• Skip to main content
  • Skip to primary sidebar
  • Skip to footer
  • Home
  • About
  • Consumer Info
  • Guideline Notes
  • Medicine and Media
  • Pharmacogenomics
  • Visit My Etsy Store

Digital PharmD

Informatics in Pharmacy

Basic Biostatistics

August 12, 2018 By Dr. G, PharmD

Print Friendly, PDF & Email

The BCPS is heavily weighted on Biostats, study design, and regulatory issues.  I recommend you buy the little biostatistics book ACCP offers (it’s cheap and it has some good practice problems in it).   It was worth more than any other book I purchased for the BCPS.  This is also a really good study guide and here’s a really, really simple sheet. This study guide has more topics in biostatistics (including the “which statistical test to pick” questions).

Biostats Definitions:

Here are some basic things in case you have forgotten them:

  • Nominal date – data with no order (yes/no, male/female)
  • Ordinal data – data with order, but no consistent difference in magnitude change (classes of heart failure, pain scales)
  • Interval data – continuous data with consistent interval difference (temperature)
  • Ratio data – continuous data with consistent interval difference, but zero is the starting point (HR, BP)
  • Mean– “Average.” Only with continuous data (parametric, normally distributed)
  • Median – 50th percentile. The data point exactly in the middle of the data points.  Usually only used with ordinal data or continuous data that is not normally distributed
  • Mode – the most frequently occurring value
  • Range – how far apart the data points are
  • Interquartile range – related to the median.  Most data is in the 25-75 percentile.
  • Standard deviation (SD) – only applicable to parametric data.  Measures how data points scatter around the mean.  Not available for nominal data or ordinal data.  99% of the data should be found in +/-3 SDs, 95% of the data in +/- 2 SDs, 68% in +/- 1 SD.
  • Standard error the mean (SEM) – smaller than the standard deviation. Average variability of data.
  • Parametric data – continuous data that is normally distributed (like a parabola)
  • Nonparametric data – continuous data that does not follow a normal distribution (skewed)
    • If mean > median, skewed to the right
  • Correlation coefficient (R) – how variables relate.  The closer the number is to 1, the stronger the relationship.
  • R2 – How much of the relationship is due to Y (ie: 70% of weight gain is due to calories, 30% is unknown).
  • Narange Scale – the probability that an adverse effect is related to drug toxicity.
  • Lot Proportional Hazard – survival data

Therapeutic Index

  • Therapeutic Index = Median Toxic Dose / Medicontinuousive Dose (also Lethal dose 50/effective dose 50)
  • The higher the TI, the safer the drug
  • IF LD50>ED50 TI is large so the drug is safe

Specificity, Sensitivity, Predictive Values and Accuracy

  • Sensitivity = True Positives / (True Positives + False Negatives) Sensitivity measures true positives.  If a highly sensitive test is negative, you can be sure they don’t have the disease (SNOUT Rules Things Out)
  • Specificity = True Negatives / (True Negatives + False Positives) Specificity measures true negative.  If a highly specific test is positive, you can be sure they have the disease (SPin Rules Things In)
  • Bigger Numbers are more significant.
  • Positive Predictive Value = True Positives / (True Positives + False Positives)  This is the percentage of people who test positive who actually have the disease. *Bigger numbers are more significant*
  • Negative Predictive Value = True Negatives / (True Negatives  + False Negatives )  This is the percentage of people who test negative who don’t have the disease. *Bigger numbers are more significant*
  • Accuracy = (True Positives + True Negatives) / Total
  • When you increase sensitivity, you decrease specificity.  You get more diagnosis but more false positives.
  • Prevalence = the number of cases / total at risk; incidence = new cases/total population at risk

Some people like to set up a table (this is called a “confusion matrix” in the statistics world):

 +– 
+TPFPTP+FP
–FNTNFN+TN
 TP+FNTN+FPTP+FP+FN+TN
  • Sensitivity= TP/(TP+FN) (column 1)
  • Specificity = TN/ (TN+FP) (column 2)
  • PPV = TP/ (TP+FP) (row 1)
  • NPV = TN/(TN+FN) (row 2)
  • Accuracy = diagonal down chart : TP+TN/ (TP+FP+FN+TN)

Hypothesis Testing:

The null hypothesis is that there is no difference between groups in a study. In order to find significance, you need to REJECT the null. This can be a little confusing.

