Clinical activity of ipilimumab for metastatic uveal melanoma: a retrospective review of the Dana-Farber Cancer Institute, Massachusetts General Hospital, Memorial Sloan-Kettering Cancer Center, and University Hospital of Lausanne experience.

BACKGROUND: Uveal melanoma exhibits a high incidence of metastases; and, to date, there is no systemic therapy that clearly improves outcomes. The anticytotoxic T-lymphocyte-associated protein 4 (anti-CTLA-4) antibody ipilimumab is a standard of care for metastatic melanoma; however, the clinical activity of CTLA-4 inhibition in patients with metastatic uveal melanoma is poorly defined. METHODS: To assess ipilimumab in this setting, the authors performed a multicenter, retrospective analysis of 4 hospitals in the United States and Europe. Clinical characteristics, toxicities, and radiographic disease burden, as determined by central, blinded radiology review, were evaluated. RESULTS: Thirty-nine patients with uveal melanoma were identified, including 34 patients who received 3 mg/kg ipilimumab and 5 who received 10 mg/kg ipilimumab. Immune-related response criteria and modified World Health Organization criteria were used to assess the response rate (RR) and the combined response plus stable disease (SD) rate after 12 weeks, after 23 weeks, and overall (median follow-up, 50.4 weeks [12.6 months]). At week 12, the RR was 2.6%, and the response plus SD rate was 46.%; at week 23, the RR was 2.6%, and the response plus SD rate was 28.2%. There was 1 complete response and 1 late partial response (at 100 weeks after initial SD) for an immune-related RR of 5.1%. Immune-related adverse events were observed in 28 patients (71.8%) and included 7 (17.9%) grade 3 and 4 events. Immune-related adverse events were more frequent in patients who received 10 mg/kg ipilimumab than in those who received 3 mg/kg ipilimumab. The median overall survival from the first dose of ipilimumab was 9.6 months (95% confidence interval, 6.3-13.4 months; range, 1.6-41.6 months). Performance status, lactate dehydrogenase level, and an absolute lymphocyte count ≥ 1000 cells/μL at week 7 were associated significantly with survival. CONCLUSIONS: In this multicenter, retrospective analysis of 4 hospitals in the United States and Europe of patients with uveal melanoma, durable responses to ipilimumab and manageable toxicity were observed

A method for comparing multiple imputation techniques: A case study on the U.S. national COVID cohort collaborative

Healthcare datasets obtained from Electronic Health Records have proven to be extremely useful for assessing associations between patients’ predictors and outcomes of interest. However, these datasets often suffer from missing values in a high proportion of cases, whose removal may introduce severe bias. Several multiple imputation algorithms have been proposed to attempt to recover the missing information under an assumed missingness mechanism. Each algorithm presents strengths and weaknesses, and there is currently no consensus on which multiple imputation algorithm works best in a given scenario. Furthermore, the selection of each algorithm's parameters and data-related modeling choices are also both crucial and challenging. In this paper we propose a novel framework to numerically evaluate strategies for handling missing data in the context of statistical analysis, with a particular focus on multiple imputation techniques. We demonstrate the feasibility of our approach on a large cohort of type-2 diabetes patients provided by the National COVID Cohort Collaborative (N3C) Enclave, where we explored the influence of various patient characteristics on outcomes related to COVID-19. Our analysis included classic multiple imputation techniques as well as simple complete-case Inverse Probability Weighted models. Extensive experiments show that our approach can effectively highlight the most promising and performant missing-data handling strategy for our case study. Moreover, our methodology allowed a better understanding of the behavior of the different models and of how it changed as we modified their parameters. Our method is general and can be applied to different research fields and on datasets containing heterogeneous types

Modeling Storm Water Runoff and Soil Interflow in a Managed Forest, Upper Coastal Plain of the Southeast US.

The Forest Service-Savannah River is conducting a hectare-scale monitoring and modeling study on forest productivity in a Short Rotation Woody Crop plantation at the Savannah River Site, which is on Upper Coastal Plain of South Carolina. Detailed surveys, i.e., topography, soils, vegetation, and dainage network, of small (2-5 ha) plots have been completed in a 2 square-km watershed draining to Fourmile Creek, a tributary of the Savannah River. We wish to experimentally determine the relative importance of interflow on water yield and water quality at this site. Interflow (shallow subsurface lateral flow) can short-circuit rainfall infiltration, preventing deep seepage and resulting in water and chemical residence times in the watershed much shorter than that if deep seepage were the sole component of infiltration. The soil series at the site (Wagram, Dothan, Fuquay, Ogeechee, and Vaucluse) each have a clay-rich B horizon of decimeter-scale thickness at depths of 1-2 m below surface. As interflow is affected by rainfall intensity and duration and soil properties such as porosity, permeability, and antecedent soil moisture, our calculations made using the Green and Ampt equation show that the intensity and duration of a storm event must be greater than about 3 cm per hour and 2 hours, respectively, in order to initiate interflow for the least permeable soils series (Vaucluse). Tabulated values of soil properties were used in these preliminary calculations. Simulations of the largest rainfall events from 1972-2002 data using the Green and Ampt equation provide an interflow: rainfall ratio of 0 for the permeable Wagram soil series (no interflow) compared to 0.46 for the less permeable Vaucluse soil series. These initial predictions will be compared to storm water hydrographs of interflow collected at the outflow point of each plot and refined using more detailed soil property measurements

Evolutionary dynamics and information hierarchies in biological systems

The study of evolution has entered a revolutionary new era, where quantitative and predictive methods are transforming the traditionally qualitative and retrospective approaches of the past. Genomic sequencing and modern computational techniques are permitting quantitative comparisons between variation in the natural world and predictions rooted in neo-Darwinian theory, revealing the shortcomings of current evolutionary theory, particularly with regard to large-scale phenomena like macroevolution. Current research spanning and uniting diverse fields and exploring the physical and chemical nature of organisms across temporal, spatial, and organizational scales is replacing the model of evolution as a passive filter selecting for random changes at the nucleotide level with a paradigm in which evolution is a dynamic process both constrained and driven by the informational architecture of organisms across scales, from DNA and chromatin regulation to interactions within and between species and the environment

Conceptualising value creation for social change management.

Australian and international governments are increasingly adopting social marketing as a social change management tool to deal with complex social problems. Government decision makers typically need to balance the use of business models and management theories whilst maintaining the integrity of government policy. In taking this approach, decision makers experience management tensions between a social mission to equitably deliver social services and the accountability and affordability of providing quality social and health services to citizens. This is a significant challenge as the nature of the ‘social product’ in government is often more service-oriented than goods-based. In this paper the authors examine value creation in government social marketing services. The contribution of this paper is a value creation process model, which considers the nature of governments to create social good. This is particularly important for governments where consumers still expect value and quality in the service delivered, despite that offering being ‘free’