Replies to post #80265 on Rivulet Media Inc (fka RIVU)

[Blushing green]

lol any sample size will provide an accurate p-value. the sample size only effects consistency.

[Inoviorulez]

I liked what you wrote but I will have to disagree with needing more than 10. You might ask why??? Simply because this is only a phase 1 trial!

The majority of biotechs start off phase 1 with a small sample size 10 to 20 just to test the efficacy and safety slightly. Once it gets to phase 2 then they enroll 100 to 150 and then in phase 3 normally there is 300 or more patients enrolled. It's always been like this. It is not uncommon for phase 1 to only have 10 patients as a sample size!

[To theTop]

I disagree. Through each phase more people will be introduced. You think they want to risk more people lives in phase I? No way. I could see an increase to 15 max but no more than that.
You have no idea what questions they have asked and no one on this board does so please don't make those claims.

[reginaliberta]

What would that change increasing pool size in study when efficacy is demonstrated? Remember most R&d are underfunded.
Have you read the peer review?

interested to see results from human studies in trials...

[Stock84]

One cannot start the trial with a large group directly. Clinical trials are done in multiple phases.

phase I Testing of drug on healthy volunteers for dose-ranging often subtherapeutic, but with ascending doses clinical researcher 20-100 determines whether drug is safe to check for efficacy
They need to determine the dose first and determine its efficacy and then sybaequently increase the I've of the group.

[CPAP]

I recently completed two semesters of graduate bio-stats at a community health program in CT. It seems there's some truth in what everyone is saying...

When working with clinical trials and more specifically, randomized clinical trials (RCT's), we generally like to see sample sizes of n>30, because if we are dealing with interval data it can then be normalized and it becomes easier to run statistical analyses on. Additionally, this increases the power (or strength) of the findings. Another way studies gain statistical power is by blinding (single, double and triple - ie patient, physician and statistician, respectively).

Regardless of the test, we generally want to see alpha at either .05 or .01 (in rare cases, 0.10 is also acceptable, such as in AIDS testing), which means we correctly identify an observed group difference in 95 or 99 times out of 100 and the other 5 and 1 are observed merely "by chance," which is why sample size becomes so important.

That said, vital statistics indicate that the incidence and prevalence rates for aplastic anemia are incredibly low (<1 per 100,000 http://www.cancer.org/cancer/aplasticanemia/detailedguide/aplastic-anemia-key-statistics ), meaning it's challenging for researchers to assemble a large enough sample size with enough power to garner the weight needed to be recognized as being reliable.

Additionally, aplastic anemia has a high case-fatality rate with a recent publication from 2008 (Montane et al) indicating that a 2-year survival rate is less than 60%, making it difficult for companies to test their treatment because slightly more than half of the participants will live long enough to complete the study. Sadly, it would be poor science to give the treatment to all, because then you would lack a control group to compare your differences to (with the control being the currently accepted treatment for the disease). Simply put, we already have a very rare, very lethal disease...we then need to assemble representative samples with controls...all of whom have high case fatality rates. The sheer numbers make it challenging for the researchers to prove their findings. Not knocking these guys at all, just saying from a scientific/clinical research perspective, it's hard to prove their treatment works.

That said, I hope it (treatment) does work. I'm a blood banker and have only witnessed this disease once in three years and it ravaged a 12-year old girl that was incredibly active until she succumb to the disease last year.

Did these guys release their raw data or is it all proprietary at this point? I'd like to see some of their numbers and run them through SPSS and see what it looks like.

Thanks all, for the insightful input! BMSN

[moosepass]

Could you comment on why BMSN would think that 10 is an adequate number?

It seems BMSN and its team of scientists have a reason to think that a green light is possible with just 10 patients in Phase 1.

TIA for your thoughts.