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Biomedical subjects

Anne W S Rutjes

Publications and source records attributed to Anne W S Rutjes.

11 recordsLinked to original sources
PubMed2006

The haematocrit and platelet target in polycythemia vera.

Polycythemia vera (PV) is a chronic myeloproliferative disorder whose major morbidity and mortality are thrombohaemorragic events and progression to acute leukaemia or myelofibrosis. Whether the haematocrit and platelet count predict such complications remains unclear. The European Collaboration on Low-dose Aspirin in Polycythemia Vera prospective study included 1638 PV patients. A total of 164 deaths (10%), 145 (8.85%) major thrombosis and 226 (13.8%) total thrombosis were encountered during 4393 person-years follow-up (median 2.8 years). In time-dependent multivariable analysis, a haematocrit in the evaluable range of 40-55% was neither associated with the occurrence of thrombotic events, mortality nor with haematological progression in the studied population. The haematocrit of patients in the highest and lowest deciles at baseline was maintained within a narrow interval of haematocrit values ranging from 40% to 47% throughout follow-up. High platelet count was associated with a lower progression rate to acute leukaemia/myelofibrosis, whereas it had no significant relationship with thrombotic events or mortality. Our findings do not suggest that the range of haematocrit (<55%) and platelet counts (<600 x 10(9)/l) we encountered in our population had an impact on the outcome of PV patients treated by current therapeutic strategies.

Aged↗
PubMed2006

Reproducibility of the STARD checklist: an instrument to assess the quality of reporting of diagnostic accuracy studies.

BACKGROUND: In January 2003, STAndards for the Reporting of Diagnostic accuracy studies (STARD) were published in a number of journals, to improve the quality of reporting in diagnostic accuracy studies. We designed a study to investigate the inter-assessment reproducibility, and intra- and inter-observer reproducibility of the items in the STARD statement. METHODS: Thirty-two diagnostic accuracy studies published in 2000 in medical journals with an impact factor of at least 4 were included. Two reviewers independently evaluated the quality of reporting of these studies using the 25 items of the STARD statement. A consensus evaluation was obtained by discussing and resolving disagreements between reviewers. Almost two years later, the same studies were evaluated by the same reviewers. For each item, percentages agreement and Cohen's kappa between first and second consensus assessments (inter-assessment) were calculated. Intraclass Correlation coefficients (ICC) were calculated to evaluate its reliability. RESULTS: The overall inter-assessment agreement for all items of the STARD statement was 85% (Cohen's kappa 0.70) and varied from 63% to 100% for individual items. The largest differences between the two assessments were found for the reporting of the rationale of the reference standard (kappa 0.37), number of included participants that underwent tests (kappa 0.28), distribution of the severity of the disease (kappa 0.23), a cross tabulation of the results of the index test by the results of the reference standard (kappa 0.33) and how indeterminate results, missing data and outliers were handled (kappa 0.25). Within and between reviewers, also large differences were observed for these items. The inter-assessment reliability of the STARD checklist was satisfactory (ICC = 0.79 [95% CI: 0.62 to 0.89]). CONCLUSION: Although the overall reproducibility of the quality of reporting on diagnostic accuracy studies using the STARD statement was found to be good, substantial disagreements were found for specific items. These disagreements were not so much caused by differences in interpretation of the items by the reviewers but rather by difficulties in assessing the reporting of these items due to lack of clarity within the articles. Including a flow diagram in all reports on diagnostic accuracy studies would be very helpful in reducing confusion between readers and among reviewers.

Advisory Committees↗
PubMed2006

Evaluation of QUADAS, a tool for the quality assessment of diagnostic accuracy studies.

BACKGROUND: A quality assessment tool for diagnostic accuracy studies, named QUADAS, has recently been developed. Although QUADAS has been used in several systematic reviews, it has not been formally validated. The objective was to evaluate the validity and usefulness of QUADAS. METHODS: Three reviewers independently rated the quality of 30 studies using QUADAS. We assessed the proportion of agreements between each reviewer and the final consensus rating. This was done for all QUADAS items combined and for each individual item. Twenty reviewers who had used QUADAS in their reviews completed a short structured questionnaire on their experience of QUADAS. RESULTS: Over all items, the agreements between each reviewer and the final consensus rating were 91%, 90% and 85%. The results for individual QUADAS items varied between 50% and 100% with a median value of 90%. Items related to uninterpretable test results and withdrawals led to the most disagreements. The feedback on the content of the tool was generally positive with only small numbers of reviewers reporting problems with coverage, ease of use, clarity of instructions and validity. CONCLUSION: Major modifications to the content of QUADAS itself are not necessary. The evaluation highlighted particular difficulties in scoring the items on uninterpretable results and withdrawals. Revised guidelines for scoring these items are proposed. It is essential that reviewers tailor guidelines for scoring items to their review, and ensure that all reviewers are clear on how to score studies. Reviewers should consider whether all QUADAS items are relevant to their review, and whether additional quality items should be assessed as part of their review.

Consensus↗
PubMed2006

Evidence of bias and variation in diagnostic accuracy studies.

BACKGROUND: Studies with methodologic shortcomings can overestimate the accuracy of a medical test. We sought to determine and compare the direction and magnitude of the effects of a number of potential sources of bias and variation in studies on estimates of diagnostic accuracy. METHODS: We identified meta-analyses of the diagnostic accuracy of tests through an electronic search of the databases MEDLINE, EMBASE, DARE and MEDION (1999-2002). We included meta-analyses with at least 10 primary studies without preselection based on design features. Pairs of reviewers independently extracted study characteristics and original data from the primary studies. We used a multivariable meta-epidemiologic regression model to investigate the direction and strength of the association between 15 study features on estimates of diagnostic accuracy. RESULTS: We selected 31 meta-analyses with 487 primary studies of test evaluations. Only 1 study had no design deficiencies. The quality of reporting was poor in most of the studies. We found significantly higher estimates of diagnostic accuracy in studies with nonconsecutive inclusion of patients (relative diagnostic odds ratio [RDOR] 1.5, 95% confidence interval [CI] 1.0-2.1) and retrospective data collection (RDOR 1.6, 95% CI 1.1-2.2). The estimates were highest in studies that had severe cases and healthy controls (RDOR 4.9, 95% CI 0.6-37.3). Studies that selected patients based on whether they had been referred for the index test, rather than on clinical symptoms, produced significantly lower estimates of diagnostic accuracy (RDOR 0.5, 95% CI 0.3-0.9). The variance between meta-analyses of the effect of design features was large to moderate for type of design (cohort v. case-control), the use of composite reference standards and the use of differential verification; the variance was close to zero for the other design features. INTERPRETATION: Shortcomings in study design can affect estimates of diagnostic accuracy, but the magnitude of the effect may vary from one situation to another. Design features and clinical characteristics of patient groups should be carefully considered by researchers when designing new studies and by readers when appraising the results of such studies. Unfortunately, incomplete reporting hampers the evaluation of potential sources of bias in diagnostic accuracy studies.

Clinical Trials as Topic↗
PubMed2005

Case-control and two-gate designs in diagnostic accuracy studies.

BACKGROUND: In some diagnostic accuracy studies, the test results of a series of patients with an established diagnosis are compared with those of a control group. Such case-control designs are intuitively appealing, but they have also been criticized for leading to inflated estimates of accuracy. METHODS: We discuss similarities and differences between diagnostic and etiologic case-control studies, as well as the mechanisms that can lead to variation in estimates of diagnostic accuracy in studies with separate sampling schemes ("gates") for diseased (cases) and nondiseased individuals (controls). RESULTS: Diagnostic accuracy studies are cross-sectional and descriptive in nature. Etiologic case-control studies aim to quantify the effect of potential causal exposures on disease occurrence, which inherently involves a time window between exposure and disease occurrence. Researchers and readers should be aware of spectrum effects in diagnostic case-control studies as a result of the restricted sampling of cases and/or controls, which can lead to changes in estimates of diagnostic accuracy. These spectrum effects may be advantageous in the early investigation of a new diagnostic test, but for an overall evaluation of the clinical performance of a test, case-control studies should closely mimic cross-sectional diagnostic studies. CONCLUSIONS: As the accuracy of a test is likely to vary across subgroups of patients, researchers and clinicians might carefully consider the potential for spectrum effects in all designs and analyses, particularly in diagnostic accuracy studies with differential sampling schemes for diseased (cases) and nondiseased individuals (controls).

Case-Control Studies↗
PubMed2005

Quality of reporting of diagnostic accuracy studies.

PURPOSE: To evaluate quality of reporting in diagnostic accuracy articles published in 2000 in journals with impact factor of at least 4 by using items of Standards for Reporting of Diagnostic Accuracy (STARD) statement published later in 2003. MATERIALS AND METHODS: English-language articles on primary diagnostic accuracy studies in 2000 were identified with validated search strategy in MEDLINE. Articles published in journals with impact factor of 4 or higher that regularly publish articles on diagnostic accuracy were selected. Two independent reviewers evaluated quality of reporting by using STARD statement, which consists of 25 items and encourages use of a flow diagram. Total STARD score for each article was calculated by summing number of reported items. Subgroup analyses were performed for study design (case-control or cohort study) by using Student t tests for continuous outcomes and chi(2) tests for dichotomous outcomes. RESULTS: Included were 124 articles published in 2000 in 12 journals: 33 case-control and 91 cohort studies. Only 41% of articles (51 of 124) reported on more than 50% of STARD items, while no articles reported on more than 80%. A flow chart was presented in two articles. Assessment of reporting on individual items of STARD statement revealed wide variation, with some items described in 11% of articles and others in 92%. Mean STARD score (0-25 points available) was 11.9 (range, 3.5-19.5). Mean difference in STARD score between cohort studies and case-control studies was 1.53 (95% confidence interval: 0.24, 2.82). CONCLUSION: Quality of reporting in diagnostic accuracy articles published in 2000 is less than optimal, even in journals with high impact factor. Authors, editors, and reviewers should pay more attention to reporting by checking STARD statement items and including a flow diagram to represent study design and patient flow.

Case-Control Studies↗
PubMed2005

A systematic review finds that diagnostic reviews fail to incorporate quality despite available tools.

BACKGROUND AND OBJECTIVE: To review existing quality assessment tools for diagnostic accuracy studies and to examine to what extent quality was assessed and incorporated in diagnostic systematic reviews. METHODS: Electronic databases were searched for tools to assess the quality of studies of diagnostic accuracy or guides for conducting, reporting or interpreting such studies. The Database of Abstracts of Reviews of Effects (DARE; 1995-2001) was used to identify systematic reviews of diagnostic studies to examine the practice of quality assessment of primary studies. RESULTS: Ninety-one quality assessment tools were identified. Only two provided details of tool development, and only a small proportion provided any indication of the aspects of quality they aimed to assess. None of the tools had been systematically evaluated. We identified 114 systematic reviews, of which 58 (51%) had performed an explicit quality assessment and were further examined. The majority of reviews used more than one method of incorporating quality. CONCLUSION: Most tools to assess the quality of diagnostic accuracy studies do not start from a well-defined definition of quality. None has been systematically evaluated. The majority of existing systematic reviews fail to take differences in quality into account. Reviewers should consider quality as a possible source of heterogeneity.

Bias↗
PubMed2005

Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews.

BACKGROUND AND OBJECTIVES: Studies of diagnostic accuracy most often report pairs of sensitivity and specificity. We demonstrate the advantage of using bivariate meta-regression models to analyze such data. METHODS: We discuss the methodology of both the summary Receiver Operating Characteristic (sROC) and the bivariate approach by reanalyzing the data of a published meta-analysis. RESULTS: The sROC approach is the standard method for meta-analyzing diagnostic studies reporting pairs of sensitivity and specificity. This method uses the diagnostic odds ratio as the main outcome measure, which removes the effect of a possible threshold but at the same time loses relevant clinical information about test performance. The bivariate approach preserves the two-dimensional nature of the original data. Pairs of sensitivity and specificity are jointly analyzed, incorporating any correlation that might exist between these two measures using a random effects approach. Explanatory variables can be added to the bivariate model and lead to separate effects on sensitivity and specificity, rather than a net effect on the odds ratio scale as in the sROC approach. The statistical properties of the bivariate model are sound and flexible. CONCLUSION: The bivariate model can be seen as an improvement and extension of the traditional sROC approach.

Data Interpretation, Statistical↗
PubMed2004

Sources of variation and bias in studies of diagnostic accuracy: a systematic review.

BACKGROUND: Studies of diagnostic accuracy are subject to different sources of bias and variation than studies that evaluate the effectiveness of an intervention. Little is known about the effects of these sources of bias and variation. PURPOSE: To summarize the evidence on factors that can lead to bias or variation in the results of diagnostic accuracy studies. DATA SOURCES: MEDLINE, EMBASE, and BIOSIS, and the methodologic databases of the Centre for Reviews and Dissemination and the Cochrane Collaboration. Methodologic experts in diagnostic tests were contacted. STUDY SELECTION: Studies that investigated the effects of bias and variation on measures of test performance were eligible for inclusion, which was assessed by one reviewer and checked by a second reviewer. Discrepancies were resolved through discussion. DATA EXTRACTION: Data extraction was conducted by one reviewer and checked by a second reviewer. DATA SYNTHESIS: The best-documented effects of bias and variation were found for demographic features, disease prevalence and severity, partial verification bias, clinical review bias, and observer and instrument variation. For other sources, such as distorted selection of participants, absent or inappropriate reference standard, differential verification bias, and review bias, the amount of evidence was limited. Evidence was lacking for other features, including incorporation bias, treatment paradox, arbitrary choice of threshold value, and dropouts. CONCLUSIONS: Many issues in the design and conduct of diagnostic accuracy studies can lead to bias or variation; however, the empirical evidence about the size and effect of these issues is limited.

Bias↗
PubMed2003

The development of QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews.

BACKGROUND: In the era of evidence based medicine, with systematic reviews as its cornerstone, adequate quality assessment tools should be available. There is currently a lack of a systematically developed and evaluated tool for the assessment of diagnostic accuracy studies. The aim of this project was to combine empirical evidence and expert opinion in a formal consensus method to develop a tool to be used in systematic reviews to assess the quality of primary studies of diagnostic accuracy. METHODS: We conducted a Delphi procedure to develop the quality assessment tool by refining an initial list of items. Members of the Delphi panel were experts in the area of diagnostic research. The results of three previously conducted reviews of the diagnostic literature were used to generate a list of potential items for inclusion in the tool and to provide an evidence base upon which to develop the tool. RESULTS: A total of nine experts in the field of diagnostics took part in the Delphi procedure. The Delphi procedure consisted of four rounds, after which agreement was reached on the items to be included in the tool which we have called QUADAS. The initial list of 28 items was reduced to fourteen items in the final tool. Items included covered patient spectrum, reference standard, disease progression bias, verification bias, review bias, clinical review bias, incorporation bias, test execution, study withdrawals, and indeterminate results. The QUADAS tool is presented together with guidelines for scoring each of the items included in the tool. CONCLUSIONS: This project has produced an evidence based quality assessment tool to be used in systematic reviews of diagnostic accuracy studies. Further work to determine the usability and validity of the tool continues.

Bias↗