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Notes
Supported by grants from Istituto Superiore di
Sanita "VII Progetto AIDS 1994 and VIII Progetto
AIDS 1995" (M. Clerici); and by grant CNRACRO n. 95. 00486. PF 39; 1995 (E. Clerici).
Correspondence to: Gene M. Shearer, Ph.D.,
National Institutes of Health, Bldg. 10, Rm. 4B17, Bethesda,MD 20892.
462
CORRESPONDENCE
Phase II Studies: Which
Is Worse, False Positive or
False Negative?
When comparing treatments in phase
III studies, we judge whether a new
treatment is superior to a standard control. In this case, the control is of known
efficacy and should not be superseded
without serious evidence of the superiority of its competitor. Accordingly,
we set the chance of a false positive to
5% (a = 0.05 = type I error) and the
chance of a false negative to a larger
number, say 20% or less (P = 0.2 = 1 power = type II error), in the extreme.
These error limits are used to determine
study design elements, such as sample
size and stopping rules.
In phase II trials, the relative costs of
false-positive and false-negative conclusions may be reversed (J). On the one
hand, we do not want to inflict an ineffective treatment on more patients than
is absolutely necessary, but we do not
want to reject a potentially effective
treatment. The cost of a false positive in
phase II trials is that of repeated studies,
which will eventually demonstrate the
lack of efficacy. However, the cost of a
false negative is that a useful treatment
is completely discarded.
Statisticians usually assign a higher
cost to false positives than to false negatives. This practice is appropriate for
phase III studies, but is misplaced in
phase II studies. Accordingly, if we
were to set the chance of a false positive
to, say, a = 0.15 and the chance of a
false negative to P = 0.05, we would be
protecting the new treatment from an
untimely demise. Furthermore, to a first
approximation, sample size should not
be affected by this interchange. For example, suppose we test the null hypothesis that a treatment has a 15%
response frequency versus the alternative of a 35% response frequency. We
use an early-stopping design to limit the
use of a clearly ineffective treatment.
The study will be stopped early if fewer
than three responses are observed
among the first 17 patients, and the
treatment is deemed ineffective. Otherwise, after evaluating 35 patients, if nine
or more responses are observed, we may
reject the null hypothesis. The trial has a
2.8% type I error and an 83% power
(17% type II error). If we change the cut
point from nine to seven responses,
using the same sample size, the trial has
a 13% type I error and a 94% power
(6% type II error). The sum of error
probabilities is about the same for both
arrangements, but the second design
protects an effective treatment from
premature rejection. Moreover, by increasing power from 83% to 94%, we
have decreased the false-negative error
probability by a factor of three.
We recommend this shift of emphasis
in future phase II trials.
ANDRE ROGATKO
SAMUEL LTTWIN
Department of Biostatistics
Fox Chase Cancer Center
Philadelphia, PA
Reference
(/) Herson J. Statistical aspects in the design and
analysis of phase II clinical trials. In: Buyse
ME, Staquet MJ, Sylvester RJ, editors. Cancer
clinical trials: methods and practice. Oxford:
Oxford Univ Press, 1992:239-57.
Note
Correspondence to: Andr6 Rogatko, Ph.D.,
Department of Biostatistics, Fox Chase Cancer
Center, 7701 Burholme Ave., Philadelphia, PA
19111.
Are Time or Intensity Factors
Important to the Definition
of Metastases of
Unknown Origin?
Barista et al. (7) have recently
proposed that time and intensity factors
should be incorporated into the definition of metastasis of unknown origin
(MUO), suggesting that "MUO be defined as the presence of metastatic illness with an unknown primary site after
2 weeks of intensive investigation."
While it is interesting to draw a diagnostic parallel between the definition of
fever of unknown origin (2) and MUO,
our data suggest that the specific diagnostic studies employed during the
evaluation are more important than time
or intensity.
Journal of the National Cancer Institute, Vol. 88, No. 7, April 3, 1996