Final: Lecture 13 Flashcards

1
Q

Absolute Differences

A

Subtracting frequencies (subtracting Counts) assume that….

  • 135 outcomes in Group 1 & 25 outcomes in Group 2
    • Group 1 had 110 more outcome occurrences, or…
    • Group 2 had 110 FEWER outcome occurrences
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Relative Differences

A

Ratio of Frequencies (division of counts). Still assuming..

  • 135 outcomes in Group 1 & 25 outcomes in Group 2
  • -Group 1 had over 5 time the number of cases (over 500% increase)
  • -Group 2 had less than 20% of the outcomes seen in Group 1
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Risk a.k.a, Incidence Risk (IR)

A
  • Probability of outcome in Exposed (risk in exposed)
  • A ÷ (A+B)
  • Probability of outcome in Non-Exposed (risk in Non-exposed)
  • C ÷ (C+D)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Risk Ratio (RR) or “Relative Risk”

A

Ratio of the Risk from 2 different groups

  • Risk Exposed ÷ Risk Non-exposed
  • a risk ratio of 1 says there is NO difference in risk of disease between exposed and non-exposed
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

When is a Risk Ratio/Relative Risk (RR) customarily used?

A

In studies when the subjects are allocated based on exposure (y/n) and evaluated for disease (outcome) e.g. cohort studies. Think 2 x 2 table

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

What is Risk?

A

A PROPORTION PART÷WHOLE

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

Interpreting Ratio’s, Risk (RR), Odds (OR), Hazard (HR):

When the ratio is equal to 1

A

No difference (no increase/no decrease in risk/odds/ratio

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Interpreting Ratio’s, Risk (RR), Odds (OR), Hazard (HR):

When the ratio is >1.0

A

Increased “ratio” (RR/OR/HR)

  • +1.00001 to +1.99= use decimal value (converted to %) for interpretation
  • if RR =1.53 then a 53% increased ( or greater) risk in the comparator group. Increased because “ratio” value is above 1.0
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Interpreting Ratio’s, Risk (RR), Odds (OR), Hazard (HR):

When the ratio is ≥ 2.0

A

use statement of “times Control” for interpretation
+2.0 to ∞
- if OR= 6.18, then comparator group is 6.18 times greater odds. Greater because “ratio” value is above 1.0

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

Interpreting Ratio’s, Risk (RR), Odds (OR), Hazard (HR):

when the ratio is < 1.0

A

Decreased “ratio” (RR/OR/HR)
0.00001 to 0.99 = subtract decimal value from 1 (answer converted to %) for interpretation

If HR = 073, then a 27% lower probability of the hazard outcome, LOWER b/c “ratio” value is BELOW 1.0

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

Absolute Risk Reduction (ARR) [a.k.a. Attributable Risk (AR)]

A

Simple “absolute” difference (subtraction) in risks
-if Risk in “exposed” = 1.5 & risk in “unexposed” = 1.2 then… “exposed” had a 0.3 times (or 30%) greater risk (compared to “unexposed”)

AR defines the excess risk of the outcome among “exposed” that can be “attributed” to the actual exposure.

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

Relative Risk Reduction (RRR)

A

(ARR) ÷ R unexposed. From the ARR example note card, 0.3 ÷ 1.2 = 25% relative greater risk i “exposed”

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

Number Needed to Treat (NNT) & Number needed to Harm (NNH)

A

interpretation: number of (whole) patients needed to be treated to receive the stated benefit/harm

1 ÷ Absolute Risk Reduction (1/ARR)

From ARR note card 1 ÷ 0.3 = 3.33; [ 4 patients ]

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

Odds

A

Odds of exposure vs. odds of NOT being exposed (in cases)
A ÷ C (not a simple percentage)

Odds of exposures vs. odds of NOT being exposed (in Controls)
B ÷ D (not a simple Percentage)

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

Odds Ratio (OR)

A

Odds of exposure in Cases vs. odds of exposure in Controls.

Odds of Exposure (in cases) ÷ odds of exposure (in controls) *** calculated as [(A ÷ C) ÷ (B ÷ D)]

  • you can also cross-multiply in 2x2 table to get same answer
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

When are Odds Ratio (OR) customarily used?

A

In studies where subjects are allocated based on disease presence (y/n) and evaluated for exposure. e.g. Case-Control Studies

17
Q

What is Z for?

A

ZAK, which isn’t funny.