scholarly journals Methodological quality of machine learning-based quantitative imaging analysis studies in esophageal cancer: a systematic review of clinical outcome prediction after concurrent chemoradiotherapy

2021 ◽  
Author(s):  
Zhenwei Shi ◽  
Zhen Zhang ◽  
Zaiyi Liu ◽  
Lujun Zhao ◽  
Zhaoxiang Ye ◽  
...  
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Cancer Research ◽  
Esophageal Cancer ◽  
Methodological Quality ◽  
Concurrent Chemoradiotherapy ◽  
Quantitative Imaging ◽  
External Validation ◽  
Imaging Analysis

Abstract Purpose Studies based on machine learning-based quantitative imaging techniques have gained much interest in cancer research. The aim of this review is to critically appraise the existing machine learning-based quantitative imaging analysis studies predicting outcomes of esophageal cancer after concurrent chemoradiotherapy in accordance with PRISMA guidelines. Methods A systematic review was conducted in accordance with PRISMA guidelines. The citation search was performed via PubMed and Embase Ovid databases for literature published before April 2021. From each full-text article, study characteristics and model information were summarized. We proposed an appraisal matrix with 13 items to assess the methodological quality of each study based on recommended best-practices pertaining to quality. Results Out of 244 identified records, 37 studies met the inclusion criteria. Study endpoints included prognosis, treatment response, and toxicity after concurrent chemoradiotherapy with reported discrimination metrics in validation datasets between 0.6 and 0.9, with wide variation in quality. A total of 30 studies published within the last 5 years were evaluated for methodological quality and we found 11 studies with at least 6 “good” item ratings. Conclusion A substantial number of studies lacked prospective registration, external validation, model calibration, and support for use in clinic. To further improve the predictive power of machine learning-based models and translate into real clinical applications in cancer research, appropriate methodologies, prospective registration, and multi-institution validation are recommended.

Current Status and Quality of Machine Learning-Based Radiomics Studies for Glioma Grading: A Systematic Review

Oncology ◽  
2021 ◽  
pp. 1-11
Author(s):  
Mohsen Tabatabaei ◽  
Ali Razaei ◽  
Amir Hossein Sarrami ◽  
Zahra Saadatpour ◽  
Aparna Singhal ◽  
...  
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
External Validation ◽  
Class Imbalance ◽  
Final Analysis ◽  
Current Status ◽  
Maximum Score ◽  
Glioma Grading ◽  
Minimum Score

<b><i>Introduction:</i></b> Radiomics now has significant momentum in the era of precision medicine. Glioma is one of the pathologies that has been extensively evaluated by radiomics. However, this technique has not been incorporated into clinical practice. In this systematic review, we selected and reviewed the published studies about glioma grading by radiomics to evaluate this technique’s feasibility and its challenges. <b><i>Material and Methods:</i></b> Using seven different search strings, we considered all published English manuscripts from 2015 to September 2020 in PubMed, Embase, and Scopus databases. After implementing the exclusion and inclusion criteria, the final papers were selected for the methodological quality assessment based on our in-house Modified Radiomics Standard Scoring (RQS) containing 43 items (minimum score of 0, maximum score of 44). Finally, we offered our opinion about the challenges and weaknesses of the selected papers. <b><i>Results:</i></b> By our search, 1,177 manuscripts were found (485 in PubMed, 343 in Embase, and 349 in Scopus). After the implementation of inclusion and exclusion criteria, 18 papers remained for the final analysis by RQS. The total RQS score ranged from 26 (59% of maximum possible score) to 43 (97% of maximum possible score) with a mean of 33.5 (76% of maximum possible score). <b><i>Conclusion:</i></b> The current studies are promising but very heterogeneous in design with high variation in the radiomics software, the number of extracted features, the number of selected features, and machine learning models. All of the studies were retrospective in design; many are based on small datasets and/or suffer from class imbalance and lack of external validation data­sets.

scholarly journals Evaluating Methodological Quality of Prognostic Prediction Models on Patient Reported Outcome Measurements after Total Hip Replacement and Total Knee Replacement Surgery: a systematic review protocol

2021 ◽  
Author(s):  
Wei-Ju Chang ◽  
Justine Naylor ◽  
Pragadesh Natarajan ◽  
Spiro Menounos ◽  
Masiath Monuja ◽  
...  
Keyword(s):  
Systematic Review ◽  
Knee Osteoarthritis ◽  
Prediction Model ◽  
Methodological Quality ◽  
Prediction Models ◽  
External Validation ◽  
Model Development ◽  
Patient Reported ◽  
Modelling Studies

