scholarly journals Placental growth factor (alone or in combination with soluble fms-like tyrosine kinase 1) as an aid to the assessment of women with suspected pre-eclampsia: systematic review and economic analysis

2016 ◽  
Vol 20 (87) ◽  
pp. 1-160 ◽  
Author(s):  
Geoff K Frampton ◽  
Jeremy Jones ◽  
Micah Rose ◽  
Liz Payne

BackgroundPre-eclampsia (PE) prediction based on blood pressure, presence of protein in the urine, symptoms and laboratory test abnormalities can result in false-positive diagnoses. This may lead to unnecessary antenatal admissions and preterm delivery. Blood tests that measure placental growth factor (PlGF) or the ratio of soluble fms-like tyrosine kinase 1 (sFlt-1) to PlGF could aid prediction of PE if either were added to routine clinical assessment or used as a replacement for proteinuria testing.ObjectivesTo evaluate the diagnostic accuracy and cost-effectiveness of PlGF-based tests for patients referred to secondary care with suspected PE in weeks 20–37 of pregnancy.DesignSystematic reviews and an economic analysis.Data sourcesBibliographic databases including MEDLINE, EMBASE, Web of Science and The Cochrane Library and Database of Abstracts of Reviews of Effects were searched up to July 2015 for English-language references. Conferences, websites, systematic reviews and confidential company submissions were also accessed.Review methodsSystematic reviews of test accuracy and economic studies were conducted to inform an economic analysis. Test accuracy studies were required to include women with suspected PE and report quantitatively the accuracy of PlGF-based tests; their risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) criteria. The economic studies review had broad eligibility criteria to capture any types of economic analysis; critical appraisal employed standard checklists consistent with National Institute for Health and Care Excellence criteria. Study selection, critical appraisal and data extraction in both reviews were performed by two reviewers.Economic analysisAn independent economic analysis was conducted based on a decision tree model, using the best evidence available. The model evaluates costs (2014, GBP) from a NHS and Personal Social Services perspective. Given the short analysis time horizon, no discounting was undertaken.ResultsFour studies were included in the systematic review of test accuracy: two on Alere’s Triage®PlGF test (Alere, Inc., San Diego, CA, USA) for predicting PE requiring delivery within a specified time and two on Roche Diagnostics’ Elecsys®sFlt-1 to PlGF ratio test (Roche Diagnostics GmbH, Mannheim, Germany) for predicting PE within a specified time. Three studies were included in the systematic review of economic studies, and two confidential company economic analyses were assessed separately. Study heterogeneity precluded meta-analyses of test accuracy or cost-analysis outcomes, so narrative syntheses were conducted to inform the independent economic model. The model predicts that, when supplementing routine clinical assessment for rule-out and rule-in of PE, the two tests would be cost-saving in weeks 20–35 of gestation, and marginally cost-saving in weeks 35–37, but with minuscule impact on quality of life. Length of neonatal intensive care unit stay was the most influential parameter in sensitivity analyses. All other sensitivity analyses had negligible effects on results.LimitationsNo head-to-head comparisons of the tests were identified. No studies investigated accuracy of PlGF-based tests when used as a replacement for proteinuria testing. Test accuracy studies were found to be at high risk of clinical review bias.ConclusionsThe Triage and Elecsys tests would save money if added to routine clinical assessment for PE. The magnitude of savings is uncertain, but the tests remain cost-saving under worst-case assumptions. Further research is required to clarify how the test results would be interpreted and applied in clinical practice.Study registrationThis study is registered as PROSPERO CRD42015017670.FundingThe National Institute for Health Research Health Technology Assessment programme.

2022 ◽  
Vol 11 (1) ◽  
Author(s):  
Yuelun Zhang ◽  
Siyu Liang ◽  
Yunying Feng ◽  
Qing Wang ◽  
Feng Sun ◽  
...  

