Glossary

Table 1 gives an overview of the acronyms and abbreviations used in the user guides.

Table 1: List of terms used in the user guides

Name	Definition
Cap	A limit on the number of subjects recruited. In FACTS N-CRM users can specify a cap on the overall number of subjects to be recruited in the trial (the ‘Overall Cap’) and specify stopping rules to define when the trial should stop before it reaches cap.
Control	Is the treatment arm with which the novel treatment(s) are principally being compared. Control may be placebo, or some existing standard of care, or therapy, against which the novel treatment has to be benchmarked in order to determine its likely usefulness.
Core	FACTS Core: A mode of FACTS for designing trials where multiple treatments, (possibly different doses of a novel treatment) are tested against a control and optionally an active comparator.
CRM	Continual Reassessment Method – a dose escalation design where the dose-toxicity is estimated using a simple Bayesian model, and the resulting estimates used to control the dose escalation and estimate the Maximum Tolerated Dose (MTD).
DE	Dose Escalation: a mode of FACTS where subjects are treated in cohorts and dose escalation is determined by the number of toxicities observed.
ED	Enrichment Designs: a mode of FACTS for designing trials where the same treatment is testing in different settings for example different sub-populations or different but related indications.
FACTS	Fixed and Adaptive Clinical Trial Simulator.
Final Endpoint	The final value, or state, of a subject’s endpoint.
GUI	Graphical User Interface, the part of the FACTS application that the user interacts with.
Method	In the FACTS documentation we try to reserve the term ‘method’ for the algorithms used in the simulation (as opposed to the analysis) part of the program. In the analysis part we use the term ‘Model’, see below.
Model	In the FACTS documentation we try to reserve the term ‘model’ for the statistical models used in the analysis of the trial data (in the ‘design’ section of the FACTS user interface). Where mathematical algorithms are used for other purposes in FACTS (for instance in the generation of the simulated data) we try to use the term ‘method’. We have found that initially it is very easy for users to be confused between these two parts of FACTS and we feel that using distinct terminology may help to reduce this.
MTD	The dose most likely to be the Maximum Tolerated Dose (MTD) – the dose with the highest Pr(MTD).
MTD+	The dose most likely to be the MTD+ – the dose with the highest Pr(MTD+).
Pr(MTD)	A dose’s probability of being MTD is the probability that it is the dose with the highest probability of having a toxicity rate in the acceptable toxicity band, and (if a threshold has been specified) does not have a probability of excess or unacceptable toxicity above the threshold. This estimate of MTD is constrained to select one of the available doses.
Pr(MTD+)	A dose’s probability of being the MTD+ is the probability that it is the dose with the highest probability of having a toxicity rate in the acceptable band, and (if a threshold has been specified) does not have a probability of excess or unacceptable toxicity above the threshold. Unlike Pr(MTD), Pr(MTD+) includes estimating whether a dose below or a dose above the range of those being tested is more likely to have a toxicity in the acceptable band than any of the doses in the range.
Profile	A profile is a specification of one aspect of a scenario. A scenario is made up of one profile of each of the required types for the type of trial being simulated. FACTS allows the user to specify multiple profiles of each type and then presents all the possible combinations of profiles as scenarios that can be used to drive simulations.
Response	The change in a subject’s endpoint compared to their baseline state.
Scenario	A scenario is the complete specification of the unknown external factors that determine the data observed on the trial and its timing. The exact factors depend on the type of trial being simulated but typically include: -) the distribution of the final change from base line, or probability of response or rate of events in the different treatment groups -) the properties of subjects’ early responses and the correlation with their final outcome -) the rate at which subjects are recruited into the trial -) the rate at which subjects drop out of the trial.
SPEC	The Design Engine Specification, describes the system algorithms, and meaning of parameters.
Response	The change in a subject’s endpoint compared to their baseline state.
Subject	Someone recruited onto a clinical trial for the purposes of learning about the properties of a treatment. Depending on the type of trial they might be patients or they might be healthy volunteers.
Treatment Arm	Subjects on entering the study are randomized to different ‘treatment arms’. Subjects randomized to the same arm receive the same treatment and the responses of the subjects in the arm analyzed to determine the expected response to that treatment, allowing the expected responses to the different treatments to be compared.
UG	The User Guide; describes how to use the system.