 Null is TrueNull is False
Accept Nullcorrect decision Type II Error (β)
Reject NullType I error (alpha)correct decision
  • Type 1 error: Reject the null hypothesis when it is true.  A difference is found where none exists. The maximum acceptable alpha error is usually 0.05 (think of alpha as the p-value you are designing the study to obtain).
  • Type 2 Errors: Accept the null hypothesis when it is not true.  No difference found when one exists.  The maximum acceptable probability of a Type II error should be 20% (β = 0.2).
    • Beta errors are usually due to sample size or a poorly powered study. The easiest way to decrease Beta is to increase the sample size. Alpha and sample size have the greatest impact on study power.
  • You’ll always have the risk of making either a Type 1 or Type 2 error, but never have the risk of making both. If the p-value is significant, you have the risk of making a Type 1 error. If it is not, you have the risk of making a Type 2. For example, a p-value of 0.01 would mean there is a chance of committing a Type I error (i.e.: you found the p was significant, rejected the null and stated there was a different between the groups. In real life, there was no difference between the two groups).
  • “If the p-value is low, the null must go.” If the p-value is less than alpha, the null is rejected.
  • P VALUES DO NOT SUGGEST CLINICAL SIGNIFICANCE, just statistical significance. Clinical significance can only be assessed by reading the study and finding the methods, inclusion criteria, etc.
  • Confidence intervals:
    • The closer a data point lies to the 95% confidence interval, the more likely it represents the population.
    • For a ratio confidence interval, if it includes 1, it’s not significant (think 1/1 = 1, no difference)
    • For a continuous confidence interval, if it includes 0, it’s not significant (think 1-1 = 0, no difference)

Relative Risk

  • Relative Risk = incidence in exposed patients / incidence in non-exposed patients
    • >1 incidence in the exposed group is higher
    • <1 incidence in the exposed group is lower
  • Absolute risk reduction = Risk Reduction in the control group – Risk Reduction in the treatment group
  • For this one, use a table for sure (these will likely be on the test):
TreatmentDiseaseNo Disease
ExposedAB
UnexposedCD
  • Relative Risk = A/(A+B)
  • Absolute Risk Reduction (ARR) = C/(C+D)
  • Odd Ratio = AD/CB
    • Only used in retrospective studies
    • If used in a prospective study, odds ratio overestimates the risks. They may try to trip you up on this.
    • The further the OR is from 1, the more the OR overestimates the RR
  • Number needed to treat or Number Needed to Harm: 1/ARR (it’s a decimal, not a percentage)
    • Include duration of study = must treat 10 patients for 5 years
  1. AR (absolute risk) = the number of events (good or bad) in treated or control groups, divided by the number of people in that group.
  2. ARC = the AR of events in the control group.
  3. ART = the AR of events in the treatment group.
  4. ARR (absolute risk reduction) = ARC – ART.
  5. RR (relative risk) = ART / ARC.

Filed Under: Biostatistics, Guideline Materials and Tips, Spotlight Tagged With: biostatistics, Guidelines

Primary Sidebar

Newsletter

More to See

What You Need to Know About the 2022 Avian Influenza Outbreak

March 20, 2022 By Dr. G, PharmD

Endocarditis Guideline Review

February 24, 2022 By Dr. G, PharmD

Sinus Troubles: When Should I See My Doctor

January 5, 2022 By Dr. G, PharmD

Tags

acid base acidosis acute coronary syndrome alkalosis analgesics anaphylaxis aortic dissection arrhythmia Beta-Blockers biostatistics blood pressure cardiac markers CHA2DS2-VasC cocaine COVID-19 diabetes diabetes inspidius Guidelines heart failure Heparin hypersensitivity hypertension hypovolemic shock intubation ionotropes journal club lipids LMWH medication safety morphine conversions myocardial infarction needs work NOAC NSTEMI obstructive shock pharmacoeconomics pheochromocytoma pressors reference materials right mi sedation septic shock shock STEMI Updated 2020

Footer

Medical Disclaimer

The medical information on this website is provided “as is” without any representations or warranties, express or implied. GoPharmD makes no representations or warranties in relation to the medical information on this website.

GoPharmD does not warrant that:

  • the medical information on this website will be constantly available, or available at all; or
  • the medical information on this website is complete, true, accurate, up-to-date, or non-misleading.
  • You must not rely on the information on this website as an alternative to medical advice from your doctor or other professional healthcare provider.
  • If you have any specific questions about any medical matter you should consult your doctor or other professional healthcare provider.

Recent

  • Smoking
  • What You Need to Know About the 2022 Avian Influenza Outbreak
  • Endocarditis Guideline Review
  • Sinus Troubles: When Should I See My Doctor
  • Common Pharmacogenomic SNPs and Interactions

Search

Tags

acid base acidosis acute coronary syndrome alkalosis analgesics anaphylaxis aortic dissection arrhythmia Beta-Blockers biostatistics blood pressure cardiac markers CHA2DS2-VasC cocaine COVID-19 diabetes diabetes inspidius Guidelines heart failure Heparin hypersensitivity hypertension hypovolemic shock intubation ionotropes journal club lipids LMWH medication safety morphine conversions myocardial infarction needs work NOAC NSTEMI obstructive shock pharmacoeconomics pheochromocytoma pressors reference materials right mi sedation septic shock shock STEMI Updated 2020