Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

CICM > Stats > Flashcards

Stats Flashcards

1
Q

EBM

A

the conscientious, explicit and judicious use of current best evidence in making decisions about the care of individual patients. The practice of EBM means integrating individual clinical expertise with the best available external clinical evidence from systematic research

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Advantages of EBM

A

improves clinical appraisal skills
leads to the abandonment of unhelpful practices
makes the process of decision making transparent to patients and colleagues

leads to a better appreciation of uncertaintly in clinical practice

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Disadvantages of EBM

A

sometimes is impossible
time consuming and expensive
excessively rigorous criteria may lead to useful papers being disregarded
Evidence can be manipulated
evidence is frequently out of date
RCTs are treated a gold standard, but in some settings other designs are more appropriate

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Good clinical practice

A

n interntational standard for the design, conduct, performance,
monitoring, auditing, recording, analyses, and reporting of clinical trials that provides
assurance that the data and reported results are credible and accurate, and that the rights,
integrity, and confidentiality of trial subjects are protected

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Levels of evidence (NHMRC)

A

1 - systematic review of all relevant RCTs
2 - RCT
3/1 - pseudorandomised trial of high quality
3/2 - cohort study or case control study - with a control group
3/3 - cohort study with historical controls or no control group
4 - case series

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Grades of recommendation

A

A - consistent with level 1 studies
B - consistnet with level 2 or 3 studies, or extrapolations from level 1
C - level 4 studies or extrapolations from level 2 or 3
D - level 5 (oxford definitions - expert opinion) or inconsistent studies of any level

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

CONSORT

A

consolidated standards for reporting trials

  • governs the reporting of trial data
  • designed to produce literature with the highest degree of transparency
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Absolute risk

A

Actual event rate in the group
Essentially is the incidence rate

Number of cases in group/total number of group

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Absolute risk reduction

A

AR in exposed - AR in unexposed

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

NNT

A

1/ARR

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

relative risk

A

the difference in event rates between 2 groups, expressed as proportion of the event rate in the untreated group

AR in treatment group/AR in control group

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

relative risk reduction

A

1 - relative risk

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

attributable risk

A

a measure of the absolute effect of the risk of those exposed compared to the unexposed -

INcidence (exposed) - incidence( unexposed)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

sensitivity

A

the ability of a test to correctly identify those with the disease (true positive rate)

true positives / (true positives + false negatives)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

specificity

A

the ability of the test to correctly identify those without the disease (true negative rate).

true negatives / (true negatives + false positives)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

POsitive predictive value

A

true positives / total positives

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Negative predictive value

A

true negatives / total negatives

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

positive likihood ratio

A

sensitivity / (1- specificity)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

negative liklihood ratio

A

specificity / (1 - sensitivity)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

power

A

the probobility that a statistical test correctly rejects the null hypothesis when the null hypothesis is false

1 - false positive rate

or

1 - beta error

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

prevelance

A

number of affected individuals / total number in population

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

incidence

A

number of affected individuals / total exposed population

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

phases of clinical trial

A

in vitro activity
Animal model
Phase 1 - healthy volunteers
Phase 2 - patients with the disease of interest
Phase 3 - large scale trial on the patients with disease
Pahse 4 - post marketing experience

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

intention to treat analysis

A

once randomised, always randomised
preserves the bias-protective effect of randomisation
minimises type 1 error (false positives)

25
Q

confidence interval

A

the range of values between which the actual result is found

gives an indication of precision of the sample mean as an estimate of the true population mean

26
Q

p value

A

probability of the observed result occuring by change

27
Q

Type 1 error

A

false positive

the null hypothesis is incorrectly rejected (there is no treatment effect but the study finds one)

alpha value determines the risk of this happening

28
Q

Type 2 error

A

false negative

the null hypotesis incorrectly accepted (there is a treatment affect but the study doesnt detect it)

beta value
usually set at 0.8 (20% chance of a T 2 error)

29
Q

determinants of sample size

A

alpha value
beta value
statistical test you plan to use
varience of the population (greater varience, larger sample needed)
effect size (smaller effect size, larger sample needed)

30
Q

Methods of maintaining balance in several prognostic variables (ie way to ensure that pre-identified confounding factors are equally distributed

A

stratification

  • separate randomisation list is generated for each prognostic subgroup.
  • Usually limited to 23 variables

Minimisation algorithm
- maintains a running total of the prognostic variables in patients that have already been randomised and then subsequent patients are assigned using a weighting system that minimizes imbalance in those prognostic variables.