Abstract Background Systematic review is an indispensable tool for optimal evidence collection and evaluation in evidence-based medicine. However, the explosive increase of the original literatures makes it difficult to accomplish critical appraisal and regular update. Artificial intelligence (AI) algorithms have been applied to automate the literature screening procedure in medical systematic reviews. In these studies, different algorithms were used and results with great variance were reported. It is therefore imperative to systematically review and analyse the developed automatic methods for literature screening and their effectiveness reported in current studies. Methods An electronic search will be conducted using PubMed, Embase, ACM Digital Library, and IEEE Xplore Digital Library databases, as well as literatures found through supplementary search in Google scholar, on automatic methods for literature screening in systematic reviews. Two reviewers will independently conduct the primary screening of the articles and data extraction, in which nonconformities will be solved by discussion with a methodologist. Data will be extracted from eligible studies, including the basic characteristics of study, the information of training set and validation set, and the function and performance of AI algorithms, and summarised in a table. The risk of bias and applicability of the eligible studies will be assessed by the two reviewers independently based on Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). Quantitative analyses, if appropriate, will also be performed. Discussion Automating systematic review process is of great help in reducing workload in evidence-based practice. Results from this systematic review will provide essential summary of the current development of AI algorithms for automatic literature screening in medical evidence synthesis and help to inspire further studies in this field. Systematic review registration PROSPERO CRD42020170815 (28 April 2020).


2017 ◽  
Vol 13 (2) ◽  
pp. 138-156 ◽  
Author(s):  
Alex Pollock ◽  
Eivind Berge

High quality up-to-date systematic reviews are essential in order to help healthcare practitioners and researchers keep up-to-date with a large and rapidly growing body of evidence. Systematic reviews answer pre-defined research questions using explicit, reproducible methods to identify, critically appraise and combine results of primary research studies. Key stages in the production of systematic reviews include clarification of aims and methods in a protocol, finding relevant research, collecting data, assessing study quality, synthesizing evidence, and interpreting findings. Systematic reviews may address different types of questions, such as questions about effectiveness of interventions, diagnostic test accuracy, prognosis, prevalence or incidence of disease, accuracy of measurement instruments, or qualitative data. For all reviews, it is important to define criteria such as the population, intervention, comparison and outcomes, and to identify potential risks of bias. Reviews of the effect of rehabilitation interventions or reviews of data from observational studies, diagnostic test accuracy, or qualitative data may be more methodologically challenging than reviews of effectiveness of drugs for the prevention or treatment of stroke. Challenges in reviews of stroke rehabilitation can include poor definition of complex interventions, use of outcome measures that have not been validated, and poor generalizability of results. There may also be challenges with bias because the effects are dependent on the persons delivering the intervention, and because masking of participants and investigators may not be possible. There are a wide range of resources which can support the planning and completion of systematic reviews, and these should be considered when planning a systematic review relating to stroke.


Cancers ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 5755
Author(s):  
Diana Russo ◽  
Pierluigi Mariani ◽  
Vito Carlo Alberto Caponio ◽  
Lucio Lo Russo ◽  
Luca Fiorillo ◽  
...  

(1) Background: An accurate prediction of cancer survival is very important for counseling, treatment planning, follow-up, and postoperative risk assessment in patients with Oral Squamous Cell Carcinoma (OSCC). There has been an increased interest in the development of clinical prognostic models and nomograms which are their graphic representation. The study aimed to revise the prognostic performance of clinical-pathological prognostic models with internal validation for OSCC. (2) Methods: This systematic review was performed according to the Cochrane Handbook for Diagnostic Test Accuracy Reviews chapter on searching, the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines, and the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS). (3) Results: Six studies evaluating overall survival in patients with OSCC were identified. All studies performed internal validation, while only four models were externally validated. (4) Conclusions: Based on the results of this systematic review, it is possible to state that it is necessary to carry out internal validation and shrinkage to correct overfitting and provide an adequate performance for optimism. Moreover, calibration, discrimination and nonlinearity of continuous predictors should always be examined. To reduce the risk of bias the study design used should be prospective and imputation techniques should always be applied to handle missing data. In addition, the complete equation of the prognostic model must be reported to allow updating, external validation in a new context and the subsequent evaluation of the impact on health outcomes and on the cost-effectiveness of care.


