Optimal search strategies for identifying sound clinical prediction studies in EMBASE

BACKGROUND: Clinical prediction guides assist clinicians by pointing to specific elements of the patient's clinical presentation that should be considered when forming a diagnosis, prognosis or judgment regarding treatment outcome. The numbers of validated clinical prediction guides are growing in the medical literature, but their retrieval from large biomedical databases remains problematic and this presents a barrier to their uptake in medical practice. We undertook the systematic development of search strategies ("hedges") for retrieval of empirically tested clinical prediction guides from EMBASE. METHODS: An analytic survey was conducted, testing the retrieval performance of search strategies run in EMBASE against the gold standard of hand searching, using a sample of all 27,769 articles identified in 55 journals for the 2000 publishing year. All articles were categorized as original studies, review articles, general papers, or case reports. The original and review articles were then tagged as 'pass' or 'fail' for methodologic rigor in the areas of clinical prediction guides and other clinical topics. Search terms that depicted clinical prediction guides were selected from a pool of index terms and text words gathered in house and through request to clinicians, librarians and professional searchers. A total of 36,232 search strategies composed of single and multiple term phrases were trialed for retrieval of clinical prediction studies. The sensitivity, specificity, precision, and accuracy of search strategies were calculated to identify which were the best. RESULTS: 163 clinical prediction studies were identified, of which 69 (42.3%) passed criteria for scientific merit. A 3-term strategy optimized sensitivity at 91.3% and specificity at 90.2%. Higher sensitivity (97.1%) was reached with a different 3-term strategy, but with a 16% drop in specificity. The best measure of specificity (98.8%) was found in a 2-term strategy, but with a considerable fall in sensitivity to 60.9%. All single term strategies performed less well than 2- and 3-term strategies. CONCLUSION: The retrieval of sound clinical prediction studies from EMBASE is supported by several search strategies

Health Economic and Safety Considerations for Artificial Intelligence Applications in Diabetic Retinopathy Screening

Systematic screening for diabetic retinopathy (DR) has been widely recommended for early detection in patients with diabetes to address preventable vision loss. However, substantial manpower and financial resources are required to deploy opportunistic screening and transition to systematic DR screening programs. The advent of artificial intelligence (AI) technologies may improve access and reduce the financial burden for DR screening while maintaining comparable or enhanced clinical effectiveness. To deploy an AI-based DR screening program in a real-world setting, it is imperative that health economic assessment (HEA) and patient safety analyses are conducted to guide appropriate allocation of resources and design safe, reliable systems. Few studies published to date include these considerations when integrating AI-based solutions into DR screening programs. In this article, we provide an overview of the current state-of-the-art of AI technology (focusing on deep learning systems), followed by an appraisal of existing literature on the applications of AI in ophthalmology. We also discuss practical considerations that drive the development of a successful DR screening program, such as the implications of false-positive or false-negative results and image gradeability. Finally, we examine different plausible methods for HEA and safety analyses that can be used to assess concerns regarding AI-based screening

Predicting Incremental and Future Visual Change in Neovascular Age-Related Macular Degeneration Using Deep Learning

PURPOSE: To evaluate the predictive utility of quantitative imaging biomarkers, acquired automatically from optical coherence tomography (OCT) scans, of cross-sectional and future visual outcomes of patients with neovascular age-related macular degeneration (AMD) starting anti-vascular endothelial growth factor (VEGF) therapy. DESIGN: Retrospective cohort study. PARTICIPANTS: Treatment-naïve, first-treated eyes of patients with neovascular AMD between 2007 and 2017 at Moorfields Eye Hospital (a large, UK single-centre) undergoing anti-VEGF therapy METHODS: Automatic segmentation was carried out by applying a deep learning segmentation algorithm to 137,379 OCT scans from 6467 eyes of 3261 patients with neovascular AMD. After applying selection criteria 926 eyes of 926 patients were taken forward for analysis. MAIN OUTCOME MEASURES: Correlation coefficients (R2) and mean absolute error (MAE) between quantitative OCT (qOCT) parameters and cross-sectional visual-function. The predictive value of these parameters for short-term visual change i.e. incremental visual acuity [VA] resulting from an individual injection, as well as, VA at distant timepoints (up to 12 months post-baseline). RESULTS: VA at distant timepoints could be predicted: R2 0.80 (MAE 5.0 ETDRS letters) and R2 0.7 (MAE 7.2) post-injection 3 and at 12 months post-baseline (both p < 0.001), respectively. Best performing models included both baseline qOCT parameters and treatment-response. Furthermore, we present proof-of-principle evidence that the incremental change in VA from an injection can be predicted: R2 0.14 (MAE 5.6) for injection 2 and R2 0.11 (MAE 5.0) for injection 3 (both p < 0.001). CONCLUSIONS: Automatic segmentation enables rapid acquisition of quantitative and reproducible OCT biomarkers with potential to inform treatment decisions in the care of neovascular AMD. This furthers development of point-of-care decision-aid systems for personalized medicine