31
Q

Sources of symmetry in funnel plots

A

Reporting biases

  • Delayed publication (also known as time lag or pipeline) bias
  • Location biases (eg, language bias, citation bias, multiple publication bias)
  • Selective outcome reporting
  • Selective analysis reporting

Poor methodological quality i.e. smalle studies inflated the effect size

  • Poor methodological design
  • Inadequate analysis
  • Fraud

True heterogeneity
- Size of effect differs according to study size
(eg, in smaller studies the intervention was less intense: eg. PROSEVA trial)

Artefactual
- In some circumstances, sampling variation can lead to an association between the intervention effect and its standard error

Chance
- Asymmetry may occur by chance, which motivates the use of asymmetry tests

32
Q

What is a funnel plot

A

a simple scatter plot of the intervention effect estimates from individual studies against some measure of each study’s size or precision (effect vs study size)

It is used to identify publication bias

33
Q

What do the outer dashed lines and solid vertical line of a funnel plot mean

A

Outer dashed lines-triangular region where 95% of studies are expected to lie

Solid vertical line- no intervention effect, corresponds to an OR of 1.00.

34
Q

External validity:

A

the extent to which the study results can be generalised to the greater population

35
Q

Factors that affect external validity

A

The setting and the population from which the sample was selected
The inclusion and exclusion criteria
The “randomness” of the sample, and the baseline chacteristics of the patients
The difference between the trial control group and the routine practice
The changes in practice since the publication of the trial
The use of patient centered outcomes
The degree to which the surrogate outcome measures are related to patient-centered outcomes

36
Q

Bias

A

a systematic error which distorts study findings

It is caused by flaws in study design, data collection or analysis
It is not altered by sample size (increasing sample size only decreases random variations and the influence of chance)
It can creep in at any stage in research, from the literature search to publishing of the results.

37
Q

Selection bias:

A

The selection of specific patients which results in a sample group which is not random, and which is not representative of a population.

This can be avoided by randomisation, and allocation concealment.

38
Q

Advantages of meta analysis over review of single studies

A

↑ Statistical power by ↑ sample size.

Resolve uncertainty when studies disagree.

Improve estimates of effect size.

Inconsistency of results across studies can be quantified and analysed e.g. heterogeneity of studies, sampling error.

Presence of publication bias can be investigated.

Establish questions for future RCTs.

May provide information regarding generalisability of results.

39
Q

A good meta-analysis has:

A

Research questions clearly defined

Transparent search strategy

Thorough search protocol

Authors contacted and unpublished data collected

Definition of inclusion and exclusion criteria for studies

Sensible exclusion and inclusion criteria

Assessment of methodological quality of the included studies

Transparent methodology of assessment

Calculation of a pooled estimate

Plot of the results (Forest Plot)

Measurement of heterogeneity

Assessment of publication bias (Funnel Plot)

Reproduceable meta-analysis strategy (eg. multiple reviewers perform the same meta-analysis, according to the same methods)

40
Q

NHMRC levels:

A

Level I: systematic review of RCTs
Level II: RCT
Level III-1: pseudorandomised trial of high quality
Level III-2: cohort studies or case control studies - but with a control group
Level III-3: cohort studies with historical controls, or no control group
Level IV: case series

41
Q

Confidence interval:

A

CI gives a range of results and the percentage chance that the same experimental design would produce results within this range if the experiment were repeated.

42
Q

What is a ROC curve and what does it show

A

The ROC curve is a plot of sensitivity versus false positive rate (1-specificity) for all observed values of a diagnostic test.

It is a graphical representation of a tests’ diagnostic accuracy

It allows the comparison of accuracy between tests

It allows the determination of cutoff values

It can be used to generate confidence intervals for sensitivity and specificity and likelihood ratios.

43
Q

Advantages of a ROC curve

A
  • Simple and graphical
  • Represents accuracy over the entire range of the test
  • It is independent of prevalence
  • Tests may be compared on the same scale
  • Allows comparison of accuracy between several tests.
44
Q

What is the role of meta-analysis in evidence based medicine?

