Introduction to Study Design and RCTs Simon Thornley.

Introduction to Study Design and RCTs

Simon Thornley

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Cohort

Participants

UnexposedDisease

Unexposed No disease

ExposedDisease

Exposed no disease

Exposed

Unexposed

Participants Exposure Outcomes

By measurement

Cohort study

eg FraminghamPatients without diseaseGroup by exposureCan use a variety of exposuresFollow until disease develops

Cohort advantages

Exposure precedes disease Disease status does not influence selection Several outcomes possible Good for rare exposures Control group obvious (compare case-control)

Cohort disadvantages

Prospective costlyInefficient for rare diseases with long latencySeveral outcomes possibleExposed followed more closely than unexposed?Loss to follow up causes bias

Do computer screens cause spontaneous abortions?

1991

Participants

UnexposedDisease


ExposedDisease

Exposed no disease

Exposed

Unexposed


Computer screens

No computers

abortion No abortion

Female telephone operators

54 312

82 434

Time


Incidence in exposed Relative risk = ----------------------------

Incidence in unexposed 54/(54+312)

= ------------------- = 0.93 82/(82+434)

In pictures - Actual

Null hypothesis; No effect

Effect of Monitors on abortion

Risk ratio

Fre

qu

en

cy

0 1 2 3 4 5

02

00

40

06

00

80

01

00

01

20

01

40

0

Cross sectional

Participants sampled at one point or short duration

Exposures and outcomes assessed at same point in time

Participants

UnexposedDisease


ExposedDisease

Exposed no disease

Exposed

Unexposed


By measurement

Cross-sectional

AdvantagesDescribes pattern of

diseaseVariety of outcomes

and exposuresCheapInexpensive

DisadvantagesPrevalent rather than

incident casesCan not distinguish

cause and effectMust survive long

enough to be included in study

Short duration diseases under-represented (e.g. Influenza)

Cross-Sectional study - bias

Imagine... People with disease that are sedentary die

early Cross-sectional study of disease (outcome)

and exercise (exposure) Only sample survivors, so find high proportion

of people who exercise with disease What would you infer about causal

relationships?

Does wearing fluoro gear protect you from bike crashes?

Participants

UnexposedDisease


ExposedDisease

Exposed no disease

Exposed

Unexposed


Fluoro colours

No fluoro colours

Bike crash No bike crash

CyclistsTaupo bike race

162 323

588 1343


Cum. Incidence in exposed Relative risk = ----------------------------

Cum. Incidence in unexposed162/(162+323)

= ------------------- = 1.10 588/(588+1343)

In pictures- Actual

Independent

Case-control

Investigator selects cases and controls based on disease statusCarefully defined population (cases = control population)Exposure history examined Derive P(exposure | case status)

Case-control study: Cases

Ideally, pcase=pdisease

Prevalent From surveypeople with disease at particular point in timeselection bias/favours long lived, chronic cases

Incident from population registryexposure and disease tied only to development of disease, not duration or prognosis.

Case control study: Controls

Ideally, pcontrol=pundiseased

Population vs. hospital controlsHospital controls likely to have disease related to exposure, even if not disease of interest.Population controls, from source of cases, generally better approach, but $$ can be prohibitive

Electoral rollsRandom digit dialling

Reality More complex; rarely have matches, but

frequency matching more common. E.g. Cot death study Cases – infants who died from cot death

(area)

Method Sampling frame – all births in geographic area Frequency matched Control randomly allocated age for interview

similar to age distribution to cot deaths from previous years (about 3 months old)

DOB calculated and adjusted to fit day of week (weekends higher chance of becoming cases)

Obstetric hospital randomly chosen in proportion to number of births in previous financial year

CC - advantages

Good for long latency/ rare diseasesLook at many exposuresSmaller sample size

CC - disadvantages

Only one diseaseCan't estimate disease risk, because work backwards from disease to exposure*More susceptible to selection bias as exposure has already occurred.More susceptible to information biasNot efficient for rare exposures (Why?)

Case-Control study -example

Participants

UnexposedDisease


ExposedDisease

Exposed no disease

Exposed

Unexposed


Fenoterol

Ventolin/other

Cases Controls

Adults in hospital with asthma

Fenoterol study, Neil Pearce (guest lecturer)

60 189

57 279

Effect measure

odds of exposure in cases Odds ratio= ----------------------------

odds of exposure in controls 60/57= -------------- = 1.55 189/279

Actual

Null hypothesis; No effect

Questions Which study design is best for assessing

causation, assuming no other limitations are present? A) Cross-sectional study B) Randomised controlled trial C) Case-control study D) Cohort study E) Case-series

Questions In a cross sectional study of risk factors for

angina, a random sample of elderly subjects were asked the question “Do you smoke cigarettes?” Answers were used to classify respondents as smokers or non-smokers. Further, subjects were classified as positive for angina if they had, at some time in the past, been told by a doctor that they suffered from this condition.

When the data from the study was analysed, no statistically significant association was found between cigarette smoking status and angina status.

Has the study measured incidence or prevalence of angina? Explain your answer.

A considerable body of past evidence suggests that the risk of angina increases with increasing tobacco consumption. Suggest reasons why the study described here failed to find an association.

Suggest an alternative design of study that would be more suitable for investigating whether smoking causes angina. Consider the question(s) that you would ask the chosen subjects about their smoking habits.

SummaryCharacteristic Cross-

sectionalCase-control Cohort RCT

Selection bias Medium High Low Low

Recall bias High High Low Low

Loss to follow up NA NA High High

Confounding Medium Medium Medium Low

Time required Low Medium High High

Cost Medium Medium High High

Summary

Observational

Cohort

Many outcomes, exposures limited

Case- control

One outcome, many exposures

Cross – sectional

Many exposure, many outcomes;

Temporality limits causal inference

ExperimentalRandomised controlled

trial

Ethical constraints

Ideal design

Introduction to Study Design and RCTs Simon Thornley.

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