RESUMEN
Objectives: The persistence in therapy of rheumatoid arthritis drugs and particularly bDMARD is a limiting factor for their long-term use. The randomized controlled trials (RCTs) may not reflect real-world contexts due to strict inclusion and exclusion criteria. Baricitinib, which targets both JAK1 and JAK2, has been used in Italy for several years. The aim of this multi-center study is to assess the real world persistence on therapy of baricitinib in RA patients and to identify predictive factors of baricitinib's survival rate. Methods: This is a retrospective, multicentric, Italian, longitudinal study. All patients were enrolled according to the following criteria: a) age ≥ 18 years old; b) diagnosed with RA according 2010 ACR/EULAR classification criteria; c) treated with baricitinib. In order to describe baricitinib clinical efficacy, the survival rate was evaluated by The Kaplan-Meier curve. Then, predictive factors of drug retention rate were assessed by performing the Cox analysis, identifying which risk factors influenced treatment persistence. Results: Overall, we included 478 patients treated with baricitinib. Among them, 380 (79.5%) were females. Baricitinib's survival rate was 94.6% at 6 months, 87.9% at 12 months, 81.7% at 24 months and 53.4% at 48 months. The Cox analysis regression showed that a higher bDMARDs/tsDMARD line of therapy seems to be a negative prognostic factor for the drug retention rate (HR 1.26 CI 95% 1.07-1.49, p = 0.006. Conclusion: Real-life study confirms baricitinib effectiveness up to 4 years, but previous treatment with bDMARDs was a negative prognostic factor for its survival rate.
RESUMEN
COVID-19 pandemic is a global emergency caused by SARS-CoV-2 infection. Without efficacious drugs or vaccines, mass quarantine has been the main strategy adopted by governments to contain the virus spread. This has led to a significant reduction in the number of infected people and deaths and to a diminished pressure over the health care system. However, an economic depression is following due to the forced absence of worker from their job and to the closure of many productive activities. For these reasons, governments are lessening progressively the mass quarantine measures to avoid an economic catastrophe. Nevertheless, the reopening of firms and commercial activities might lead to a resurgence of infection. In the worst-case scenario, this might impose the return to strict lockdown measures. Epidemiological models are therefore necessary to forecast possible new infection outbreaks and to inform government to promptly adopt new containment measures. In this context, we tested here if technical analysis methods commonly used in the financial market might provide early signal of change in the direction of SARS-Cov-2 infection trend in Italy, a country which has been strongly hit by the pandemic. We conclude that technical analysis indicators can be usefully adopted to this aim.