Short- and long-term effects of imatinib in patients hospitalised for COVID-19 infection: A randomised controlled trial (preprint)

We report the short- and long-term results of the SOLIDARITY Finland on mortality and other patient-important outcomes in patients hospitalised for COVID-19. Between 08/2021 and 03/2023, we randomised 156 patients in 15 hospitals. In the imatinib group, 7.2% of patients had died at 30 days and 13.3% at 1 year and in the standard of care group 4.1% and 8.3% (adjusted HR at 30 days 1.09, 95% CI 0.23-5.07). In a meta-analysis of randomised trials of imatinib versus standard of care (n=732), allocation to imatinib was associated with a mortality risk ratio of 0.73 (95% CI 0.32-1.63). At 1-year, self-reported recovery occurred in 79.0% in imatinib and in 88.3% in standard of care (RR 0.91, 95% CI 0.78-1.06). Of the 21 potential long COVID symptoms, patients often reported moderate or major bother from fatigue (24%), sleeping problems (19%) and memory difficulties (17%). We found no convincing difference between imatinib and standard of care groups in quality of life or symptom outcomes. The evidence raises serious doubts regarding the benefit of imatinib in reducing mortality, improving recovery and preventing potential long COVID symptoms when given to patients hospitalised for COVID-19.

Health, socioeconomic and genetic predictors of COVID-19 vaccination uptake: a nationwide machine-learning study (preprint)

Reduced participation in COVID-19 vaccination programs is a key societal concern. Understanding factors associated with vaccination uptake can help in planning effective immunization programs. We considered 2,890 health, socioeconomic, familial, and demographic factors measured on the entire Finnish population aged 30 to 80 (N=3,192,505) and genome-wide information for a subset of 273,765 individuals. Risk factors were further classified into 12 thematic categories and a machine learning model was trained for each category. The main outcome was uptaking the first COVID-19 vaccination dose by 31.10.2021, which has occurred for 90.3% of the individuals. The strongest predictor category was labor income in 2019 (AUC evaluated in a separate test set = 0.710, 95% CI: 0.708-0.712), while drug purchase history, including 376 drug classes, achieved a similar prediction performance (AUC = 0.706, 95% CI: 0.704-0.708). Higher relative risks of being unvaccinated were observed for some mental health diagnoses (e.g. dissocial personality disorder, OR=1.26, 95% CI : 1.24-1.27 ) and when considering vaccination status of first-degree relatives (OR=1.31, 95% CI:1.31-1.32 for unvaccinated mothers) We derived a prediction model for vaccination uptake by combining all the predictors and achieved good discrimination (AUC = 0.801, 95% CI: 0.799-0.803). The 1% of individuals with the highest risk of not vaccinating according to the model predictions had an average observed vaccination rate of only 18.8%. We identified 8 genetic loci associated with vaccination uptake and derived a polygenic score, which was a weak predictor of vaccination status in an independent subset (AUC=0.612, 95% CI: 0.601-0.623). Genetic effects were replicated in an additional 145,615 individuals from Estonia (genetic correlation=0.80, 95% CI: 0.66-0.95) and, similarly to data from Finland, correlated with mental health and propensity to participate in scientific studies. Individuals at higher genetic risk for severe COVID-19 were less likely to get vaccinated (OR=1.03, 95% CI: 1.02-1.05). Our results, while highlighting the importance of harmonized nationwide information, not limited to health, suggest that individuals at higher risk of suffering the worst consequences of COVID-19 are also those less likely to uptake COVID-19 vaccination. The results can support evidence-informed actions for COVID-19 and other areas of national immunization programs.