BackgroundThe area under the receiver operating characteristic (ROC) curve, referred to as the AUC, is an appropriate measure for describing the overall accuracy of a diagnostic test or a biomarker in early phase trials without having to choose a threshold. There are many approaches for estimating the confidence interval for the AUC. However, all are relatively complicated to implement. Furthermore, many approaches perform poorly for large AUC values or small sample sizes.MethodsThe AUC is actually a probability. So we propose a modified Wald interval for a single proportion, which can be calculated on a pocket calculator. We performed a simulation study to compare this modified Wald interval (without and with continuity correction) with other intervals regarding coverage probability and statistical power.ResultsThe main result is that the proposed modified Wald intervals maintain and exploit the type I error much better than the intervals of Agresti-Coull, Wilson, and Clopper-Pearson. The interval suggested by Bamber, the Mann-Whitney interval without transformation and also the interval of the binormal AUC are very liberal. For small sample sizes the Wald interval with continuity has a comparable coverage probability as the LT interval and higher power. For large sample sizes the results of the LT interval and of the Wald interval without continuity correction are comparable.ConclusionsIf individual patient data is not available, but only the estimated AUC and the total sample size, the modified Wald intervals can be recommended as confidence intervals for the AUC. For small sample sizes the continuity correction should be used.

Presentation of patients with acute GIB in the ED is age and sex specific and shows seasonal and circadian differences in distribution, with an increased incidence in winter months and during night-time. This should be considered when determining possible emergency endoscopic interventions and the availability of emergency endoscopy services.

Here, we identified prognostic factors and propose a prognostic score to estimate survival, which can be applied to all patients independent of tumour site and before initial treatment. Further validation in prospective trials is required.

In the context of both drug licensing and reimbursement, the target population is sometimes restricted to a specific subgroup. In the setting of drug licensing the discussion concerns a negative benefit/risk assessment in a relevant subgroup. For reimbursement the debate involves the detection of an additional benefit compared with standard treatment, which can in some situations not be accepted for the overall study population. In their Methods Paper, the Institute for Quality and Efficiency in Health Care (IQWiG) refers to published articles that name criteria for the evaluation of credibility to claim a therapeutic effect on the basis of results in the subgroups of a study population (BMJ 340:850-854, 2010). A number of these criteria have found their way into the regulatory debate, which was recently published in a draft guideline of the European Medicines Agency (EMA). However, the significance of the interaction/heterogeneity test has been mentioned as one criterion for the credibility of a finding in a subgroup of the study population. This aspect is critically challenged in our paper. In our estimation, the application of this criterion hinders the critical discussion of whether a global treatment effect is applicable to relevant subgroups of a study population and the potential implications of this. We feel that biostatistical support for decision-making strategies should be the same in both worlds, even though in some instances the outcomes in a specific situation may be different, depending on the objective to be demonstrated.