randomized-controlled-trial

name	randomized-controlled-trial
category	methodology
discipline	medical
description	RCT design protocol with randomization, blinding, CONSORT flow diagram, and sample size calculation

Randomized Controlled Trial

When to Use

When designing, conducting, or reporting a randomized controlled trial to evaluate the efficacy or effectiveness of an intervention. RCTs are the gold standard for establishing causality between interventions and outcomes. This protocol covers superiority, non-inferiority, and equivalence trials.

Protocol

Step 1: Define the Research Question (PICO)

• Population: Define target population, including demographic and clinical characteristics
• Intervention: Specify the experimental treatment/intervention in detail (type, dose, route, frequency, duration, provider, setting)
• Comparator: Define the control condition (placebo, active comparator, usual care, waitlist, sham)
• Outcome: Specify primary and secondary outcomes with measurement instruments and time points
• Determine the trial type:
  • Superiority: tests if intervention is better than comparator
  • Non-inferiority: tests if intervention is not worse than comparator by more than a pre-specified margin
  • Equivalence: tests if intervention and comparator produce similar effects within a margin
• Define the trial phase (for drug trials): Phase I (safety), Phase II (efficacy/dosing), Phase III (confirmatory), Phase IV (post-marketing)

Step 2: Calculate Sample Size

• Specify:
  • Alpha (type I error rate): typically 0.05 (two-sided) or 0.025 (one-sided for non-inferiority)
  • Power (1 - beta): typically 0.80 or 0.90
  • Minimum clinically important difference (MCID): the smallest effect worth detecting — base on clinical relevance, not pilot data convenience
  • Expected variability: SD for continuous outcomes, event rate for dichotomous outcomes — from pilot studies, literature, or clinical judgment
  • Allocation ratio: 1:1 (most efficient) or unequal (e.g., 2:1 for safety data)
• Calculate using:
  • Continuous outcome (two-sample t-test): n per group = 2 * ((Z_alpha/2 + Z_beta) * SD / delta)^2
  • Dichotomous outcome (chi-square): n per group from Fleiss or arcsine formula
  • Time-to-event: use Schoenfeld formula based on number of events
  • Non-inferiority/equivalence: add margin to the calculation
• Adjust for:
  • Expected dropout/loss to follow-up (inflate by 1/(1-dropout rate))
  • Multiple primary endpoints (alpha correction)
  • Interim analyses (alpha spending function)
  • Clustering (if cluster-randomized design: multiply by design effect 1 + (m-1)*ICC)
• Report the software used for calculation (G*Power, PASS, R pwr/samplesize)

Step 3: Choose the Randomization Method

• Simple randomization: coin-flip equivalent; risk of imbalance with small N
• Block randomization: ensures balance at regular intervals
  • Use random block sizes (e.g., 4, 6, 8) to prevent prediction
  • Smaller blocks maintain balance; larger blocks reduce predictability
• Stratified randomization: block randomization within strata of key prognostic factors
  • Limit to 2-3 stratification factors to avoid sparse strata
• Minimization (adaptive): dynamically allocates to minimize imbalance across multiple factors
  • Include a random element (e.g., 70-80% probability of deterministic allocation)
• Cluster randomization: randomize groups (clinics, schools) rather than individuals
  • Required when individual randomization risks contamination
  • Must account for clustering in sample size and analysis (ICC)
• Generate the allocation sequence using a validated computer program
• Ensure the sequence is generated by someone NOT involved in enrollment
• Use sequentially numbered, opaque, sealed envelopes (SNOSE) or centralized phone/web-based system

Step 4: Plan the Blinding Strategy

• Open-label (unblinded): both participants and investigators know allocation — necessary when blinding is impossible (e.g., surgical vs medical therapy)
• Single-blind: participant blinded, investigator aware (or vice versa)
• Double-blind: both participant and investigator blinded — gold standard
• Triple-blind: participant, investigator, and outcome assessor all blinded
• Blinding methods:
  • Identical placebo (matched in appearance, taste, smell, route)
  • Sham procedures for surgical interventions
  • Double-dummy technique for comparing different routes of administration
• Assess success of blinding: ask participants and investigators to guess allocation at study end (Bang's blinding index)
• Plan for emergency unblinding procedures
• If blinding is not possible, use blinded outcome assessment and blinded data analysis

Step 5: Design the Intervention Protocol

• Standardize the intervention with a detailed manual or protocol
• Define:
  • Treatment initiation, dose escalation, maintenance, and discontinuation criteria
  • Training requirements for intervention providers
  • Adherence monitoring (pill counts, diaries, electronic monitoring, biomarkers)
  • Co-intervention restrictions (concomitant treatments allowed/prohibited)
  • Rescue medication rules
• Define the comparator protocol with equal rigor
• Address the Hawthorne effect: ensure equivalent contact time and attention across groups

