Exam 1 Flashcards
What is a placebo? What is it not?
Something that is inert (inactive, not therapeutic) but use it because of that placebo effect (the thought in the mind that it is doing something)
- It is not “nothing”
What two individual are accredited for the development of evidence-based medicine?
Dr. James Lind
Dr. David Sackett
Describe the relationship between Dr. James Lind and EBM
- accredited for discovering scurvy
- took 12 sailors, paired them, one got nothing and the other got oranges/lemons
- ompared both groups
- early version of a study
Describe the relationship between Dr David Sackett and EBM
- Father of EBM
- Established core principles of EBM in a landmark article in 1996
- Established 3 core principles:
a) Research
b) Clinical Expertise
c) Patient
Define EBM.
Evidence-based medicine (EBM) is the integration of best research evidence with clinical expertise and patient values
In EBM, what is a critical factor to evaluate effectiveness?
- Must be applied to the patient
- Although it may say in the guidelines, need to consider if it is useful for the patient
Why do we need EBM?
New therapies
New indications
New formulations
New “experts”
What are the five steps of EBM?
Ask: Develop your question
Acquire: Find the (best) solution
Appraise: critically evaluate the evidence for validity and usefulness
Apply: Use results in your practice
Assess: Evaluate your performance
In Step 1 (ASK): one should develop the __________
Research Question
A research question should be based on:
Population/Patient (Among….)
Intervention/Exposure (does…..)
Comparison (versus….)
Outcome (effect)
In step 2 (Acquire), one should ….. Examples?
Get the evidence - literature search
Medline, pubmed, cocharnae database, socialmedia, google scholar
In regards to a question about therapy, the ideal study type is:
RCT
In regards to a rsearch question about prevention, what is the ideal type of study?
RCT > Cohort Study > Case Control
In regards to a diagnosis question, what is the ideal type of study?
Prospective, blind controlled trial comparison to gold standard
In regards to prognosis, what is the ideal study design?
Cohort Study > Case Control > Case scenario/case report
For a research question on etiology/harm, what is the ideal study design?
RCT > Cohort Study > Case Control
For a cost analysis research question, the ideal study type is…..
Economic analysis
What often provides the best answers for clinical questions?
Meta-analyses and systematic reviews, when available, often provide the best answers to clinical questions
What is the benefit of a meta-analysis?
Meta-analyses and systematic review, when avilable, often provide the best answers to clinical questions
Describe the different types of research study designs
Study the graph
Describe the hierarchy of study design.
Study the pyramid
Define descriptive study. What is it simply?
One that is designed to describe the distribution of one or more variables, without regard to any causation or other hypothesis. (Just a snap shot in time)
Define analytic study.
Analytic studies test hypotheses about exposure- outcome relationships and measures the association between exposure and outcome throughout time.
How should one be able to distinguish and RCT?
Should be able to pick out RCT’s as should mention “randomization” in the methods
In step 3 (appraise), one should….
Critically Appraise: The process of carefully and systematically examining research to judge its validity, results and relevance.
Why is critical appraisal important?
Study results are not always:
Valid (actually due to the intervention/exposure)
Safe (invalid results can be harmful/wasteful)
Useful (meaningful or applicable to your patient)
Define internal validity
The degree of confidence that the causal relationship you are testing is not influenced by other factors or variables
Are the results due to the intervention (or exposure) we are studying… or something else?
What are the 3 major threats to internal validity?
Chance
Confounding
Bias
Define external validity . What does it depend on?
Are the results applicable (generalizable) to other populations (patients), settings and time?
Typically depends on study population (inclusion and exclusion criteria) and setting
Give an example of internal and external validity
Internal: Those who took Vitamin D scored 10% higher, is this due to the Vitamin D or something else
External: Depends on the exclusion and inclusion principles –> Can you apply those results of the Pharm.D. students to engineering students.
What is chance?
Random error
Inherent in all measurements (we are only taking a sample of all the possible observations)
The more there is, the less precise the results
What is an example of chance? Can you fully eliminate chance?
In the Vitamin D group, exam results were higher. Can I take those results and apply them to every pharmacy student in Canada –> NO
If we measured all pharmacy students in Canada, results are more precise; however, never fully able to eliminate chance.
The more measurements we take the more precise and closer to the actual results.
What is bias?
