A Whitepaper by NJ Stark and e-Conference by Dr. Robert Thiel
I read an interesting comment in a press release this morning. The CEO of Spectranetics said: "Our physician customers prefer randomized, controlled studies to assist them with their clinical decisions...." and "Our clinical trial program ... demonstrates our commitment to evidence-based medicine."
Every book or guidance document I read has a different way of categorizing clinical studies. One obvious categorization for medical devices is by whether or not you are doing a single-group (single-arm) study with no comparator, or whether or not you will compare your device to another. My experience is that most device studies are single-arm designs so I read the Spectranetics press release with a loud hurrah.
A poll—what's everybody else doing?
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Non-inferiority studies use smaller sample sizes
The difficulty arises when you calculate the sample size. Sample sizes are calculated based on the difference between the average values of an endpoint. The greater the difference between your device and mine, the fewer the number of subjects you'll need to show it. As the difference between your device and mine gets smaller, the sample size gets larger and larger. As the difference becomes infinitesimally small, i.e., the devices become equivalent, the sample size skyrockets to infinity.
Enter non-inferiority. Instead of showing that two devices are the same, a clever FDA statistician named Blackwelder looked at things differently and developed a strategy called "Proving the Null Hypothesis". He figured that if we stopped trying to prove the hypothesis and reject the null, and instead rejected the hypothesis and proved the null, we could accomplish the same thing as an equivalence trial but with a much smaller sample size. Blackwelder's ground-breaking paper was published in 1982.
FDA's new guidance document
Recently, FDA issued a draft guidance document titled "Guidance for Industry - Non-Inferiority Clinical Trials" (Mar2010). The guidance was issued by CDER and CBER because non-inferiority trials require active controls rather than placebos—something new for the drug world. We device people are familiar and comfortable with active controls (who would use a placebo heart valve?), and there is much a good biostatistician like Robert Thiel can teach us with regard to medical devices and diagnostics.
What device companies already know
Learn more: take the e-conference
Addendum: Brief Comments on Missing Data
There are three basic kinds of missing data:
A good study design has a plan (called a statistical analysis plan or SAP) that, among other things, determines beforehand how missing data will be identified and handled. Dr. Thiel will take a few final moments to discuss this important, but neglected, issue.
Dr. Thiel will discuss
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Who should attend (no, you do not need to be a statistician)
Date, time, registration
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