Statistical methods for testing plaque removal efficacy in clinical trials.
OBJECTIVE
To evaluate the ability of different statistical approaches in finding a statistically significant difference in plaque removal efficiency between brushes in clinical trials.


METHODS
The approaches, which are evaluated, concern the scores after brushing only, the difference in scores before and after brushing and the relative difference scores (i.e. score before minus score after brushing divided by the score before brushing). In each case the scores before brushing may be included as a covariate. Except for the relative difference scores, the power of the test statistics of the approaches has been compared by assuming a simple statistical model. These theoretical results have been compared with the numerical results of two particular clinical trials--one with a between-subject design and one with a within-subject design.


RESULTS
The numerical results of these clinical trials show that the calculated p-values support the conclusions drawn from the statistical model, i.e. the power of the F-test is highest when evaluating the data after brushing with the data before brushing included as a covariate. Using the differences in scores before and after brushing--again with the data before brushing as a covariate--does not add additional power to the test. Omitting the data before brushing as a covariate only gives satisfactory results when the variance over the subjects or the error variance is zero, which in general is not the case.


CONCLUSIONS
This investigation reveals that in general the approach of analysing the scores after brushing with the scores before brushing as a covariate yields the highest chance of finding a statistically significant difference between two brushes.
Heynderickx
I
I
Philips Research Laboratories, Eindhoven, the Netherlands.
Engel
J
J
D000328:Adult; D000704:Analysis of Variance; D003742:Dental Devices, Home Care; D003773:Dental Plaque / Q000628:therapy*; D003774:Dental Plaque Index; D006801:Humans; D016014:Linear Models; D015233:Models, Statistical; D016037:Single-Blind Method; D014099:Toothbrushing / Q000295:instrumentation*