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![REFERENCES
1. Sougata Sarkar,Vartika Srivastava, Manjushree Mohanty. Postgraduate Pharmacology. Second edition. Hyderabad:
Paras Medical Books; 2025.
2. Rituparna Maiti. Postgraduate topics in Pharmacology.Third Edition. Hyderabad: Paras Medical Books; 2019.
3. Khanal Arun Bhadra, Jaypee Brothers (Jaypeedigital. Mahajan’s Methods in Biostatistics for Medical Students and
ResearchWorkers. Jaypee Brothers Medical Publisher (P) Ltd; 2016.
4. Kamalu I, Niyomwungere F, İlker Etikan.A Comprehensive Analysis of Cluster Sampling versus Multi-Stage Sampling
Techniques: Methodologies,Applications, and Comparative Insights. Pioneer Journal of Biostatistics and Medical
Research [Internet]. 2024 Mar 26;2(1):21–30.
5. WHO. Survey methods [Internet]. www.who.int.Available from: https://www.who.int/teams/immunization-
vaccines-and-biologicals/immunization-analysis-and-insights/global-monitoring/immunization-coverage/survey-
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- 1. RANDOMIZATION IN CLINICAL TRIALS Moderator: Dr DhirendraK Mahawar Associate Professor Department of Pharmacology SMS Medical College, Jaipur Presented by: Dr Harsh & Dr Deep PG Residents Department of Pharmacology SMS Medical College, Jaipur
- 2. LEARNING OBJECTIVES • Introduction:Epidemiological studies & Clinical trials • Randomization • Types of Randomization
- 3. RANDOMIZATION Random allocation ofintervention to the participants All participants have the same chance of being allocated to each of the study groups
- 4. TYPES OF STUDYDESIGNS Epidemiological study designs Analytical Descriptive Experimental Observational Observational Comparison group Exposure • RCTs • Non RCTs • Cohort • Case Control • Cross sectional study • Case report • Case series • Cross sectional study • Ecological study
- 5. “Prospective, ethically designedinvestigation in human subjects to objectively discover, verify, & compare the results of two or more therapeutic measures” Therapeutic measures = Drugs, dosage regimens, other interventions May be conducted in: • Healthy volunteers: Determination of safety, tolerability, Pk • Volunteer patients: Therapeutic efficacy CLINICAL TRIALS
- 6. TYPES OF TRIALDESIGNS Single arm studies • Simplest • Preliminary evidence of efficacy & safety • Useful for limited patient pool Limitations Interpretation of trial result ↓ Difficult No frame of reference for comparison Effect due to → Treatment? → Placebo? Inability to distinguish → Natural history? Multiple arm studies Examples: • Parallel design • Cross over design etc.
- 7. CONTROLS A group ofclinical trial participants who do not receive the drug/treatment being investigated Yardstick against which efficacy and safety of drug under investigation is measured Selection: Comparability to the target population Test & Control group Similar in all aspects that could influence outcome (except intervention) Types of Controls: Historical control Concurrent control • Placebo controlled • Active controlled • No treatment Self controlled trial ↓ Achieved by Randomization
- 8. RANDOMIZATION Random allocation ofintervention All participants have the same chances of being allocated to each of the study group Reduces differences between groups by → Equal distribution of unique characteristics amongst all trial arms • Random allocation is done during or after sampling • Makes groups comparable • Basis for assumption free statistical tests Protects against: • Bias (Selection, Allocation) • Confounding factors (Known/Unknown)
- 9. Easy implementation Groups • Similar size& composition • Indistinguishable • Only differ in intervention Same chance receiving either of the interventions Chance mechanism Participant and investigator can’t anticipate Criteria Unpredictability Simplicity Balance
- 10. RANDOMIZATION TECHNIQUES Coin flipCurrency note numbers Lottery* Table of Random numbers* Computer generated* *Requires numbered list of all participants
- 11. METHODS OF RANDOMIZATION Fixedallocation randomization • Prespecified probability for assigning participants • Not altered as study progresses 1. Simple randomization 2. Systematic randomization 3. Stratified randomization 4. Cluster randomization Adaptive randomization Probability for assigning participants changes 1. Restricted randomization 2. Minimization randomization 3. Covariate adaptive randomization 4. Response adaptive randomization 5. Covariate adjusted response adaptive randomization (CARA) 5. Multistage randomization 6. Block randomization 7. Unequal randomization
- 12. 4 Agent Control 2 SIMPLE RANDOMIZATION Every unitof the population ↓ Equal chance of getting recruited Unrestricted Random Sampling Sample is drawn unit by unit Population characteristics: • Small • Homogenous • Readily available Advantages: Simple & Easy Disadvantage: Imbalance in number of subjects
- 13. SYSTEMATIC RANDOMIZATION Kth patientrecruited K =Total population/Desirable sample size First recruitment: Random number less than K used Population characteristics • Complete list of population available • Large • Scattered • Non homogenous/homogenous (accurate result) Advantages: • Simple and easy • Little time and labour Disadvantages: • Need of complete list of population
- 14. STRATIFIED RANDOMIZATION Control andbalance the influence of covariates → Accurate results 1. Population divided into homogenous groups → Strata 2. Sample drawn from each strata at random 3. Sample size → Proportional to the size of each strata Population characteristics • Non homogenous Advantages: • Representative sample → Greater accuracy • Simple and useful for small clinical trials Disadvantages: • Complicated if many covariates • Difficult to implement in large clinical trials • Time & Labour intensive
