Time-to-event data

Categorical Data and Why Zero and Missing Results Differ Greatly 102 Performing Many-to-Many Comparisons/Joins 106 Using Medical Dictionaries 108 Other Tricks and Traps in Data Manipulation 112 Common Analysis Data Sets 118 Critical Variables Data Set 118 Change-from-Baseline Data Set 118 Time-to-Event Data Set 121... 

In this section we take the aforementioned principles and guidelines for analysis data sets and apply them to creating the most common analysis data sets. The critical variables, change-from-baseline, and time-to-event data sets are presented. Although these are the most common analysis data sets that a statistical programmer will encounter, they are by no means all of the possible analysis data sets. When it comes to analysis data sets, there is no limit to the diversity of data that you may have to create. 

So for every clinical event of concern there is an event binomial flag and a time-to-event variable. Time-to-event data sets are typically represented in a flat denormalized single observation per subject data set. 

The following is a very simplistic example of what a time-to-event data set might look like when the event of interest is seizure. Here you assume that there is a seizure event form that collects whether a subject had a seizure and the date when the seizure occurred. You also assume that you do not need to search other ancillary data forms such as adverse events for seizure events. 

Program 4.15 Creating a Time-to-Event Data Set for Seizures... 

Anderson, H., Spliid, H., Larsen, S. and Dali, V (2000). Statistical analysis of time to event data from preclinical safety pharmacology studies. Tox. Methods 10 111-125. 

The sample size calculation should be detailed in the trial publication, indicating the estimated outcomes in each of the treatment groups (and this will define, in particular, the clinically relevant difference to be detected), the type I error, the type II error or power and, for a continuous primary outcome variable in a parallel group trial, the within-group standard deviation of that measure. For time-to-event data details on clinically relevant difference would usually be specified in terms of the either the median event times or the proportions event-free at a certain time point. 

Incorrect analysis of time-to-event data in terms of the definition for the origin of the measurement - the point of randomisation is the only origin that can be used in a randomised trial... 

Cox EH, Sheiner LB. Model for repeated measures time-to-event data with time-varying concentration and hazard. 2001. (Internet at ftp //ftp.gIobomaxnm. com/ Public / nonmem/ noncon tinuous.)... 

Although we do not cover them in detail, there ate parametric methods to analyze time to event data of this type, the most notable of which is Cox s proportional hazards model. 

Survival analysis. The analysis of time to event data in particular, but not exclusively, where the event is death. A common feature of such data is that they are very skewed and that there are many censored values. Survival analysis is one of the single most important topics in medical statistics, although its importance to pharmaceutical statistics is, because of the nature of the trials usually run in drug development, relatively less important than the contents of standard textbooks on medical statistics might suggest. 

Stitelman, O.M. and M.J. van der Laan. Collaborative targeted maximum likelihood for time to event data. Technical Report 260. Division of Biostatistics, University of California, Berkeley, CA, 2010. 

Interval-Censored Time-to-Event Data Methods and Applications... 

Joint Models for Longitudinal and Time-to-Event Data With Applications in R... 

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