Anavex Life Sciences Corp (AVXL)

[F1ash]

Some food for thought.

“The observed 3-year effect was large: 88% improvement compared to lower dose for ADCS-ADL (p<0.0001) and 64 % less decline for MMSE (p<0.0008).”

What do the P values mean?

I believe it means that there is a .01% chance of getting that result randomly for ADCS-ADL and .08% for MMSE.

“For example, suppose that a vaccine study produced a P value of 0.04. This P value indicates that if the vaccine had no effect, you’d obtain the observed difference or more in 4% of studies due to random sampling error.”

https://blog.minitab.com/blog/adventures-in-statistics-2/how-to-correctly-interpret-p-values

However:

“First, P values are calculated based on the assumptions that the null is true for the population and that the difference in the sample is caused entirely by random chance. Consequently, P values can’t tell you the probability that the null is true or false because it is 100% true from the perspective of the calculations.

Second, while a low P value indicates that your data are unlikely assuming a true null, it can’t evaluate which of two competing cases is more likely:

The null is true but your sample was unusual.
The null is false.”

https://blog.minitab.com/blog/adventures-in-statistics-2/how-to-correctly-interpret-p-values


IMHO the P values are very encouraging.

Some more thoughts:

If dosing has remained constant since the 5 week point then Anavex could give the results for each individual dose if they wanted to do that. Many/most companies choose to reveal how each dose did in relation to the other doses. Presenting results in a traditional fashion along side of the “concentration” method Anavex chose would probably help make Anavex’s case stronger if both data sets agree.

I’m not a huge fan of taking four different doses and dividing them into two separate groups especially if it’s not based on dose. Where does one draw the line between high and low concentration? I would draw the line wherever it made my data look the best. That’s probably not the most objective way to accomplish the task but it would be the best for my company’s share price.

Some more “critical thinking” thoughts.

If no one in the Phase 2A AD trial taking 50 mg has had a single AE in the last year, why not include a 50 mg dose in the PDD trial? Why go with only 10 and 20 mg? Why was the initial PDD Trial registered as dosing from 20 to 50 Mgs? Why not 10 to 50 mgs?

If you administer an “effective” drug to a population of patients, shouldn’t the average scores for the “entire patient population” improve in relation to historical norms since “some patients” improved that would not otherwise be expected to improve, which would show up in the overall average?


https://www.anavex.com/wp-content/uploads/2018/10/ANAVEX2-73_CTAD_2018_Presentation.pdf

Someone still needs to explain to me how a graph that seem to represent the same time period “57 weeks” appears to show 26 patients for ADCS-ADL and only 21 for MMSE. WTH?


Previous statement notwithstanding could one take the numbers from page 13 (# on high dose and # on low dose) and determine how the entire population performed in relation to historical norms by using the graphs on page 16 and 17?

I believe it is possible (but perhaps not accurate because who knows why the heck the patient count seems to jump around erratically).

Does the entire population outperform historical norms. It probably should if the drug works, right?