RESUMEN
Rituximab, anti-CD20 monoclonal antibody, has broad clinical application. The aim of this study is to compare the safety and cost of the original reference rituximab (MabThera) and its biosimilar (Riximyo). This retrospective analysis of 262 patients receiving Riximyo in the Department of Hematology of Wroclaw Medical University in Poland from the period of 1 October 2020 to 21 June 2021 focused on infusion-related reactions (IRRs), which occurred in 4,96% of patients (N = 13). 109 patients (41,6%) had previously been treated with the reference drug and 2 IRRs were reported after switching therapy. During the study period, after biosimilar introduction, the cost of rituximab decreased by 41%. Rixmyo while maintaining similar safety profile is much more cost-effective.
Asunto(s)
Biosimilares Farmacéuticos , Efectos Colaterales y Reacciones Adversas Relacionados con Medicamentos , Enfermedades Hematológicas , Trastornos Linfoproliferativos , Humanos , Rituximab , Biosimilares Farmacéuticos/efectos adversos , Estudios Retrospectivos , Trastornos Linfoproliferativos/diagnóstico , Trastornos Linfoproliferativos/tratamiento farmacológico , Trastornos Linfoproliferativos/etiologíaRESUMEN
BACKGROUND: During the COVID-19 pandemic there has been a strong interest in forecasts of the short-term development of epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland for the period from January through April 2021. METHODS: We evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland. These were issued by 15 different forecasting models, run by independent research teams. Moreover, we study the performance of combined ensemble forecasts. Evaluation of probabilistic forecasts is based on proper scoring rules, along with interval coverage proportions to assess calibration. The presented work is part of a pre-registered evaluation study. RESULTS: We find that many, though not all, models outperform a simple baseline model up to four weeks ahead for the considered targets. Ensemble methods show very good relative performance. The addressed time period is characterized by rather stable non-pharmaceutical interventions in both countries, making short-term predictions more straightforward than in previous periods. However, major trend changes in reported cases, like the rebound in cases due to the rise of the B.1.1.7 (Alpha) variant in March 2021, prove challenging to predict. CONCLUSIONS: Multi-model approaches can help to improve the performance of epidemiological forecasts. However, while death numbers can be predicted with some success based on current case and hospitalization data, predictability of case numbers remains low beyond quite short time horizons. Additional data sources including sequencing and mobility data, which were not extensively used in the present study, may help to improve performance.
We compare forecasts of weekly case and death numbers for COVID-19 in Germany and Poland based on 15 different modelling approaches. These cover the period from January to April 2021 and address numbers of cases and deaths one and two weeks into the future, along with the respective uncertainties. We find that combining different forecasts into one forecast can enable better predictions. However, case numbers over longer periods were challenging to predict. Additional data sources, such as information about different versions of the SARS-CoV-2 virus present in the population, might improve forecasts in the future.