STUDY DESIGNS: case control, cohort and qualitative. Dr TAMSIN Newlove-delgado DOCTORAL RESEARCH FELLOW UNIVERSITY OF EXETER. Aims and objectives. To outline and revise: Causation Case control study design, advantages and disadvantages The odds ratio
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STUDY DESIGNS:case control, cohort and qualitative Dr TAMSIN Newlove-delgado DOCTORAL RESEARCH FELLOW UNIVERSITY OF EXETER
Aims and objectives • To outline and revise: • Causation • Case control study design, advantages and disadvantages • The odds ratio • Cohort study design, advantages and disadvantages • Relative risk • To summarize some key points about qualitative study design: • Use • Methods • Advantages and disadvantages
Relevant Paper 3 Syllabus • 3.1.10. Knows the benefits and weaknesses of different quantitative study designs to address different clinical questions: • Case-control • Cohort • 3.6 Critically appraises cohort and case control studies
Relevant Paper 3 Syllabus • 3.4. Qualitative Methods • Knows when to apply qualitative research methodologies • Additional approaches to sampling in qualitative studies • Different approaches to data gathering in qualitative studies • The role of qualitative methodologies in instrument (i.e. screening, diagnostic, outcome measure) development • Methods for validating qualitative data • Methods for minimising bias • Methods of analyzing data • Data saturation • 3.6 – Critically appraises qualitative research
Plan of afternoon • 1pm-2.30pm – Case control and cohort studies: including coffee break and exam questions • 2.30pm – 3.30pm – Qualitative studies
Example MCQ • Which of the following is not one of the Bradford-Hill criteria? • Temporality • Biological gradient • Plausibility • Residual confounding • Strength of association
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RCT: not always the answer1 • Unnecessary • Impractical/Unethical • Inappropriate • Prognosis • Diagnosis • Quality issues • And more
Investigating aetiology • Epidemiological studies of aetiology are usually observational not experimental • An observed association may be due to: • True cause • Reverse causation • Chance (random error) • Bias (systematic error) • Confounding
Assessing causation • Criteria?
Questions of causation • The Bradford-Hill criteria (J Roy Soc Med 1965:58:295-300) • 1. Strength of the association.2. Consistency of findings.3. Specificity of the association.4. Temporal sequence of association.5. Biological gradient.6. Biological plausibility.7. Coherence.8. Experiment. • Can you think of examples where this doesn’t work?
Advantages • Efficient for studies of rare diseases and diseases with long latent periods • Cheap, simple, quick (in comparison to cohorts) • Can examine multiple exposures – generate hypotheses • Sometimes the only practical option (e.g. where long latent period between exposure and disease)
Disadvantages • There are many! • Can study only one outcome • Notorious for being prone to bias: • Sampling/selection bias – selection of cases and controls • Observation and recall bias • Not good for rare exposures • The temporal sequence between exposure and disease may be difficult to determine. • As with all studies, confounding
Selecting cases • Need a clear case definition and source • Cases selected for a study should be representative of all cases of the disease in the population. • This is difficult!: many cases not diagnosed or misdiagnosed • A hospital sample in some diseases may be very different from a community sample
Selecting controls • Controls are used to estimate the prevalence of exposure in the population which gave rise to the cases. • The ideal control group would comprise a random sample from the general population that gave rise to the cases. • Controls should meet all the criteria for cases, apart from having the disease itself; but they should have the potential to develop it
Methods of selecting controls • Convenience sample • Matched sample • Using two or more control groups • Using population base sample e.g. from registers • Recruiting more than one control per case may improve the statistical power of the study (up to 4 controls per case)
Selecting controls: matching • Matching – Some studies are matched to select cases/controls who are as similar as possible e.g on age, ethnicity etc • Can be useful in small samples – as we might not have sufficient subjects to adjust for several variables at once. • Difficult/complicated to match on too many factors • Important not to match on basis of risk factor of interest / too many factors – ‘overmatching’ may make the controls unrepresentative and underestimate the true difference
Example of selection bias • Bias introduced through poor selection of controls • Case control studies of NSAIDS (exposure) in colorectal cancer3
Case control studies in psychiatry • Suicide a popular subject……. • Barraclough, B., Bunch, J., Nelson, B., et al (1974) A hundred cases of suicide: clinical aspects. British Journal of Psychiatry, 125, 355-373. • More modern examples: • Fuller Torrey E, Rawlings R, Yolken RH. The antecedents of psychoses: a case-control study of selected risk factors. SchizophrRes2000; 46: 17–23.