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- 16. CLUSTER RANDOMIZATION Unit ofrandomization is group of individuals Cluster: Randomly selected group (Units of population) Natural groups (village, ward, school, etc.) • Technique allows small number of target population to be sampled - Small sample • Data provided is statistically valid (95% Confidence limits & 10% variation) - Higher Standard error Eg. National vaccination programmes
- 17. Advantages: • Large populationcan be studied • Less expensive • Less time, workforce • Simple & Feasible to implement List all states → Cities,Village, ward, schools, slums etc. →Total no. of clusters → Random selection of Clusters (Systematic) → Collect data from whole cluster or (With population) Implement random selection Disadvantages: • Higher sampling error • May fail to reflect the diversity of population • Complex procedure requiring proper planning
- 18. MULTISTAGE RANDOMIZATION More intricatevariant of cluster sampling • Sampling procedures carried out in several stages • Random sampling techniques used Study characteristics: • Large country surveys Advantages: • Flexible • Decreased labour Eg. Stool sample collection for hookworm survey First Sampling frame Eg. Cities ↓ Random sampling ↓ Second sampling frame Eg.Village ↓ Random sampling ↓ 10% people in selected villages sampled
- 19. MULTIPHASE SAMPLING Symptoms ofCough ↓ Mantoux test ↓ Mantoux test + ↓ Chest X Ray ↓ Chest X Ray + ↓ Sputum smear Part of information taken from sample ↓ Part of information taken from Subsample Number in subsample becomes smaller at each step Advantage: • Less cost & work Mantoux test – Chest X Ray –
- 20. BLOCK RANDOMIZATION • Commonlyused design in RCT Randomizing participants into blocks ↓ Equal number of subjects assigned for each intervention Blocks: • Small (size determined by investigator, half allocated in each arm) • Size should be multiple of the number of arms in study • Predetermined subject assignments Advantage: • Balance between number of participants between groups is guaranteed Disadvantage: • Analysis of data complicated • Small & fixed blocks → may be predicted b/2 b/2 b
- 21. Example: 1. For sampleof 16 participants and 2 treatment arms (A & B), block randomization is done. 2. Size of Blocks → Multiple of arms (4, 6, 8 etc.) for equal division. 3. Block size of 4 participants selected 4. Possible combinations to randomize participants 5. Block recruited → Participants randomized BLOCK RANDOMIZATION AABB ABAB BABA BAAB ABBA BBAA
- 22. UNEQUAL RANDOMIZATION • Equalrandomization → Maximizes statistical power • Issues: Ethical/Economical/Practical Eg. Cost difference between treatments, Outcome difference between arms (Placebo) ↓ Randomize fewer patients into expensive treatment or to less efficacious treatment • Smaller randomization ratio may be used (2:1) • Modest loss of statistical power → Cost savings / More practical & ethical design
- 23. ADAPTIVE RANDOMIZATION Restrictive Randomization Usespast treatment assignments Objective: Balance number of participants between arms Probability of treatment assignment changes ↓ According to assigned treatments of patients already in the trial Response-adaptive Randomization Past treatment assignments and patient response ↓ Calculate probability of future treatment assignments Objective: • Maximize power • Minimize expected treatment failures
- 24. ADAPTIVE RANDOMIZATION Covariate-adaptive randomization Pasttreatment assignments among patient covariates ↓ Calculate probability of future treatment assignments Objective: • Balance prognostic factors • Treatment assignments b/w covariates Minimization Randomization Adaptive stratified sampling Minimize imbalance between number of patients in each covariate across arms Eg.: Gender, age group, disease stage *Probability is not calculated Objective: • Balance prognostic factors • Treatment assignments b/w covariates Covariate-adjusted response-adaptive (CARA) randomization Combination of covariate adaptive and response adaptive randomization
- 25. ADAPTIVE RANDOMIZATION Minimization Randomization Adaptivestratified sampling Minimize imbalance between number of patients in each covariate across arms Eg.: Gender, age group, disease stage *Probability is not calculated Objective: • Balance prognostic factors • Treatment assignments b/w covariates
- 26. RECOMMENDED METHODS Large study(several hundred participants) Blocked randomization or stratified randomization Small study (~100 participants) Blocked randomization or stratified randomization Very small study (~50 participants) Adaptive randomization
- 27. REFERENCES 1. Sougata Sarkar,VartikaSrivastava, Manjushree Mohanty. Postgraduate Pharmacology. Second edition. Hyderabad: Paras Medical Books; 2025. 2. Rituparna Maiti. Postgraduate topics in Pharmacology.Third Edition. Hyderabad: Paras Medical Books; 2019. 3. Khanal Arun Bhadra, Jaypee Brothers (Jaypeedigital. Mahajan’s Methods in Biostatistics for Medical Students and ResearchWorkers. Jaypee Brothers Medical Publisher (P) Ltd; 2016. 4. Kamalu I, Niyomwungere F, İlker Etikan.A Comprehensive Analysis of Cluster Sampling versus Multi-Stage Sampling Techniques: Methodologies,Applications, and Comparative Insights. Pioneer Journal of Biostatistics and Medical Research [Internet]. 2024 Mar 26;2(1):21–30. 5. WHO. Survey methods [Internet]. www.who.int.Available from: https://www.who.int/teams/immunization- vaccines-and-biologicals/immunization-analysis-and-insights/global-monitoring/immunization-coverage/survey- methods
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