Quality assessment of breast cancer studies conducted with the Delphi technique.

Methodological quality assessment tools for diagnosis and prognosis research: overview and guidance

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The Attack on Breast Cancer Screening

Measurement properties of quality assessment tools for studies of diagnostic accuracy

Breast cancer, menopause, and long-term survivorship: critical issues for the 21st century

ObjectivesQuality can be a challenge for Investigator initiated trials (IITs) since these trials are scarcely overseen by a sponsor or monitoring team. Therefore, quality assessment for departments managing clinical research grants program is important and urgently needed. Our study aims at developing a handy quality assessment tool for IITs that can be applied by both departments and project teams.MethodsThe framework of the quality assessment tool was developed based on the literature studies, accepted guidelines and the Delphi method. A total of 272 ongoing IITs funded by Shanghai non-profit organizations in 2015 and 2016 were used to extract quality indexes. Confirmatory factor analysis (CFA) was used to further evaluate the validity and feasibility of the conceptual quality assessment tool.ResultsThe tool consisted of 4 critical quality attributes, including progress, quality, regulation, scientificity, and 13 observed quality indexes. A total of 257 IITs were included in the validity and feasibility assessment. The majority (60.29%) were Randomized Controlled Trial (RCT), and 41.18% were multi-center studies. In order to test the validity and feasibility of IITs quality assessment tool, CFA showed that the model fit the data adequately. (CMIN/DF = 1.868, GFI = 0.916; CFI = 0.936; TLI = 0.919; RMSEA = 0.063; SRMR = 0.076). Different types of clinical studies fit well in the tool. However, RCT scored lower than prospective cohort and retrospective study in enrollment progress (7.02 vs. 7.43, 9.63, respectively).ConclusionThis study established a panoramic quality assessment tool based on the Delphi method and CFA, and the feasibility and effectiveness of the tool were verified through clinical research examples. The use of this tool can help project management departments effectively and dynamically manage research projects, rationally allocate resources, and ensure the quality of IITs.

Real world research

Points to consider: is there evidence to support BRCA1/2 and other inherited breast cancer genetic testing for all breast cancer patients? A statement of the American College of Medical Genetics and Genomics (ACMG)

Background: Breast cancer (BC) is the most common cancer in women all over the world and the second most common cause of cancer-related mortality. Imaging examination plays an important role in the diagnosis of early breast cancer. Due to different imaging principles and methods, all kinds of examinations have their advantages and disadvantages. It is particularly important for clinicians to choose these examination methods reasonably to achieve the best diagnostic effect. The objectives of this systematic review and NMA are to determine the diagnostic accuracy of imaging technologies for breast cancer and to compare the diagnostic accuracy of different index tests and to support guidelines development and clinical practice.Methods: PubMed, Embase.com, the Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang, and SinoMed will be searched to identify relevant studies up to August 31, 2021. We will include random controlled trials, cross-sectional studies, case-control studies, and cohort studies that evaluate the diagnostic accuracy of different imaging diagnostic methods for breast cancer. The Quality Assessment of Diagnostic Accuracy Studies 2 quality assessment tool will be used to assess the risk of bias in each study. Standard pairwise meta-analysis and NMA will be performed using STATA V.12.0, MetaDiSc 1.40, and R 3.4.1 software to compare the diagnostic efficacy of different imaging diagnostic methods. Subgroup analyses and sensitivity analyses will be conducted to investigate the sources of heterogeneity.Results: The results of this study will be published in a peer-reviewed journal.Conclusion: This study will comprehensively evaluate the accuracy of different imaging diagnostic methods in the diagnosis of breast cancer. The results of this study will provide high-quality evidence to support clinical practice and guidelines development.

This study evaluates the effectiveness of patient navigation to increase screening for colorectal, breast, and cervical cancer in populations adversely affected by health care disparities. Eligible studies were identified through English-language searches of Ovid® MEDLINE®, PsycINFO®, SocINDEX, and Veterans Affairs Health Services database (January 1, 1996, to July 5, 2019) and manual review of reference lists. Randomized trials and observational studies of relevant populations that evaluated the effectiveness of patient navigation on screening rates for colorectal, breast, or cervical cancer compared with usual or alternative care comparison groups were included. Two investigators independently abstracted study data and assessed study quality and applicability using criteria adapted from the U.S. Preventive Services Task Force. Discrepancies were resolved by consensus with a third reviewer. Results were combined using profile likelihood random effects models. Thirty-seven studies met inclusion criteria (28 colorectal, 11 breast, 4 cervical cancers including 3 trials with multiple cancer types). Screening rates were higher with patient navigation for colorectal cancer overall (risk ratio [RR] 1.64; 95% confidence interval [CI] 1.42 to 1.92; I2 = 93.7%; 22 trials) and by type of test (fecal occult blood or immunohistochemistry testing [RR 1.69; 95% CI 1.33 to 2.15; I2 = 80.5%; 6 trials]; colonoscopy/endoscopy [RR 2.08; 95% CI 1.08 to 4.56; I2 = 94.6%; 6 trials]). Screening was also higher with navigation for breast cancer (RR 1.50; 95% CI 1.22 to 1.91; I2 = 98.6%; 10 trials) and cervical cancer (RR 1.11; 95% CI 1.05 to 1.19; based on the largest trial). The high heterogeneity of cervical cancer studies prohibited meta-analysis. Results were similar for colorectal and breast cancer regardless of prior adherence to screening guidelines, follow-up time, and study quality. In populations adversely affected by disparities, colorectal, breast, and cervical cancer screening rates were higher in patients provided navigation services. Registration: PROSPERO: CRD42018109263.

