USMLE Step 3 Biostats Notes

Odds Ratio

• Calculated in Case Control
• (A/C)/(B/D) or AD/BC
  
• Control studies to compare exposure of participants with the disease (cases) to those without the disease (controls)
• Remember: Odds of exposure in the cases divided by Odds of exposure in the controls (because you are looking back in time). So it’s not like in RR where you are looking forward at risk of disease/outcome (risk of disease/outcome in exposed vs. risk of disease/outcome in non-exposed)

Relative Risk

• Calculated in Cohort
• A/(A+B) / C/(C+D)
  
• Remember: In RR you are looking forward at risk of a disease/outcome in the exposed vs unexposed groups
  
• risk of disease/outcome in exposed vs. risk of disease/outcome in non-exposed
• RR comparing groups
  • If the RR of an outcome in group A as compared to group B is x then the RR in group B as compared to group A is 1/x

Calculate Sensitivity

• TP/(TP+FN)
  
• probability that pt with a given disease will have positive result, so a negative result helps rule it out
  
• High sensitivity means low FN

Calculate Specificity

• TN/(TN+FP)
  
• probability that the pt does not have a given disease and has negative result, so a positive result helps rule it in
  
• High specificity means low FP

Positive Predictive Value

• TP/(TP+FP)
  
• probability that a positive test correctly identifies a pt with the disease
  
• Since higher specificity decreases FP, then PPV increases as well
• PPV depends on Prevalence, and increases as prevalence increases

Negative Predictive Value (NPV)

• TN/(TN+FN)
  
• probability that a negative test correctly identifies a pt without the disease
  
• Since higher sensitivity decreases FN, then NPV increases as well

Likelihood Ratio

• the probability of a given test result occurring in a patient with the disorder compared with the probability of the same result occurring in the patient without the disorder
• – Independent of prevalence like sens/spec
• – used to grade clinical significance of various results when >2 different test results are possible
• Positive LR= sensitivity/(1-specificity)
• Negative LR= (1-sensitivity)/specificity)

Number Needed to Treat

• used to measure efficacy of a therapy and the risk of adverse events
  
• NNT= 1/ARR

Number Needed to Harm

• Number needed to harm=1/ARI
  
• number of pts that need to be exposed to risk factor over certain period of time before harmful event occurs to 1 patient

Risk Reduction

• RR<1 means decreased risk in numerator group
  
• RR=1 means no difference in risk between groups
  
• RR>1 means increased risk in numerator group
  
• RR is a measure of the strength of association between exposure and disease

Relative Risk Reduction (RRR)

• RRR= (risk in unexposed-risk in exposed)/risk in unexposed
  
• RRR=1-RR where RR=risk in exposed/risk in unexposed

Absolute risk reduction calculation (ARR)

• subtract risk of tx group from risk of placebo group

Attributable risk reduction (ARR)

• (risk in exposed-risk in unexposed)/risk in exposed
  
• OR
  
• (RR-1)/RR
  
• Measure of excess risk

Type I Error (false positive)

• Occurs when a study rejects a null hypothesis when it is true
  
• Usually reflects the significance of a test
  
• A higher rate of TI errors (denoted by alpha) decreases type II errors

Type II Error (false negative)

• Occurs when study fails to reject null hypothesis when it is false
  
• Related to the power of a study
  
• TII error=1-power or Power=1-type II error
  
• (ranges from 0-1)

Confounding Bias

• occurs when the exposure-disease relationship is obscured by the effect of an extraneous factor that is associated with both.
• Randomization helps to remove the effects of both known and unknown confounders

Lead time bias

• the overestimation of survival due to early diagnosis

Observer Bias

• when observers misclassify data due to individual differences in interpretation or preconceived expectations regarding treatment

Measures of Central Tendency

• In Right/Negatively skewed mean<median<mode
  
• In Left/Positively skewed mode<median<mean
  
• In strongly skewed distributions, median is a better measure of central tendency than mean

Power of a study

• Is the ability to detect the difference between two groups. Increasing sample size increases power and narrows confidence interval

Biostatistics Formula

High Yield Notes:

• (+) Likelihood ratio = sensitivity / 1-­‐specificity = likelihood of having the disease given a positive result. This is different from PPV in that PPV is prevalence dependent.

• (-­‐) Likelihood ratio = 1-­‐sensitivity/specificity = likelihood of not having the disease after a test result comes back negative. NPV, in contrast, is prevalence dependent.

• PPV increases with increased specificity. NPV increases with increased sensitivity. Therefore a test with the highest PPV will have the highest specificity. A test with the highest NPV will have the highest sensitivity.

• Higher prevalence increases PPV and decreases NPV. Lower prevalence decreases PPV and increases NPV.

• Nominal data is dichotomous and only has two categories (e.g., male vs female).

• Ordinal data has ranking but no numerical value (e.g., freshman, sophomore, junior, senior).

• The median is a better indicator of central tendency (vs mean) in data with a highly skewed distribution.
• Hazards Ratio:
  • Measure of how much effect something actually had.
  • Value of 1.00 means there is no difference between the two groups.
  • A ratio < 1 indicates a protective effect, and > 1 indicates a detrimental effect.
  • If the confidence interval of the hazard ratio includes 1.00 (null value), then the effect wasn’t statistically significant.
  • If the interval doesn’t include the value, the difference was significant.