Small bound for birational automorphism groups of algebraic varieties (with an Appendix by Yujiro Kawamata)

We give an effective upper bound of |Bir(X)| for the birational automorphism group of an irregular n-fold (with n = 3) of general type in terms of the volume V = V(X) under an ''albanese smoothness and simplicity'' condition. To be precise, |Bir(X)| < d_3 V^{10}. An optimum linear bound |Bir(X)|-1 < (1/3)(42)^3 V is obtained for those 3-folds with non-maximal albanese dimension. For all n > 2, a bound |Bir(X)| < d_n V^{10} is obtained when alb_X is generically finite, alb(X) is smooth and Alb(X) is simple.Comment: Mathematische Annalen, to appea

Challenges for Optimizing Real-World Evidence in Alzheimer’s Disease: The ROADMAP Project

ROADMAP is a public-private advisory partnership to evaluate the usability of multiple data sources, including real-world evidence, in the decision-making process for new treatments in Alzheimer’s disease, and to advance key concepts in disease and pharmacoeconomic modeling. ROADMAP identified key disease and patient outcomes for stakeholders to make informed funding and treatment decisions, provided advice on data integration methods and standards, and developed conceptual cost-effectiveness and disease models designed in part to assess whether early treatment provides long-term benefit

Ethical and Social Implications of Using Predictive Modeling for Alzheimer's Disease Prevention: A Systematic Literature Review.

BACKGROUND: The therapeutic paradigm in Alzheimer's disease (AD) is shifting from symptoms management toward prevention goals. Secondary prevention requires the identification of individuals without clinical symptoms, yet "at-risk" of developing AD dementia in the future, and thus, the use of predictive modeling. OBJECTIVE: The objective of this study was to review the ethical concerns and social implications generated by this new approach. METHODS: We conducted a systematic literature review in Medline, Embase, PsycInfo, and Scopus, and complemented it with a gray literature search between March and July 2018. Then we analyzed data qualitatively using a thematic analysis technique. RESULTS: We identified thirty-one ethical issues and social concerns corresponding to eight ethical principles: (i) respect for autonomy, (ii) beneficence, (iii) non-maleficence, (iv) equality, justice, and diversity, (v) identity and stigma, (vi) privacy, (vii) accountability, transparency, and professionalism, and (viii) uncertainty avoidance. Much of the literature sees the discovery of disease-modifying treatment as a necessary and sufficient condition to justify AD risk assessment, overlooking future challenges in providing equitable access to it, establishing long-term treatment outcomes and social consequences of this approach, e.g., medicalization. The ethical/social issues associated specifically with predictive models, such as the adequate predictive power and reliability, infrastructural requirements, data privacy, potential for personalized medicine in AD, and limiting access to future AD treatment based on risk stratification, were covered scarcely. CONCLUSION: The ethical discussion needs to advance to reflect recent scientific developments and guide clinical practice now and in the future, so that necessary safeguards are implemented for large-scale AD secondary prevention.</p

Health outcome prioritisation in Alzheimer’s disease: understanding the ethical landscape

Objective: Health outcome prioritisation is the ranking in order of desirability or importance of a set of disease related objectives and their associated cost or risk. We analyse the complex ethical landscape in which this takes place in the most common dementia, Alzheimer’s disease. Background: Dementia has been described as the greatest global health challenge in the 21st century on account of longevity gains increasing its incidence, escalating health and social care pressures. These pressures highlight ethical, social, political challenges about healthcare resource allocation, what health improvements matter to patients, and how they are measured. This study highlights the complexity of the ethical landscape, relating particularly to the balances that need to be struck when allocating resources; when measuring and prioritising outcomes; and when individual preferences are sought. Methods: Narrative review of literature published since 2007, incorporating snowball sampling where necessary. We identified, thematised and discussed key issues of ethical salience. Results: Eight areas of ethical salience for outcome prioritisation emerged: (1) Public health and distributive justice, (2) Scarcity of resources, (3) Heterogeneity and changing circumstances, (4) Knowledge of treatment, (5) Values and circumstances, (6) Conflicting priorities, (7) Communication, autonomy and Caregiver issues, (8) Disclosure of risk. Conclusion: These areas highlight the difficult balance to be struck when allocating resources, when measuring and prioritising outcomes, and when individual preferences are sought. We conclude by reflecting on how tools in social sciences and ethics can help address challenges posed by resource allocation, measuring and prioritising outcomes, and eliciting stakeholder preferences.</p

Challenges for optimizing real-world evidence in Alzheimer’s disease: The ROADMAP Project

ROADMAP is a public-private advisory partnership to evaluate the usability of multiple data sources, including real-world evidence, in the decision-making process for new treatments in Alzheimer's disease, and to advance key concepts in disease and pharmacoeconomic modeling. ROADMAP identified key disease and patient outcomes for stakeholders to make informed funding and treatment decisions, provided advice on data integration methods and standards, and developed conceptual cost-effectiveness and disease models designed in part to assess whether early treatment provides long-term benefit