A critical appraisal of the quality of head and neck cancer imaging guidelines using the AGREE II tool: A EuroAIM initiative

Romeo, Valeria; Stanzione, Arnaldo; Cocozza, Sirio; Ugga, Lorenzo; Cuocolo, Renato; Brunetti, Arturo; Bisdas, Sotirios

doi:10.1002/cam4.1933

Cited by 29 publications

(21 citation statements)

References 28 publications

(57 reference statements)

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“…Evaluations of CPGs for paediatric hearing loss and newborn hearing screening found that the majority of guidelines scored <60% in multiple domains. Similar findings have been found in reviews of guidelines for imaging of adult head and neck cancers and management of paediatric type 2 diabetes mellitus 8,34 . Given that the only guideline receiving a ‘High’ score overall explicitly mentioned the use of published guideline development manuals, we strongly recommend that future CPG developers and reviewers make use of AGREE II guidelines when formulating their recommendations, especially given they are among the main stakeholders for whom AGREE II was developed 35 .…”

Section: Discussionsupporting

confidence: 72%

“…Possible standardised scores range from 0% to 100%. In accordance with previous literature, 8,10 a threshold of 60% was to be considered satisfactory in each domain. The designation of ‘high’ was assigned to CPGs with ≥5 domains scoring ≥60%, ‘average’ for CPGs with 3–4 domains of ≥60%, and ‘low’ if ≤2 domains were ≥60%.…”

Section: Methodssupporting

confidence: 55%

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Appraisal of clinical practice guidelines for the evaluation and management of neck masses in children

Shin

Prasad

Arguelles

et al. 2021

J Paediatrics Child Health

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Aim The purpose of this systematic review was to use the Appraisal of Guidelines for Research and Evaluation tool to assess the methodological quality of clinical practice guidelines (CPGs) for the workup and management of paediatric neck masses. Methods MEDLINE, Embase, Cochrane and grey literature were searched to identify CPG incorporating paediatric neck masses. Four authors with previous training of the Appraisal of Guidelines for Research and Evaluation tool evaluated the included studies. Results Nine studies met inclusion criteria. The highest scoring domains were ‘Scope and Purpose’ (74.0 ± 4.5) and ‘Clarity of Presentation’ (72.9 ± 6.3). The lowest scoring domains were ‘Rigour and Development’ (18.8 ± 7.5) and ‘Applicability’ (23.7 ± 6.1). One study was ‘High’ quality, three received scores of ‘Average’ and five were found to be ‘Low’ quality. Conclusion The majority of paediatric neck mass CPGs were low to average quality. The domains in need of greatest improvement were ‘Rigour and Development’ and ‘Applicability’, suggesting significant concerns in current CPGs focused on paediatric neck masses.

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Section: Discussionsupporting

confidence: 72%

Section: Methodssupporting

confidence: 55%

Appraisal of clinical practice guidelines for the evaluation and management of neck masses in children

Shin

Prasad

Arguelles

et al. 2021

J Paediatrics Child Health

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“…Continuous variables are presented as mean ± standard deviation. Following previous experiences both with RQS and other scoring systems [22,23], inter-reader reproducibility was evaluated by calculating the intraclass correlation coefficient (ICC) for the total RQS score obtained by each study. In accordance with recent guidelines, a two-way, random-effects, single-rater, absolute agreement ICC model was used [24].…”

Section: Discussionmentioning

confidence: 99%

Meningioma MRI radiomics and machine learning: systematic review, quality score assessment, and meta-analysis

et al. 2021

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Purpose To systematically review and evaluate the methodological quality of studies using radiomics for diagnostic and predictive purposes in patients with intracranial meningioma. To perform a meta-analysis of machine learning studies for the prediction of intracranial meningioma grading from pre-operative brain MRI. Methods Articles published from the year 2000 on radiomics and machine learning applications in brain imaging of meningioma patients were included. Their methodological quality was assessed by three readers with the radiomics quality score, using the intra-class correlation coefficient (ICC) to evaluate inter-reader reproducibility. A meta-analysis of machine learning studies for the preoperative evaluation of meningioma grading was performed and their risk of bias was assessed with the Quality Assessment of Diagnostic Accuracy Studies tool. Results In all, 23 studies were included in the systematic review, 8 of which were suitable for the meta-analysis. Total (possible range, −8 to 36) and percentage radiomics quality scores were respectively 6.96 ± 4.86 and 19 ± 13% with a moderate to good inter-reader reproducibility (ICC = 0.75, 95% confidence intervals, 95%CI = 0.54–0.88). The meta-analysis showed an overall AUC of 0.88 (95%CI = 0.84–0.93) with a standard error of 0.02. Conclusions Machine learning and radiomics have been proposed for multiple applications in the imaging of meningiomas, with promising results for preoperative lesion grading. However, future studies with adequate standardization and higher methodological quality are required prior to their introduction in clinical practice.

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“…Each appraiser was asked to assign a score to each item and to the Overall Assessment section as well as to indicate whether he/she would recommend the use of the guideline in clinical practice. Whereas they had previous exposure to the AGREE II tool (15), the appraisers also carried out the freely available online training tool consisting of an overview tutorial and a practice exercise (17).…”

Section: Methodsmentioning

confidence: 99%

A Critical Appraisal of the Quality of Glioma Imaging Guidelines Using the AGREE II Tool: A EuroAIM Initiative

et al. 2019

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Background: Following the EuroAIM initiative to assess the quality of medical imaging guidelines by using the Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument, we aimed to evaluate the quality of the current imaging guidelines in patients with gliomas. Methods: A literature search was conducted to identify eligible imaging guidelines considered in the management of adult patients with gliomas. The selected guidelines were evaluated using the AGREE II instrument by four independent appraisers. The agreement among the four appraisers was estimated using the intraclass correlation coefficient (ICC) analysis. Results: Seven guidelines were selected for the appraisal. Six out of the seven guidelines showed an average level of quality with only one showing a low quality. The highest scores were found in Domain 1 “Scope and purpose” (mean score = 81.2%) and Domain 4 “Clarity of presentation” (mean score = 77.6%). The remaining domains showed a low level of quality and, in particular, Domain 5 “Applicability” was the most critical with a mean score of 41.7%, mainly related to a minor attention to barriers and facilitators as well as costs and resources implications of applying the guidelines. The ICC analysis showed a very good agreement among the four appraisers with ICC values ranging from 0.907 to 0.993. Conclusions: The available guidelines on glioma imaging emerged as of average quality according to the AGREE II tool analysis. Based on these results, further efforts should be made in order to involve different professional bodies and stakeholders and increase patient and public involvement in any future guideline drafting as well as to improve the applicability of these guidelines into the clinical practice.

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A critical appraisal of the quality of head and neck cancer imaging guidelines using the AGREE II tool: A EuroAIM initiative

Cited by 29 publications

References 28 publications

Appraisal of clinical practice guidelines for the evaluation and management of neck masses in children

Appraisal of clinical practice guidelines for the evaluation and management of neck masses in children

Meningioma MRI radiomics and machine learning: systematic review, quality score assessment, and meta-analysis

A Critical Appraisal of the Quality of Glioma Imaging Guidelines Using the AGREE II Tool: A EuroAIM Initiative

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