Open Letter from Short Course Coordinator

Excited anticipation describes my feelings as the Iowa Science Teacher\u27s Short Course has taken shape. Each year I\u27ve felt we hit a peak in imparting new knowledge and interests in so short a time, and our Short Course this March will certainly be no exception to that

Limiting nutrients for bean production on contrasting soil types of Lake Victoria Crescent of Uganda

Common bean (Phaseolus vulgaris L.) is one of the most important grain legumes in East Africa, but its yield has remained below the genetic potential. Declining soil fertility is among the primary constraints to bean production in most East African bean producing regions. Often existing recommendations are generic and inept to guide farm level decision making on nutrient replenishment. A greenhouse nutrient omission study was conducted to determine the limiting nutrients in three soils of Masaka District, commonly cropped to beans: “Liddugavu” a Phaeozem, “Limyufumyufu” a Cambisol and “Luyinjayinga” an Umbrisol soil. Nine treatments; (i) complete nutrient treatment, (ii) N omitted, (iii) P omitted, (iv) K omitted, (v) Mg omitted, (vi) S omitted, (vii) Ca omitted, (viii) Micronutrients omitted and (ix) control without nutrients. Each treatment was randomly assigned to the three soils and replicated three times using a completely randomised design. Nitrogen, phosphorus and potassium were limiting nutrients for bean production in Umbrisol (Luyinjayinja) while in Cambisol (‘Limyufumyufu), common bean production was most limited by soil acidity. The performance varied with soil types, with beans grown on the Phaeozem registering greater leaf number and growth, confirming both scientist’s and local farmer’s knowledge that this soil has greater potential than the other two soils

Phase I/II Clinical Trial-Based Early Economic Evaluation of Acalabrutinib for Relapsed Chronic Lymphocytic Leukaemia

Objectives: The objective of this study was to construct an early economic evaluation for acalabrutinib for relapsed chronic lymphocytic leukaemia (CLL) to assist early reimbursement decision making. Scenarios were assessed to find the relative impact of critical parameters on incremental costs and quality-adjusted life-years (QALYs). Methods: A partitioned survival model was constructed comparing acalabrutinib and ibrutinib from a UK national health service perspective. This model included states for progression-free survival (PFS), post-progression survival (PPS) and death. PFS and overall survival (OS) were parametrically extrapolated from ibrutinib publications and a preliminary hazard ratio based on phase I/II data was applied for acalabrutinib. Deterministic and probabilistic sensitivity analyses were performed, and 1296 scenarios were assessed. Results: The base-case inc

The Application and Implications of Novel Deterministic Sensitivity Analysis Methods

Deterministic sensitivity analyses (DSA) remain important to interpret the effect of uncertainties in individual parameters on results of cost-effectiveness analyses. Classic DSA methodologies may lead to wrong conclusions due to a lack of or misleading information regarding marginal effects, non-linearity, likelihood and correlations. In addition, tornado diagrams are misleading in some situations. Recent advances in DSA methods have the potential to provide decision makers with more reliable information regarding the effects of uncertainties in individual parameters. This practical application discusses advances to classic DSA methods and their implications. Three methods are discussed: stepwise DSA, distributional DSA and probabilistic DSA. For each method, the technical specifications, options for presenting results, and its implications for decision making are discussed. Options for visualizing DSA results in incremental cost-effectiveness ratios and in incremental net benefits are presented. The use of stepwise DSA increases interpretability of marginal effects and non-linearities in the model, which is especially relevant when arbitrary ranges are implemented. Using the probability distribution of each parameter in distributional DSA provides insight on the likelihood of model outcomes while probabilistic DSA also includes the effects of correlations between parameters. Probabilistic DSA, preferably expressed in incremental net benefit, is the most appropriate method for providing insight on the effect of uncertainty in individual parameters on the estimate of cost effectiveness. However, the opportunities provided by probabilistic DSA may not always be needed for decision making. Other DSA methods, in particular distributional DSA, can sometimes be sufficient depending on model features. Decision makers must determine to which extent they will accept and implement these new and improved DSA methodologies and adjust guidelines accordingly

Assessing the cost of global biodiversity and conservation knowledge

Knowledge products comprise assessments of authoritative information supported by stan-dards, governance, quality control, data, tools, and capacity building mechanisms. Considerable resources are dedicated to developing and maintaining knowledge productsfor biodiversity conservation, and they are widely used to inform policy and advise decisionmakers and practitioners. However, the financial cost of delivering this information is largelyundocumented. We evaluated the costs and funding sources for developing and maintain-ing four global biodiversity and conservation knowledge products: The IUCN Red List ofThreatened Species, the IUCN Red List of Ecosystems, Protected Planet, and the WorldDatabase of Key Biodiversity Areas. These are secondary data sets, built on primary datacollected by extensive networks of expert contributors worldwide. We estimate that US$160million (range: US$116–204 million), plus 293 person-years of volunteer time (range: 278–308 person-years) valued at US$14 million (range US$12–16 million), were invested inthese four knowledge products between 1979 and 2013. More than half of this financingwas provided through philanthropy, and nearly three-quarters was spent on personnelcosts. The estimated annual cost of maintaining data and platforms for three of these knowl-edge products (excluding the IUCN Red List of Ecosystems for which annual costs were notpossible to estimate for 2013) is US$6.5 million in total (range: US$6.2–6.7 million). We esti-mated that an additional US$114 million will be needed to reach pre-defined baselines ofdata coverage for all the four knowledge products, and that once achieved, annual mainte-nance costs will be approximately US$12 million. These costs are much lower than those tomaintain many other, similarly important, global knowledge products. Ensuring that biodi-versity and conservation knowledge products are sufficiently up to date, comprehensiveand accurate is fundamental to inform decision-making for biodiversity conservation andsustainable development. Thus, the development and implementation of plans for sustain-able long-term financing for them is critical