Background: Scant evidence exists among the different psychological issues between patients with breast cancer and their spouses. The objective of our study was to develop the measuring instrument testing psychological reaction and compare the difference in psychological reaction between patients with breast cancer and their spouses during the period of diagnosis and treatment.Method: The semi-structured interview guideline was guided by the psychological stress model. In-depth interviews were conducted among patients with breast cancer and their spouses. Qualitative data was used to establish the item pool for the psychological reaction. Delphi method was used for item modifications. The items were conducted to find common factors through exploration factor analysis. Comparing the differences of common factors through t-test between patients with breast cancer and their spouses.Results: Five couples were interviewed directed by the semi-structured interview guideline. About 38 items were reserved to formulate the questionnaire through the Delphi method. A total of 391 respondents (216 patients and 175 spouses) were recruited to complete the questionnaire. Two common structures were found through exploration factor analysis, which was named as reaction to role and body image change and negative coping reaction. The t-test found that the dimension of reaction to role and body image change (95% CI = 2.34–5.01, p < 0.001) reflects the difference between patients with breast cancer and their spouses.Conclusion: The reactions to role and body image change between patients with breast cancer and their spouses are different during the period of diagnosis and treatment. Clinical workers should pay attention to the different reactions and help couples deal with breast cancer smoothly.

Health care policy backgroundFindings from scientific studies form the basis for evidence-based health policy decisions.Scientific backgroundQuality assessments to evaluate the credibility of study results are an essential part of health technology assessment reports and systematic reviews. Quality assessment tools (QAT) for assessing the study quality examine to what extent study results are systematically distorted by confounding or bias (internal validity). The tools can be divided into checklists, scales and component ratings.Research questionsWhat QAT are available to assess the quality of interventional studies or studies in the field of health economics, how do they differ from each other and what conclusions can be drawn from these results for quality assessments?MethodsA systematic search of relevant databases from 1988 onwards is done, supplemented by screening of the references, of the HTA reports of the German Agency for Health Technology Assessment (DAHTA) and an internet search. The selection of relevant literature, the data extraction and the quality assessment are carried out by two independent reviewers. The substantive elements of the QAT are extracted using a modified criteria list consisting of items and domains specific to randomized trials, observational studies, diagnostic studies, systematic reviews and health economic studies. Based on the number of covered items and domains, more and less comprehensive QAT are distinguished. In order to exchange experiences regarding problems in the practical application of tools, a workshop is hosted.ResultsA total of eight systematic methodological reviews is identified as well as 147 QAT: 15 for systematic reviews, 80 for randomized trials, 30 for observational studies, 17 for diagnostic studies and 22 for health economic studies. The tools vary considerably with regard to the content, the performance and quality of operationalisation. Some tools do not only include the items of internal validity but also the items of quality of reporting and external validity. No tool covers all elements or domains. Design-specific generic tools are presented, which cover most of the content criteria.DiscussionThe evaluation of QAT by using content criteria is difficult, because there is no scientific consensus on the necessary elements of internal validity, and not all of the generally accepted elements are based on empirical evidence. Comparing QAT with regard to contents neglects the operationalisation of the respective parameters, for which the quality and precision are important for transparency, replicability, the correct assessment and interrater reliability. QAT, which mix items on the quality of reporting and internal validity, should be avoided.ConclusionsThere are different, design-specific tools available which can be preferred for quality assessment, because of its wider coverage of substantive elements of internal validity. To minimise the subjectivity of the assessment, tools with a detailed and precise operationalisation of the individual elements should be applied. For health economic studies, tools should be developed and complemented with instructions, which define the appropriateness of the criteria. Further research is needed to identify study characteristics that influence the internal validity of studies.

Background Psychological symptoms such as depression and anxiety are quite common among stroke survivors and have great negative impacts on patients. Objective To develop a care bundle through reviewing and integrating care strategies for psychological symptoms after stroke and then improve the bundle by Delphi study. Methods A structured search of the literature was performed to identify studies evaluating interventions for stroke patients with psychological symptoms such as depression and anxiety. Two trained researchers screened papers through the titles, abstracts, and full-texts independently. All studies complying with the eligibility criteria were appraised using quality assessment tools. Related interventions with evaluated evidence levels formed the preliminary bundle. Afterward, the Delphi study was carried out to improve the bundle, and the experts were contacted by e-mail. Ten clinical experts specialized in stroke and psychological rehabilitation were recruited. The reliability of experts was represented by the effective response rate and authority coefficient (Cr). The consensus was deemed to be reached when the mean score for item importance is all equal or above 3.50 and the coefficient of variation (CV) is all equal or below 0.20. The Kendall coefficient W test was adopted to evaluate the consensus on agreement among the experts as well. Data analysis was performed using SPSS V.22.0. Results Through a systematic evidence summary and two-round Delphi study, the items that were given high scores and got consensus by experts were chosen for the bundle. The iDAME bundle consisted of five interventions eventually: maintaining Interaction, tailored Diet, Acupressure, mindfulness Meditation, and physical Exercise. Conclusion The development of an evidence-based and consensus-based iDAME bundle which integrated western and traditional Chinese medicine intervention was described. Evidence summary made the bundle become scientific, while the Delphi study made it more maneuverable. Based on these results, the bundle would be potentially implemented in stroke patients for their psychological symptoms.

