Allocation concealment By: Dr. Lisa Calder December 2012
Allocation concealment is an important principle in RCT design as it helps ensure that study personnel and clinicians are unaware of how a study intervention or control is assigned. Historically, there have been instances where study personnel or clinicians have attempted to “guess” treatment allocation to ensure their patient gets assigned the “right” study group based on their own clinical biases. The robustness of an RCT is enhanced by clear reporting of how allocation was concealed, and even further if the adequacy of their concealment was evaluated.
Blinding of Treatment Allocation By: Dr. Lisa Calder January 2013
Contamination in Randomized Trials By: Dr. Ian Stiell May 2014
Cluster Randomized Controlled Trials By Dr. Ian Stiell May 2012
A cluster randomized trial is a trial in which individuals are randomized in groups (i.e. the group is randomized, not the individual); for example, all patients treated by a particular EMS service or at a particular hospital. Reasons for performing cluster randomized trials vary. Sometimes the intervention can only be administered to the group, for example an addition to the water supply; sometimes the motivation is to avoid contamination amongst health care providers; sometimes the design is simply more convenient or economical. Such trials are often appropriate when the intervention is a psychomotor task (e.g. CPR) but not when the intervention is a drug. Specific sample size and data analytic approaches are required.
Equivalence or Non-Inferiority Trials By Dr. Ian Stiell May 2012
Trials of healthcare interventions are often described as either explanatory or pragmatic. Explanatory trials generally measure efficacy - the benefit a treatment produces under ideal conditions, often using carefully defined subjects in a research clinic. Pragmatic trials measure effectiveness - the benefit the treatment produces in routine clinical practice. Pragmatic trials generally reflect the reality of how the intervention will perform in everyday care. For more, see
Flow Diagram By Dr. Ian Stiell December 2011
Investigators and editors developed the CONSORT Statement (revised 2010 ) to improve the reporting of randomized controlled trials (RCTs) by means of a checklist and flow diagram. The flow diagram is intended to depict the passage of participants through an RCT and depicts numbers and explanations from four stages of a trial (enrollment, intervention allocation, follow-up, and analysis). The diagram explicitly shows the number of participants, for each intervention group, included in the primary data analysis.
The hazard ratio is akin to relative risk but is used for survival analyses such as Cox proportional hazards regression. It is most often used to describe the outcome of therapeutic trials where the question is, to what extent can treatment shorten the duration of an illness. The hazard ratio is an estimate of the ratio of the hazard rate in the treated versus the control group. For example if there are two groups, group 1 and group 2, HR = 4.5 for treatment means that the risk (of relapse) for group 2 is 4.5 times that of group 1.
Intention-to-treat (ITT) Analyses By: Drs. Ian Stiell & Lisa Calder January 2015
By: Dr. Christian Vaillancourt
Minimal Clinically Important Difference in Clinical Trials Dr. Ian Stiell September 2014
Multiple Arm Clinical Trials By Dr. Ian Stiell April 2013
Non-inferiority Trials By: Dr. Lisa Calder January 2013
Non-inferiority trials are distinct from superiority trials such that they are designed to determine whether a given intervention is non-inferior by a pre-specified margin compared to a control. This is not the same as equivalence and a key section of the methods to examine is the sample size calculation where the non-inferiority margin is specified. Ideally, researchers explain how this margin was determined (based on previous placebo controlled trials, consensus of experts). The critical reader will ask themselves if they feel this margin is truly clinically significant.
An Assessment of Clinically Useful Measures of the Consequences of Treatment
Clinical trials involving new drugs are classified into four phases with Health Canada and the FDA generally requiring a drug to have passed through Phase 3 before general approval. Phase 1 trials test the treatment in a small group of healthy people (20-80) to evaluate its safety, dosage range, and side effects. Phase 2 trials give the treatment to patients and in larger numbers (100-300) to evaluate effectiveness and safety. Phase 3 trials give the treatment to large groups of paitents (1,000-3,000) to confirm its effectiveness, monitor side effects, and compare to commonly used treatments. Phase 4 trials are post-marketing studies to determine additional information about side effects and risks. [2a trials studies focus on proving the hypothesized mechanism of action while the larger 2b trials seek to determine the optimum dose]
Pre-specified and Post-hoc Subgroup Analyses By: Dr. Ian Stiell May 2014
Precision in RCTs By Dr. Lisa Calder October 2012
Random sampling vs Randomization By Dr. Lisa Calder June 2015
When reviewing a randomized trial, it is critical to determine how the randomization was conducted as not all randomization schemes are created equal. Proper randomization uses either computer generated randomization or random tables. Pseudo-randomization includes studies where patients are allocated based on alternating days of the week or date of birth for example. The reader can verify that randomization was conducted appropriately by examining table 1 of participant characteristics and determine whether the groups appear to be balanced.
Sample Size in Clinical Trials By Dr. Ian Stiell June 2013
Survival Analyses By Dr. Ian Stiell February 2013
Survival analyses are used in clinical trials that follow patients over time for primary outcomes such as death, relapse, adverse drug reaction, or development of a new disease. The follow-up time may range from hours to years and a different set of statistical procedures are employed to analyze the data. Terms frequently seen in papers with survival analyses include Cox proportional hazard model, hazard ratio, Kaplan-Meir curve.
Surrogate endpoints By Dr. Venkatesh Thiruganasambandamoorthy
Can be used as a measure of effect for specific treatments and might correlate with clinical outcomes. In the RE-VERSE AD (idarucizumab for dabigatran reversal) study the investigators used dilute thrombin time and ecarin clotting time as surrogate end points for reversal of dabigatran action by the study drug idarucizumab. The actual clinical end point of restoration of hemostasis was a secondary outcome. This was a small study. We need a large clinical study with a control group to confirm that clinical outcomes among patients treated with the reversal agent were better. Be wary of studies using surrogate outcomes when clinical outcomes could have been used.
Beware of studies that compare the effectiveness of interventions by using continuous data outcomes, such as pain scales (1-100), oxygen saturation values, and minutes to pain relief. These kinds of data can produce statistically significant differences between groups with relatively small sample sizes but often give you little information about clinical importance. Far better and almost always the norm are outcome measures given as proportions or percentages, such as % of patients who achieve: 20 points improvement in pain, an oxygen saturation of 90%, pain relief in less than 2 hours, or survival.
Validation of Measurement Tools By: Dr. Lisa Calder June 2014