Any systematic (not due to chance) error in a study that results in an incorrect estimate of the association between the intervention or exposure and the outcome
…or…
Problems with the way a study was designed, conducted, or classified that leads to incorrect results or conclusions
What is confounding? What msut it be related to? Provide an example?
- A confusion of effects
- When some factor(s), other than the intervention or exposure under study, influences the observed outcome
- The factor must be linked to the exposure and the outcome
- Coffee causes heart attacks; however, coffee drinkers are more likely to be smokers. Therefore, may not be coffee at all.
External validity is related to…… What is an issue associated with external validity?
Related to the inclusion/exclusion criteria
Studies (especially RCTs) are very specific about who is and isn’t allowed in the study
Often becomes an issue with drug studies:
Who should use the drug?
Who the drug is approved for?
What is chance? Is it beneficial or detrimental to studies? How is chance calculated?
Random error – inherent in all measurement
Less random error = good
More random error = not good
Estimated and reported using statistics:
P-value
What does the P-value represent?
Probability representing the strength of evidence to support the null hypothesis
P value represents the probability the results are due to chance rather than a real treatment effect (want a low p-value)
What is the null hypothesis in studies? What is the alternative hypothesis?
Null Hypothesis: Set at showing no difference between the groups
Alternative Hypothesis: There is a difference between the groups
Describe the relationship between P-value, null hypothesis, alternative hypothesis?
Large P value (>0.05) = supports null hypothesis
There is no “statistically significant” difference between the groups’ results
Small P-value (<0.05) = reject the null hypothesis
There is a “statistically significant” difference between the groups’ results
How can one deal witch chance within a study?
Increase the sample size (not always possible)
Recognize the extent (through statistics) and interpret the results accordingly
Recognize that Statistical significance ≠ clinical significance (do not go hand and hand)
Is there a relationship between statistical significance and clinical significance? Example?
Statistical significance ≠ clinical significance (do not go hand and hand)
If a study concluded a 10 day difference in survival, this could be statistically signifiant but is not clincially significant
What are some examples of confounders?
- Smoking
- Age
- Exercise Level/week
- Blood pressure
- Diet
-Sex
Some may be hard to measure: stress, socioeconomic status, genetics
Can someone get some extra addictive dumauriers to smoke saturday
How can one deal with confounding?
1) Randomization (Gold Standard)
- Ensures groups are similar in all aspects (known and unknown factors equally distributed)
2) Stratification
- Stratify by a certain factor
3) Matching
- Observational studies (match by age and sex)
4) Statistical Models (multivariable models)
- “Controlled for” or “adjusted for” –> Attempts to adjust for confounding (only variable known and can measure)
How can one indicate confounding? What should we do?
TABLE 1: BASELINE CHARACTERISTICS
- use clinical judgement to determine if there is a difference between the groups
Importance of Table 1 (population characteristics):
1) Indicate confounding
2) Provides insight on external validity (gives insight on people studied and whether can apply to patients)
What is bias? What usually causes it?
Problems with the way a study was designed, conducted, or classified that leads to incorrect results or conclusions
Usually because the groups were treated differently somehow
What are the two main types of bias? Where do they come from?
1) Selection Bias
- Problems with how the study subjects were selected
- Want everyone to be selected from the same patient population
2) Information Bias
- Problems with measuring, collecting or analyzing information (exposure and/or outcomes)
Define selection bias? What does it effect? Types of selection bias?
Systematic error (or differences) in how the study subjects were selected or who participated
Primarily affects external validity
Self Selection/volunteer bias
Healthy Worker (adherer) Bias
Attrition Bias (lost to follow up)
What is self-selection/volunteer bias? What bias is it?
- People who volunteer/participate in studies are different from those who don’t
- Selection Bias
What is healthy worker (adherer) bias?
Employed (higher SES-socioeconomic status) individuals are usually healthier
What is attrition bias (lost to follow-up)? What is the main problem and when it is an issue? Why is this detrimental to a study?
- People who leave study e.g. a/e, found process to rigorous, drop out of pharmacy, death
- Main problem is when they drop out of one group (5 and 5 would be less concerned than 10 for 1 group)
- Becomes an issue if there are differences between those who were lost and those who weren’t
a) Lose important data (why did they drop out/withdraw?)
b) If a whole ton drop out of one arm, lose benefit of randomization (not equal anymore)
c) Chance becomes more of an issue
Define information bias.
