DOI: 10.1097/01.COT.0000405241.30424.d6
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Issn Print: 0276-2234
Publication Date: 2011/08/25
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Excerpt
Okay, there's a lot wrong with that scenario. I don't think I own anything fancy enough to be called an armchair; brandy makes me retch, as does smoking; I don't own a dog (though, if I did, I would probably name him “King” in homage to the old Rodney Dangerfield sketch, in which he claims, “When I'm at home, my wife treats me like a king, calling out to me, ‘Here, King! Here, King!’”); and any section of a journal that involves statistics is often a valid substitute for Ambien to help with sleep.
But one recent article published in June in JCO (2011;29:2439-2442) did catch my eye, because it deals with an inherent challenge in requiring overall survival as the ultimate, gold standard endpoint to randomized trials in oncology. In it, the authors (Korn, Freidlin, and Abrams), all from the National Cancer Institute, play out different scenarios of how difficult it is to conduct a study of an experimental therapy vs. a standard therapy with a clean survival endpoint.
How can survival be anything but straightforward? You're either dead or alive, right?
Well, yes, but how you get there can be murky. Most trials start out cleanly enough. A patient with metastatic cancer is randomized to either experimental, or standard, therapy. The patient remains on that therapy until progression or death or unacceptable toxicities. The problem lies in what happens to that patient if she then goes on to get another therapy.
Let's say that the experimental therapy (B) controls the cancer better than the standard therapy (A)—seems as if the experimental therapy eventually should provide a survival advantage to the patient over standard therapy. But what if, upon progression on either study arm, the patient goes on to get a different, standard therapy (C) that works better at controlling the cancer after standard therapy (A) than it does after experimental therapy (B)? Any survival advantage to the experimental therapy (B) will be eliminated, and if the study has as a primary objective to detect survival differences between study arms, it will be a negative study.
Okay, but what if the subsequent standard therapy (C) works just as well at controlling the cancer in both arms. You should then be able to see that survival advantage that the experimental therapy (B) provides, right?
Maybe, but you might miss it. Remember, studies are powered to detect percent survival differences. Let's say that, with experimental therapy (B), a cancer patient lives 12 months, but with standard therapy (A) she lives 9 months. That's a 33% improvement in survival—rock on! But, what if subsequent standard therapy (C) extends patients' survival on both arms by three months. Now, the survival advantage to patients on the experimental arm (B) compared with those on the standard arm (A) is 15 months vs. 12 months—still a three-month difference, but now only a 25% improvement for the experimental arm (B)—which may not be significant if patient sample size is not increased. Again, we may be left with a negative study.
