The European Hematology Association Roadmap for European Hematology Research: a consensus document

Abstract The European Hematology Association (EHA) Roadmap for European Hematology Research highlights major achievements in diagnosis and treatment of blood disorders and identifies the greatest unmet clinical and scientific needs in those areas to enable better funded, more focused European hematology research. Initiated by the EHA, around 300 experts contributed to the consensus document, which will help European policy makers, research funders, research organizations, researchers, and patient groups make better informed decisions on hematology research. It also aims to raise public awareness of the burden of blood disorders on European society, which purely in economic terms is estimated at Euro 23 billion per year, a level of cost that is not matched in current European hematology research funding. In recent decades, hematology research has improved our fundamental understanding of the biology of blood disorders, and has improved diagnostics and treatments, sometimes in revolutionary ways. This progress highlights the potential of focused basic research programs such as this EHA Roadmap. The EHA Roadmap identifies nine sections in hematology: normal hematopoiesis, malignant lymphoid and myeloid diseases, anemias and related diseases, platelet disorders, blood coagulation and hemostatic disorders, transfusion medicine, infections in hematology, and hematopoietic stem cell transplantation. These sections span 60 smaller groups of diseases or disorders. The EHA Roadmap identifies priorities and needs across the field of hematology, including those to develop targeted therapies based on genomic profiling and chemical biology, to eradicate minimal residual malignant disease, and to develop cellular immunotherapies, combination treatments, gene therapies, hematopoietic stem cell treatments, and treatments that are better tolerated by elderly patients. Received December 15, 2015. Accepted January 27, 2016. Copyright © 2016, Ferrata Storti Foundation

The "Profiles" document: a modern revision of the objectives of undergraduate medical studies in Switzerland

The Joint Commission of the Swiss Medical Schools (SMIFK/CIMS) decided in 2000 to establish a Swiss Catalogue of Learning Objectives (SCLO) for undergraduate medical training, which was adapted from a similar Dutch blueprint. A second version of the SCLO was developed and launched in 2008. The catalogue is a prerequisite for the accreditation of the curricula of the six Swiss medical faculties and defines the contents of the Federal Licensing Examination (FLE). Given the evolution of the field of medicine and of medical education, the SMIFK/CIMS has decided to embark on a total revision of the SCLO. This article presents the proposed structure and content of Profiles, a new document which, in the future, will direct the format of undergraduate studies and of the FLE. Profiles stands for the Principal Relevant Objectives for Integrative Learning and Education in Switzerland. It is currently being developed by a group of experts from the six Swiss faculties as well as representatives of other institutions involved in these developments. The foundations of Profiles are grounded in the evolution of medical practice and of public health and are based on up-to-date teaching concepts, such as EPAs (entrustable professional activities). An introduction will cover the concepts and a tutorial will be displayed. Three main chapters will provide a description of the seven 2015 CanMEDS roles, a list of core EPAs and a series of ≈250 situations embracing the most frequent and current conditions affecting health. As Profiles is still a work in progress, it is hoped that this paper will attract the interest of all individuals involved in the training of medical students.

From regression estimates to document tables: output formatting using -estout-

Postestimation processing and formatting of regression estimates for input into document tables are tasks that many of us have to do. However, processing results by hand can be laborious, and is vulnerable to error. There are therefore many benefits to automation of these tasks while at the same time retaining user flexibility in terms of output format. The estout package meets these needs. estout assembles a table of coefficients, "significance stars", summary statistics, standard errors, t/z statistics, p-values, confidence intervals, and other statistics calculated for up to twenty models previously fitted and stored by estimates store. It then writes the table to the Stata log and/or to a text file. The estimates are formatted optionally in several styles: html, LaTeX, or tab-delimited (for input into MS Excel or Word). There are a large number of options regarding which output is formatted and how. This talk will take users through a range of examples, from relatively basic simple applications to complex ones.