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Critical appraisal of papers PHM > Lecture > Flashcards

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1
Q

What is equipoise?

A

the assumption that there is not one better intervention present during the design of a RCT

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2
Q

what are the types of evidence?

A

trials and studies

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3
Q

what are trials?

A

involves an intervention -> measure an outcome

gold standard = randomised double blinded controlled trial

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4
Q

what are studies?

A

observational, no intervention

Diagnostic - how good a diagnostic test is

Prognostic - look at rf on outcomes often of cohort study

Case control - retrospective, two groups of different outcomes

Cohort study - group of people. prospective

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5
Q

what levels of evidence are 1a/1b?

A

Ia: systematic review/meta-analysis of RCTs

Ib: at least one rct

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6
Q

what level of evidence are IIa/IIb?

A

IIa: at least one well-designed controlled study without randomisation

IIb: at least one well-designed quasi-experimental study such as a cohort study

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7
Q

what is a quasi experiment?

A

subject to concerns regarding internal validity, because the treatment and control groups may not be comparable at baseline. With random assignment, study participants have the same chance of being assigned to the intervention group or the comparison group

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8
Q

what level of evidence is III?

A

III: well designed, non-experimental descriptive study eg comparative study, correlation, case-control study, case series

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9
Q

what level of evidence is IV?

A

opinions and/or clinical experience

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10
Q

What are the levels of evidence?

A

Ia (highest)

IV (lowest

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11
Q

What is phase 1 of trials?

A

safety testing of new med on few (often) healthy volunteers - establish side effect profiles

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12
Q

What is phase 2 of trials?

A

testing on larger groups of disease patients - establish idea of efficacy and further side effects

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13
Q

what is phase 3 of trials?

A

large comparison trials on disease patients - for robust efficacy data in comparison to existing treatment

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14
Q

what is efficacy?

A

the ability to produce a desired or intended result

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15
Q

what is a null hypothesis? (Ho)

A

there is no difference between the two groups, any difference between these two groups is due to chance

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16
Q

what is the alternative hypothesis?

A

there is a difference between the two groups

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17
Q

what is the p value?

A

probability of detecting a difference with a priori assumption that the null hypothesis is true

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18
Q

what is the p value set at?

A

5% or 0.05

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19
Q

what does it mean if p value <0.05?

A

consider such a low probability that there must be an error in the logical argument - the error is considered to be in the priori assumption, therefore the null hypothesis cannot be true so the alternative hypothesis must be true

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20
Q

what are the limitations of hypothesis testing?

A 
the amount of difference is not stated
simple binary (yes/no) answer
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21
Q

what is the estimation?

A

we can never know true difference between two groups in a population so we take a sample - estimate the difference between the two groups using the data from the sample

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22
Q

what is the absolute difference?

A

the difference found in a study = estimation of the whole population

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23
Q

what is the true difference?

A

the actual difference in population

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24
Q

how can the estimation be presented?