Chapter 4: Effective Search Strategies for Systematic Reviews of Medical Tests

This article discusses techniques that are appropriate when developing search strategies for systematic reviews of medical tests. This includes general advice for searching for systematic reviews and issues specific to systematic reviews of medical tests. Diagnostic search filters are currently not sufficiently developed for use when searching for systematic reviews. Instead, authors should construct a highly sensitive search strategy that uses both controlled vocabulary and text words. A comprehensive search should include multiple databases and sources of grey literature. A list of subject-specific databases is included in this article

Smartphone-based remote monitoring of vision in macular disease enables early detection of worsening pathology and need for intravitreal therapy

BACKGROUND/AIMS: To assess the outcomes of home monitoring of distortion caused by macular diseases using a smartphone-based application (app), and to examine them with hospital-based assessments of visual acuity (VA), optical coherence tomography-derived central macular thickness (CMT) and the requirement of intravitreal injection therapy. DESIGN: Observational study with retrospective analysis of data. METHODS: Participants were trained in the correct use of the app (Alleye, Oculocare, Zurich, Switzerland) in person or by using video and telephone consultations. Automated threshold-based alerts were communicated based on a traffic light system. A ‘threshold alarm’ was defined as three consecutive ‘red’ scores, and turned into a ‘persistent alarm’ if present for greater than a 7-day period. Changes of VA and CMT, and the requirement for intravitreal therapy after an alarm were examined. RESULTS: 245 patients performing a total of 11 592 tests (mean 46.9 tests per user) were included and 85 eyes (164 alarms) examined. Mean drop in VA from baseline was −4.23 letters (95% CI: −6.24 to −2.22; p<0.001) and mean increase in CMT was 29.5 µm (95% CI: −0.08 to 59.13; p=0.051). Sixty-six eyes (78.5%) producing alarms either had a drop in VA, increase in CMT or both and 60.0% received an injection. Eyes with persistent alarms had a greater loss of VA, −4.79 letters (95% CI: −6.73 to −2.85; p<0.001) or greater increase in CMT, +87.8 µm (95% CI: 5.2 to 170.4; p=0.038). CONCLUSION: Smartphone-based self-tests for macular disease may serve as reliable indicators for the worsening of pathology and the need for treatment

EMBASE search strategies for identifying methodologically sound diagnostic studies for use by clinicians and researchers

BACKGROUND: Accurate diagnosis by clinicians is the cornerstone of decision making for recommending clinical interventions. The current best evidence from research concerning diagnostic tests changes unpredictably as science advances. Both clinicians and researchers need dependable access to published evidence concerning diagnostic accuracy. Bibliographic databases such as EMBASE provide the most widely available entrée to this literature. The objective of this study was to develop search strategies that optimize the retrieval of methodologically sound diagnostic studies from EMBASE for use by clinicians. METHODS: An analytic survey was conducted, comparing hand searches of 55 journals with retrievals from EMBASE for 4,843 candidate search terms and 6,574 combinations. All articles were rated using purpose and quality indicators, and clinically relevant diagnostic accuracy articles were categorized as 'pass' or 'fail' according to explicit criteria for scientific merit. Candidate search strategies were run in EMBASE, the retrievals being compared with the hand search data. The proposed search strategies were treated as "diagnostic tests" for sound studies and the manual review of the literature was treated as the "gold standard." The sensitivity, specificity, precision and accuracy of the search strategies were calculated. RESULTS: Of the 433 articles about diagnostic tests, 97 (22.4%) met basic criteria for scientific merit. Combinations of search terms reached peak sensitivities of 100% with specificity at 70.4%. Compared with best single terms, best multiple terms increased sensitivity for sound studies by 8.2% (absolute increase), but decreased specificity (absolute decrease 6%) when sensitivity was maximized. When terms were combined to maximize specificity, the single term "specificity.tw." (specificity of 98.2%) outperformed combinations of terms. CONCLUSION: Empirically derived search strategies combining indexing terms and textwords can achieve high sensitivity and specificity for retrieving sound diagnostic studies from EMBASE. These search filters will enhance the searching efforts of clinicians

