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SummaryBackgroundThe gold standard endpoint in clinical trials of chemotherapy and radiotherapy for lung cancer is overall survival. Although reliable and simple to measure, this endpoint takes years to observe. Surrogate endpoints that would enable earlier assessments of treatment effects would be useful. We assessed the correlations between potential surrogate endpoints and overall survival at individual and trial levels.MethodsWe analysed individual patients' data from 15 071 patients involved in 60 randomised clinical trials that were assessed in six meta-analyses. Two meta-analyses were of adjuvant chemotherapy in non-small-cell lung cancer, three were of sequential or concurrent chemotherapy, and one was of modified radiotherapy in locally advanced lung cancer. We investigated disease-free survival (DFS) or progression-free survival (PFS), defined as the time from randomisation to local or distant relapse or death, and locoregional control, defined as the time to the first local event, as potential surrogate endpoints. At the individual level we calculated the squared correlations between distributions of these three endpoints and overall survival, and at the trial level we calculated the squared correlation between treatment effects for endpoints.FindingsIn trials of adjuvant chemotherapy, correlations between DFS and overall survival were very good at the individual level (ρ2=0·83, 95% CI 0·83–0·83 in trials without radiotherapy, and 0·87, 0·87–0·87 in trials with radiotherapy) and excellent at trial level (R2=0·92, 95% CI 0·88–0·95 in trials without radiotherapy and 0·99, 0·98–1·00 in trials with radiotherapy). In studies of locally advanced disease, correlations between PFS and overall survival were very good at the individual level (ρ2 range 0·77–0·85, dependent on the regimen being assessed) and trial level (R2 range 0·89–0·97). In studies with data on locoregional control, individual-level correlations were good (ρ2=0·71, 95% CI 0·71–0·71 for concurrent chemotherapy and ρ2=0·61, 0·61–0·61 for modified vs standard radiotherapy) and trial-level correlations very good (R2=0·85, 95% CI 0·77–0·92 for concurrent chemotherapy and R2=0·95, 0·91–0·98 for modified vs standard radiotherapy).InterpretationWe found a high level of evidence that DFS is a valid surrogate endpoint for overall survival in studies of adjuvant chemotherapy involving patients with non-small-cell lung cancers, and PFS in those of chemotherapy and radiotherapy for patients with locally advanced lung cancers. Extrapolation to targeted agents, however, is not automatically warranted.FundingProgramme Hospitalier de Recherche Clinique, Ligue Nationale Contre le Cancer, British Medical Research Council, Sanofi-Aventis.

Anti-cancer drugs targeting protein kinases include small molecule inhibitors and monoclonal antibodies. Feedback loops and cross talk between signalling pathways impact significantly on the efficacy of cancer therapeutics and resistance to targeted agents is a major barrier to effective treatments. Increasingly, therapies are being designed to target multiple kinase pathways. This can be achieved using a single agent which inhibits multiple signalling pathways or a combination of highly selective agents. In this review we discuss the principles of specifically targeting multiple kinase pathways with particular reference to angiogenic signalling pathways.

Tumour heterogeneity leads to the development of multiple resistance mechanisms during targeted therapies. Identifying the dominant driver(s) is critical for treatment decision. We studied the relative dynamics of multiple oncogenic drivers in longitudinal plasma of 50 EGFR‐mutant non‐small‐cell lung cancer patients receiving gefitinib and hydroxychloroquine. We performed digital PCR and targeted sequencing on samples from all patients and shallow whole‐genome sequencing on samples from three patients who underwent histological transformation to small‐cell lung cancer. In 43 patients with known EGFR mutations from tumour, we identified them accurately in plasma of 41 patients (95%, 41/43). We also found additional mutations, including EGFR T790M (31/50, 62%), TP53 (23/50, 46%), PIK3CA (7/50, 14%) and PTEN (4/50, 8%). Patients with both TP53 and EGFR mutations before treatment had worse overall survival than those with only EGFR. Patients who progressed without T790M had worse PFS during TKI continuation and developed alternative alterations, including small‐cell lung cancer‐associated copy number changes and TP53 mutations, that tracked subsequent treatment responses. Longitudinal plasma analysis can help identify dominant resistance mechanisms, including non‐druggable genetic information that may guide clinical management.