It can be difficult to asess the "positive predictive value" of a test, even when you know the prevalence of a disease and the accuracy and false positive rate of the test. This was the winning entry for the BioVis design contest at IEEE VIS 2016 conference in Baltimore, Oct. 23, 2016.

1. Visual communication of
conditional probabilities
Christian Stolte
New York Genome Center
BIOVIS DESIGN CONTEST
WINNER

2. Mammography
What does it mean to get a positive result?
“The probability of breast cancer is 1% for a woman who participates in routine
screening. If a woman who participates in routine screening has breast cancer,
the probability is 80% that she will have a positive test result. If a woman who
participates in routine screening does not have breast cancer, the probability is
9.6% that she will have a positive test result.”
Target Question: “What is the probability that a woman who participates in
routine screening and receives a positive result has breast cancer?”
Answer: 7.8%

3. 25 x 40 = 1,000

4. 1% = 10 Cancers in 1,000

5. 80% accuracy = 2 in 10 false negatives

6. 9.6% false positives = 96 in 1,000

7. Stacked bar chart shows ratio

8. Labels help

9. Better readable from left to right

10. Trisomy
The role of false positives in rare events
“It is estimated that trisomy 21 is present in 1 out of every 800 births in Canada.
It is estimated that trisomy 18 is present in approximately in 1 out of every 6,000
births. It is estimated that trisomy 13 is present in approximately in 1 out of
every 16,000 newborns. The Harmony Test has been shown to have detection
rates of up to 99% and false positive rates as low as 0.1% for trisomy 21, 18,
and 13.”
Target Question: “What are the probabilities of having a child affected with a
trisomy 21, 18, or 13 given a positive test result, respectively?”

11. One

12. One

13. in 800
One

14. in 6,000
One

15. in 16,000
One

20. in 6,000
One

21. in 16,000
One

24. THANK YOU!