In the context of clinical trials what is meant by the following terms:
a) Stratification. (20% marks)
b) Intention to treat analysis. (20% marks)
c) Sensitivity analysis. (20% marks)
d) Kaplan-Meir curve. (20% marks)
e) Analysis of competing risk. (20% marks)
a) Stratification of clinical trials is the partitioning of subjects and results by a factor other than the treatment given
b) Intention to treat analysis is the analysis of all participants allocated to a treatment group irrespective of whether they completed the treatment, withdrew, or deviated from protocol.
c) A sensitivity analysis is the analysis of data from the trial with a change or alteration to one or more underlying assumptions used in the original analysis.
d) A Kaplan-Meir curve is a plot of probability of survival against time.
e) Analysis of competing risk is used when there are multiple endpoints of which the occurrence of one prevents the occurrence of another (e.g. death prevents the occurrence of shock reversal
- Stratification is the partitioning of subjects and results by a factor other than the treatment given.
- Stratification ensures that pre-identified confounding factors are equally distributed, to achieve balance. The objective is to remove "nuisance variables", eg. the presence of neutropenia in a trial performed on septic patients. One would want to ensure that the treatment group and the placebo group had equal numbers of these haematology disasters.
- According to Question 19 from the first paper of 2016, the official Delaney definition of stratification is as follows:
"Stratification is a process that protects against imbalance in prognostic factors that are present at the time of randomisation.
A separate randomisation list is generated for each prognostic subgroup. Usually limited to 23 variables because of increasing complexity with more variables"
Intention to treat analysis
- "Once randomised, always analysed"
- All enrolled patients have to be a part of the final analysis
- This preserves the bias-protective effect of randomisation
- Minimises Type 1 errors (false positives)
- When intention-to-treat analysis agrees with per-protocol analysis, it increases the validity of the study
- Analysis of the data from a clinical trial where some of the assumptions are intentionally changed
- One example of this is to assume that all the patients lost to follow-up or who dropped out of the study have failed treatment.
"Kaplan-Meir" curve (it's usually spelled "Meier", after Paul Meier):
- A Kaplan-Meier curve is defined as the probability of surviving in a given length of time while considering time in many small intervals
- The curve itself is a plot of the fraction of patients surviving in each group over time
Analysis of competing risk:
- A competing risk is an event that either hinders the observation of the event of interest or modifies the chance that this event occurs
- An example is death while on dialysis and getting a kidney transplant (the two eventsinterfere with one another)
- Conventional methods (eg. Kaplan–Meier and standard Cox regression) ignore the competing events and may not be appropriate and competing risk analsysi methods must be employed
Morris, Tim P., Brennan C. Kahan, and Ian R. White. "Choosing sensitivity analyses for randomised trials: principles." BMC medical research methodology 14.1 (2014): 11.
Rich, Jason T., et al. "A practical guide to understanding Kaplan-Meier curves." Otolaryngology—Head and Neck Surgery 143.3 (2010): 331-336.
Noordzij, Marlies, et al. "When do we need competing risks methods for survival analysis in nephrology?." Nephrology Dialysis Transplantation 28.11 (2013): 2670-2677.