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Objectives The purpose of this study was to understand the possible risk of discontinuation in the context of clinical care. Background Rivaroxaban is noninferior to warfarin for preventing stroke in atrial fibrillation patients. Concerns exist regarding possible increased risk of stroke and non–central nervous system (CNS) thromboembolic events early after discontinuation of rivaroxaban. Methods We undertook a post-hoc analysis of data from the ROCKET AF (Rivaroxaban Once-Daily, Oral, Direct Factor Xa Inhibition Compared With Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation, n = 14,624) for stroke or non-CNS embolism within 30 days after temporary interruptions of 3 days or more, early permanent study drug discontinuation, and end-of-study transition to open-label therapy. Results Stroke and non-CNS embolism occurred at similar rates after temporary interruptions (rivaroxaban: n = 9, warfarin: n = 8, 6.20 vs. 5.05/100 patient-years, hazard ratio [HR]: 1.28, 95% confidence interval [CI]: 0.49 to 3.31, p = 0.62) and after early permanent discontinuation (rivaroxaban: n = 42, warfarin: n = 36, 25.60 vs. 23.28/100 patient-years, HR: 1.10, 95% CI: 0.71 to 1.72, p = 0.66). Patients transitioning to open-label therapy at the end of the study had more strokes with rivaroxaban (n = 22) versus warfarin (n = 6, 6.42 vs. 1.73/100 patient-years, HR: 3.72, 95% CI: 1.51 to 9.16, p = 0.0044) and took longer to reach a therapeutic international normalized ratio with rivaroxaban versus warfarin. All thrombotic events within 30 days of any study drug cessation (including stroke, non-CNS embolism, myocardial infarction, and vascular death) were similar between groups (HR: 1.02, 95% CI: 0.83 to 1.26, p = 0.85). Conclusions In atrial fibrillation patients who temporarily or permanently discontinued anticoagulation, the risk of stroke or non-CNS embolism was similar with rivaroxaban or warfarin. An increased risk of stroke and non-CNS embolism was observed in rivaroxaban-treated patients compared with warfarin-treated patients after the end of the study, underscoring the importance of therapeutic anticoagulation coverage during such a transition.

Background: The potential impact of missing data on the results of clinical trials has received heightened attention recently. A National Research Council study provides recommendations for limiting missing data in clinical trial design and conduct, and principles for analysis, including the need for sensitivity analyses to assess robustness of findings to alternative assumptions about the missing data. A Food and Drug Administration advisory committee raised missing data as a serious concern in their review of results from the ATLAS ACS 2 TIMI 51 study, a large clinical trial that assessed rivaroxaban for its ability to reduce the risk of cardiovascular death, myocardial infarction or stroke in patients with acute coronary syndrome. This case study describes a variety of measures that were taken to address concerns about the missing data. Methods: A range of analyses are described to assess the potential impact of missing data on conclusions. In particular, measures of the amount of missing data are discussed, and the fraction of missing information from multiple imputation is proposed as an alternative measure. The sensitivity analysis in the National Research Council study is modified in the context of survival analysis where some individuals are lost to follow-up. The impact of deviations from ignorable censoring is assessed by differentially increasing the hazard of the primary outcome in the treatment groups and multiply imputing events between dropout and the end of the study. Tipping-point analyses are described, where the deviation from ignorable censoring that results in a reversal of significance of the treatment effect is determined. A study to determine the vital status of participants lost to follow-up was also conducted, and the results of including this additional information are assessed. Results: Sensitivity analyses suggest that findings of the ATLAS ACS 2 TIMI 51 study are robust to missing data; this robustness is reinforced by the follow-up study, since inclusion of data from this study had little impact on the study conclusions. Conclusion: Missing data are a serious problem in clinical trials. The methods presented here, namely, the sensitivity analyses, the follow-up study to determine survival of missing cases, and the proposed measurement of missing data via the fraction of missing information, have potential application in other studies involving survival analysis where missing data are a concern.

Summary Purpose: To identify and validate the efficacious monotherapy dosing regimen for topiramate in children aged 2 to

A Food and Drug Administration (FDA)/Industry/Academic Panel Discussion on multiplicity aspects of a real Phase III clinical trial was held at the Third International Conference on Multiple Comparisons, August 6, 2002, in Bethesda, Maryland. The goal was to develop some consensus among industry, government, and academic statisticians concerning requirements and methods for multiplicity management in typical clinical trials. The session was tape-recorded; this article mostly comes from an edited transcript.

Graphical data exploration of clinical trial results is an imperative step prior to any model-based analyses. Thorough understanding of the raw data and the biological and statistical significances will certainly increase the likelihood of constructing a useful model and evade excessive complex data representation and overfitting. In this work, we use graphical data exploration to assess the cardiovascular safety of Drug X by estimating the propensity for the drug to alter the duration of the QT interval. We also identify model building strategies and the potential models that may be tested incrementally. Insights gained from this exercise will improve the efficiency of the model building process, communicate a clear and simple representation for complex data, and provide a useful decision making instrument for the drug development program.

Telemedicine provides the opportunity to bring medical expertise to the bedside, even if the medical expert is not physically near the patient. Internet technology has facilitated telemedicine allowing for voice, video and other data to be exchanged between remote locations. To date, applications of telemedicine to anesthesia (Teleanesthesia) have been limited. Previous work by Cone et al., (Anesth Analg 2006;1463-7) demonstrated the ability to direct an anesthetic in a remote location using satellite communication. In this report, we describe the use of telemedicine to support two cases of elective living related pediatric liver transplants performed at the Narayana Hrudayalaya Institute of Medical Sciences in Bangalore, India with preoperative and intraoperative consultation provided by physicians at the Children's Hospital of Philadelphia.

Although empiricist approaches to machine translation depend vitally on data in the form of large bilingual corpora, bilingual dictionaries are also a source of information. We show how to model at least a part of the information contained in a bilingual dictionary so that we can treat a bilingual dictionary and a bilingual corpus as two facets of a unified collection of data from which to extract values for the parameters of a probabilistic machine translation system. We give an algorithm for obtaining maximum likelihood estimates of the parameters of a probabilistic model from this combined data and we show how these parameters are affected by inclusion of the dictionary for some sample words.

The time required for our translation system to handle a sentence of length l is a rapidly growing function of l. We describe here a method for analyzing a sentence into a series of pieces that can be translated sequentially. We show that for sentences with ten or fewer words, it is possible to decrease the translation time by 40% with almost no effect on translation accuracy. We argue that for longer sentences, the effect should be more dramatic.