Step 6: Define Outcomes and Measurement

• Primary outcome:
  • Single, clearly defined outcome that is clinically meaningful
  • Pre-specify the time point for the primary analysis
  • Use validated measurement instruments with known reliability and responsiveness
• Secondary outcomes:
  • Limited number (typically 3-5) to reduce multiple testing burden
  • Include patient-reported outcomes (PROs) where appropriate
  • Include safety/adverse event outcomes
• Composite outcomes: combine multiple events into a single outcome — pre-specify components and report each individually
• Surrogate outcomes: use with caution; justify with evidence of surrogacy (Prentice criteria)
• Define how and when outcomes will be measured, by whom (trained, blinded assessors), and adjudication procedures for subjective outcomes

Step 7: Plan Data Collection and Management

• Design case report forms (CRFs) — paper or electronic (REDCap, Castor, OpenClinica)
• Establish a data management plan:
  • Data entry procedures (double data entry for paper CRFs)
  • Range checks and validation rules
  • Query resolution process
  • Data lock procedures
• Define a statistical analysis plan (SAP) BEFORE unblinding:
  • Primary analysis method
  • Handling of missing data
  • Pre-specified subgroups
  • Interim analysis rules
  • Multiple comparison adjustments
• Establish a Data Safety Monitoring Board (DSMB) for:
  • Trials with mortality/serious morbidity outcomes
  • Interim efficacy and futility analyses
  • Safety monitoring and stopping rules (O'Brien-Fleming, Lan-DeMets alpha spending)

Step 8: Plan the Analysis Strategy

• Intention-to-treat (ITT):

  • Primary analysis: analyze all randomized participants in their assigned group regardless of adherence
  • Preserves the benefits of randomization
  • May underestimate treatment effect (conservative)
  • Handle missing data with multiple imputation, mixed models, or sensitivity analyses (tipping point, pattern-mixture)

• Per-protocol (PP):

  • Secondary analysis: include only participants who completed treatment per protocol
  • Pre-specify criteria for protocol violations
  • Report alongside ITT; discordance suggests adherence effects
  • PP is the primary analysis for non-inferiority trials (ITT is anti-conservative)

• Modified ITT:

  • Exclude randomized participants who never received treatment or had no post-baseline assessment
  • Pre-specify and justify exclusions

• Statistical methods by outcome type:

  • Continuous: ANCOVA adjusting for baseline value (preferred over change scores or unadjusted comparison)
  • Dichotomous: logistic regression or log-binomial for RR
  • Time-to-event: Cox proportional hazards, Kaplan-Meier curves, log-rank test
  • Count data: Poisson or negative binomial regression
  • Ordinal: proportional odds model
  • Repeated measures: mixed-effects models (preferred) or GEE

• Multiplicity adjustments:

  • Multiple primary endpoints: Bonferroni, Holm, or hierarchical testing (gatekeeping)
  • Multiple comparisons (>2 arms): Dunnett's test or closed testing procedure
  • Interim analyses: alpha spending function (O'Brien-Fleming or Pocock boundaries)

Step 9: Register the Trial

• Register BEFORE enrolling the first participant
• Required registries:
  • ClinicalTrials.gov (required for FDA-regulated and NIH-funded trials)
  • WHO ICTRP (International Clinical Trials Registry Platform)
  • EU Clinical Trials Register (EudraCT) for trials in the EU
  • National registries as applicable
• Include: study title, PICO, design, sample size, primary outcome, sponsor, contact
• Update registration with results (required within 12 months of completion on ClinicalTrials.gov)
• Obtain the registration number for manuscript reporting
• ICMJE requires prospective registration for publication

Step 10: Ethical and Regulatory Approvals

• Obtain Institutional Review Board (IRB) / Ethics Committee approval BEFORE enrollment
• Prepare and obtain informed consent:
  • Written in plain language (6th-8th grade reading level)
  • Include: purpose, procedures, risks, benefits, alternatives, voluntary participation, right to withdraw, confidentiality, compensation
  • Special considerations: vulnerable populations, pediatric assent, surrogate consent
• Comply with:
  • Declaration of Helsinki
  • ICH Good Clinical Practice (GCP) guidelines
  • Local regulatory requirements (FDA IND, EMA CTA)
• Report any protocol amendments to IRB and trial registry
• Maintain a trial master file

