Evidence Based Medicine Flashcards

Question

Observational studies

Answer 1

- Look @ / Take real world data & try to find things out from them. - Case- control - Cohort study = Collect data in future & Retrospectively = use data from the past. Follow cohorts prospectively ( in the future) through time. Prospectively = you collect the data in the future. S/ cohort studies can be like RCTs, you can set up a group like a control group & an experimental group. Though may not have the same random allocation of individuals in the 2 groups —-> enables you to test the hypothesis.

Answer 2

- Quantitative Research - Intervention Studies = RCT’S - RCT’S = Randomised Controlled trails - Cohort studies

Answer 3

- Things dealing with/ numbers , which you can do statistical tests on. - can do s/ observational studies, but if your data is rubbish (regardless of stats) you can’t prove anything/ results don’t mean anything.

Answer 4

- W/ RCTs you can find out whether s/t works or doesn’t.

Answer 5

- Describe experience of one or more people w/ disease or a drug. - often first stat alerting to new disease/ condition/adverse effect or syndrome. SPECIFIC LIMITATIONS: - No denominator (no comparison group), Don’t know how many people have been exposed to the drug from 1 or 2 cases. - No comparison= Only happening in a small number. - Study population selected = Only those prescribed the drug. - Sampling variation

Answer 6

- Does the exposure cause the effect. - Exposure = to a drug, disease or particles from Road traffic. - Mixing of the effects of the exposure with/ that of a 3rd factor. - The distortion of the apparent effect (because of other factors that you are not aware of) of an exposure brought about by the association w/ other factors that can influence the outcome.

Answer 7

- Limit of observational studies -RCTs control for confounding. - i.e Exposure = taking paracetamol Effect = it removes your headache

Answer 8

- Observational study - ALWAYS work backwards in time = Look back @ old data - Find diseased (adverse effect) & non-diseased individuals(no adverse effect). - Discover /Find exposure in groups -i.e you think that a drug is associated with/ blood cancer, so you find those w/ blood cancer & look back through their med records- to see what they have been exposed to . If the drug you concerned w/ is present, you could think that the drug & blood cancer are linked.

Answer 9

- Good for finding rare events. - Cases = Have the disease or outcome. - Controls= Do not have the disease or outcome. - Case control studies identify subjects based on outcome status ( when you start the study you already know whether they have it or not).

Answer 10

- Define your disease/outcome, that you’re looking for. - Select incident cases ( new cases) = cases w/ disease or adverse drug reaction. - Select controls from same underlying population as cases. - Matched controls to increase similarity. I.e in height, weight, diet. - Common to have 3-4 controls for each case to increase “power”= Control group is bigger than the case group = increases statistical power of the study.

Answer 11

- Concern that autism was linked to MMR vaccine. - 1294 development disorders CASES = w/ autism 78% had MMR - Follow backwards to see exposure - 4469 W/ no disorder, matched on age, sex, & GP practice CONTROLS= w/o autism , 82.1% had MMR - shows that Kids w/ MMR vaccine are less likely to have autism.

Answer 12

- Good for rare diseases w/ a long latency (long time response/ effect to happen after you have been exposed). - Allow for multiple exposures- you might find more than one influence.

Answer 13

- Observational study = subject to confounding (might find s/t else going on or an association but it’s on a 3rd factor). - Recall bias = people forget things, memory is diff when asked to recall events.

Answer 14

-Find people free of disease. - Find Cohorts of people exposed & unexposed. - Follow the cohorts through time. - Compare the risks of incident outcomes in each cohort (adverse drug reactions or the benefit that you’re looking for). - Opposite of case-control, because you find the outcome 1st & then look backwards for cohort studies and find people who have been exposed to the drug and those w/o the disease & follow these people through time. Then you compare the risk of incident outcomes.

Answer 15

- similar to RCT’S you have control group and experimental group but NO RANDOMISATION. - Can do retrospective = look at the past - Can do prospective = Look at the future - Look @ exposed and unexposed and follow through time and loom at the differences.

Answer 16

- To find a temporal relationship. - Can be used for multiple outcomes - Cohort studies identify subjects based on their exposure status ( To a drug or a pollutant).

Answer 17

- Observational – Can't prove cause and effect – just an association. Other factors may have caused the change. - Inefficient for rare diseases( use a case-controlled study) or effects with long latency.

Answer 18

- Control Group Data collection. - Intervention Group Data collection. ( intervention like medication). - Collect data as you go along. - you are interfering in the real world.

Answer 19

When to use? - Uncertainty about a treatment or an area of medicine (exposure) - When exposure can be modified ( w/ tablets or injections, 1 group gets it, 1 group doesn't). Why - Remove confounding (differences in the characteristics of exposed and unexposed individuals) so you can prove causality. - Equipoise (can’t assign people to a treatment KNOWN to be worse) – needs uncertainty. If you already know that the treatment you are going to use is worse than the pre-existing treatment you can't do the clinical trial= Unethical.

Answer 20

- Randomly allocate to either intervention or control and then you get your outcomes.

