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If trials with a positive conclusion have more discrepancies than trials with a negative conclusion, this may mean that discrepancies are used to spin trial conclusions towards a positive direction. Two independent investigators (CAvdB and PCS) will independently classify the trials, and solve differences by consensus. Data analysis According to the objectives of the study, we will analyse three end points (table 1): non-publication, discrepancies between the protocol and the publication as a proxy for selective publication and the direction of publication conclusions. Non-publication In a survival analysis of the non-publication rate, only trials that started inclusion will be analysed (box C1 of figure 1). The end point used is non-publication as peer-reviewed article, according to the definition provided above. The trial end date marks the start of follow-up (ie, the date the trial transits to the stage of progress D1 or D2, figure 1). We chose this date instead of the date of IRB approval because the trials in the cohort might differ in time span. This time span may depend, for example, on the phase of the trial and the number of participants to be recruited. In case of multiple publications of one trial protocol, we use the publication date of the primary publication. We assume that all trials that started including patients are eligible for publication. Thus, the population of the non-publication survival analysis includes all trials that started inclusion (box C1, figure 1). Trials that never started inclusion are excluded from this analysis. To identify characteristics that are associated with (non-)publication, we perform Cox regression analysis to PDE4B estimate the strength of the association between characteristics and publication status, expressed as HRs and 95% CIs. Since trials of oncolytic drugs are different with respect to the disease severity compared to most trials in other therapeutic areas (which may affect publication), a stratified analysis will be conducted as well. In addition, we will tabulate reasons for non-publication. Finally, we will describe the means of publication by other means than by the definition of publication. By doing so, we will identify the subset of trials with no results reported at all (not as peer-reviewed article and not by any other means). Selective publication For each of the seven discrepancy-items, we calculate the proportion of trials with the discrepancy. We investigate the association between characteristics and discrepancies for each item (��2 test) and for the total discrepancy summary score (paired t test). We will use multivariate logistic (individual discrepancies) and linear (total discrepancy score) regression models to estimate the strength of the association of characteristics and publication status, expressed as ORs and 95% CIs.