Interventions for unexplained subfertility : A systematic review and network meta-analysis

Peer reviewedPublisher PD

Setting clinical performance specifications to develop and evaluate biomarkers for clinical use

Background: Biomarker discovery studies often claim ‘promising’ findings, motivating further studies and marketing as medical tests. Unfortunately, the patient benefits promised are often inadequately explained to guide further evaluation, and few biomarkers have translated to improved patient care. We present a practical guide for setting minimum clinical performance specifications to strengthen clinical performance study design and interpretation. Methods: We developed a step-by-step approach using test evaluation and decision-analytic frameworks and present with illustrative examples. Results: We define clinical performance specifications as a set of criteria that quantify the clinical performance a new test must attain to allow better health outcomes than current practice. We classify the proposed patient benefits of a new test into three broad groups and describe how to set minimum clinical performance at the level where the potential harm of false-positive and false-negative results does not outweigh the benefits. (1) For add-on tests proposed to improve disease outcomes by improving detection, define an acceptable trade-off for false-positive versus true-positive results; (2) for triage tests proposed to reduce unnecessary tests and treatment by ruling out disease, define an acceptable risk of false-negatives as a safety threshold; (3) for replacement tests proposed to provide other benefits, or reduce costs, without compromising accuracy, use existing tests to benchmark minimum accuracy levels. Conclusions: Researchers can follow these guidelines to focus their study objectives and to define statistical hypotheses and sample size requirements. This way, clinical performance studies will allow conclusions about whether test performance is sufficient for intended use

The FOAM study : Is Hysterosalpingo foam sonography (HyFoSy) a cost-effective alternative for hysterosalpingography (HSG) in assessing tubal patency in subfertile women? Study protocol for a randomized controlled trial

This is an investigator initiated trial, VU medical center Amsterdam is the sponsor, contact information: prof. CJM de Groot, Department of Obstetrics and Gynaecology, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands, Tel: + 31-204444444. This study is funded by ZonMw, a Dutch organization for Health Research and Development, project number 837001504. ZonMW gives financial support for the whole project. IQ Medical Ventures provides the ExEm FOAM® kits. The funding bodies have no role in the design of the study; collection, analysis, and interpretation of data; and in writing the manuscript.Peer reviewedPublisher PD

Can hysterosalpingo-foam sonography replace hysterosalpingography as first-choice tubal patency test? A randomized non-inferiority trial

Funding Information: The FOAM study was an investigator-initiated study funded by ZonMw, The Netherlands organization for Health Research and Development (project number 837001504). ZonMw funded the whole project. IQ Medical Ventures provided the ExEm-foamVR kits free of charge. The funders had no role in study design, collection, analysis and interpretation of the data. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.Peer reviewedPublisher PD

Standards for Reporting on Diagnostic Accuracy Studies

In the evaluation of new and existing medical tests, establishing a test's diagnostic accuracy is an essential step. Accuracy studies with shortcomings in study design can produce biased results. Evidence accumulates that many published research articles fail to include key elements about study methods and findings. Standards for the Reporting of Diagnostic accuracy studies (STARD) were developed by an international group to improve the reporting of diagnostic accuracy studies. The STARD statement and the 25-item checklist have been published and adopted by major clinical and subspecialty journals. A similar initiative has been organized for prognostic tumor markers in oncology

DeSpin: A prototype system for detecting spin in biomedical publications

Improving the quality of medical research reporting is crucial to reduce avoidable waste in research and to improve the quality of health care. Despite various initiatives aiming at improving research reporting - guidelines, checklists, authoring aids, peer review procedures, etc. - overinterpretation of research results, also known as distorted reporting or spin, is still a serious issue in research reporting. In this paper, we propose a Natural Language Processing (NLP) system for detecting several types of spin in biomedical articles reporting randomized controlled trials (RCTs). We use a combination of rule-based and machine learning approaches to extract important information on trial design and to detect potential spin. The proposed spin detection system includes algorithms for text structure analysis, sentence classification, entity and relation extraction, semantic similarity assessment. Our algorithms achieved operational performance for the these tasks, F-measure ranging from 79,42 to 97.86% for different tasks. The most difficult task is extracting reported outcomes. Our tool is intended to be used as a semiautomated aid tool for assisting both authors and peer reviewers to detect potential spin. The tool incorporates a simple interface that allows to run the algorithms and visualize their output. It can also be used for manual annotation and correction of the errors in the outputs. The proposed tool is the first tool for spin detection