forest plots, funnel plots and heterogeneity Flashcards

1
Q

forest plots use

A

odd ratios

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2
Q

size of the square

A

represents the weight given to each study- the larger the square the bigger the weight

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3
Q

pooled effect size is denoted by

A

a diamond

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4
Q

vertical line- 1

A

no effect

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5
Q

if the CI line cross 1

A

the study didn’t show significance

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6
Q

p value

A

the probability that if this was repeated you would ge the same result

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7
Q

funnel plots represent

A

publication bias

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8
Q

larger studies have

A

higher/ lower odds ratios - smaller standard error

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9
Q

negative studies are

A

much less likely to be published

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10
Q

due to negative studies being less likely to be published

A

systematic reviews ill have more positive than negative outcome trials

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11
Q

forest plots show that

A

studies with equal standard error are subjected to publication bias based on whether they yield positive or negative results

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12
Q

meta-analyses are subsets of

A

systematic reviews

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13
Q

systematic reviews are

A

subsets of all reviews- narrative reviews

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14
Q

heterogeneity is

A

the difference in studies not due to chance

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15
Q

hereogenity reduces their ability to be used in

A

meta-analyses

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16
Q

clinical heterogeneity

A

differences in:

  • patients/study setting
  • study design / quality
  • interventions
  • outcomes (how they are measured)
17
Q

statistical heterogeneity

A

individual trials have results not consistent with each other

  • benefits vs harms
  • size of benefit and harm
  • evaluated statistically
18
Q

I2

A

the percentage of variation across studies that is due to heterogeneity and not due to chance

19
Q

0.25

A

low heterogeneity

20
Q

0.5

A

moderate

21
Q

0.75

A

high

22
Q

when looking at forest plots, evidence of heterogeneity

A
  • if the plots are on different sides of 1

- wide CIs

23
Q

95% CI’s

A

we can be 95% certain that the true value lies within this range of values