Compliance With Standards for STARD 2015 Reporting Recommendations in Pathology

Adherence to Complication Reporting for Randomized Controlled Trials Contained in Clinical Practice Guidelines for the Management of Carpal Tunnel Syndrome

Purpose

Randomized controlled trials (RCTs) are frequently used in creating recommendations contained within clinical practice guidelines (CPGs). However, investigations outside of hand surgery have reported that RCTs within CPGs infrequently report complications and harms-related data. Our purpose was to assess adherence to complication reporting and harms-related outcomes contained in the Consolidated Standards for Reporting (CONSORT) Extension of Harms and Standards for Reporting of Diagnostic Accuracy Studies (STARD) reporting checklists for RCTs within the American Academy of Orthopaedic Surgery (AAOS) CPGs for carpal tunnel syndrome (CTS).

Methods

We identified all RCTs within the AAOS CTS CPGs. All therapeutic RCTs and diagnostic studies were included. We used the CONSORT Harms Checklist criteria to assess adherence to the reporting of adverse events for therapeutic RCTs and the STARD criteria to assess the diagnostic accuracy of the articles. We defined adequate compliance as adherence to ≥50% of the checklist items.

Results

We identified 82 therapeutic RCTs and 90 diagnostic accuracy articles within the AAOS CTS CPG. For therapeutic RCTs, we found that the average compliance with the published checklists was 19%. For diagnostic studies, the average compliance with checklists was found to be 55%. Eleven therapeutic RCTs (13%) and 60 diagnostic studies (67%) were determined to have adequate compliance for the CONSORT and STARD checklists, respectively.

Conclusions

Randomized controlled trials in the AAOS CPGs for CTS have low compliance with the CONSORT Extension for Harms Checklist. Although the overall adherence to the items published in the STARD statement for diagnostic accuracy evaluation remains higher, future efforts should be made to improve the adherence rates to both checklists.

Clinical relevance

Improved standardization of complication reporting may aid in comparing outcomes across multiple clinical investigations of upper-extremity procedures.

Publications on the diagnostic accuracy of dermatopathology tests: A cross-sectional quality analysis

BACKGROUND

Ancillary diagnostic tests are frequent in dermatopathology practice. Publications on their accuracy influence their utilization. The transparency and completeness of these publications are unknown.

METHODS

We performed a cross-sectional study on diagnostic accuracy studies in dermatopathology published between 2020 and 2022 for compliance with Standards for Reporting of Diagnostic Accuracy Studies (STARD) and the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2).

RESULTS

14.67 ± 3.02 STARD items were reported in 62 publications (range, 9.5-23.5 out of the recommended total of 30). More items were reported in high-impact factor journals (16.01 vs. 13.32, p = 0.0002) and journals that endorsed STARD in their author instructions (17.22 vs. 14.11, p = 0.0039). Less than 10% of publications reported quantifiable hypotheses, sample size calculations, flow diagrams, or study registrations. The risk of bias by our analysis of QUADAS-2 criteria was high or uncertain for index test interpretation (36/62, 58%) and patient selection (44/62, 71%).

CONCLUSIONS

Publications on dermatopathology tests are exploratory studies without prespecified hypotheses or study designs. They do not meet the criteria for transparent reporting. We suggest that medical journal leadership should consider updating their instructions with more explicit guidance on recommended manuscript elements.

Has the quality of reporting improved since it became mandatory to use the Standards for Reporting Diagnostic Accuracy?

OBJECTIVES

To investigate whether making the Standards for Reporting Diagnostic Accuracy (STARD) mandatory by the leading journal 'Radiology' in 2016 improved the quality of reporting of diagnostic accuracy studies.

METHODS

A validated search term was used to identify diagnostic accuracy studies published in Radiology in 2015 and 2019. STARD adherence was assessed by two independent reviewers. Each item was scored as yes (1 point) if adequately reported or as no (0 points) if not. The total STARD score per article was calculated. Wilcoxon-Mann-Whitney tests were used to evaluate differences of the total STARD scores between 2015 and 2019. In addition, the total STARD score was compared between studies stratified by study design, citation rate, and data collection.

RESULTS

The median number of reported STARD items for the total of 66 diagnostic accuracy studies from 2015 to 2019 was 18.5 (interquartile range [IQR] 17.5-20.0) of 29. Adherence to the STARD checklist significantly improved the STARD score from a median of 18.0 (IQR 15.5-19.5) in 2015 to a median of 19.5 (IQR 18.5-21.5) in 2019 (p < 0.001). No significant differences were found between studies stratified by mode of data collection (prospective vs. retrospective studies, p = 0.68), study design (cohort vs. case-control studies, p = 0.81), and citation rate (two groups divided by median split [< 0.56 citations/month vs. ≥ 0.56 citations/month], p = 0.54).

CONCLUSIONS

Making use of the STARD checklist mandatory significantly increased the adherence with reporting standards for diagnostic accuracy studies and should be considered by editors and publishers for widespread implementation.

CRITICAL RELEVANCE STATEMENT

Editors may consider making reporting guidelines mandatory to improve the scientific quality.