Step 11: Monitor and Execute

• Conduct a site initiation visit and training
• Monitor enrollment rate against projections; adjust recruitment strategies if needed
• Implement monitoring plan:
  • On-site monitoring visits (source data verification)
  • Central statistical monitoring (detect data anomalies)
  • Risk-based monitoring (focus resources on high-risk sites)
• Track and report adverse events:
  • Serious Adverse Events (SAEs): report to IRB, sponsor, and DSMB within 24-72 hours
  • Suspected Unexpected Serious Adverse Reactions (SUSARs): report to regulatory authority
• Conduct interim analyses per the pre-specified plan
• Implement stopping rules if DSMB recommends

Step 12: Report Following CONSORT

• Prepare the manuscript following CONSORT 2010 (see checklist below)
• Include the CONSORT flow diagram
• Register results on ClinicalTrials.gov
• Share individual participant data (IPD) per the data sharing plan
• For extensions: CONSORT-NPT (non-pharmacological), CONSORT-PRO (patient-reported), CONSORT-Cluster, CONSORT-Adaptive, CONSORT-AI

Checklist: CONSORT 2010 (25 Items)

Title and Abstract

1a. Identification as a randomised trial in the title 1b. Structured abstract with trial design, methods, results, and conclusions

Introduction

2a. Scientific background and explanation of rationale 2b. Specific objectives or hypotheses

Methods

3a. Description of trial design (e.g., parallel, factorial) including allocation ratio 3b. Important changes to methods after trial commencement, with reasons 4a. Eligibility criteria for participants 4b. Settings and locations where data were collected 5. The interventions for each group with sufficient detail to allow replication, including how and when they were actually administered 6a. Completely defined pre-specified primary and secondary outcome measures, including how and when they were assessed 6b. Any changes to trial outcomes after the trial commenced, with reasons 7a. How sample size was determined 7b. When applicable, explanation of any interim analyses and stopping guidelines 8a. Method used to generate the random allocation sequence 8b. Type of randomisation; details of any restriction (e.g., blocking and block size) 9. Mechanism used to implement the random allocation sequence, describing any steps taken to conceal the sequence until interventions were assigned 10. Who generated the allocation sequence, who enrolled participants, and who assigned participants to interventions 11a. If done, who was blinded after assignment to interventions (e.g., participants, care providers, those assessing outcomes) and how 11b. If relevant, description of the similarity of interventions 12a. Statistical methods used to compare groups for primary and secondary outcomes 12b. Methods for additional analyses, such as subgroup analyses and adjusted analyses

Results

13a. For each group, the numbers of participants who were randomly assigned, received intended treatment, and were analysed for the primary outcome 13b. For each group, losses and exclusions after randomisation, together with reasons 14a. Dates defining the periods of recruitment and follow-up 14b. Why the trial ended or was stopped 15. A table showing baseline demographic and clinical characteristics for each group 16. For each group, number of participants (denominator) included in each analysis and whether the analysis was by original assigned groups 17a. For each primary and secondary outcome, results for each group, and the estimated effect size and its precision (such as 95% confidence interval) 17b. For binary outcomes, presentation of both absolute and relative effect sizes is recommended 18. Results of any other analyses performed, including subgroup analyses and adjusted analyses, distinguishing pre-specified from exploratory 19. All important harms or unintended effects in each group

Discussion

20. Trial limitations, addressing sources of potential bias, imprecision, and, if relevant, multiplicity of analyses
21. Generalisability (external validity, applicability) of the trial findings
22. Interpretation consistent with results, balancing benefits and harms, and considering other relevant evidence

Other Information

23. Registration number and name of trial registry
24. Where the full trial protocol can be accessed, if available
25. Sources of funding and other support (such as supply of drugs), role of funders

References

• Schulz KF, Altman DG, Moher D; CONSORT Group. CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials. BMJ. 2010;340:c332. doi:10.1136/bmj.c332
• Chan AW, Tetzlaff JM, Altman DG, et al. SPIRIT 2013 Statement: Defining Standard Protocol Items for Clinical Trials. Ann Intern Med. 2013;158(3):200-207
• ICH Harmonised Guideline. Integrated Addendum to ICH E6(R1): Guideline for Good Clinical Practice E6(R2). 2016
• World Medical Association. Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Subjects. JAMA. 2013;310(20):2191-2194
• Moher D, Hopewell S, Schulz KF, et al. CONSORT 2010 Explanation and Elaboration: updated guidelines for reporting parallel group randomised trials. BMJ. 2010;340:c869
• Julious SA. Sample Sizes for Clinical Trials. Chapman and Hall/CRC; 2010
• Pocock SJ. Clinical Trials: A Practical Approach. Wiley; 1983