I read Clinical Trials, a Methodologic Perspective (S. Piantadosi) as I was suggested by one of you.

According to the author:

A trialist must understand two different modes of thinking that support the science-clinical and statistical. They both underlie the re-emergence of therapeutics as a modern science. Each method of reasoning arose independently and must be combined skillfully if they are to serve therapeutic questions effectively.

I cannot figure out what the author means by "clinical reasoning". Can you help me to understand that notion?

Thank you in advance

  • $\begingroup$ Sounds like a term that is specific to that author. If you have found otherwise please share what you have found elsewhere and show why other uses of the term do not clear things up. $\endgroup$
    – rolando2
    Feb 26, 2011 at 14:39

2 Answers 2


I like @nico's response because it makes clear that statistical and pragmatic thinking shall come hand in hand; this also has the merit to bring out issues like statistical vs. clinical significance. But about your specific question, I would say this is clearly detailed in the two sections that directly follow your quote (p. 10).

Rereading Piantadosi's textbook, it appears that the author means that clinical thinking applies to the situation where a physician has to interpret the results of RCTs or other studies in order to decide of the best treatment to apply to a new patient. This has to do with the extent to which (population-based) conclusions drawn from previous RCT might generalize to new, unobserved, samples. In a certain sense, such decision or judgment call for some form of clinical experience, which is not necessarily of the resort of a consistent statistical framework. Then, the author said that "the solution offered by statistical reasoning is to control the signal-to-noise ratio by design." In other words, this is a way to reduce uncertainty, and "the chance of drawing incorrect conclusions from either good or bad data." In sum, both lines of reasoning are required in order to draw valid conclusions from previous (and 'localized') studies, and choose the right treatment to administer to a new individual, given his history, his current medication, etc. -- treatment efficacy follows from a good balance between statistical facts and clinical experience.

I like to think of a statistician as someone who is able to mark off the extent to which we can draw firm inferences from the observed data, whereas the clinician is the one that will have a more profound insight onto the implications or consequences of the results at the individual or population level.

  • $\begingroup$ Thank you very much for such a nice answer! Can I ask a couple a words to explain further the sentence "this is a way to reduce the chance of drawing incorrect conclusions from either good or bad data." In that setting, what are good or bad data? Thx again! $\endgroup$
    – ocram
    Feb 26, 2011 at 20:33
  • $\begingroup$ @Marco I guess by "bad data" the author means data that either departs from the initial design (missing value on covariates, lost to follow-up, etc.) or that present unexpected errors discovered afterwards (e.g., randomization to treatment errors, site-specific confounding effect) -- in this case, the statistician still has to cope with the available data. Remember that there is no substitute for good data (even machine learning cannot save us :-), but we must acknowledge the limitations of a particular statistical technique when faced with data of poor quality. $\endgroup$
    – chl
    Feb 27, 2011 at 9:04
  • $\begingroup$ Ok, noted! Thx! $\endgroup$
    – ocram
    Feb 27, 2011 at 9:46

I have not read the book, but my best guess would be that the author wants to points out that sometimes a critical reasoning has to be made when applying statistics to biological and medical issues.

The sole fact that, for instance, a treatment does not have a "statistically significant" effect does not imply that the treatment does not have a biological effect and viceversa. Statistics can tell you if a certain event is likely or unlikely to be happening, but does not give you any hint as to whether something is biologically plausible.

  • $\begingroup$ Tank you for this answer $\endgroup$
    – ocram
    Feb 26, 2011 at 16:39
  • $\begingroup$ @Marco: just bear in mind that I have not read the book, so I may be wrong! :) $\endgroup$
    – nico
    Feb 26, 2011 at 17:36
  • $\begingroup$ I give you a +1 because this response really makes sense, even if you haven't read the book. $\endgroup$
    – chl
    Feb 26, 2011 at 18:30

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