Abstract Background Prediction models for poor patient-reported surgical outcomes after total hip replacement (THR) and total knee replacement (TKR) may provide a method for improving appropriate surgical care for hip and knee osteoarthritis. There are concerns about methodological issues and the risk of bias of studies producing prediction models. A critical evaluation of the methodological quality of prediction modelling studies in THR and TKR is needed to ensure their clinical usefulness. This systematic review aims to: 1) evaluate and report the quality of risk stratification and prediction modelling studies that predict patient-reported outcomes after THR and TKR; 2) identify areas of methodological deficit and provide recommendations for future research; and 3) synthesise the evidence on prediction models associated with post-operative patient-reported outcomes after THR and TKR surgeries. Methods MEDLINE, EMBASE and CINAHL electronic databases will be searched to identify relevant studies. Title and abstract and full-text screening will be performed by two independent reviewers. We will include: 1) prediction model development studies without external validation; 2) prediction model development studies with external validation of independent data; 3) external model validation studies; and 4) studies updating a previously developed prediction model. Data extraction spreadsheets will be developed based on the CHARMS checklist and TRIPOD statement and piloted on two relevant studies. Study quality and risk of bias will be assessed using the PROBAST tool. Prediction models will be summarised qualitatively. Meta-analyses on the predictive performance of included models will be conducted if appropriate. Discussion This systematic review will evaluate the methodological quality and usefulness of prediction models for poor outcomes after THR or TKR. This information is essential to provide evidence-based healthcare for end-stage hip and knee osteoarthritis. Findings of this review will contribute to the identification of key areas for improvement in conducting prognostic research in this field and facilitate the progress in evidence-based tailored treatments for hip and knee osteoarthritis. Systematic review registration: Submitted to PROSPERO on 30 August 2021.

scholarly journals A systematic review of methodological quality of model development studies predicting prognostic outcome for resectable pancreatic cancer

BMJ Open ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. e027192 ◽  
Author(s):  
Alison Bradley ◽  
Robert Van Der Meer ◽  
Colin J McKay
Keyword(s):  
Systematic Review ◽  
Methodological Quality ◽  
External Validation ◽  
Model Development ◽  
Predictive Modelling ◽  
Secondary Outcome ◽  
Development Studies ◽  
Cancer Data ◽  
Modelling Studies

ObjectivesTo assess the methodological quality of prognostic model development studies pertaining to post resection prognosis of pancreatic ductal adenocarcinoma (PDAC).Design/settingA narrative systematic review of international peer reviewed journalsData sourceSearches were conducted of: MEDLINE, Embase, PubMed, Cochrane database and Google Scholar for predictive modelling studies applied to the outcome of prognosis for patients with PDAC post resection. Predictive modelling studies in this context included prediction model development studies with and without external validation and external validation studies with model updating. Data was extracted following the Checklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS) checklist.Primary and secondary outcome measuresPrimary outcomes were all components of the CHARMS checklist. Secondary outcomes included frequency of variables included across predictive models.Results263 studies underwent full text review. 15 studies met the inclusion criteria. 3 studies underwent external validation. Multivariable Cox proportional hazard regression was the most commonly employed modelling method (n=13). 10 studies were based on single centre databases. Five used prospective databases, seven used retrospective databases and three used cancer data registry. The mean number of candidate predictors was 19.47 (range 7 to 50). The most commonly included variables were tumour grade (n=9), age (n=8), tumour stage (n=7) and tumour size (n=5). Mean sample size was 1367 (range 50 to 6400). 5 studies reached statistical power. None of the studies reported blinding of outcome measurement for predictor values. The most common form of presentation was nomograms (n=5) and prognostic scores (n=5) followed by prognostic calculators (n=3) and prognostic index (n=2).ConclusionsAreas for improvement in future predictive model development have been highlighted relating to: general aspects of model development and reporting, applicability of models and sources of bias.Trial registration numberCRD42018105942

How Does Mindfulness Affect Cognition? A Reflection on Confounding Issues Surrounding Mindfulness-based Intervention Research Targeting Cognitive Outcomes

2018 ◽  
Author(s):  
David R Vago ◽  
Resh Gupta ◽  
Sara Lazar
Keyword(s):  
Systematic Review ◽  
Health Outcomes ◽  
Cognitive Functioning ◽  
Cognitive Processes ◽  
Methodological Quality ◽  
Cognitive Outcomes ◽  
Controlled Trials ◽  
Randomized Controlled ◽  
Existing Data

One potential pathway by which mindfulness-based meditation improves health outcomes is through changes in cognitive functioning. A systematic review of randomized controlled trials of mindfulness-based interventions (MBIs) was conducted with a focus on assessing the state of the evidence for effects on cognitive processes and associated assays. Here, we comment on confounding issues surrounding the reporting of these and related findings, including 1) criteria that appropriately define an MBI; 2) limitations of assays used to measure cognition; and 3) methodological quality of MBI trials and reporting of findings. Because these issues contribute to potentially distorted interpretations of existing data, we offer constructive means for interpretation and recommendations for moving the field of mindfulness research forward regarding the effects on cognition.

