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

Expert recommendation from the Swiss Amyloidosis Network (SAN) for systemic AL-amyloidosis

Systemic amyloidosis is a heterogeneous group of diseases associated with protein misfolding into insoluble beta-sheet rich structures that deposit extracellularly in different organs, eventually compromising their function. There are more than 30 different proteins, known to be amyloidogenic with “light chain” (AL)-amyloidosis being the most common type, followed by transthyretin (ATTR)-, and amyloid protein A (AA)-amyloidosis. Systemic amyloidosis is a rare disease with an incidence of around 10 patients in 1 million inhabitants. Recently several new therapeutic options have been developed for subgroups of amyloidosis patients, and the introduction of novel therapies for plasma cell myeloma has led to an increase in the therapeutic armamentarium for plasma cell disorders, including AL amyloidosis. Among them, proteasome inhibitors, immunomodulatory agents (-imids), and monoclonal antibodies have been successfully introduced into clinical practice. Still, high-quality data from randomised controlled trials regarding the benefit of these cost-intensive drugs in AL amyloidosis are widely lacking, and due to the rarity of the disease many physicians will not gain routine experience in the management of these frail patients. The diagnosis of AL amyloidosis relies on a close collaboration between clinicians, pathologists, imaging experts, and sometimes geneticists. Diagnosis and treatment options in this complex disorder should be discussed in dedicated multidisciplinary boards. In January 2020, the first meeting of the Swiss Amyloidosis Network took place in Zurich, Switzerland. One aim of this meeting was to establish a consensus guideline regarding the diagnostic work-up and the treatment recommendations for systemic amyloidosis tailored to the Swiss health care system. Forty-five participants from different fields in medicine discussed many aspects of amyloidosis. These are the Swiss Amyloidosis Network recommendations which focus on diagnostic work-up and treatment of AL-amyloidosis