Sample size determination for bibliographic retrieval studies

<p>Abstract</p> <p>Background</p> <p>Research for developing search strategies to retrieve high-quality clinical journal articles from MEDLINE is expensive and time-consuming. The objective of this study was to determine the minimal number of high-quality articles in a journal subset that would need to be hand-searched to update or create new MEDLINE search strategies for treatment, diagnosis, and prognosis studies.</p> <p>Methods</p> <p>The desired width of the 95% confidence intervals (W) for the lowest sensitivity among existing search strategies was used to calculate the number of high-quality articles needed to reliably update search strategies. New search strategies were derived in journal subsets formed by 2 approaches: random sampling of journals and top journals (having the most high-quality articles). The new strategies were tested in both the original large journal database and in a low-yielding journal (having few high-quality articles) subset.</p> <p>Results</p> <p>For treatment studies, if W was 10% or less for the lowest sensitivity among our existing search strategies, a subset of 15 randomly selected journals or 2 top journals were adequate for updating search strategies, based on each approach having at least 99 high-quality articles. The new strategies derived in 15 randomly selected journals or 2 top journals performed well in the original large journal database. Nevertheless, the new search strategies developed using the random sampling approach performed better than those developed using the top journal approach in a low-yielding journal subset. For studies of diagnosis and prognosis, no journal subset had enough high-quality articles to achieve the expected W (10%).</p> <p>Conclusion</p> <p>The approach of randomly sampling a small subset of journals that includes sufficient high-quality articles is an efficient way to update or create search strategies for high-quality articles on therapy in MEDLINE. The concentrations of diagnosis and prognosis articles are too low for this approach.</p

Cannabinoids for treating neurogenic lower urinary tract dysfunction in patients with multiple sclerosis: a systematic review and meta-analysis

OBJECTIVES: To systematically review all available evidence on efficacy and safety of cannabinoids for treating neurogenic lower urinary tract dysfunction (NLUTD) in patients with multiple sclerosis (MS). PATIENTS AND METHODS: The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Studies were identified by electronic search of Cochrane register, Embase, Medline, Scopus (last search on 11 November 2016). RESULTS: After screening 8469 articles, two randomized controlled trials and one open label study enrolling a total of 426 patients, were included. Cannabinoids relevantly decreased incontinence episodes in all three studies. Pooling data showed mean difference in incontinence episodes per 24 hours to be -0.35 (95% confidence interval -0.46 to -0.24). Mild adverse events were frequent (38-100%), but only two patients (0.7%) reported a serious adverse event. CONCLUSIONS: Preliminary data imply, that cannabinoids might be an effective and safe treatment option for NULTD in patients with MS. However, evidence base is poor and more high-quality, well-designed, adequately powered and sampled studies are urgently needed to reach definitive conclusions. This article is protected by copyright. All rights reserved

High-throughput, quantitative analyses of genetic interactions in E. coli.

Large-scale genetic interaction studies provide the basis for defining gene function and pathway architecture. Recent advances in the ability to generate double mutants en masse in Saccharomyces cerevisiae have dramatically accelerated the acquisition of genetic interaction information and the biological inferences that follow. Here we describe a method based on F factor-driven conjugation, which allows for high-throughput generation of double mutants in Escherichia coli. This method, termed genetic interaction analysis technology for E. coli (GIANT-coli), permits us to systematically generate and array double-mutant cells on solid media in high-density arrays. We show that colony size provides a robust and quantitative output of cellular fitness and that GIANT-coli can recapitulate known synthetic interactions and identify previously unidentified negative (synthetic sickness or lethality) and positive (suppressive or epistatic) relationships. Finally, we describe a complementary strategy for genome-wide suppressor-mutant identification. Together, these methods permit rapid, large-scale genetic interaction studies in E. coli

Phenotypic Detection of Clonotypic B Cells in Multiple Myeloma by Specific Immunoglobulin Ligands Reveals their Rarity in Multiple Myeloma

In multiple myeloma, circulating “clonotypic” B cells, that express the immunoglobulin rearrangement of the malignant plasma cell clone, can be indirectly detected by PCR. Their role as potential “feeder” cells for the malignant plasma cell pool remains controversial. Here we established for the first time an approach that allows direct tracking of such clonotypic cells by labeling with patient-specific immunoglobulin ligands in 15 patients with myeloma. Fifty percent of patients showed evidence of clonotypic B cells in blood or bone marrow by PCR. Epitope-mimicking peptides from random libraries were selected on each patient's individual immunoglobulin and used as ligands to trace cells expressing the idiotypic immunoglobulin on their surface. We established a flow cytometry and immunofluorescence protocol to track clonotypic B cells and validated it in two independent monoclonal B cell systems. Using this method, we found clonotypic B cells in only one out of 15 myeloma patients. In view of the assay's validated sensitivity level of 10−3, this surprising data suggests that the abundance of such cells has been vastly overestimated in the past and that they apparently represent a very rare population in myeloma. Our novel tracing approach may open perspectives to isolate and analyze clonotypic B cells and determine their role in myeloma pathobiology