Celsion Corp. Message Board

• daviscupper daviscupper Jan 8, 2013 1:52 PM Flag

Seeking Alpha Model Analyzed...

Today's Seeking Alpha article "Celsion's Phase III Blockbuster Data Revealed And It's Been Right Underneath Your Nose," takes a very similar approach to my original model, which I had posted here a couple of months back.

Some have asked me to analyze it so I will.

The model is strikingly similar to mine in its approach. It does not attempt to divine how well the ThermoDox patients should do based on the science or scant Clinical evidence we have from our Phase I trial. Rather, it takes the total known PFS events and then subtracts what the expected number of events from the control group should be, based on a significant amount of data we have about our RFA patients, enrollment data and time in trial, and then arrives at the number of PFS events from the treatment group. From here it a very simple calculation to determine how well the Treatment group is doing in comparison to the Control group. After running the numbers he concludes the Treatment group is exceeding everyone's expectations.

Let's look at the models side by side.

1. He calculates a 10.5 median monthly PFS rate for the Control group. I use a 12 month median.

2. His enrollment data and time in trial data match almost perfectly with mine from what I have seen so far.

3. His Total median PFS rate is 25.6 months. I arrived at 25 months.

4. He does not calculate a PFS rate for the Thermodox +RFA group because he claims less than half of the patients have evented, so this is not possible. Uh, this is not right. He calculates there have been 123 events from the ThermoDox patients. Well, given that we know the time in trial for all the Treatment patients it is just a matter of running a number of different PFS rates over the times in trial to arrive at a PFS rate that will yield 123 events. He did not do this. Oversight, perhaps.

5. He claims that the ThermoDox + RFA patients will show an improvement over the control patients in the neighborhood of 144 percent. There is a serious error in his calculation.

He arrives at his figure by noting that the Total PFS rate is 25.6 months. He also calculates, if you recall, that the control arm has a 10.5 PFS rate. He then performs the following calculations:

25.6/10.5 = 2.44. In other word, according to him, it takes the Treatment arm 2.44 times longer to event than Control arm. That is a 144 percent improvement. This is a serious error.

The error stems from the fact that he is comparing the Total PFS rate to the Control PFS rate. He should be comparing the Treatment PFS rate to the Control PFS rate.

The relationship looks more like this (Not adjusting for the non-linearity of the patient enrollment data and the non-linear PFS distributions):

Total PFS rate = .5 x PFS rate of Control + .5 x PFS rate of Treatment, hence
25.6 = .5 x 10.5 + .5 x PFS rate of Treatment.
20.35 = .5 x PFS rate of Treatment
40.7 = PFS rate of the Treatment group.

Now, comparing Treatment to Control yeilds:
40.7/10.5 = 3.88, that is the treatment group takes 3.88 times longer to event.
That is a 288 percent improvement for the Treatment group over the Control group.

Conclusion: I agree with his analysis in the main. Given the historical data on seriously ill liver cancer patients with tumors in the 3-7cm range and their tendency to even in under 12 months, ThermoDox must be working exceeding well. His model is roughly 10.5 vs 40.7

Nice, very nice.