Purpose Interim positron emission tomography (PET) using the tracer, [F]fluorodeoxyglucose, may predict outcomes in patients with aggressive non-Hodgkin lymphomas. We assessed whether PET can guide therapy in patients who are treated with cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP). Patients and Methods Newly diagnosed patients received two cycles of CHOP-plus rituximab (R-CHOP) in CD20-positive lymphomas-followed by a PET scan that was evaluated using the ΔSUV method. PET-positive patients were randomly assigned to receive six additional cycles of R-CHOP or six blocks of an intensive Burkitt's lymphoma protocol. PET-negative patients with CD20-positive lymphomas were randomly assigned or allocated to receive four additional cycles of R-CHOP or the same treatment with two additional doses rituximab. The primary end point was event-free survival time as assessed by log-rank test. Results Interim PET was positive in 108 (12.5%) and negative in 754 (87.5%) of 862 patients treated, with statistically significant differences in event-free survival and overall survival. Among PET-positive patients, 52 were randomly assigned to R-CHOP and 56 to the Burkitt protocol, with 2-year event-free survival rates of 42.0% (95% CI, 28.2% to 55.2%) and 31.6% (95% CI, 19.3% to 44.6%), respectively (hazard ratio, 1.501 [95% CI, 0.896 to 2.514]; P = .1229). The Burkitt protocol produced significantly more toxicity. Of 754 PET-negative patients, 255 underwent random assignment (129 to R-CHOP and 126 to R-CHOP with additional rituximab). Event-free survival rates were 76.4% (95% CI, 68.0% to 82.8%) and 73.5% (95% CI, 64.8% to 80.4%), respectively (hazard ratio, 1.048 [95% CI, 0.684 to 1.606]; P = .8305). Outcome prediction by PET was independent of the International Prognostic Index. Results in diffuse large B-cell lymphoma were similar to those in the total group. Conclusion Interim PET predicted survival in patients with aggressive lymphomas treated with R-CHOP. PET-based treatment intensification did not improve outcome.
Objectives: The first wave of the SARS-CoV-2 pandemic in Germany lasted from week 10 to 23 in 2020. The aim is to provide estimates of excess mortality in Germany during this time. Methods: We analyzed age-specific numbers of deaths per week from 2016 to week 26 in 2020. We used weekly mean numbers of deaths of 2016-2019 to estimate expected weekly numbers for 2020. We estimated standardized mortality ratios (SMR) and 95% confidence intervals. Results: During the first wave observed numbers of deaths were higher than expected for age groups 60-69, 80-89, and 90 +. The age group 70-79 years did not show excess mortality. The net excess number of deaths for weeks 10-23 was + 8,071. The overall SMR was 1 •03 (95%CI 1 •03-1 •04). The largest increase occurred among people aged 80-89 and 90 + (SMR = 1 •08 and SMR = 1 •09). A sensitivity analysis that accounts for demographic changes revealed an overall SMR of 0 •98 (95%CI 0 •98-0 •99) and a deficit of 4,926 deaths for week 10-23, 2020. Conclusions: The excess mortality existed for two months. The favorable course of the first wave may be explained by a younger age at infection at the beginning of the pandemic, lower contact rates, and a more efficient pandemic management.
We classify the almost perfect nonlinear (APN) functions in dimensions 4 and 5 up to affine and CCZ equivalence using backtrack programming and give a partial model for the complexity of such a search. In particular, we demonstrate that up to dimension 5 any APN function is CCZ equivalent to a power function, while it is well known that in dimensions 4 and 5 there exist APN functions which are not extended affine (EA) equivalent to any power function. We further calculate the total number of APN functions up to dimension 5 and present a new CCZ equivalence class of APN functions in dimension 6.
Introduction Excess mortality is a suitable indicator of health consequences of COVID-19 because death from any cause is clearly defined contrary to death from Covid-19. We compared the overall mortality in 2020 with the overall mortality in 2016 to 2019 in Germany, Sweden and Spain. Contrary to other studies, we also took the demographic development between 2016 and 2020 and increasing life expectancy into account. Methods Using death and population figures from the EUROSTAT database, we estimated weekly and cumulative Standardized Mortality Ratios (SMR) with 95% confidence intervals (CI) for the year 2020. We applied two approaches to calculate weekly numbers of death expected in 2020: first, we used mean weekly mortality rates from 2016 to 2019 as expected mortality rates for 2020, and, second, to consider increasing life expectancy, we calculated expected mortality rates for 2020 by extrapolation from mortality rates from 2016 to 2019. Results In the first approach, the cumulative SMRs show that in Germany and Sweden there was no or little excess mortality in 2020 (SMR = 0.976 (95% CI: 0.974–0.978), and 1.030 (1.023–1.036), respectively), while in Spain the excess mortality was 14.8% (1.148 (1.144–1.151)). In the second approach, the corresponding SMRs for Germany and Sweden increased to 1.009 (1.007–1.011) and 1.083 (1.076–1.090), respectively, whereas results for Spain were virtually unchanged. Conclusion In 2020, there was barely any excess mortality in Germany for both approaches. In Sweden, excess mortality was 3% without, and 8% with consideration of increasing life expectancy.
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