Trifluridine-tipiracil plus bevacizumab versus capecitabine plus bevacizumab as first-line treatment for patients with metastatic colorectal cancer ineligible for intensive therapy (SOLSTICE): a randomised, open-label phase 3 study.

BACKGROUND: Trifluridine-tipiracil plus bevacizumab has shown efficacy in previous phase 2 studies including patients with unresectable metastatic colorectal cancer. We aimed to investigate first-line trifluridine-tipiracil plus bevacizumab versus capecitabine plus bevacizumab in patients with unresectable metastatic colorectal cancer ineligible for intensive treatment. METHODS: In this open-label, randomised, phase 3 study, we enrolled patients aged 18 years and older with histologically confirmed metastatic colorectal cancer, ineligible for full-dose doublet or triplet chemotherapy and curative resection across 25 countries and regions. Participants were randomly allocated (1:1) to trifluridine-tipiracil plus bevacizumab or capecitabine plus bevacizumab until disease progression or unacceptable toxicity using an interactive web response system, stratified by Eastern Cooperative Oncology Group (ECOG) performance status (0 vs 1 vs 2), primary tumour location (right vs left colon), and the main reason for not being a candidate for intensive therapy (clinical condition vs non-clinical condition). The primary endpoint was investigator-assessed progression-free survival, defined as the time from randomisation to radiological progression or death from any cause, in the intention-to-treat population. Safety was assessed in all patients having taken at least one dose of the study drug. The trial is ongoing, findings presented here are those of the primary analysis of progression-free survival, conducted after 629 events had occurred. This study is registered with ClinicalTrials.gov, NCT03869892. FINDINGS: Between March 21, 2019, and Sept 14, 2020, 856 patients (54% male, 46% female) were randomly assigned to trifluridine-tipiracil plus bevacizumab (n=426) or capecitabine plus bevacizumab (n=430). After a median follow-up of 16·6 months (95% CI 16·5-17·1), the hazard ratio for progression-free survival for trifluridine-tipiracil plus bevacizumab versus capecitabine plus bevacizumab was 0·87 (0·75-1·02; p=0·0464; protocol-defined significance level of p=0·021 not met). Investigator-assessed median progression-free survival was 9·4 months (95% CI 9·1-10·9) with trifluridine-tipiracil plus bevacizumab versus 9·3 months (8·9-9·8) with capecitabine plus bevacizumab. The most common grade 3 and higher treatment-emergent adverse events were neutropenia (220 [52%] of 423 patients in the trifluridine-tipiracil plus bevacizumab group vs six [1%] of 427 in the capecitabine plus bevacizumab group), decreased neutrophil count (78 [18%] vs four [<1%]), anaemia (60 [14%] vs 16 [4%]), and hand-foot syndrome (none vs 61 [15%]). Nine deaths (five in the trifluridine-tipiracil plus bevacizumab group and four in the capecitabine plus bevacizumab group) were treatment related. INTERPRETATION: First-line trifluridine-tipiracil plus bevacizumab was not superior to capecitabine plus bevacizumab in this population. As expected, the safety profile differed between the two treatments, but there were no new safety concerns. Trifluridine-tipiracil plus bevacizumab represents a feasible alternative to capecitabine plus bevacizumab in this population. FUNDING: Servier International Research Institute, Suresnes, France.

A Bayesian approach for event predictions in clinical trials with time-to-event outcomes.

In clinical trials with time-to-event outcome as the primary endpoint, the end of study date is often based on the number of observed events, which drives the statistical power and the sample size calculation. It is of great value for study sponsors to have a good understanding of the recruitment process and the event milestones to manage the logistical tasks, which require a considerable amount of resources. The objective of the proposed statistical approach is to predict, as accurately as possible, the timing of an analysis planned once a target number of events is collected. The method takes into account the enrollment, the time to event, and the time to censor processes, using Weibull models in a Bayesian framework. We also consider a possible delay in the event reporting by the investigators, and covariates may also be included. Several metrics can be obtained, such as the probability of study completion at specific timepoints or the credible interval of the date of study completion. The approach was applied to oncology trials, with progression-free survival as primary outcome. A retrospective analysis shows the accuracy of the approach on these examples, as well as the benefit of updating the predictive probability of study completion as data are accumulating or new information becomes available. We also evaluated the performances of the proposed method in a comprehensive simulation study.