Answer 21

- No therapy - Similar therapy or drug - Placebo ( So people don't know what groups they are in/ secret) - Pre-existing standard ( goal standard treatment) - Depends on the question and EQUIPOISE - How serious the illness is i.e for HIV a placebo =unethical.

Answer 22

Carried out to balance characteristics (i.e. gender) of control and treatment group. *Small studies are less likely to achieve balance. You get imbalance. *1ST THING YOU SHOULD LOOK @ IN CLINICAL TRIALS=Check baseline characteristics ( Tells you whether there is a bias in the control & treatment group & what the 2 populations in the groups are).

Answer 23

- Can include - Age - Male/ female ratio Extra info= women tend to be under represented in clinical trials.

Answer 24

- Generalisability of the study population ( Collected from particular groups of people). - RCT populations are v/ particular as the study has v/ specific criteria. - Generalisability of the study environment. - You will be seen in a hospital environment routinely if you are apart of a clinical study. - Limited questions & v/ specific - Limited Clinical applicability = linked to the type of questions being asked.

Answer 25

- Patients allocated to control and intervention @ start of the study). - Analysis carried out on the group (control or intervention) they were initially allocated to... - Regardless of whether they dropped out, took the medicines, started on another drug etc. - Assesses effectiveness – as mirrors REAL LIFE as similar problems may occur.

Answer 26

- risk= Probability of s/t happening - Harm= Outcome of that risk. - risk = number of events of interest / total number of observations - risk = Number of people who had the outcome/ Total number of people in that specific group - example 24 people climbing trees, and 6 fall - risk of a fall = 6 falls/24 who could have fallen = 6/24 = ¼ = 0.25 = 25% have fallen off out of the potential 100% who could have fallen.

Answer 27

- odds = number of events of interest/number without the event - Odds= Number of people who had the outcome/ Number of people who did not have the outcome - Add the numerator and denominator together you get the total population. - example 24 people climbing trees, and 6 fall -odds of a fall = 6 falls/18 did not fall = 6/18 = 1/3 = 0.33 (not usually as %)

Answer 28

- Risk ratio=Relative risk - Risk on treatment/risk on control - Where risk ratio = 1, this implies no difference in effect

Answer 29

RISK - What was the risk in % - How much was the risk reduced by % ODDS - How much was the odds reduced by % - comparison of control and treatment

Answer 30

- Odds ratio = odds on treatment/odds on control - Where odds ratio = 1, this implies no difference in effect.

Answer 31

- risk on treatment – risk on control example for Blum et al 119/164 – 130/164 = 0.726 – 0.793 = -0.067 usually expressed as a %, -6.7% If - = reduced If + = increased - treatment reduced the risk of being dyspeptic by about 7 percentage points - Where risk difference = 0, this implies no difference in effect

Answer 32

These are not good ways of reviewing evidence. - Summary of all data - More up to date than a textbook(?) tend to be 5-10 years out of date. - Subjective – reflecting bias of author

Answer 33

- Bring together similar RCTs & set a criteria - Systematic collection of good quality RCTs - Uses pre-defined explicit methodology (reduces bias) of which databases your going to search. - Seeks to minimise bias - May combine statistics (meta-analysis) - Not merely a review – since criteria for inclusion of RCTs explicit (a scientific process)

Answer 34

- Not all have numbers you can meta analyse.

Answer 35

- Have to have a predefined question.

Answer 36

- “Does aspirin increase the chance of survival to 6 months after an acute stroke?= Tells us what the drug is, the condition & the outcome of the condition - The questions should be specific

Answer 37

- can't get an average by adding the studies together as all the studies are diff. - Effect measure = Risk ratio & Relative risk

Answer 38

- Line of no effect in the centre - If data arms do not touch the line of no effect = statistically significant ( could show that the drug works). - Black box = Effect size for the study. - The bigger the box the more patients in the study. - Arms either side = confidence intervals = can be 95% confident that the true effect size of the study is w/i those arms. - On right side = drug works - on left side =drug doesn't work - Small studies = give wider confidence intervals ( To reduce uncertainty about the results w/ the effect size you need lots of patients. - Diamond = Combination of all studies = Summary effect measure. - Meta- analysis puts all of the studies together & creates a summary effect measure.

Answer 39

-When more than one study has estimated an effect ( Can't do meta-analysis w/o having an effect size). - When there are no differences in the study characteristics that are likely to substantially affect outcome (Studies have to be similar) - When the outcome has been measured in similar ways - When the data are available (take care with interpretation when only some data are available), S/studies are not published & there is publication bias and bias in academics.

Answer 40

- physiological or surrogate outcomes e.g. changes in blood pressure, blood lipid levels, etc. - Measure things in your body that may be correlated to other health aspects but are not actually the thing that you are concerned about. - Not as good as POOs.

Answer 41

- outcomes that matter directly to patients: e.g. morbidity, mortality, symptom improvement, cost reduction and/or quality of life. - Measures things that matter to patients.