Non-Randomised Controlled Studies

Types of Non-Randomised Controlled Studies

1. Cohort Studies

• Prospective cohort: Participants are identified by exposure status and followed forward in time to observe outcomes.
• Retrospective cohort: Data are collected from historical records; exposure and outcome have already occurred.
• Examples: comparing outcomes in patients who received Drug A vs. Drug B based on physician choice.

2. Case-Control Studies

• Cases (those with the outcome) and controls (without the outcome) are identified, then their past exposures are compared.
• Efficient for rare outcomes and long latency diseases.
• Highly susceptible to recall bias and selection bias.

3. Controlled Before-After (CBA) Studies

• Outcomes are measured in the same or a comparable group before and after an intervention, with a concurrent control group that does not receive the intervention.
• More rigorous than simple before-after studies because the control group accounts for secular trends.

4. Interrupted Time Series (ITS)

• Multiple measurements taken before and after an intervention at a population or group level.
• Can detect changes in level and slope of an outcome over time.
• Used often for policy evaluations (e.g., drug prescribing regulations).

5. Quasi-Experimental Studies (Natural Experiments)

• Exploit naturally occurring variation in exposure (e.g., geographic differences, policy changes, regression discontinuity designs).
• Include difference-in-differences analysis and instrumental variable approaches.

6. Non-Randomised Trials (Preference Trials / Pragmatic Non-Random Allocation Trials)

• Participants or clinicians choose the intervention arm rather than being randomly assigned.
• Sometimes run in parallel with an RCT (parallel preference design).

7. Cross-Sectional Studies

• Exposure and outcome measured at the same point in time.
• Cannot establish temporality; useful for prevalence and hypothesis generation.

Position in the Evidence Hierarchy

Key Sources of Bias in NRCS (ROBINS-I Framework)

Advantages of NRCS

• Feasible when randomisation is unethical (e.g., studying harm from smoking) or impractical.
• Reflect real-world practice (high external validity).
• Useful for rare outcomes requiring large sample sizes.
• Can evaluate long-term outcomes that RCTs cannot follow.
• Lower cost and faster to conduct than RCTs.

Limitations

• Confounding by indication is the major threat - sicker patients may systematically receive one treatment.
• Cannot establish causality as robustly as RCTs.
• Selection bias: non-random allocation means groups may differ in unmeasured ways.
• Recall bias (especially in case-control designs).

Methods to Reduce Bias in NRCS

NRCS vs. RCT - Quick Comparison

Non-Randomized Trials

Park's Textbook of Preventive and Social Medicine (PSM)

Why Non-Randomized Trials Are Used

1. Ethical reasons - e.g., smoking and lung cancer, or induction of cancer by viruses cannot be directly tested in humans.
2. Administrative reasons - Some preventive measures can only be applied to groups or on a community-wide basis (e.g., community trials of water fluoridation).
3. Logistic/cost reasons - When disease frequency is low and natural history is long (e.g., cancer cervix), RCTs require follow-up of thousands of people for a decade or more.

"Where the approach is sophisticated in randomized controlled trials, it is rather crude in non-randomized trials. As there is no randomization in non-experimental trials, the degree of comparability will be low and the chances of a spurious result higher than where randomization had taken place. In other words, the validity of causal inference remains largely a matter of extra-statistical judgement." - Park

Types of Non-Randomized Trials (as per Park)

1. Uncontrolled Trials

• Trials with no comparison group.
• Classic example: Pap test for cervical cancer - introduced in the 1920s with no RCT; evidence of effectiveness came from over a dozen uncontrolled studies showing reduction in cervical cancer mortality.
• Uses:
  • Evaluating whether a therapy has any value in a disease
  • Determining appropriate dose
  • Investigating adverse reactions
• Even in these trials, one uses implied "historical controls" - the experience of earlier untreated patients with the same disease.

2. Natural Experiments

• The epidemiologist identifies "natural circumstances" that mimic an experiment when true experiments are impossible.
• People "naturally" separate into groups (e.g., smokers vs. non-smokers) and epidemiologists test hypotheses from this natural separation.
• Other populations used in natural experiments:
  • (a) Migrants
  • (b) Religious or social groups
  • (c) Atomic bombing of Japan
  • (d) Famines
  • (e) Earthquakes
• Classic example: John Snow's "grand experiment" on cholera (London, 1853) - identified two naturally mixed populations differing only in their source of water supply:

• Lambeth Co. water came from above London (clean); Southwark & Vauxhall drew from sewage-polluted water.
• This demonstrated cholera is water-borne before the bacteriological era.

3. Before and After Comparison Studies

A. Before and After Comparison Studies WITHOUT Control

• Compare incidence of disease before and after introduction of a preventive measure.
• The experiment serves as its own control - eliminates virtually all group differences.
• Classic examples:
  • Prevention of scurvy by James Lind (1750) using fresh fruit in sailors
  • John Snow's cholera studies (1854)
  • Prevention of polio by Salk and Sabin vaccines

• (a) Data on disease incidence before AND after must be available
• (b) Only one factor should be changed; all others remain the same (e.g., adding fluorine to drinking water)
• (c) Diagnostic criteria must remain the same
• (d) Preventive measures should be adopted over a wide area
• (e) Reduction in incidence must be large (no control group to compare against)
• (f) Several trials may be needed before evaluation is conclusive

B. Before and After Comparison Studies WITH Control

• A "natural" control group is used to account for secular trends.
• If a preventive programme applies to an entire community, select another similar community as control.
• One is arbitrarily chosen as study group, the other as control.

• The existence of a control strengthens the conclusion that the fall in deaths/injuries was due to seat-belt legislation.

Evaluation of Preventive Measures (3 Key Questions, Park)

1. How much will it benefit the community? - Measured by the difference in incidence rate between experimental and control groups (combined outcome of effectiveness + acceptability).
2. What are the risks to recipients? - Immediate and long-term risks.
3. Cost in money and manpower? - Whether the measure is economical and practical.

"It is now conceded that no health measure should be introduced on a large scale without proper evaluation." - Park

Summary Table

• Park's Textbook of Preventive and Social Medicine, pp. 97-100