Clinical Trial Study Designs

Study Designs

• Health research uses two distinct study designs: observational and experimental
• Observational studies do not intentionally intervene in participants' lives or treatments
• Clinical trials (experimental) are specifically designed to intervene and evaluate health outcomes

Objectives of Clinical Trials

• Diagnose or detect a disease
• Prevent disease or early death
• Treat or cure existing disorders and manage symptoms
• Change behaviors or lifestyle habits to reduce risk factors

Trial Locations

• Clinical trials can be conducted in low, middle, and high-income countries reflecting local health issues
• The design and analysis are similar, but the conduct and delivery vary, particularly in administering interventions and collecting follow-up and outcome data

Interventions

• Interventions include injected, infused, swallowed, inhaled, or absorbed substances, medical devices, surgical procedures, radiotherapy, behavioral or psychological therapy, health service delivery improvements, health education, or alternative therapies

Modern Therapies

• Biological and targeted therapies have revolutionized the treatment of several disorders by using biomarkers, genetic abnormalities, or imaging markers to select therapies
• Vaccines can prevent disease or reduce disease progression

Regimen

• A combination of interventions is called a regimen (e.g., chemotherapy and surgery for cancer)

Investigational Products

• Drugs or micronutrients examined in clinical trials for treating, preventing, or diagnosing diseases are called Investigational Medicinal Products (IMP) or Investigational New Drugs (IND)
• Most clinical trial regulations cover IMP studies and several medical devices

Regulations

• IMP regulations are in the UK and European Union
• IND regulations are in the United States, Canada, and Japan

Regulatory Requirements

• New drugs and some medical devices need a license or marketing authorization from a national regulatory authority
• Availability to the target population requires a health technology assessment (HTA) or payer/reimbursement organization review through a process called market access

Terminology

• Intervention, treatment, and therapy are used interchangeably

Participants

• People in a trial are participants if healthy or patients if already ill

PICO

• PICO (Participants/Population, Intervention, Control, and Outcome) focuses on key design elements that must always be defined

PPIE

• Patient and Public Involvement and Engagement (PPIE) involves lay members in trial design, conduct, and interpretation

AI

• Artificial intelligence may identify eligible participants from medical records and analyze clinical data plus biomarkers

Decentralized Trials

• Decentralized trials use electronic processes for participant selection, treatment allocation, data collection, and remote assessments

James Lind's Trial

• James Lind conducted the first clinical trial in 1747
• Lind examined 6 treatments for scurvy among 12 sailors
• Two sailors received each treatment: cider, diluted sulphuric acid, vinegar, sea-water, a mixture of foods including nutmeg and garlic, and oranges and lemons
• Lind standardized living conditions to ensure changes were due to treatments, discovering that fruit cured scurvy

Key Trial Features

• Comparison between two or more interventions
• Attempting to ensure participants had similar characteristics

Randomization

• A key element missing from Lind's trial
• The Medical Research Council's trial of streptomycin and tuberculosis used random allocation

Natural Variation

• People vary in genetics, body characteristics, and lifestyles
• Variability leads to different responses to treatments

Evaluating Interventions

• Consider if responses are due to natural variation or a real treatment effect

Alternatives to Clinical Trials

• Clinical trials (RCTs), observational studies, or historical control trials can examine interventions
• Observational studies support effectiveness and safety evidence
• Care is needed when interpreting studies other than RCTs, as observational studies can give the same or conflicting results

Observational Study Examples

• Review of 20 observational studies: the influenza vaccine may halve the risk of respiratory and flu-like symptoms
• Review of 6 observational studies: high β-carotene intake reduced cardiovascular death risk by 31%

Risks

• 4 RCTs suggest high β-carotene intake increases the risk by 12%

Observational Study Usefulness

• May be helpful in evaluating treatments with large effects
• Uncertainty remains regarding the actual effect size

Sample Size

• These studies can have a larger sample size than RCTs and provide more evidence for side effects, especially uncommon ones

Confounding and Bias

• Design limitations of observational studies can make it difficult to establish if a new intervention is effective
• Called confounding and bias

