono, MSD, GSK, Spectrum and Blueprint. A.A. received grant consultancies from Takeda, MSD, BMJ, AstraZeneca, Roche and Pfizer. M.D.M. received research funding from Tesaro-GlaxoSmithKline and acted in a consulting/advisory role for Novartis, Pfizer, Eisai, Takeda, Janssen, Astellas, Roche and AstraZeneca. D.J.P. received lecture fees from ViiV Healthcare and Bayer Healthcare; travel expenses from BMS and Bayer Healthcare; consulting fees for Mina Therapeutics, EISAI, Roche and AstraZeneca and research funding (to the institution) from MSD and BMS. M.T. received honoraria from MSD, BMS, Boehringer (BI), Takeda and AstraZeneca and research funding from AstraZeneca. A.C. received speaker fees and grant consultancies from AstraZeneca, MSD, BMS, Roche, Novartis, Istituto Gentili and Astellas. All the other authors declare no competing interests.