A
  1. as a number
  2. as an absolute difference
  3. as a ratio
  4. as a proportion
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25
what are confidence intervals?
is the range around the estimation | normal 95% CI = the range between which there is 95% chance that the true value will lie
26
what are the units of no effect in confidence intervals?
with absolute difference - no difference would be 0 with a ratio - no difference would be 1
27
what is good about confidence intervals?
width of interval indicates PRECISION of estimate can be used to estimate type 2 statistical error indicates lack of statistical significance if interval crosses unit of no effect gives info of size and direction of difference
28
what is a type 2 statistical error?
the study has shown that there is no statistically significant difference in the groups but in the real world there might be (false negative)
29
what is the primary outcome?
the variable outcome of most interest | any difference in outcome between the groups is believe to be due to the intervention
30
what is the minimum clinically important difference?
the least difference outcome that is clinically important - | looking at the clinical significance with statistical significance
31
what is the intervention?
what we do to the patient that can change things
32
what are time points to measure?
when the outcome is measured
33
what is the power of a study?
the probability that a trial will detect a difference that truly exists
34
what does the power calculation look at?
type 1 error: finding a difference when there isn't one in real life (false positive) = ALPHA type 2 error: not finding a difference when there is one (false negative) = BETA
35
power is dependent on what four things?
- probability of T1 error (0.05) [ALPHA] - sample size - standard deviation of sample - minimal clinically significant difference
36
what does power equal (calc)
1-beta beta = probability of getting a type 2 error
37
what is a type 1 error?
false positive incorrectly rejecting null hypothesis experiment shows significant difference when the null hypothesis is true (no difference in actual population) probability of type 1 error = alpha
38
what is a type 2 error?
false negative incorrectly accepting null hypothesis experiment does not show significant difference when the alternative hypothesis is true (there is a difference in actual population) probability of type 2 error = beta
39
what is type 1 error due to?
- bias - confounding factors - multiple hypothesis testing
40
what is type 2 error due to?
sample size
41
what is sample size?
number of participants required to detect a difference of a specified size
42
what is screening?
physically identifying potentially eligible participants
43
what criteria do you use when screening patients?
inclusion/exclusion - every pt that fulfils inclusion criteria must be recorded - everyone must have exclusion criteria applied -> if not, must record why
44
what is allocation concealment?
allocation sequence is concealed from all staff (reducing selection bias)
45
what is randomisation?
process of assigning to groups with known chance for each participant to enter any group (reduces allocation bias) equally distribute confounders
46
what is blinding?
treatment assignment is concealed (reduces ascertainment bias) concealment if whether in placebo group or not
47
how do you get ethics for your research?
submit protocols to REC/IRB for approval
48
what are the types of data?
continuous | categorical
49
what is reported in continuous data?
normally distributed - mean and standard deviation non-normally distributed - median and inter-quartile range
50
what is categorical data?
nominal (without order) e.g. colour, gender | ordinal (with order) e.g. scale - slow, medium, fast
51
what is intention to treat analysis?
analysis includes every subject who is randomized according to randomized treatment assignment. It ignores noncompliance, protocol deviations, withdrawal, and anything that happens after randomization
52
what is imputation for missing data?
replacing missing data with substituted values
53
what are the measurements of central tendency?
mean median mode
54
what is the mean?
the average used in normally distributed data SD measured
55
what is the median?
central value use if data is skewed IQR measured
56
what is the mode?
most frequent value rarely used
57
what are the techniques for comparing groups?
categorical: chi-squared (X2) continuous: depends on distribution - T-test, ANOVA
58
does funding need to be stated?
yes - all funding needs to be clearly stated and role of funders
59
what is enrolment?
if they fit inclusion criteria - sign consent (NOK if don't have capacity or PLR by nurse/doctor)
60
what is risk?
the probability of an event occurring
61
what is the absolute risk reduction? (ARR)
the difference between the event rate in the treatment group and the event rate in the control group (event rate in control group) - (event rate in treatment group)
62
what is numbers needed to treat?
the number of patients that need to be exposed to intervention for one of them to sustain the effect 1/ARR
63
what is the risk ratio? aka relative risk
ratio of risk of outcome in treatment group to risk of outcome in control group RR > 1 then the risk of the event in the treatment group occurring is great than the rate in the control group RR<1 the risk of event in the treatment group occurring is less than the rate in the control group (event rate in treatment group)/(event rate in control group)
64
What is the relative risk reduction?
the proportion by which the intervention reduces the outcome rate watch out for high RRR in events that are rare e.g. increased risk of breast cancer in young women due to OCP - high RRR, low ARR proportion of ARR to the control event rate (CER-EER)/CER
65
What are odds?
another way to express chance the ratio of the number of times an event occurs to the number of times it does not occur the odds of rolling a six on a dice = 1/5 =0.2 (NB risk of rolling a six = 1/6)
66
what is an odds ratio?
ratio of odds of event in treatment group to odds of an event in control group expresses how much more likely the event will occur in treatment group in comparison to control ``` >1 = the event rate is greater in the treatment group <1 = the event rate is greater in the control group ```
67
what is accuracy?
inaccuracy is due to systematic error (bias) an accurate study hits bullseye every time but have poor spread within bullseye
68
what is precision?
imprecision due to random error (chance) precise study has closely clustered results but may not in the gold
69
what is accuracy in a test?
the proportion of patients correctly identified by the test (true positives and true negs)
70
what is the reference standard in 2x2 diagnostics?
definition of having the disease for the purposes of the paper
71
what is the gold standard?
definition of having the disease as recognised by international medical community
72
what is sensitivity?
proportion of patients with the disease that have a positive test ability of a test to correctly classify patients as having disease true positive/(true positive + false negative)
73
what is specificity?
proportion of patients without the disease that have a negative test ability of test to correctly classify patients as not having disease true neg/(false pos + true neg)
74
What is SpIn?
Rule in a disease Test with high specificity (with few false positives) accurately rules in the diagnosis
75
what is SnOut?
Want to rule out disease Test with high sensitivity (few false negatives) accurately rules out a diagnosis
76
does changing the population prevalence change the sens/specificity?
nope - about the test
77
what is the positive predictive value?
proportion of patients with positive test that have disease true pos/(true pos + false pos)
78
what is the negative predictive value?
proportion of patients with neg test that do not have disease true neg/(false neg + true neg)
79
will PPV and NPV change with population prev?
yes - about the patient
80
What happens to PPV and NPV when the prevalence increases?
PPV rises NPV drops Sens/spec stay the same
81
What kind of diagnostics do we use in ED?
Usually use tests to RULE OUT a diagnose more often than to rule in so often have high SENSITIVITY (SnOut) and low specificity
82
What do you want in order to diagnose something?
high positive predictive value but low prevalence gives low PPV so need to perform initial test on population that has a high prevalence -> aka screening
83
What is a likelihood ratio?
(probability of individual with condition having the test result)/(probability of an indiv without the condition having the test result)
84
How do you measure likelihood ratio for positive test?
sensitivity/(1-specificity)
85
How do you measure the likelihood ratio for negative test?
(1-sensitivity)/specificity
86
What does the likelihood ratio measure?
how much more likely (for positive) or less likely (negative) than the pre-test probability is it that a patient has the disease
87
what is a receiver operating characteristic curve?
another way of gauging the usefulness of a diagnostic test x-axis: 1-specificity y-axis: sensitivity want each to be perfect = 1
88
what does the area under the curve represent?
the closer to 1 - the better the test (between 0.5 and 1) the bigger the area - the better the test

Critical appraisal of papers PHM (1 decks)

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