Flu Vaccine Observational Studies

• Studies examine the effect of the influenza vaccine in preventing flu and respiratory disease in the elderly, although an adjustment may be required for confounding factors

Confounding Factor

• A third factor creates a spurious relationship between an intervention and a disorder

Confounding

• It represents natural relationships between physical and biochemical characteristics, genetic make-up, and lifestyle/behavioral habits affecting treatment response
• It cannot be removed from research but can be measured for statistical analysis

Bias

• A study design feature affects how participants are selected, treated, managed, or assessed
• Systematically distorts results in one trial group

Bias

• It can be prevented, but human nature sometimes makes this difficult
• It is difficult to adjust for bias in statistical analyses because it often cannot be measured

Randomisation

• It minimises the effect of confounding and some biases

Trial Categories

• Clinical trials have four categories (Phases I, II, III, and IV), based on the main goal

Trial Phase Priorities

• Phase I: Safety and toxicity
• Phase II: Efficacy and safety
• Phase III: Efficacy, safety, adherence, quality of life, and health economics
• Phase IV: Effectiveness, long-term safety, uncommon side effects, and new indications

Words in Italics

• The commonly indicate the primary focus of that trial phase

Efficacy

• Sometimes used when participants are a select group with high adherence
• Effectiveness applies to routine practice and better reflects treatment use in the target group

Relationship Between Efficacy and Effectiveness

• The magnitude of benefit of a new therapy is sometimes greater when using efficacy than effectiveness

Historic Trial Structure

• The tradition is that clinical trial involve a sepearte trial for phases I, II and III, particularly for pharmaceutical drugs
• To cut down the evaluation time different phases can be merged into the same protocol (e.g. phase I/II)

Phase I

• The first time a new regimen is examined in humans
• Evaluates a licensed drug for a new use or a new drug combination
• Study includes few participants, often less than 50
• Primary aims are to check the toxicity and find a tolerable dose

Phase II

• Often has 30-100 people
• Aims to estimate drug efficacy
• May include a single arm or randomised control
• Results help design the confirmatory, phase III trial

Phase III

• Should be randomised with a control group
• Has 100's-1000's of people
• Aims to provide a definitive answer on tx
• Used to obtain a marketing authorisation for a new drug

Phase IV

• relatively large
• used to monitor ongoing efficacy and safety of a product
• It can also be a randomised pragmatic study of currently existing treatments

Key Clinical Features

• Clinical trials share key design characteristics

Inclusion

• Specifying eligibility with inclusion/exclusion criteria

Homogeneous Groups

• Having many criteria makes it easier to detect an effect
• However, results may not be generalizable

Heterogeneous Groups

• Have many criteria
• Make treatment generalisable
• But introduce more variability
• And requires stronger effects to be measurable

Biomarkers

• They are increasingly used to determine what patients can benefit from a treatment

Intervention

• New interventions have been developed
• Descrition should be clear to replicate
• Aims to deliver superior effects to the control

Comparator

• They can include a current standard of care or a placebo

Control Selection

• Selecting the treatment to use as a control can include local guidelines or regualtory requirements
• Placebos should not be used where treatments already exist

Randomisation

• All trial participants should have equal chances
• The research team should not be able to influence allocation
• Avoids both known and unknown confounders

Randomisation advantages

• There are distinct advantages over randomisation
• Statistical adjustments only affect known confounders

Variance

• There will be always small differences
• Randomisation does not produce identical groups

Allocation Bias

• Selection bias should be avoided
• And no personal knowledge may be leveraged
• By either partipants or researchers

Randomisation

• Can be done with excel
• with existing software
• by coders
• allocation can also be unequal

Considerations

• trial size
• straticiation

Larger Trials

• large trials should consider simple randomisation

Stratification factors

• There are few options or wish random numbers can use stratifcation
• More complex options exist too

Design

• It should not be possible to bias treatements

Goals

• The goal of any treatement is clinical relevance

Study Goals

• Outcome measures are clinical or sympomatic
• They can be quantified with an assigned numeric value

Phase I

• Can measure multiple measures
• With a heavy focus on adverse events

Phase II or III

• Have 1-3 primary endpoints

Sources

• Data comes from forms and health records
• personal measures
• biological records