Has the STARD statement improved the quality of reporting of diagnostic accuracy studies published in European Radiology?

OBJECTIVES

To investigate whether encouraging authors to follow the Standards for Reporting Diagnostic Accuracy (STARD) guidelines improves the quality of reporting of diagnostic accuracy studies.

METHODS

In mid-2017, European Radiology started encouraging its authors to follow the STARD guidelines. Our MEDLINE search identified 114 diagnostic accuracy studies published in European Radiology in 2015 and 2019. The quality of reporting was evaluated by two independent reviewers using the revised STARD statement. Item 11 was excluded because a meaningful decision about adherence was not possible. Student's t test for independent samples was used to analyze differences in the mean number of reported STARD items between studies published in 2015 and in 2019. In addition, we calculated differences related to the study design, data collection, and citation rate.

RESULTS

The mean total number of reported STARD items for all 114 diagnostic accuracy studies analyzed was 15.9 ± 2.6 (54.8%) of 29 items (range 9.5-22.5). The quality of reporting of diagnostic accuracy studies was significantly better in 2019 (mean ± standard deviation (SD), 16.3 ± 2.7) than in 2015 (mean ± SD, 15.1 ± 2.3; p < 0.02). No significant differences in the reported STARD items were identified in relation to study design (p = 0.13), data collection (p = 0.87), and citation rate (p = 0.09).

CONCLUSION

The quality of reporting of diagnostic accuracy studies according to the STARD statement was moderate with a slight improvement since European Radiology started to recommend its authors to follow the STARD guidelines.

KEY POINTS

• The quality of reporting of diagnostic accuracy studies was moderate with a mean total number of reported STARD items of 15.9 ± 2.6. • The adherence to STARD was significantly better in 2019 than in 2015 (16.3 ± 2.7 vs. 15.1 ± 2.3; p = 0.016). • No significant differences in the reported STARD items were identified in relation to study design (p = 0.13), data collection (p = 0.87), and citation rate (p = 0.09).

Systematic review identifies deficiencies in reporting of diagnostic test accuracy among clinical decision support systems

OBJECTIVES

This systematic review assesses the reporting quality and risk of bias in studies evaluating the diagnostic test accuracy (DTA) of clinical decision support systems (CDSS).

STUDY DESIGN AND SETTING

The Cochrane Library, PubMed/MEDLINE, Scopus, and Web of Science were searched for studies, published between January 1, 2016 and May 31, 2021, evaluating the DTA of CDSS for human patients. Articles using a patient's self-diagnosis, assessing disease severity, focusing on treatment/follow-up, or comparing pre-post CDSS implementation periods were excluded. All eligible studies were assessed for reporting quality using STARD 2015 and for risk of bias using QUADAS-2. Item ratings were presented using heat maps. This study was reported as per PRISMA-DTA.

RESULTS

In total, 158 of 2,820 screened articles were included in the analysis. The studies were heterogeneous in terms of study characteristics, reporting quality, risk of biases, and applicability concerns with few highly rated studies. Mostly the overall quality was deficient for items addressing the domains 'methodology,' 'results,' and 'other information'.

CONCLUSION

Our analysis revealed shortcomings in critical domains of reporting quality and risk of bias, indicating the need for additional guidance and training in an interdisciplinary scientific field with mixed biostatistical expertise.

Reporting of Artificial Intelligence Diagnostic Accuracy Studies in Pathology Abstracts: Compliance with STARD for Abstracts Guidelines

Artificial intelligence (AI) research is transforming the range tools and technologies available to pathologists, leading to potentially faster, personalized and more accurate diagnoses for patients. However, to see the use of tools for patient benefit and achieve this safely, the implementation of any algorithm must be underpinned by high quality evidence from research that is understandable, replicable, usable and inclusive of details needed for critical appraisal of potential bias. Evidence suggests that reporting guidelines can improve the completeness of reporting of research, especially with good awareness of guidelines. The quality of evidence provided by abstracts alone is profoundly important, as they influence the decision of a researcher to read a paper, attend a conference presentation or include a study in a systematic review.

AI abstracts at two international pathology conferences were assessed to establish completeness of reporting against the STARD for Abstracts criteria. This reporting guideline is for abstracts of diagnostic accuracy studies and includes a checklist of 11 essential items required to accomplish satisfactory reporting of such an investigation. A total of 3488 abstracts were screened from the United States & Canadian Academy of Pathology annual meeting 2019 and the 31st European Congress of Pathology (ESP Congress). Of these, 51 AI diagnostic accuracy abstracts were identified and assessed against the STARD for Abstracts criteria for completeness of reporting. Completeness of reporting was suboptimal for the 11 essential criteria, a mean of 5.8 (SD 1.5) items were detailed per abstract. Inclusion was variable across the different checklist items, with all abstracts including study objectives and no abstracts including a registration number or registry. Greater use and awareness of the STARD for Abstracts criteria could improve completeness of reporting and further consideration is needed for areas where AI studies are vulnerable to bias.