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NBME 22 Answers
A screening test for cancer is developed and ...
Data point labeled ‘A’
SPin and SNout. Specificity in, sensitivity out.
Excellent explanation but a minor typo. 1-0.99 = 0.01 not 0.10 :)
The question is asking what point would be the most likely to rule in cancer, and high specificity when positive rules in cancer. The highest specificity value is A, bc the the X axis shows (1-specificity)!
brise is correct. Knowing the LR+ value = 10 does not help in this situation because estimating where "10" should fall on an axis is arbitrary.
The way to approach this Q is to know that a high specificity is will mean that a positive result is very very likely to be a true positive. In theory, suppose that the specificity was 0.99. This is 99% specificity. Then, you look at the graph. The X-axis is "1-specificity." So, suppose the best test has a specificity of 99%. Then, calculating 1-specificity = 1 - 0.99 = 0.1. You would then chose the datapoint that corresponds to having an "X-value" that is closest to the origin. In this problem, it corresponds to data point "A."