RESUMO
Purpose: Insomnia in cancer patients is a common symptom contributing to poor quality of life and poor functioning. Sleep disturbances have been associated with inflammatory activity, and systemic cancer therapies chemotherapy, hormonal therapy, and immunotherapy may cause insomnia. We have carried out a meta-analysis to estimate the occurrence of insomnia in patients with solid cancer treated with immunotherapy using checkpoint inhibitors (CPI). Methods: PubMed and ClinicalTrials.gov were searched for phase 3 studies in solid tumours where treatment included a checkpoint inhibitor in the experimental arm. Data on the incidence of insomnia were acquired from the adverse events tables available from clinicaltrials.gov and/or from the full texts. Random effect logistic model was used to compare pooled data. Heterogeneity between studies was assessed using Cochrane Q statistics and I2 statistics. Results: A total of 54 studies (including six three-arm studies) involving 37,352 patients were included in the analysis. Insomnia was reported in 8.3% of subjects (95% confidence interval [CI] 8.0%-8.7%) treated with immunotherapy. Insomnia was significantly more common in patients receiving immunotherapy compared to those enrolled in study arms with inactive treatment (odds ratio [OR] 1.49, 95% CI 1.13-1.96). The odds for insomnia were similar between the arms for studies comparing CPI versus chemotherapy and CPI versus non-immunologic targeted therapies (OR 1.07, 95% CI 0.94-1.22 and OR 1.40, 95% CI 0.90-2.18, respectively). The OR for insomnia was higher for cytotoxic T-lymphocyte antigen 4 (CTLA-4) receptor inhibitors compared to the inhibitors of programmed death-1 (PD-1) receptor (OR 1.36, 95% CI 1.06 - 1.74). Conclusion: Cancer immunotherapy using CPI is associated with insomnia but the odds of developing the symptom are not greater with immunotherapy than with other systemic modalities including chemotherapy and non-immunologic targeted therapies.
RESUMO
We collected a multi-centric retrospective dataset of patients (N = 213) who were admitted to ten hospitals in Czech Republic and tested positive for SARS-CoV-2 during the early phases of the pandemic in March-October 2020. The dataset contains baseline patient characteristics, breathing support required, pharmacological treatment received and multiple markers on daily resolution. Patients in the dataset were treated with hydroxychloroquine (N = 108), azithromycin (N = 72), favipiravir (N = 9), convalescent plasma (N = 7), dexamethasone (N = 4) and remdesivir (N = 3), often in combination. To explore association between treatments and patient outcomes we performed multiverse analysis, observing how the conclusions change between defensible choices of statistical model, predictors included in the model and other analytical degrees of freedom. Weak evidence to constrain the potential efficacy of azithromycin and favipiravir can be extracted from the data. Additionally, we performed external validation of several proposed prognostic models for Covid-19 severity showing that they mostly perform unsatisfactorily on our dataset.