Randomised Controlled Trials
The randomised controlled trial is the gold standard for evaluating the efficacy of interventions, using random allocation to minimise bias and confounding, with intention-to-treat analysis preserving the integrity of randomisation.
Key Facts
- RCTs are the gold standard for evaluating treatment efficacy; provide Level 1b evidence
- Randomisation ensures groups are comparable for known and unknown confounders
- Allocation concealment prevents selection bias by keeping group assignment hidden until enrolment
- Blinding reduces performance and detection bias: single-blind (participant), double-blind (participant + assessor), triple-blind (+ analyst)
- Intention-to-treat (ITT) analysis: analyses all participants in their allocated group regardless of adherence; preserves randomisation benefit
- Per-protocol analysis: analyses only those who completed treatment as intended; may overestimate treatment effect
- Power calculation: sample size determined to detect a clinically meaningful difference with adequate statistical power (typically 80-90%)
- CONSORT statement: standardised reporting framework for RCTs; includes flow diagram
Overview
Key Facts
The RCT is the most rigorous method for determining whether a cause-effect relationship exists between an intervention and outcome. Proper conduct requires attention to randomisation, blinding, sample size, and analysis.
Study Conduct
- Define research question (PICO: Population, Intervention, Comparator, Outcome)
- Calculate sample size (power calculation)
- Recruit participants (inclusion/exclusion criteria)
- Randomisation (simple, block, stratified, minimisation)
- Allocation concealment
- Intervention delivery
- Blinding of participants, clinicians, outcome assessors
- Follow-up and outcome measurement
- Analysis (ITT primary; per-protocol secondary)
- Reporting (CONSORT)
Types of RCT
- Parallel group: most common; two or more groups run simultaneously
- Crossover: each participant receives both treatments in sequence; washout period between
- Factorial: tests two or more interventions simultaneously (e.g. ISIS-2: aspirin × streptokinase)
- Cluster: randomises groups (e.g. GP practices) rather than individuals
- Non-inferiority/equivalence: tests whether new treatment is not worse than standard
- Adaptive: allows modification of trial design based on interim results
Randomisation Methods
- Simple: coin flip/random number generator
- Block: ensures balanced groups at regular intervals
- Stratified: stratifies by important prognostic factors before randomisation
- Minimisation: algorithm-based allocation balancing multiple factors
Clinical Presentation
Interpreting RCT Results
- Primary outcome: pre-specified main outcome of interest
- Secondary outcomes: additional outcomes; hypothesis-generating
- Absolute risk reduction (ARR): difference in event rates between groups
- Relative risk reduction (RRR): proportional reduction in risk
- NNT: number needed to treat to prevent one event (1/ARR)
- Confidence interval: range within which true effect likely lies (95% CI); if CI for RR crosses 1.0, not statistically significant
- P-value: probability of observing result if null hypothesis true; p<0.05 conventionally significant
Threats to Validity
- Selection bias (inadequate randomisation/allocation concealment)
- Performance bias (lack of blinding)
- Attrition bias (differential loss to follow-up)
- Detection bias (unblinded outcome assessment)
- Reporting bias (selective outcome reporting)
Differential Diagnosis
| RCT Feature | Purpose | Threat if Absent |
|---|---|---|
| Randomisation | Equalise confounders between groups | Confounding |
| Allocation concealment | Prevent foreknowledge of allocation | Selection bias |
| Blinding (participants) | Prevent placebo effect | Performance bias |
| Blinding (assessors) | Prevent biased outcome measurement | Detection bias |
| ITT analysis | Preserve randomisation benefit | Attrition bias |
| Adequate sample size | Detect true differences | Type II error |
| Pre-registered protocol | Prevent outcome switching | Reporting bias |
Diagnosis / Investigation
Critical Appraisal of RCTs (CASP)
- Was the trial focused on a clear question?
- Was allocation randomised and concealed?
- Were groups similar at baseline?
- Were participants/clinicians/assessors blinded?
- Were all participants accounted for (follow-up rate)?
- Were outcomes measured in a standard, valid way?
- Were results reported for all pre-specified outcomes?
- Was the treatment effect size clinically important?
- Were confidence intervals precise?
- Can results be applied to your population?
Statistical Concepts
- Type I error (α): false positive (rejecting true null hypothesis); conventionally set at 0.05
- Type II error (β): false negative (failing to reject false null hypothesis); conventionally 0.1-0.2
- Power: 1 − β; probability of detecting a true difference
- Intention-to-treat: includes all randomised participants; conservative estimate
- Per-protocol: includes only compliant participants; may overestimate effect
Management
Landmark UK Medical Trials
- MRC Streptomycin Trial (1948): first properly randomised clinical trial
- ISIS-2 (1988): aspirin + streptokinase in acute MI; factorial design
- HOPE (2000): ramipril in high-risk CVD patients
- UKPDS (1998): intensive glucose control in T2DM
- PARADIGM-HF (2014): sacubitril/valsartan in heart failure
- DAPA-HF (2019): dapagliflozin in heart failure
- RECOVERY (2020): dexamethasone in COVID-19
Ethical Considerations
- Equipoise: genuine uncertainty about which treatment is better
- Informed consent: participants fully informed of risks, benefits, alternatives
- Data Safety Monitoring Board (DSMB): independent review of interim safety data
- Stopping rules: pre-defined criteria for early termination (harm or overwhelming benefit)
- Research Ethics Committee: approval required before recruitment
- Clinical trial registration: mandatory prospective registration (e.g. ClinicalTrials.gov, ISRCTN)
Prognosis
- RCTs provide the most reliable evidence for treatment decisions when properly conducted
- Even well-designed RCTs may have limited external validity if populations are highly selected
- Publication bias means positive trials are more likely published; funnel plots and Egger test assess this
- Fragility index: number of patients whose outcome would need to change to make result non-significant
- Replication of findings across multiple RCTs increases confidence in treatment effects
Other Relevant Information
CONSORT Flow Diagram Components
| Stage | Information |
|---|---|
| Enrolment | Assessed for eligibility, excluded (with reasons) |
| Allocation | Randomised to intervention vs control |
| Follow-up | Lost to follow-up (with reasons), discontinued |
| Analysis | Analysed (ITT), excluded from analysis (with reasons) |
NNT Calculation Example
| Group | Event Rate |
|---|---|
| Control | 20% (0.20) |
| Treatment | 15% (0.15) |
| ARR | 5% (0.05) |
| NNT | 1/0.05 = 20 |