A

It offers an objective quantitative appraisal of evidence
It reduces the probability of false negative results
The combination of samples leads to an improvement of statistical power
Increased sample size may increase the accuracy of the estimate
It may explain heterogeneity between the results of different studies
Inconsistencies among trials may be quantified and analysed

45
Q

Significance of intention to treat analysis:

A

All enrolled patients have to be a part of the final analysis

Maintains prognostic balance generated from the original random treatment allocation (preserving the bias- reducing effects of randomisation)

Avoids overoptimistic estimates of the treatment’s efficacy

Accurately models the effect of noncompliance and protocol deviations in clinical practice

Prevents bias introduced due to outcome-associated dropouts

Prevents bias by resisting the post-hoc manipulation of data to eliminate inconvenient outcomes

Preserves the sample size, thus preserving the statistical power

Minimises Type 1 error

Allows for the greatest external validity

Supported by the CONSORT statement

Essential for a superiority trial

46
Q

Significance of randomisation:

A

Minimises selection bias

Minimises group heterogeneity

Controls unknown confounders, which should be randomly and evenly distributed among the groups

Allows probability theory to be used to express the likelihood that chance is responsible for the diffences in outcome among groups.

Failure to use random allocation and concealment of allocation were associated with relative increases in estimates of effects of 150% or more.

47
Q

parametric and non-parametric tests use

A

To determine P value

48
Q

parametric test uses

A

Parametric tests are more accurate, but require assumptions to be made about the data, eg. that the data is normally distributed (in a bell curve). If the data deviate strongly from the assumptions, the parametric test could lead to incorrect conclusions.

49
Q

Non parametric test uses

A

Non-parametric tests make no assumptions about the distribution of the data. If the assumptions for a parametric test are not met (eg. the distribution has a lot of skew in it), one may be able to use an analogous non-parametric tests.

Non-parametric tests are particularly good for small sample sizes (<30). However, non-parametric tests have less power.

50
Q

Examples of parametric tests:

A

Students T Test
Analysis of variance
Pearson correlation coefficient
Regression or multiple regression

51
Q

Examples of non-parametric tests:

A 
Mann-Whitney U test
Wilcoxon sum test
Wilcoxon signed-rank test
Kruskal-Wallis test
Friedman's test
Spearman's rank order
52
Q

Dimensions of evidence to be assessed in systematic review (as per NHMRC)

A

Strength of evidence

  • level of evidence
  • quality of evidence
  • statistical precision

Size of effect

Relevance of evidence

53
Q

Bland-Altman plot

A

a difference plot

a graphical method to compare two measurements techniques.

the ratios between the two techniques (test 1 - Test 2) are plotted against the averages of the two techniques.

54
Q

Types of bias

A

Selection - selection of patients not random, avoided by randomisation

Detection - results pursued more diligently in internvention, avoided by blinding

Observer - investigator makes subjective decisions about outcome, avoid by blinding Ix

Response - if patients self enroll in trial - avoid by random sampling

Recall - pts report different outcomes knowing their allocation, avoid by blinding Pt

Publication

Hawthorne effect

Interpretive - there are man y types, but it refers to the way the reader interprets the findings of the trial, usually to confirm ones own beliefs

55
Q

Propensity score analysis

A

statistical method to control for selection bias in observational studies

Allows observational studies to be conducted to mimic some characteristics of RCTs

If a group of subjects have the same propensity score, they should all have same baseline characteristics

56
Q

Ways to randomise

A

Simple

Block

stratification - pre-identified confounding factors are equally distributed between groups

Minimisation algorithm - an alternatie to stratification to maintain the balance of confounders/prognostic variables between groups
- the algorithm maintians a running totoal of the variables of patients that have already been randomised and uses a weighting system to allocate subsequent patients

57
Q

Blinding vs allocation concealment

A

Allocation concealment occurs before randomisation- it ensures that no one can predict which group the next patient withh be randomised to

Blinding prevents the Ix and the patients from knowing who is getting the treatment, after the patient has been allocated

58
Q

Sources of asymmetry in funnel plots

A

reporting bias
Poor methodological quality
True heterogeneity
Chance

CICM (20 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions