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Many abstracts of diagnostic accuracy studies are currently insufficiently informative. We extended the STARD (Standards for Reporting Diagnostic Accuracy) statement by developing a list of essential items that authors should consider when reporting diagnostic accuracy studies in journal or conference abstracts. After a literature review of published guidance for reporting biomedical studies, we identified 39 items potentially relevant to report in an abstract. We then selected essential items through a two round web based survey among the 85 members of the STARD Group, followed by discussions within an executive committee. Seventy three STARD Group members responded (86%), with 100% completion rate. STARD for Abstracts is a list of 11 quintessential items, to be reported in every abstract of a diagnostic accuracy study. We provide examples of complete reporting, and developed template text for writing informative abstracts.

BACKGROUND AND AIM: Elevated alanine transaminase (ALT) is a strong predictor of metabolic syndrome, but there are few data from the Australian population. We aimed to determine the prevalence of elevated ALT and association with metabolic risk factors. METHODS: In this cross-sectional study including adult participants (N = 9,447) from a nationwide, population-based survey, we assessed the prevalence of elevated ALT [defined as ≥ 40 IU/L (men) and ≥ 30 IU/L (women) as baseline, and ALT as ≥ 30 IU/L (men) and ≥ 19 IU/L (women) as lower threshold], distribution of metabolic risk factors, and independent predictors of elevated ALT in logistic regression models. Analyses were weighted to the population with population weights. RESULTS: Elevated ALT levels were found in 11.2% of the Australian population. People with elevated ALT were younger (43 vs 46 yrs) with more truncal adiposity (100 vs 91 cm), higher pro-atherogenic lipids and glucose and exercised less (120 vs 160 min per week, P

Incomplete reporting has been identified as a major source of avoidable waste in biomedical research. Essential information is often not provided in study reports, impeding the identification, critical appraisal, and replication of studies. To improve the quality of reporting of diagnostic accuracy studies, the Standards for Reporting of Diagnostic Accuracy Studies (STARD) statement was developed. Here we present STARD 2015, an updated list of 30 essential items that should be included in every report of a diagnostic accuracy study. This update incorporates recent evidence about sources of bias and variability in diagnostic accuracy and is intended to facilitate the use of STARD. As such, STARD 2015 may help to improve completeness and transparency in reporting of diagnostic accuracy studies.

The validity and practical utility of observational medical research depends critically on good study design, excellent data quality, appropriate statistical methods and accurate interpretation of results. Statistical methodology has seen substantial development in recent times. Unfortunately, many of these methodological developments are ignored in practice. Consequently, design and analysis of observational studies often exhibit serious weaknesses. The lack of guidance on vital practical issues discourages many applied researchers from using more sophisticated and possibly more appropriate methods when analyzing observational studies. Furthermore, many analyses are conducted by researchers with a relatively weak statistical background and limited experience in using statistical methodology and software. Consequently, even 'standard' analyses reported in the medical literature are often flawed, casting doubt on their results and conclusions. An efficient way to help researchers to keep up with recent methodological developments is to develop guidance documents that are spread to the research community at large. These observations led to the initiation of the strengthening analytical thinking for observational studies (STRATOS) initiative, a large collaboration of experts in many different areas of biostatistical research. The objective of STRATOS is to provide accessible and accurate guidance in the design and analysis of observational studies. The guidance is intended for applied statisticians and other data analysts with varying levels of statistical education, experience and interests. In this article, we introduce the STRATOS initiative and its main aims, present the need for guidance documents and outline the planned approach and progress so far. We encourage other biostatisticians to become involved.

Objectives To determine the accuracy of a clinical decision rule (the traffic light system developed by the National Institute for Health and Clinical Excellence (NICE)) for detecting three common serious bacterial infections (urinary tract infection, pneumonia, and bacteraemia) in young febrile children. Design Retrospective analysis of data from a two year prospective cohort study Setting A paediatric emergency department. Participants 15 781 cases of children under 5 years of age presenting with a febrile illness. Main outcome measures Clinical features were used to categorise each febrile episodes as low, intermediate, or high probability of serious bacterial infection (green, amber, and red zones of the traffic light system); these results were checked (using standard radiological and microbiological tests) for each of the infections of interest and for any serious bacterial infection. Results After combination of the intermediate and high risk categories, the NICE traffic light system had a test sensitivity of 85.8% (95% confidence interval 83.6% to 87.7%) and specificity of 28.5% (27.8% to 29.3%) for the detection of any serious bacterial infection. Of the 1140 cases of serious bacterial infection, 157 (13.8%) were test negative (in the green zone), and, of these, 108 (68.8%) were urinary tract infections. Adding urine analysis (leucocyte esterase or nitrite positive), reported in 3653 (23.1%) episodes, to the traffic light system improved the test performance: sensitivity 92.1% (89.3% to 94.1%), specificity 22.3% (20.9% to 23.8%), and relative positive likelihood ratio 1.10 (1.06 to 1.14). Conclusion The NICE traffic light system failed to identify a substantial proportion of serious bacterial infections, particularly urinary tract infections. The addition of urine analysis significantly improved test sensitivity, making the traffic light system a more useful triage tool for the detection of serious bacterial infections in young febrile children.

Carbohydrate-deficient transferrin (CDT) has been used as a test for excessive alcohol consumption in research, clinical, and medico-legal settings, but there remain conflicting data on its accuracy, with sensitivities ranging from20% to 100%. We examined evidence of its benefit over a conventional and less expensive test, gamma-glutamyltransferase (GGT), and compared the accuracy of different CDT assay methods.We performed a systematic review using summary ROC analysis of 110 studies prior to June 1998 on the use of CDT in the detection of alcohol dependence or hazardous/harmful alcohol use.We identified several potential sources of bias in studies. In studies examining CDT and GGT in the same subjects, subject characteristics were less likely to influence the comparison. In such paired studies, the original Pharmacia CDT assay was significantly more accurate than GGT, but the modified CDTect assay did not perform as well as the original and was not significantly better than GGT. The accuracy of the AXIS %CDT assay was statistically indistinguishable from modified CDTect. Several CDT assay methods appeared promising, in particular, liquid chromatography (chromatofocusing, HPLC, fast protein liquid chromatography) and isoelectric focusing, but there were insufficient paired studies from which to draw firm conclusions.In studies published before June 1998, the results obtained with commercially available CDT assays were not significantly better than GGT as markers of excessive alcohol use in paired studies. Further high-quality studies comparing CDTect (modified) and other CDT assays with GGT in the same subjects are needed.