Mild to moderate renal failure is a frequent complication during treatment with TDF although severe renal impairment is scarce. Risk factors include age, duration of treatment with TDF, elevated baseline creatinine levels, and treatment with protease inhibitor boosted with ritonavir combinations.

Bayesian reasoning, survival analysis and multi-state models are used to assess survival times for Stage IV non-small-cell lung cancer patients and the evolution of the disease over time. Bayesian estimation is done using minimum informative priors for the Weibull regression survival model, leading to an automatic inferential procedure. Markov chain Monte Carlo methods have been used for approximating posterior distributions and the Bayesian information criterion has been considered for covariate selection. In particular, the posterior distribution of the transition probabilities, resulting from the multi-state model, constitutes a very interesting tool which could be useful to help oncologists and patients make efficient and effective decisions.

Monoclonal antibodies targeting the calcitonin gene-related peptide have been introduced into the therapeutic arsenal of migraine prophylaxis. Clinical trials report similar efficacy between them, and there is no evidence of switching to another one after failure. We aim to describe our experience in switching from erenumab to galcanezumab after therapeutic failure. We retrospectively reviewed 30 migraine patients who received monoclonal antibodies, with 15 of them switched after failure to achieve reduction in migraine days per month ≥30%. A ≥30% reduction in migraine days per month compared to baseline was observed in 8/15 (4/15 ≥ 50%) patients after switch. Some nonresponsive patients may benefit from switching between monoclonal antibodies with different therapeutic targets.

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