To consider methods and related evidence for evaluating bias in non-randomised intervention studies. Systematic reviews and methodological papers were identified from a search of electronic databases; handsearches of key medical journals and contact with experts working in the field. New empirical studies were conducted using data from two large randomised clinical trials. Three systematic reviews and new empirical investigations were conducted. The reviews considered, in regard to non-randomised studies, (1) the existing evidence of bias, (2) the content of quality assessment tools, (3) the ways that study quality has been assessed and addressed. (4) The empirical investigations were conducted generating non-randomised studies from two large, multicentre randomised controlled trials (RCTs) and selectively resampling trial participants according to allocated treatment, centre and period. In the systematic reviews, eight studies compared results of randomised and non-randomised studies across multiple interventions using meta-epidemiological techniques. A total of 194 tools were identified that could be or had been used to assess non-randomised studies. Sixty tools covered at least five of six pre-specified internal validity domains. Fourteen tools covered three of four core items of particular importance for non-randomised studies. Six tools were thought suitable for use in systematic reviews. Of 511 systematic reviews that included non-randomised studies, only 169 (33%) assessed study quality. Sixty-nine reviews investigated the impact of quality on study results in a quantitative manner. The new empirical studies estimated the bias associated with non-random allocation and found that the bias could lead to consistent over- or underestimations of treatment effects, also the bias increased variation in results for both historical and concurrent controls, owing to haphazard differences in case-mix between groups. The biases were large enough to lead studies falsely to conclude significant findings of benefit or harm. Four strategies for case-mix adjustment were evaluated: none adequately adjusted for bias in historically and concurrently controlled studies. Logistic regression on average increased bias. Propensity score methods performed better, but were not satisfactory in most situations. Detailed investigation revealed that adequate adjustment can only be achieved in the unrealistic situation when selection depends on a single factor. Results of non-randomised studies sometimes, but not always, differ from results of randomised studies of the same intervention. Non-randomised studies may still give seriously misleading results when treated and control groups appear similar in key prognostic factors. Standard methods of case-mix adjustment do not guarantee removal of bias. Residual confounding may be high even when good prognostic data are available, and in some situations adjusted results may appear more biased than unadjusted results. Although many quality assessment tools exist and have been used for appraising non-randomised studies, most omit key quality domains. Healthcare policies based upon non-randomised studies or systematic reviews of non-randomised studies may need re-evaluation if the uncertainty in the true evidence base was not fully appreciated when policies were made. The inability of case-mix adjustment methods to compensate for selection bias and our inability to identify non-randomised studies that are free of selection bias indicate that non-randomised studies should only be undertaken when RCTs are infeasible or unethical. Recommendations for further research include: applying the resampling methodology in other clinical areas to ascertain whether the biases described are typical; developing or refining existing quality assessment tools for non-randomised studies; investigating how quality assessments of non-randomised studies can be incorporated into reviews and the implications of individual quality features for interpretation of a review's results; examination of the reasons for the apparent failure of case-mix adjustment methods; and further evaluation of the role of the propensity score.

BackgroundThe usability of electronic health (eHealth) and mobile health apps is of paramount importance as it impacts the quality of care. Methodological quality assessment is a common practice in the field of health for different designs and types of studies. However, we were unable to find a scale to assess the methodological quality of studies on the usability of eHealth products or services.ObjectiveThis study aimed to develop a scale to assess the methodological quality of studies assessing usability of mobile apps and to perform a preliminary analysis of of the scale’s feasibility, reliability, and construct validity on studies assessing usability of mobile apps, measuring aspects of physical activity.MethodsA 3-round Delphi panel was used to generate a pool of items considered important when assessing the quality of studies on the usability of mobile apps. These items were used to write the scale and the guide to assist its use. The scale was then used to assess the quality of studies on usability of mobile apps for physical activity, and it assessed in terms of feasibility, interrater reliability, and construct validity.ResultsA total of 25 experts participated in the Delphi panel, and a 15-item scale was developed. This scale was shown to be feasible (time of application mean 13.10 [SD 2.59] min), reliable (intraclass correlation coefficient=0.81; 95% CI 0.55-0.93), and able to discriminate between low- and high-quality studies (high quality: mean 9.22 [SD 0.36]; low quality: mean 6.86 [SD 0.80]; P=.01).ConclusionsThe scale that was developed can be used both to assess the methodological quality of usability studies and to inform its planning.