Systematic errors in the way subjects were measured or classified
What are the types of errors that lead to information bias? Examples?
Outcome errors (RCT and observational studies)
-Problems with measuring tools (one electronic bp monitor, one group manual)
-Problems with actual measurements
Exposure errors (more so with observational studies)
- Problems with how subjects are categorized (non- vit. D group taking a multivitamin)
- Problems with measuring tools
Subject or observer variation (interpretation of pain) – everyone different and unique
When is information bias a concern?
Primarily a concern when the likelihood of being misclassified is unequal between groups
What are some examples of information bias?
Recall Bias
Interviewer Bias (Minimized by standardized forms, questions)
Surveillance/detection bias
Define recall bias
Individuals remember things differently
Subjects with the outcome (especially if negative) are more likely to remember their exposure – e.g. woman born with a baby birth defect (I did take that bp med one time, where as someone with a healthy baby would not)
Define interviewer bias? How can it be minimized?
Interviewer asks about exposure/outcome differently
Leading, probing or influencing questions
Multiple interviewers
Minimized by standardized forms, questions
Define surveillance/detection bias.
One study group followed more closely than the other
“If you look…you will find”
More outcomes identified because more follow-up, not necessarily because it occurred more in that group
What is a goal of studies in regards to bias?
Goal is to minimize bias when designing the study
Will never completely eliminate
Recognize and acknowledge it
Study the Graph on Slide 16
What are some strategies for reducing bias?
Clear definition of study and sample population
Ensure all groups are treated the same except for the intervention
Standardized measurements
- Same questionnaire for all subjects
- Same interviewers
- Automated devices
- Centralized labs (all analysis in same labs)
Collect the same information from all subjects in the same way
Blinding (pt or researcher or both are unaware of what group a t is)
What is publication bias? What does it effect? Example?
Authors and journals tend to publish positive findings, especially with drug trials
May lead readers to think there is a consistent association when it’s not really the case
Not effecting internal validity
E.g. Trial A finds that a new drug is effective (publish), Trial B shows significant adverse effects (not publish) potentially giving a misleadingly favorable impression of the new drug’s effectiveness and safety
What is a randomized controlled trial?
Test whether an intervention works by comparing it to a control condition
How are subjects divided in an RCT?
Subjects assigned to a study group:
Intervention group
…or…
Control group (no intervention, alternate intervention)
In an RCT, what does it mean to be randomized? What groups are randomized?
Randomized = subjects assigned to study groups randomly
Have an equal probability of being assigned to any group
Can be more than 2 groups
Randomization is critical for…..
Minimize confounding
Can randomization occur in an observational study?
- No. Cannot occur in an observational study.
What are the different types of RCT types?
Parallel
Cluster Randomized
Cross-over
Describe a parallel RCT study design?
A study sample is selected from a population. From the study sample, subjects are further divided into an intervention or control/comparison group. These groups are followed over time and monitored for the outcome.
Describe a clustered-randomized RCT study design?
Clusters of individuals are randomized instead of individuals (e.g. cities, classes, pharmacies, hospitals)
A cluster randomized trial (CRT) is a randomized controlled trial in which pre-existing groups, called clusters, of individuals are randomly allocated to treatment arms.
When is a cluster-randomized trial used?
- Most commonly used when studying an approach to patient care
Describe a cross-over RCT?
A study sample is selected from a population. From the study sample, subjects are further divided into an intervention or control/comparison group. These groups are followed over time and monitored for the outcome.
There is then a washout period in both study arms. After the washout period then the groups are flipped.
Intervention Group –> Control group
Control Group –> Intervention Group
We then follow the groups over time and monitor the outcome.
The outcomes are then compared. One is acting as their own control.
What is a beneficial characteristic of a cross-over RCT? What is the limitation?
- The individuals act as their own control and therefore confounding is effectively minimized
- This type of study does not require as many subjects
- It is a more complicated study to run and the wash out period can be lengthy
In regards to selecting an RCT design, what is a critical rule to follow? Why is this rule critical?
The study must be designed before it has begun
- This limits bias and maintains integrity
How is the research question established for an RCT?
Population – who’s going to be included?
Intervention – what are we testing?
Comparison – what are we comparing it to?
Outcome – what outcome are we looking for?