Phase 3 trials of ixekizumab in moderate-to-severe plaque psoriasis

BACKGROUND Two phase 3 trials (UNCOVER-2 and UNCOVER-3) showed that at 12 weeks of treatment, ixekizumab, a monoclonal antibody against interleukin-17A, was superior to placebo and etanercept in the treatment of moderate-to-severe psoriasis. We report the 60-week data from the UNCOVER-2 and UNCOVER-3 trials, as well as 12-week and 60-week data from a third phase 3 trial, UNCOVER-1. METHODS We randomly assigned 1296 patients in the UNCOVER-1 trial, 1224 patients in the UNCOVER-2 trial, and 1346 patients in the UNCOVER-3 trial to receive subcutaneous injections of placebo (placebo group), 80 mg of ixekizumab every 2 weeks after a starting dose of 160 mg (2-wk dosing group), or 80 mg of ixekizumab every 4 weeks after a starting dose of 160 mg (4-wk dosing group). Additional cohorts in the UNCOVER-2 and UNCOVER-3 trials were randomly assigned to receive 50 mg of etanercept twice weekly. At week 12 in the UNCOVER-3 trial, the patients entered a long-term extension period during which they received 80 mg of ixekizumab every 4 weeks through week 60; at week 12 in the UNCOVER-1 and UNCOVER-2 trials, the patients who had a response to ixekizumab (defined as a static Physicians Global Assessment [sPGA] score of 0 [clear] or 1 [minimal psoriasis]) were randomly reassigned to receive placebo, 80 mg of ixekizumab every 4 weeks, or 80 mg of ixekizumab every 12 weeks through week 60. Coprimary end points were the percentage of patients who had a score on the sPGA of 0 or 1 and a 75% or greater reduction from baseline in Psoriasis Area and Severity Index (PASI 75) at week 12. RESULTS In the UNCOVER-1 trial, at week 12, the patients had better responses to ixekizumab than to placebo; in the 2-wk dosing group, 81.8% had an sPGA score of 0 or 1 and 89.1% had a PASI 75 response; in the 4-wk dosing group, the respective rates were 76.4% and 82.6%; and in the placebo group, the rates were 3.2% and 3.9% (P<0.001 for all comparisons of ixekizumab with placebo). In the UNCOVER-1 and UNCOVER-2 trials, among the patients who were randomly reassigned at week 12 to receive 80 mg of ixekizumab every 4 weeks, 80 mg of ixekizumab every 12 weeks, or placebo, an sPGA score of 0 or 1 was maintained by 73.8%, 39.0%, and 7.0% of the patients, respectively. Patients in the UNCOVER-3 trial received continuous treatment of ixekizumab from weeks 0 through 60, and at week 60, at least 73% had an sPGA score of 0 or 1 and at least 80% had a PASI 75 response. Adverse events reported during ixekizumab use included neutropenia, candidal infections, and inflammatory bowel disease. CONCLUSIONS In three phase 3 trials involving patients with psoriasis, ixekizumab was effective through 60 weeks of treatment. As with any treatment, the benefits need to be weighed against the risks of adverse events. The efficacy and safety of ixekizumab beyond 60 weeks of treatment are not yet known

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

National Preclinical Sepsis Platform: developing a framework for accelerating innovation in Canadian sepsis research

Abstract Despite decades of preclinical research, no experimentally derived therapies for sepsis have been successfully adopted into routine clinical practice. Factors that contribute to this crisis of translation include poor representation by preclinical models of the complex human condition of sepsis, bias in preclinical studies, as well as limitations of single-laboratory methodology. To overcome some of these shortcomings, multicentre preclinical studies—defined as a research experiment conducted in two or more research laboratories with a common protocol and analysis—are expected to maximize transparency, improve reproducibility, and enhance generalizability. The ultimate objective is to increase the efficiency and efficacy of bench-to-bedside translation for preclinical sepsis research and improve outcomes for patients with life-threatening infection. To this end, we organized the first meeting of the National Preclinical Sepsis Platform (NPSP). This multicentre preclinical  research collaboration of Canadian sepsis researchers and stakeholders was established to study the pathophysiology of sepsis and accelerate movement of promising therapeutics into early phase clinical trials. Integrated knowledge translation and shared decision-making were emphasized to ensure the goals of the platform align with clinical researchers and patient partners. 29 participants from 10 independent labs attended and discussed four main topics: (1) objectives of the platform; (2) animal models of sepsis; (3) multicentre methodology and (4) outcomes for evaluation. A PIRO model (predisposition, insult, response, organ dysfunction) for experimental design was proposed to strengthen linkages with interdisciplinary researchers and key stakeholders. This platform represents an important resource for maximizing translational impact of preclinical sepsis research

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press