2017 ◽  
Vol 6 (1) ◽  
Author(s):  
Trevor A. McGrath ◽  
Mostafa Alabousi ◽  
Becky Skidmore ◽  
Daniël A. Korevaar ◽  
Patrick M. M. Bossuyt ◽  
...  

2018 ◽  
pp. 251-253 ◽  
Author(s):  
Herney Andrés García-Perdomo

Systematic reviews (SR) have been important tools for determining the magnitude of an effect, with appropriate methodology, rigor and scientific quality. This epidemiologic design was developed to conduct an exhaustive, systematic and explicit assessment of the literature, based on a clearly research question, an explicit methodology, a critical appraisal using a variety of tools and a qualitative summary of the evidence. On the other hand, the meta-analysis (MA), is the statistical analysis used in the synthesis of the evidence at the end of a very well performed systematic review. It compares head to head interventions, however nowadays, we have another tool to perform indirect or mixed comparisons (Network meta-analysis). This new statistical tool evaluates the effectiveness when comparing different treatments with similar characteristics, which have not been directly compared in a study. Unlike the traditional meta-analysis, this new tool compares the results of different studies that have a point or a common intervention without a direct comparison.


2016 ◽  
Vol 10 (2) ◽  
pp. 148-153
Author(s):  
Patrick Jones ◽  
Helen Ewan ◽  
Timothy Lane ◽  
Jim Adshead ◽  
Nikhil Vasdev ◽  
...  

Systematic reviews provide high-quality critical appraisal and evidence-based summaries on a topic. They represent a key resource for time-pressured clinicians as they strive to deliver better patient care. Robust methodology and adhering to rigorous standards forms the foundation of this type of article. As such, writing a systematic review can prove a great challenge. This article aims to provide an overview of the methodology as well as certain tips and tricks which will help the surgeon when taking on such a project.


Author(s):  
Whitney A. Townsend ◽  
Patricia F. Anderson ◽  
Emily C. Ginier ◽  
Mark P. MacEachern ◽  
Kate M. Saylor ◽  
...  

Objective: The project identified a set of core competencies for librarians who are involved in systematic reviews.Methods: A team of seven informationists with broad systematic review experience examined existing systematic review standards, conducted a literature search, and used their own expertise to identify core competencies and skills that are necessary to undertake various roles in systematic review projects.Results: The team identified a total of six competencies for librarian involvement in systematic reviews: “Systematic review foundations,” “Process management and communication,” “Research methodology,” “Comprehensive searching,” “Data management,” and “Reporting.” Within each competency are the associated skills and knowledge pieces (indicators). Competence can be measured using an adaptation of Miller’s Pyramid for Clinical Assessment, either through self-assessment or identification of formal assessment instruments.Conclusions: The Systematic Review Competencies Framework provides a standards-based, flexible way for librarians and organizations to identify areas of competence and areas in need of development to build capacity for systematic review integration. The framework can be used to identify or develop appropriate assessment tools and to target skill development opportunities.


2021 ◽  
pp. 175045892199469
Author(s):  
Veronica Phillips ◽  
Eleanor Barker

This article aims to provide an overview of the structure, form and content of systematic reviews. It focuses in particular on the literature searching component, and covers systematic database searching techniques, searching for grey literature and the importance of librarian involvement in the search. It also covers systematic review reporting standards such as PRISMA-P and PRISMA, critical appraisal and tools and resources to support the review and ensure it is conducted efficiently and effectively. Finally, it summarizes the requirements when screening search results for inclusion in the review, and the statistical synthesis of included studies’ findings.


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