STUDY DESIGNS.ppt
- 2. Learning Objectives • Classify study designs • Define the unique features of the study designs • Discuss weaknesses and strengths associated with each study design • Discuss the most appropriate study design to answer certain research questions
- 3. Determining a study design • Identify topic of interest • State question of interest • State objectives of the study • Choose the best design to answer question Topic Research question Objectives (Hypothesis)
- 4. Types of Study Designs Observational • -- Case report • -- Case series • -- Ecological Studies • -- Cross-sectional • -- Case-control • -- Cohort Experimental • -- Randomized clinical trial
- 6. Overview of study designs
- 8. Case Report /Case Series Case reports Case series Selective by nature, providing little information May help identify potential health problems Uses of case series and reports 1 patient: Case Report More patients: Case Series
- 9. Ecological Studies Describe disease occurrence on population level Evaluate an association using the population -not the individual -as the unit of analysis. The rates of disease are examined in relation to factors described on the population level Example: Association between cancer and fat intake? National Cancer Rate High Low High Low National Diet Fat-Intake
- 10. Ecological Studies Key issues Ecological fallacy: We do not know if the individuals who have cancer were also the individuals with the high fat intake • Explores correlations between group level exposure and outcomes • Unit of analysis: usually not individual, but clusters (e.g. countries, counties, schools) • Useful for generating hypothesis • Cannot adjust well for confounding due to lack of comparability (due to lack of data on all potential covariates) • Missing data is another concern
- 11. Example
- 12. Types of ecological studies • Multiple group study Compares disease rates among many regions during the same period • Time-trend studies Comparison of disease rates over time in one population • Mixed designs Multiple groups + multiple time periods
- 14. Examples of time series
- 15. Uses of ecological studies • Are appropriate designs when generating • May be used for testing a new hypothesis BUT have limited value due to in-built design errors • Only design possible when adequate measurement of individual-level variables is not possible/not ethical Example: Holding off immunization • When funds or time is limited to do individual level studies
- 16. Advantages of ecological studies • Are low cost and convenience • Simple to analyze and present • Often helpful for generating new hypotheses for further research • Aggregated data on exposure and health outcomes often publicly available in state and national databases
- 17. Disadvantages of ecological studies • Cannot adjust well for confounding due to lack of data on all potential covariates • Measures of exposure are only a proxy based on the average in the population • Lack of available data on confounding factors. • Missing data is another concern • Prone to Ecological fallacy: We do not know if grouped results apply on the individual level
- 18. Ecological fallacy • Also called ecological inference fallacy or population fallacy • is an error where conclusions are inappropriately inferred about individuals from the results of aggregate data • Example: If countries with more Protestants tend to have higher suicide rates, then Protestants must be more likely to commit suicide • How can it be avoided: If individual data is not available difficult to control for except through modelling
- 19. Why ecological studies • Low cost and convenience • Some measurements cannot be made on individuals • Ecologic effects are the main interest (at the population level) • Simplicity of analyses and presentation • Often helpful for generating new hypotheses for further research
- 20. Cross-sectional studies • Exposure and disease are determined simultaneously for each person a snapshot of the population at one point in time • No follow up in this design • This can only indicate association, but cannot give a time-sequence. • Good for prevalence studies and testing association
- 23. Strengths • Fast • Inexpensive • May answer question of interest • Used to determine both prevalence of outcomes and exposures • May be used to design future studies • Start of cohort study • May even be used for repeat cross-sectional analyses
- 24. Weaknesses • Only prevalence cases, can’t measure incidence • Cannot determine whether exposure preceded outcome (Outcome may precede exposure) • Unable to establish causal relations – need for longitudinal study designs
- 25. Case-Control study Start: Cases and Control Population Cases (with disease) Controls (Without disease) Exposed Non- Exposed Non- Exposed Exposed Direction of inquiry Present Past
- 26. Case-Control study • Compares cases to controls in order find out what factors are associated and could possibly have contributed to the problem • Cases: Diseased • Controls: Not diseased • Association measure = OR
- 27. Features of case control studies • Less expensive than cohort studies and experiments • Small number of participants needed • Bes t design for diseases with long latent period • Very efficient for rare diseases • Multiple etiologic factors can be studied at one time • Cannot yield estimates of incidence or prevalence • Riskier due to biases (especially recall bias)
- 28. Cohort studies • A cohort is a group of subjects that are followed over time starting at a specified point in time and usually have something in common at the start • Cohort study is where participants are selected with respect to exposure • Individuals exposed to a risk factor (study group) are compared those not exposed (the control group). • Starts with measuring exposure, looks forward to the outcome
- 29. Cohort cont…. Purpose • To study incidence of disease or other conditions • To study associations between exposures and outcomes (risk factors, determinants) Measure association = OR /RR
- 30. Nested Case-Control Study Special case-control study and is within an ongoing cohort study advantage: no recall bias, temporal relation between exposure and disease possible, on selected group of persons more expensive test can be performed
- 31. WHY OBSERVATIONAL STUDIES • Usually the only option if the predictor is a potentially harmful exposure or risk factor • Even if the predictor is an intervention, an RCT may not be feasible due to duration between exposure and outcome • Financial reasons: intervention studies can be significantly more expensive than observational studie • More intellectually interesting than RCTs?
