Medical Study Analysis Outline and Excerpt

OUTLINE

- INTRODUCTION
- OBJECTIVES
- ACRONYMS

- STUDY TYPES
- Introduction
- Randomized controlled trials
- Randomization
- Blinding
- Procedural studies
- Unblinding by treatment effects
- Observational studies
- Cohort studies
- Case-control studies
- Advantages
- Disadvantages
- Confounders
- Selection bias
- Surveillance bias
- Protopathic bias
- Reverse causation
- Causality
- Meta-analysis
- Advantages
- Disadvantages
- Example
- Network meta-analysis

- STATISTICAL THEORY
- The normal distribution
- 95% Confidence Interval
- 95% CI and sample size
- The p-value
- Statistical significance
- Multiple comparisons

- STUDY DESIGN
- Introduction
- Study power
- Outcome analysis
- Intention-to-treat analysis (ITTA)
- Per-protocol analysis (PPA)
- Patient adherence
- When PPA matters
- As-treated analysis (ATA)
- On-treatment analysis (OTA)
- Modified ITTA
- Noninferiority outcomes

- ABSOLUTE VS RELATIVE RISK
- Definitions
- NNT / NNH

- SENSITIVITY AND SPECIFICITY
- Definitions
- PPV / NPV
- Interplay between the two

- OTHER
- Recall bias
- Reporting bias
- Sensitivity analysis
- Bayesian theory/inference
- Cluster randomization
- Pragmatic trials
- Propensity score matching

EXCERPT

Doctors order a lot of tests, most of which have a sensitivity and specificity for some condition. On the surface, these terms seem self-explanatory. If a test is sensitive, it's usually positive if a condition is present. If a test is specific, a positive test makes the condition very likely. Most people understand these concepts, but applying the information can sometimes be confusing. To illustrate, I'm going to present you with a clinical scenario.

*A very distraught 52-year-old female comes to see you in your clinic. Your colleague ordered a Cologuard test on her, and it came back positive. Someone from your office called her and gave her the results, and since then, she has been unable to sleep and having daily panic attacks because she is afraid she is going to die from colon cancer. She tells you she went to the Cologuard website and read that the test has a sensitivity of 92% and a specificity of 90%. She starts to cry hysterically and says, "That means there is only a 10% chance the test is wrong."*

So what do you want to tell her? Does she really have a 90% chance of having colon cancer? Let's break these two measures down and see if we can give her an educated answer.

First, let's tackle sensitivity, defined as the percentage of people with the disease who get a positive result. If a test has high sensitivity, almost everyone with the disease will have a positive test. Cologuard has a sensitivity of 92%, which means only 8% of people with colon cancer will get a negative result (false negatives). High sensitivity tests are most useful when negative because it means the disease is very unlikely. The significance of a positive result depends on the specificity.

Specificity is the percentage of people without the disease who get a negative result. Cologuard has a specificity of 90% which means only 10% of people without colon cancer will get a positive result (false positives). A test with high specificity is most useful when positive because it makes the disease likely. The illustrations below help to explain the relationship. [71]

So what do you want to tell her? Does she really have a 90% chance of having colon cancer? Let's break these two measures down and see if we can give her an educated answer.

First, let's tackle sensitivity, defined as the percentage of people with the disease who get a positive result. If a test has high sensitivity, almost everyone with the disease will have a positive test. Cologuard has a sensitivity of 92%, which means only 8% of people with colon cancer will get a negative result (false negatives). High sensitivity tests are most useful when negative because it means the disease is very unlikely. The significance of a positive result depends on the specificity.

Specificity is the percentage of people without the disease who get a negative result. Cologuard has a specificity of 90% which means only 10% of people without colon cancer will get a positive result (false positives). A test with high specificity is most useful when positive because it makes the disease likely. The illustrations below help to explain the relationship. [71]