Study designs. Kate O’Donnell General Practice & Primary Care.

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Presentation transcript:

Study designs. Kate O’Donnell General Practice & Primary Care

Epidemiological questions. How common is the problem? What are the risks of further problems? Are treatments effective? What are the causes of the problems described? How effective are services?

Underpinning concepts. What concepts underpin these types of questions? Risk Effectiveness Association Likelihood Population level data applied to individuals

What can studies do? Describe the situation: Descriptive. Explain the situation: Analytical. Compare approaches: Experimental.

Study designs. Descriptive Cross-sectional, longitudinal. Analytic Case-control studies. Cohort studies. Quasi-experimental Natural experiments, policy interventions. Experimental Randomised controlled trial.

Study designs

PrevalenceCross-sectional Cause/ Aetiology Cross-sectional; Case-control; Cohort. PrognosisCohort. HarmCase-control; Cohort. EffectivenessRandomised controlled trial.

PresentFuture Past Cross-sectional Case-control Cohort From Altman. Practical Statistics for Medical Research, 1991.

Sample Randomise Intervention group Control group Randomised controlled trial

Case control studies: Key features. Retrospective, i.e. backward looking. Relate an effect or outcome to a probable cause. Individuals with disease (cases) compared to individuals without disease (controls).

Case control study. From:

Advantages & disadvantages AdvantagesDisadvantages Quicker than cohort studiesNo measure of incidence Relatively small study population required Can only investigate one disease at a time & no temporal association Good for rare diseases – can select all known cases Retrospective, so data may be biased, e.g. poor records; memory recall Case selection bias – must define cases very explicitly Control selection bias Matching controls to cases can be difficult Can only determine the odds ratio, not relative risk

Appraising case control studies Methodological approach: Are cases and controls similar, except for exposure to the putative cause? Is collection of retrospective data objective? Is there evidence of “causation”? Statistical reporting: Type of data – influences statistical analysis. Reporting of risk.

Cohort studies: Key features. Prospective, i.e. forward looking. Follow a population sample over a period of time, often years. Record new disease events, i.e. the disease incidence. Cohorts can be selected in either of two ways.

Selection of a cohort: External controls. i.A cohort of individuals that have been exposed to a postulated causal factor of disease. The cohort is followed up and all new cases of the disease recorded. In this type of study, the exposed group would be compared to a matched, unexposed group and the incidence of disease in the two groups compared, i.e. an external control. ii.An example would be a study to record the incidence of mesothelioma in factory workers exposed, or not, to asbestos.

Cohort studies. From:

Selection of a cohort: Internal controls. A population cohort can be selected and followed up over many years to determine the incidence of disease(s). In this type of study, those in the cohort who do not develop the disease act as the controls for those who do, i.e. an internal control. An example would be the MIDSPAN study.

Cohort studies. From:

Advantages & disadvantages AdvantagesDisadvantages Calculate incidenceNeed a large population Don’t have to select controlsFollow-up can take many years, so expensive Prospective data collection, so less bias Not good for rare diseases Can study more than one disease or outcome Lose individuals in follow-up Temporal associationPotential for bias in recruitment, assessment and follow-up. Standardised assessmentAssessment criteria may “drift” with time Can estimate relative riskMay become irrelevant before the end of the study

Appraising cohort studies Methodological approach: Representativeness of the inception cohort. Characterisation at study baseline. Nature and completeness of follow-up. Statistical reporting: Type of data – influences statistical analysis. Reporting of risk.

PrevalenceCross-sectional Cause/ Aetiology Cross-sectional; Case-control; Cohort. PrognosisCohort. HarmCase-control; Cohort. EffectivenessRandomised controlled trial.

Randomised controlled trials A clinical trial in which: at least two treatments, programmes, interventions are compared. one of these is a control group. allocation uses a random, unbiased method.

Population Group 1 Group 2 Outcome New treatment Control treatment From: Critical Appraisal Skills Programme (CASP), Oxford. Randomised controlled trials

Explanatory trials Measure efficacy: the benefit a treatment produces under ideal conditions. e.g. Phase III drug trials.

Pragmatic trials Measure effectiveness: the benefit a treatment produces in routine clinical practice. Aim to inform choices between treatments. Patients should be analysed in the group to which they were initially randomised, i.e. intention to treat analysis.

Intention to treat analysis All patients allocated to one arm of a RCT are analysed in that arm, whether or not they completed the prescribed treatment/regimen.

Two by two table

Appraising RCTs Methodological approach: Was assignment to the different groups randomised? Was the randomisation process/list concealed? Was everyone who entered the trial accounted for at the end? Were subjects and assessors “blind” to treatment allocation when assessing outcomes? Were groups similar at start of trial and treated similarly throughout the study?

Appraising RCTs Statistical reporting: Were subjects analysed in the group to which they were randomised: intention to treat analysis. Type of data – influences statistical analysis. Reporting of risk: RRR vs ARR.