University of Lausanne

About: University of Lausanne is a education organization based out in Lausanne, Switzerland. It is known for research contribution in the topics: Population & Medicine. The organization has 20508 authors who have published 46458 publications receiving 1996655 citations. The organization is also known as: Université de Lausanne & UNIL.

Use of GRADE for assessment of evidence about prognosis: rating confidence in estimates of event rates in broad categories of patients.

Abstract: Introduction The term prognosis refers to the likelihood of future health outcomes in people with a given disease or health condition or with particular characteristics such as age, sex, or genetic profile. Patients and healthcare providers may be interested in prognosis for several reasons, so prognostic studies may have a variety of purposes,1–4 including establishing typical prognosis in a broad population, establishing the effect of patients’ characteristics on prognosis, and developing a prognostic model (often referred to as a clinical prediction rule) (Table 1). Considerations in determining the trustworthiness of estimates of prognosis arising from these types of studies differ. This article covers studies answering questions about the prognosis of a typical patient from a broadly defined population; we will consider prognostic studies assessing risk factors and clinical prediction guides in subsequent papers. Knowing the likely course of their disease may help patients to come to terms with, and plan for, the future. Knowledge of the risk of adverse outcomes or the likelihood of spontaneous resolution of symptoms is critical in predicting the likely effect of treatment and planning diagnostic investigations.5 If the probability of facing an adverse outcome is very low or the spontaneous remission of the disease is high (“good prognosis”), the possible absolute benefits of treatment will inevitably be low and serious adverse effects related to treatment or invasive diagnostic tests, even if rare, will loom large in any decision. If instead the probability of an adverse outcome is high (“bad prognosis”), the impact of new diagnostic information or of effective treatment may be large and patients may be ready to accept higher risks of diagnostic investigation and treatment related adverse effects. Inquiry into the credibility or trustworthiness of prognostic estimates has, to date, largely focused on individual studies of prognosis. Systematic reviews of the highest quality evidence including all the prognostic studies assessing a particular clinical situation are, however, gaining increasing attention, including the Cochrane Collaboration’s work (in progress) to define a template for reviews of prognostic studies (http://prognosismethods.cochrane.org/scope-ourwork). Trustworthy systematic reviews will not only ensure comprehensive collection, summarization, and critique of the primary studies but will also conduct optimal analyses. Matters that warrant consideration in such analyses include the method used to pool rates and whether analyses account for all the relevant covariates; the literature provides guidance on both questions.6 7 In this article, we consider how to establish degree of confidence in estimates from such bodies of evidence. The guidance in this article is directed primarily at researchers conducting systematic reviews of prognostic studies. It will also be useful to anyone interested in prognostic estimates and their associated confidence (including guideline developers) when evaluating a body of evidence (for example, a guideline panel using baseline risk estimates to estimate the absolute effect of Summary poIntS

Inflammasome Components NALP 1 and 3 Show Distinct but Separate Expression Profiles in Human Tissues Suggesting a Site-specific Role in the Inflammatory Response:

Abstract: Several autoinflammatory disorders such as Muckle-Wells syndrome are characterized by mutations in the NALP3/cryopyrin gene. NALP3 and NALP1 proteins can assemble to inflammasomes that activate caspase-1, resulting in the processing of pro-inflammatory cytokines IL-1beta and IL-18. The present study was designed to determine which cells and tissues express NALP1 and NALP3. Monoclonal antibodies were developed and their use revealed distinct distribution profiles of NALP1 and NALP3. Granulocytes, monocytes (very weakly), dendritic cells, and B and T cells all express NALP1 and NALP3. Highest levels of NALP1 are found in T cells and Langerhans cells. Furthermore, NALP1 is present in glandular epithelial structures such as stomach, gut, lung, and, surprisingly, in neurons and testis. In contrast to NALP1, NALP3 shows a more restricted tissue distribution with expression mainly in non-keratinizing epithelia in the oropharynx, esophagus, and ectocervix. Moreover, NALP3 expression is found in the urothelial layer in the bladder. Likewise, a difference in subcellular distribution between NALP1 and NALP3 is observed because NALP1 is localized mainly in the nucleus, whereas NALP3 is predominantly cytoplasmic. We propose that the presence of NALP3 in epithelial cells lining the oral and genital tracts allows the rapid sensing of invading pathogens, thereby triggering an innate immune response.

Thirty new loci for age at menarche identified by a meta-analysis of genome-wide association studies

Abstract: To identify loci for age at menarche, we performed a meta-analysis of 32 genome-wide association studies in 87,802 women of European descent, with replication in up to 14,731 women. In addition to the known loci at LIN28B (P = 5.4 × 10⁻⁶⁰) and 9q31.2 (P = 2.2 × 10⁻³³), we identified 30 new menarche loci (all P < 5 × 10⁻⁸) and found suggestive evidence for a further 10 loci (P < 1.9 × 10⁻⁶). The new loci included four previously associated with body mass index (in or near FTO, SEC16B, TRA2B and TMEM18), three in or near other genes implicated in energy homeostasis (BSX, CRTC1 and MCHR2) and three in or near genes implicated in hormonal regulation (INHBA, PCSK2 and RXRG). Ingenuity and gene-set enrichment pathway analyses identified coenzyme A and fatty acid biosynthesis as biological processes related to menarche timing.