Hepatocellular carcinoma and cancer-related mortality after kidney transplantation with rituximab treatment

Purpose@#There are increased therapeutic usages of rituximab in kidney transplantation (KT). However, few studies have evaluated the effect of rituximab on cancer development following KT. This study aimed to evaluate the effect of rituximab on the cancer occurrence and mortality rate according to each type of cancer. @*Methods@#Five thousand consecutive recipients who underwent KT at our center were divided into era1 (1990–2007) and era2-rit– (2008–2018), and era2-rit+ (2008–2018) groups. The era2-rit+ group included patients who received single-dose rituximab (200–500 mg) as a desensitization treatment 1–2 weeks before KT. @*Results@#The 5-year incidence rates of malignant tumors after KT were 3.1%, 4.3%, and 3.5% in the era1, era2-rit–, and era2-rit+ group, respectively. The overall incidence rate of cancer after transplantation among the 3 study groups showed no significant difference (P = 0.340). The overall cancer-related mortality rate was 17.1% (53 of 310). Hepatocellular carcinoma (HCC) had the highest mortality rate (61.5%) and relative risk of cancer-related death (hazard ratio, 8.29; 95% confidence interval, 2.40–28.69; P = 0.001). However, we found no significant association between rituximab and the incidence of any malignancy. @*Conclusion@#Our results suggest that single-dose rituximab for desensitization may not increase the risk of malignant disease or cancer-related mortality in KT recipients. HCC was associated with the highest risk of cancer-related mortality in an endemic area of HBV infection.

High resolution proximity statistics as early warning for US universities reopening during COVID-19

Reopening of colleges and universities for the Fall semester of 2020 across the United States has caused significant COVID-19 case spikes, requiring reactive responses such as temporary closures and switching to online learning. Until sufficient levels of immunity are reached through vaccination, Institutions of Higher Education will need to balance academic operations with COVID-19 spread risk within and outside the student community. In this work, we study the impact of proximity statistics obtained from high resolution mobility traces in predicting case rate surges in university counties. We focus on 50 land-grant university counties (LGUCs) across the country and show high correlation (PCC > 0.6) between proximity statistics and COVID-19 case rates for several LGUCs during the period around Fall 2020 reopenings. These observations provide a lead time of up to [~]3 weeks in preparing resources and planning containment efforts. We also show how features such as total population, population affiliated with university, median income and case rate intensity could explain some of the observed high correlation. We believe these easily explainable mobility metrics along with other disease surveillance indicators can help universities be better prepared for the Spring 2021 semester.