- 32. .
- 35. Clinical Trial: Definition A clinical trial is a prospective study comparing the effect of intervention(s) against a control A research activity that involves the administration of a test regimen Note: A proper clinical trial Always prospective Must have 1 or more interventions Must have a control group
- 37. Clinical Trial Objectives • To asses the efficacy of a new intervention or drug • To asses the effectiveness of a new intervention or drug • To asses the safety of a new intervention or drug
- 38. History of Clinical Trials • Daniel 1:12-16. A diet experiment (Royal food and wine versus vegetables and water) for 10 days • 17th century: Lancaster (captain of a ship) – experiment to examine the effect of lemon juice on scurvy for sailors. – Ships with lemons were free of scurvy compared to ships without lemons having scurvy. • Lind (1753) – Study of 5 tx for scurvy in 10 pts (2/tx) plus 2 pts without tx (control). – First two pts given orange and lemons recovered quickly and was fit for duty after 6 days, compared favorably with all other patients • Smallpox experiment (1721) at the Newgate prison in Great Britain. Voluntary inmates were inoculated and were free from smallpox.
- 39. Key Elements of a Clinical Trial • Selection of subjects • Allocation of exposure • Blinding • Data collection • Statistical issues • Ethical considerations
- 40. Selection of Subjects Population at risk/Target population ENTIRE group of individuals to generalize results The intervention is intended to benefit this population Accessible population Population to which the researcher has reasonable access May be a subset of the target Study population Group of participants actually studied Subset of population meeting eligibility criteria Inclusion criteria – identifies the target population Exclusion criteria – excludes people from the study, mainly for safety reasons
- 41. Allocation of exposure • Studies without controls – not a clinical trial although still an experiment • Studies with controls: Types of controls/Comparison groups Historical controls (compare with the past) Simultaneous non-randomized controls (concurrent group/quasi experiment) Randomization - true controls • Importance of controls For comparisons Allow to determine if outcome is caused by intervention vs other factors
- 42. Randomized controlled Trials (RCT) • Exposure assigned in a random way, participant have equal chance of being in either control or intervention group • Balances the known and unknown risk factors for the outcome under study – eliminates confounding due to measured and unmeasured factors • Methods for randomization Simple randomization (fish bowel method, tossing a coin) Random number table Computer-generated list of assignments
- 43. Blinding/ Masking • The team assessing the outcome are not aware of treatment assignment • To prevent the biased assessment of the outcome Single-blinded study • Either pts or physicians are blinded to the tx allocation Double-blinded study • Both pts and physicians are blinded to the tx allocation
- 44. Analysis of trials • Should always start with a baseline comparison of groups Note: Investigator cannot dictate what a participant does in a clinical trial, may or may not comply with Rx Intent-to-treat (ITT) – Participants are analyzed according to the groups they were randomized – If 100 randomized to a treatment, all analysed whether took it or not Per-protocol analysis • Analysis is only for participants who completed the treatment Both analyses are recommended and compare conclusions
- 45. Phases of Clinical Trials • Phase I: clinical pharmacology and toxicity – 1st experiment in human for new drug – Primary concern: Safety – Typically required 15-30 patients • Phase II: Initial Assessment of Efficacy – examine the efficacy and refine the safety – Goal is to screen out ineffective drugs – Has 30-100 participants • Phase III: Full-scale Evaluation of Treatment Efficacy – Compare new treatment with standard treatment – Aim is to define the ‘best’ treatment – Hundreds to thousands of participants • Phase IV: Postmarking Surveillance – monitoring the adverse effects
- 46. Ethical Principles in Trials • Respect for Persons – Voluntary, informed consent – Protection of vulnerable populations – Right to end participation in research at any time – Right to safeguard integrity – Protection of privacy and well-being • Beneficence – Non-malfeasance – Benefits should outweigh cost/risks • Justice – Protection from physical, mental and emotional harm – Fairness ALL TRIALS MUST BE REGISTERED IN A CLINICAL TRIAL REGISTRY
- 48. Factorial Design Population Sample Int A and Int B Int A and Pbo B Pbo A and Int B Pbo A and Pbo B Outcome Outcome Outcome Outcome
- 49. Experimental vs. Observational Observational • Predictor = exposure or risk factor • Usually biased • Confounding usually an issue Experimental • Predictor = intervention (treatment or therapy) •Minimize bias •Confounding eliminated