scholarly journals Molecular mechanisms of Zika virus teratogenesis from animal studies: a systematic review protocol

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Gabriela Elis Wachholz ◽  
Julia do Amaral Gomes ◽  
Juliano André Boquett ◽  
Fernanda Sales Luiz Vianna ◽  
Lavínia Schuler-Faccini ◽  
...  
Keyword(s):  
Systematic Review ◽  
Animal Models ◽  
Zika Virus ◽  
Methodological Quality ◽  
Molecular Mechanisms ◽  
Grey Literature ◽  
Standard Form ◽  
Teratogenic Effect ◽  
Control Group

Abstract Background Due to the diversity of studies in animal models reporting that molecular mechanisms are involved in the teratogenic effect of the Zika virus (ZIKV), the objective of the present study is to evaluate the methodological quality of these studies, as well as to demonstrate which genes and which molecular pathways are affected by ZIKV in different animal models. Methods This search will be performed in four databases: PubMed/MEDLINE, EMBASE, Web of Science, and Scopus, as well as in the grey literature. The studies selection process will be reported through the PRISMA Statement diagram model. All studies describing the molecular mechanisms possibly involved in the development of malformations caused by embryonic/fetal ZIKV exposure in animal models with an appropriate control group and methodology will be included (including, for instance, randomized and non-randomized studies). All animals used as experimental models for ZIKV teratogenesis may be included as long as exposure to the virus occurred during the embryonic/fetal period. From the selected studies, data will be extracted using a previously prepared standard form. Bias risk evaluation will be conducted following the SYRCLE’s Risk of Bias tool. All data obtained will be tabulated and organized by outcomes (morphological and molecular). Discussion With the proposed systematic review, we expect to present results about the methodological quality of the published studies with animal models that investigated the molecular mechanisms involved in the teratogenic effect of ZIKV, as well as to show the studies with greater reliability. Systematic review registration PROSPERO CRD42019157316

scholarly journals Barriers to Incident Reporting among Nurses: A Qualitative Systematic Review

2021 ◽  
pp. 019394592199944
Author(s):  
Moataz Mohamed Maamoun Hamed ◽  
Stathis Konstantinidis
Keyword(s):  
Systematic Review ◽  
Methodological Quality ◽  
Incident Reporting ◽  
Negative Consequences ◽  
Incident Reporting Systems ◽  
Qualitative Systematic Review ◽  
Blame Culture ◽  
Critical Appraisal Skills ◽  
Definition Of

Incident reporting in health care prevents error recurrence, ultimately improving patient safety. A qualitative systematic review was conducted, aiming to identify barriers to incident reporting among nurses. Joanna Briggs Institute methodology for qualitative systematic reviews was followed, with data extracted using JBI QARI tools, and selected studies assessed for methodological quality using Critical Appraisal Skills Program (CASP). A meta-aggregation synthesis was carried out, and confidence in findings was assessed using GRADE ConQual. A total of 921 records were identified, but only five studies were included. The overall methodological quality of these studies was good and GRADE ConQual assessment score was “moderate.” Fear of negative consequences was the most cited barrier to nursing incident reporting. Barriers also included inadequate incident reporting systems and lack of interdisciplinary and interdepartmental cooperation. Lack of nurses’ necessary training made it more difficult to understand the importance of incident reporting and the definition of error. Lack of effective feedback and motivation and a pervasive blame culture were also identified.

scholarly journals Toward the Development of a Comprehensive Clinically Oriented Patient Profile: A Systematic Review of the Purpose, Characteristic, and Methodological Quality of Classification Systems of Adult Spinal Deformity

Neurosurgery ◽  
2021 ◽  
Author(s):  
Kenny Yat Hong Kwan ◽  
J Naresh-Babu ◽  
Wilco Jacobs ◽  
Marinus de Kleuver ◽  
David W Polly ◽  
...  
Keyword(s):  
Systematic Review ◽  
Decision Making ◽  
Classification System ◽  
Methodological Quality ◽  
Literature Search ◽  
Adult Spinal Deformity ◽  
Classification Systems ◽  
Systematic Literature Search ◽  
Patient Profile

