In addition, they must provide direct access to all necessary study documents, including original patient documents relevant to the study. is expected to finish in December 2016. Conclusions The early identification of patients who are responding to an anti-TNF antibody is therapeutically beneficial. At the same time, patients who are not responding can be identified earlier. The development of a therapeutic algorithm for identifying patients as responders or non-responders can thus help prescribing physicians to both avoid ineffective treatments and adjust dosages when necessary. This in turn promotes a higher degree of treatment tolerance and patient safety in the case of anti-TNF antibody administration. ClinicalTrial German Clinical Trials Register, Deutsches Register Klinischer Studien DRKS00005940; https://drks-neu.uniklinik-freiburg.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00005940 (Archived by WebCite at http://www.webcitation.org/6i4Xoo1sH) values obtained are thus interpreted according to Fishers method: a value is considered a metric value, and the smaller the value, the larger the significance of the corresponding effect. No interim analyses are planned. Data analysis is carried out only once, at the end of the study. Hypotheses The following two-tailed test problem is used for the primary outcome: Hypothesis 0: beta1=0 versus Hypothesis 1: beta10, where beta1 is the coefficient of the logistic regression model, and null hypothesis: H0. There is no correlation between a significant reduction in fecal calprotectin of 50% from baseline in Week 6 and clinical response to therapy with golimumab in Week 26. Therefore, our research hypothesis, H1, is that there is a (S,R,S)-AHPC-PEG3-NH2 correlation between a significant reduction in fecal calprotectin of 50% from baseline in Week 6 and clinical response to therapy with golimumab in Week 26. Sample Size Rationale Sample size is planned based on data from studies researching a correlation between fecal calprotectin and response to an anti-TNF therapy. De Vos et al [10] (S,R,S)-AHPC-PEG3-NH2 describe response rates as: After 10 weeks anti-TNF therapy induced endoscopic remission in 63% (confidence interval: 47C78%) of patients. Molander et al [11] describe the correlation between the predictive quality of fecal calprotectin and the remission rate. The results are displayed in Table 1. Table 1 Cross classification of fecal calprotectin predictive quality and remission. thead br / Fecal calprotectin declineTotal br / YesNo /thead Remission br / br / br / br / Yes30333 br / No62127Total362460 Open in a separate window Based on these results, the odds ratio (OR) is calculated as OR (30*21) / (6*3)=35. It should be noted that for the above study the cut-off point for fecal calprotectin decline was a reduction of 75% from baseline. Lower cut-off points, for example, a 50% reduction, would lead to smaller OR, as the number of individuals with neither decrease nor response is definitely described as becoming almost constant in the above-mentioned literature: Absence of decrease in calprotectin levels at week 6 recognized individuals resistant to the treatment [11]. It is therefore assumed for sample size (S,R,S)-AHPC-PEG3-NH2 calculation that 80% of the individuals will have a fecal calprotectin decrease. Table 2 summarizes the scenarios that have been taken into consideration. Table 2 Sample size rationale: Response rates and their effect on producing OR for 9 different scenarios. thead ScenarioResponse rate (%)OR /thead 140102402034030450105502065030760108602096030 Open in a separate (S,R,S)-AHPC-PEG3-NH2 window Calculation Sample size calculation is definitely carried out with the statistical analysis software SAS. Table 3 shows the required quantity of evaluable individuals for each scenario. It is expected that 5% of the intention-to-treat basic principle population will become excluded. Sample size is definitely inversely proportional GDF5 to the OR and the response rate. Table 3 Sample size calculation: Quantity of evaluable subject and total number of subjects considering dropouts for 9 different scenarios. thead ScenarioResponse rate, %OREvaluable subjects, nSubjects including potential dropouts, br / total n /thead 140105861240204042340303436450105053550203436650302931760104548860203133960302628 Open in a separate window To prevent study failure due to an underpowered study, a worst case scenario with a response rate of 40% and an OR of 10 is (S,R,S)-AHPC-PEG3-NH2 used like a basis for sample size. A total of 58 evaluable subjects are consequently necessary for the trial, therefore 61 individuals must be recruited. Study Populace The evaluation of main and secondary results is definitely carried out according to the intention-to-treat basic principle. The related populace comprises all individuals included in the study no matter possible protocol violations.