Case control studies and the odds ratio • Estimates the strength of association between an exposure and an outcome • Does not calculate relative risk as retrospective • Does not give incidence/prevalence – unless all cases in a population are included • The odds ratio is a measure of the odds of exposure in the cases, compared to the odds of exposure in the control group.
OR: 2 by 2 table OR = (a/c)/(b/d)
Imaginary example– are cats associated with schizophrenia? • Odds of exposure in the cases: 80/20 = 4 • Odds of exposure in the controls: 100/300 = 0.33 • Odds ratio: 4/0.33 = 12.12 • So……the odds of having had a cat as a child in the group with schizophrenia were over 12 times the odds of having had a cat as a child in the control group – • Or those with schizophrenia were over 12 times more likely to have had a cat as a child….
Feline bias • Selection bias • Cases recruited through a charity that runs ‘pet experiences’ for people with mental illness • Controls were a hospital sample recruited from an allergy clinic • Both of these would spuriously increase estimate of effect • Recall bias • Are those with schizophrenia more likely to remember/report having had a cat – particularly if aware of hypothesis in question
Cohort study design • Usually prospective; but can be retrospective
Prospective and retrospective cohort • Cohort studies may be prospective or retrospective, but both types define the cohort on the basis of exposure, not outcome.
Advantages • Can investigate risk factors impossible to study in controlled trials - e.g. smoking or asbestos • Describe incidence and natural history • Multiple outcomes can be measured for any one exposure. • Exposure is measured before the onset of disease (in prospective cohort studies). • Good for measuring rare exposures, for example among different occupations. • Demonstrate direction of causality. • Can calculate relative risk
Disadvantages • Expensive, time consuming • Loss to follow up can introduce bias • Need a large sample size – especially for less common outcomes • Not good for rare outcomes or long latency periods • Need to maintain consistency of follow up over time • Systematic misclassification of exposure or outcome status – information bias
Sources of bias in cohort studies • Differential misclassification: can lead to an over- or underestimate of the effect between exposure and outcome. • Losses to follow up : degree to which losses to follow up are related to either exposure or outcome can lead to serious bias in the measurement of effect of exposure and outcome.2
Cohort studies in psychiatry • Andreasson et al: cannabis consumption and development of schizophrenia in a cohort of 45,570 Swedish conscripts4.
Relative risk in cohort studies • Analysis • Riskexp = a / (a+c) (divide by total exposed) • Riskunexp = b / (b+d) (divide by total unexposed) • Estimate relative risk = Riskexp / Riskunexp • Indicates increased/decreased risk of disease assoc with exp: • RR = 1 – risk is same in exposed and unexposed groups • RR > 1 – risk is greater in exposed group • RR < 1 – reduction in risk in exposed group
Qualitative studies • Answers questions such as: • What is X & how does X vary in diff circumstances & why? • Not ‘how big is X or how many X’s are there? • Concerned withmeanings people attach to their experience & how they make sense of world
Uses of qualitative research • Preliminaryto quantitative research • Helps ensure validity of data obtained • E.g. interviews to inform a survey • Generate theory • To validate quantitative research or provide a diff perspective on same phenomena. Mixed methods • Used independently to uncover processes or practice not amenable to quantitative research • Address the 'gap' between evidence based approaches and practice
Example: Owens et al 20115 • Objective To shed light on the difficulties faced by relatives, friends, and colleagues in interpreting signs of suicidality and deciding whether and how to intervene. • Design Qualitative study of completed suicides, based on in-depth interviews with multiple informants. • Setting London, southwest England, and south Wales. • Participants 31 lay informants (one to five for each case), including parents, partners, siblings, friends, and colleagues of 14 cases of suicide in which the deceased was aged 18-34 and was not in contact with secondary mental health services
Quotes5 • Friend: “He’s a bloke, isn’t he? We don’t do emotion.” • Sibling: “I’d try and get things out of him about how he felt, especially when he’d had a few drinks, but he never ever opened up . . . He was a typical bloke in that respect . . . So I never really pushed it. I didn’t want to make him feel uncomfortable.”