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

A case of late isolated ovarian relapse of acute lymphoblastic leukemia after an allogeneic stem cell transplant.

We report the case of a 30-year-old Caucasian female who had an isolated ovarian relapse 13 years after a diagnosis of acute lymphoblastic leukemia (ALL) and 8 years after an allogeneic peripheral blood hematopoietic stem cell transplant (HSCT)

Research Topic: Measurable Residual Disease in Hematologic Malignancies. Can digital droplet PCR improve measurable residual disease monitoring in chronic lymphoid malignancies?

Minimal/measurable residual disease (MRD) monitoring is progressively changing the management of hematologic malignancies. The possibility of detecting the persistence/reappearance of disease in patients in apparent clinical remission offers a refined risk stratification and a treatment decision making tool. Several molecular techniques are employed to monitor MRD, from conventional real-time quantitative polymerase chain reaction (RQ-PCR) to next generation sequencing and digital droplet PCR (ddPCR), in different tissues or compartments through the detection of fusion genes, immunoglobulin and T-cell receptor gene rearrangements or disease-specific mutations. RQ-PCR is still the gold standard for MRD analysis despite some limitations. ddPCR, considered the third-generation PCR, yields a direct, absolute, and accurate detection and quantification of low-abundance nucleic acids. In the setting of MRD monitoring it carries the major advantage of not requiring a reference standard curve built with the diagnostic sample dilution and of allowing to reduce the number of samples below the quantitative range. At present, the broad use of ddPCR to monitor MRD in the clinical practice is limited by the lack of international guidelines. Its application within clinical trials is nonetheless progressively growing both in acute lymphoblastic leukemia as well as in chronic lymphocytic leukemia and non-Hodgkin lymphomas. The aim of this review is to summarize the accumulating data on the use of ddPCR for MRD monitoring in chronic lymphoid malignancies and to highlight how this new technique is likely to enter into the clinical practice

Comparison of two real-time quantitative polymerase chain reaction strategies for minimal residual disease evaluation in lymphoproliferative disorders: Correlation between immunoglobulin gene mutation load and real-time quantitative polymerase chain reaction performance

We compared two strategies for minimal residual disease evaluation of B-cell lymphoproliferative disorders characterized by a variable immunoglobulin heavy chain (IGH) genes mutation load. Twenty-five samples from chronic lymphocytic leukaemia (n=18) or mantle cell lymphoma (n=7) patients were analyzed. Based on IGH variable region genes, 22/25 samples carried >2% mutations, 20/25>5%. In the IGH joining region genes, 23/25 samples carried >2% mutations, 18/25>5%. Real-time quantitative polymerase chain reaction was performed on IGH genes using two strategies: method A utilizes two patient-specific primers, whereas method B employs one patient-specific and one germline primer, with different positions on the variable, diversity and joining regions. Twenty-three samples (92%) resulted evaluable using method A, only six (24%) by method B. Method B poor performance was specifically evident among mutated IGH variable/joining region cases, although no specific mutation load above, which the real-time quantitative polymerase chain reaction failed was found. The molecular strategies for minimal residual disease evaluation should be adapted to the B-cell receptor features of the disease investigated. © 2013 John Wiley & Sons, Ltd