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Objectives Antiepileptic and antiarrhythmic drugs inhibit voltage-gated sodium (Na+) channels (VGSCs), and preclinical studies show that these medications reduce tumour growth, invasion and metastasis. We investigated the association between VGSC inhibitor use and survival in patients with breast, bowel and prostate cancer.Design Retrospective cohort study.Setting Individual electronic primary healthcare records extracted from the Clinical Practice Research Datalink.Participants Records for 132 996 patients with a diagnosis of breast, bowel or prostate cancer.Outcome measures Adjusted Cox proportional hazards regression was used to analyse cancer-specific survival associated with exposure to VGSC inhibitors. Exposure to non-VGSC-inhibiting antiepileptic medication and other non-VGSC blockers were also considered. Drug exposure was treated as a time-varying covariate to account for immortal time bias.Results During 1 002 225 person-years of follow-up, there were 42 037 cancer-specific deaths. 53 724 (40.4%) patients with cancer had at least one prescription for a VGSC inhibitor of interest. Increased risk of cancer-specific mortality was associated with exposure to this group of drugs (HR 1.59, 95% CI 1.56 to 1.63, p

A multi-scenario, multi-model ensemble of simulations from regional climate models is outlined to provide the core data source for a set of climate projections and a climate change service. A subset of realisations from CMIP6 Global Climate Models (GCMs) are selected for downscaling by Regional Climate Models (RCMs) under a ‘sparse matrix’ framework using the CORDEX guidelines for Shared Socio-economic Pathways that feature low emissions (SSP1-2.6) and high emissions (SSP3-7.0). The subset excludes poor performing models, with performance assessed by the climatology over a large Indo-Pacific domain and an Australian-specific domain, the simulation of atmospheric circulation and teleconnections to major drivers, then incorporating other evaluation from the literature. The models are selected to be relatively independent by simply choosing one model from each ‘family’ where possible. The projected change in temperature and rainfall in climatic regions of Australia in the selected models are broadly representative of that from the whole CMIP6 ensemble, after deliberately treating models with very high climate sensitivity separately. A limited but carefully constructed ensemble will not represent statistically balanced estimates but can be used effectively under a ‘storylines’ style approach and can maximise representativeness within limits. The resulting ensemble can be used as a key data source for the future climate component of climate services in Australia. The ensemble will be used in conjunction with CMIP6 and large ensembles of GCM simulations as important context, and targeted ‘convective permitting resolution’ modelling, deep learning models and emulators for added insights to inform climate change planning in Australia.