Abstract BACKGROUND Existing adult spinal deformity (ASD) classification systems are based on radiological parameters but management of ASD patients requires a holistic approach. A comprehensive clinically oriented patient profile and classification of ASD that can guide decision-making and correlate with patient outcomes is lacking. OBJECTIVE To perform a systematic review to determine the purpose, characteristic, and methodological quality of classification systems currently used in ASD. METHODS A systematic literature search was conducted in MEDLINE, EMBASE, CINAHL, and Web of Science for literature published between January 2000 and October 2018. From the included studies, list of classification systems, their methodological measurement properties, and correlation with treatment outcomes were analyzed. RESULTS Out of 4470 screened references, 163 were included, and 54 different classification systems for ASD were identified. The most commonly used was the Scoliosis Research Society-Schwab classification system. A total of 35 classifications were based on radiological parameters, and no correlation was found between any classification system levels with patient-related outcomes. Limited evidence of limited quality was available on methodological quality of the classification systems. For studies that reported the data, intraobserver and interobserver reliability were good (kappa = 0.8). CONCLUSION This systematic literature search revealed that current classification systems in clinical use neither include a comprehensive set of dimensions relevant to decision-making nor did they correlate with outcomes. A classification system comprising a core set of patient-related, radiological, and etiological characteristics relevant to the management of ASD is needed.

scholarly journals 459 - Psychometric properties of the Geriatric Anxiety Inventory : A systematic review

2020 ◽  
Vol 32 (S1) ◽  
pp. 180-180
Author(s):  
Philippe Landreville ◽  
Alexandra Champagne ◽  
Patrick Gosselin
Keyword(s):  
Systematic Review ◽  
Psychometric Properties ◽  
Internal Consistency ◽  
Methodological Quality ◽  
The Body ◽  
Self Report ◽  
Test Reliability ◽  
Cosmin Checklist ◽  
Validity Indices

Background.The Geriatric Anxiety Inventory (GAI) is a widely used self-report measure of anxiety symptoms in older adults. Much research has been conducted on the psychometric properties of the GAI in various populations and using different language versions. Previous reviews of this literature have examined only a small proportion of studies in light of the body of research currently available and have not evaluated the methodological quality of this research. We conducted a systematic review of the psychometric properties of the GAI.Method.Relevant studies (N = 30) were retrieved through a search of electronic databases (Pubmed, PsycINFO, CINAHL, EMBASE and Google Scholar) and a hand search. The methodological quality of the included studies was assessed by two independent reviewers using the ‘‘COnsensusbased Standards for the selection of health status Measurement INstruments’’ (COSMIN) checklist.Results.Based on the COSMIN checklist, internal consistency and test reliability were mostly rated as poorly assessed (62.1% and 70% of studies, respectively) and quality of studies examining structural validity was mostly fair (60% of studies). The GAI showed adequate internal consistency and test-retest reliability. Convergent validity indices were highest with measures of generalized anxiety and lowest with instruments that include somatic symptoms. A substantial overlap with measures of depression was reported. While there was no consensus on the factorial structure of the GAI, several studies found it to be unidimensional.Conclusions.The GAI presents satisfactory psychometric properties. However, future efforts should aim to achieve a higher degree of methodological quality.

scholarly journals The prevalence of diabetes in Afghanistan: a systematic review and meta-analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sohail Akhtar ◽  
Jamal Abdul Nasir ◽  
Amara Javed ◽  
Mariyam Saleem ◽  
Sundas Sajjad ◽  
...  
Keyword(s):  
Risk Factors ◽  
Systematic Review ◽  
Methodological Quality ◽  
Meta Analysis ◽  
Population Based ◽  
Included Study ◽  
Cochrane Library ◽  
Or Education ◽  
Meta Regression

Abstract Background The aim of this paper is to investigate the prevalence of diabetes and its associated risk factors in Afghanistan through a systematic review and meta–analysis. Methods A comprehensive literature search was conducted using EMBASE, PubMed, Web of Sciences, Google Scholar and the Cochrane library, carried out from inception to April 312,020, without language restriction. Meta–analysis was performed using DerSimonian and Laird random-effects models with inverse variance weighting. The existence of publication bias was initially assessed by visual inspection of a funnel plot and then tested by the Egger regression test. Subgroup analyses and meta-regression were used to explore potential sources of heterogeneity. This systematic review was reported by following the PRISMA guidelines and the methodological quality of each included study was evaluated using the STROBE guidelines. Results Out of 64 potentially relevant studies, only 06 studies fulfilled the inclusion criteria and were considered for meta-analysis. The pooled prevalence of diabetes in the general population based on population-based studies were 12.13% (95% CI: 8.86–16.24%), based on a pooled sample of 7071 individuals. Results of univariate meta-regression analysis revealed that the prevalence of diabetes increased with mean age, hypertension and obesity. There was no significant association between sex (male vs female), smoking, the methodological quality of included articles or education (illiterate vs literate) and the prevalence of diabetes. Conclusions This meta-analysis reports the 12.13% prevalence of diabetes in Afghanistan,with the highest prevalence in Kandahar and the lowest in Balkh province. The main risk factors include increasing age, obesity and hypertension. Community-based care and preventive training programmes are recommended. Trial registration This review was registered on PROSPERO (registration number CRD42020172624).

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