watsonhelper - Specificity vs Sensitivity. "I have seen a lot of confusion on sensitivity vs specificity. I wanted to help some in simple terms.
Specificity calls out the disease itself in the raw. 65% of the patients have the disease, this means 65/100 tested have it at this point, as far as we know. There are variables, those are worth worrying about since the published variables are so low.
Sensitivity rules out the doubt. 94% sensitivity shows 9.4 of 10 people are sure the test is right and confirms the disease. Or look at it this way, if a test is highly sensitive with a negative result, you can be nearly certain that you don’t have disease. If it's highly sensitive with a positive specificity result, you probably have ALZ.
So why does it matter at the end of the day. Specificity is good in LP-002. It's not great, it's good. Keep in mind that's all we're looking for. Proof beyond guessing and symptoms is great, that's the win for AMBS. Keep in mind that they can use whatever data they want, they can still use LP-001 if they choose for marketing. LP-002 added variables for a reason, like dementia. This is a protective factor for AMBS or any company like them to cover tracks and rule yourself out as a risk. They faired very well, read SEC filings to see that they still have the ball in their court with which results they use.
The good news, if 35% of the people tested negative for ALZ, the test being 94% sensitive would mean they are almost beyond a reasonable doubt willing to say ALZ doesn't exist in that patient. To the contrary, for the 65% testing positive, they are 94% willing to say they have ALZ. It's not easy to identify it in the markers, this is the challenge, thus why sensitivity is critical, that 94% means the world.
Good or bad for the company? It's actually very good in the big picture and an attractive test for any doctor. Many you use today have less than 60% specificity and less than 90% sensitivity, you just never asked"
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Thanks for the feedback, what I say in my own mind doesn't always make it easy to read. I found a UTI study of 1,000 women. This may be the best way for people to understand, you can use like math and change the figures out:
1,000 Participants - Be careful with the wording when calculating....
Sensitivity of 71% means that only 213 (71% of 300) women with UTI would have a positive test result. The remaining 87 would have a negative test result. Specificity of 85% means that 595 (85% of 700) women without UTI would have a negative test result. The remaining 105 would have a positive test result. Thus, of 318 positive test results, only 213 would be correct (213/318 = 67% PPV); a positive test result makes the diagnosis of UTI more likely than not but not certain. There would also be 682 negative tests, of which 595 are correct (595/682 = 87% NPV), making the diagnosis of UTI much less likely but still possible; 13% of patients with a negative test result would actually have a UTI.
Specificity calls out the disease itself in the raw. 65% of the patients have the disease, this means 65/100 tested have it at this point, as far as we know. There are variables, those are worth worrying about since the published variables are so low.
Sensitivity rules out the doubt. 94% sensitivity shows 9.4 of 10 people are sure the test is right and confirms the disease. Or look at it this way, if a test is highly sensitive with a negative result, you can be nearly certain that you don’t have disease. If it's highly sensitive with a positive specificity result, you probably have ALZ.
So why does it matter at the end of the day. Specificity is good in LP-002. It's not great, it's good. Keep in mind that's all we're looking for. Proof beyond guessing and symptoms is great, that's the win for AMBS. Keep in mind that they can use whatever data they want, they can still use LP-001 if they choose for marketing. LP-002 added variables for a reason, like dementia. This is a protective factor for AMBS or any company like them to cover tracks and rule yourself out as a risk. They faired very well, read SEC filings to see that they still have the ball in their court with which results they use.
The good news, if 35% of the people tested negative for ALZ, the test being 94% sensitive would mean they are almost beyond a reasonable doubt willing to say ALZ doesn't exist in that patient. To the contrary, for the 65% testing positive, they are 94% willing to say they have ALZ. It's not easy to identify it in the markers, this is the challenge, thus why sensitivity is critical, that 94% means the world.
Good or bad for the company? It's actually very good in the big picture and an attractive test for any doctor. Many you use today have less than 60% specificity and less than 90% sensitivity, you just never asked"
MORE-
Thanks for the feedback, what I say in my own mind doesn't always make it easy to read. I found a UTI study of 1,000 women. This may be the best way for people to understand, you can use like math and change the figures out:
1,000 Participants - Be careful with the wording when calculating....
Sensitivity of 71% means that only 213 (71% of 300) women with UTI would have a positive test result. The remaining 87 would have a negative test result. Specificity of 85% means that 595 (85% of 700) women without UTI would have a negative test result. The remaining 105 would have a positive test result. Thus, of 318 positive test results, only 213 would be correct (213/318 = 67% PPV); a positive test result makes the diagnosis of UTI more likely than not but not certain. There would also be 682 negative tests, of which 595 are correct (595/682 = 87% NPV), making the diagnosis of UTI much less likely but still possible; 13% of patients with a negative test result would actually have a UTI.
