Closed loop stimulation in patients with chronic heart failure and severe chronotropic incompetence: Responders versus non-responders.

Background: Clinical effects of rate-adaptive pacing (RAP) are unpredictable and highly variable among cardiac resynchronization therapy (CRT) patients with chronotropic incompetence. Physiologic sensors such as Closed Loop Stimulation (CLS), measuring intracardiac impedance changes (surrogate for ventricular contractility), may add clinical benefit and help identify predictors of response to RAP. The objective of the present BIOlCREATE study subanalysis was to identify criteria for selection of CRT patients who are likely to respond positively to CLS-based RAP.

Impact of closed loop stimulation on prognostic cardiopulmonary variables in patients with chronic heart failure and severe chronotropic incompetence: a pilot, randomized, crossover study.

Aims: Clinical effects of rate-adaptive pacing in heart failure patients with chronotropic incompetence (CI) undergoing cardiac resynchronization therapy (CRT) remain unclear. Closed loop stimulation (CLS) is a new rate-adaptive sensor in CRT devices. We evaluated the effectiveness of CLS in CRT patients with severe CI, focusing primarily on key prognostic variables assessed by cardiopulmonary exercise (CPX) testing.

A DAG-based comparison of interventional effect underestimation between composite endpoint and multi-state analysis in cardiovascular trials.

Background: Composite endpoints comprising hospital admissions and death are the primary outcome in many cardiovascular clinical trials. For statistical analysis, a Cox proportional hazards model for the time to first event is commonly applied. There is an ongoing debate on whether multiple episodes per individual should be incorporated into the primary analysis.

Simulating recurrent event data with hazard functions defined on a total time scale.

Background: In medical studies with recurrent event data a total time scale perspective is often needed to adequately reflect disease mechanisms. This means that the hazard process is defined on the time since some starting point, e.g.

Sample-size calculation and reestimation for a semiparametric analysis of recurrent event data taking robust standard errors into account.

In some clinical trials, the repeated occurrence of the same type of event is of primary interest and the Andersen-Gill model has been proposed to analyze recurrent event data. Existing methods to determine the required sample size for an Andersen-Gill analysis rely on the strong assumption that all heterogeneity in the individuals' risk to experience events can be explained by known covariates. In practice, however, this assumption might be violated due to unknown or unmeasured covariates affecting the time to events.

Sample size in cluster-randomized trials with time to event as the primary endpoint.

In cluster-randomized trials, groups of individuals (clusters) are randomized to the treatments or interventions to be compared. In many of those trials, the primary objective is to compare the time for an event to occur between randomized groups, and the shared frailty model well fits clustered time-to-event data. Members of the same cluster tend to be more similar than members of different clusters, causing correlations.

Effectiveness of postoperative radiotherapy in patients with small oral and oropharyngeal squamous cell carcinoma and concomitant ipsilateral singular cervical lymph node metastasis (pN1) : A meta-analysis.

Background: The positive effect of radiation therapy for patients with advanced oropharyngeal squamous cell carcinoma (OSCC) has been substantially verified. The present work investigated whether a meta-analysis of current data is able to evaluate the effectiveness of postoperative radiotherapy (PORT) in patients with small OSCC (pT1, pT2) and a single ipsilateral lymph node metastasis (pN1).

Methods: The meta-analysis comprises randomized and non-randomized studies.

Adaptive trial design: a general methodology for censored time to event data.

Adaptive designs allow a clinical trial design to be changed according to interim findings without inflating type I error. The Inverse Normal method can be considered as an adaptive generalization of classical group sequential designs. The use of the Inverse Normal method for censored survival data was demonstrated only for the logrank statistic.