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Patient selection can affect required sample sizes and outcomes in
randomised clinical trials and the optimal selection may depend on how the
tested drug differentially affects patients. Bruynesteyn K et al. [1,2]
have investigated these effects in rheumatoid arthritis based on an
outcome measure of radiological damage progression.
An absolute reduction (AR) drug which reduces the expe...
An absolute reduction (AR) drug which reduces the expected number of
new erosions per year by, say, 2 in all patients irrespective of their
initial erosive risk is conceivable. Similarly, a relative reduction (RR)
drug which reduces the expected number of new erosions per year by, say,
20% in all patients is also conceivable, thus by, say, 1 new erosion per
year in medium risk patients and by, say, 3 new erosions in high risk
However, the authors’ absolute and relative risk reduction drug
models (ARR, RRR, respectively) differ from those described above in that
they reduce the risk of the number of new erosions exceeding a pre-
determined limit, smallest detectable change, by absolute or relative
amounts . Although valid as means of quantifying the effect of drugs
[3,4], ARR and RRR are not appropriate statistical models of drug action.
In fact, the authors’ ARR model represents a drug which reduces the number
of new erosions in ‘high’ and ‘low’ risk patients by similar absolute
amounts but is 50% less effective in patients at ‘medium’ risk of disease
progression. It is this inappropriate drug model which gives rise to the
statement (1): “From a statistical point of view, it would be wise to
avoid groups of patients with an average prior risk (of disease
progression) …. such patient groups provide less statistical power, as
compared to trials with patient groups with a low or a high prior risk”
rather than any valid reason to avoid enrolling average risk patients.
In a realistic absolute reduction (AR) drug model, the ‘medium’ risk
group is the optimum choice (representing patients with progression
critically near the pre-determined on/off event limit, Table 1.2 in ).
If the drug effect is averaged across all patients, results for an AR drug
are unaffected by patient selection. Thus the article inadvertently
highlights the caution required if on/off events, as opposed to group
averaged results, are used as outcome measures in trials.
Within the limits of such an evaluation, re-examination of the given
trial results  using corrected AR, RR models, indicate that:
methotrexate in combination with cyclosporin A is a pure RR drug, reducing
the occurrence of erosions in patients in proportion to their initial
risk; whilst the combination therapy in the COBRA trials follows a mixed
AR/RR model, reducing the occurrence of erosions more in high risk
patients than in low risk patients but not as much as might be expected by
their relative risk. Both studies confirm that patients at medium and high
risk of radiological disease progression are the optimum choice in
clinical trials where radiological damage is the outcome.
(1). Bruynesteyn K, Wanders A, Landewé R, van der Heijde D. How the
type of risk reduction influences required sample sizes in randomised
clinical trials. Ann Rheum Dis 2004; 63:1368-1371.
(2). Bruynesteyn K, Landewé R, van der Linden S, van der Heijde D.
Radiography as primary outcome in rheumatoid arthritis: acceptable sample
sizes for trials with 3 months follow-up. Ann Rheum Dis 2004; Published
Online First 22/03/2004. doi:10.1136/ard.2003.014043.
(3). Osiri M, Suarez-Almazor ME, Wells GA, Robinson V, Tugwell P.
Number needed to treat (NNT): implication in rheumatology clinical
practice. Ann Rheum Dis 2003; 62:316-321.
(4). Rothwell PM. Can overall results of clinical trials be applied to
all patients?[see comment]. Lancet 1995; 345:1616-1619.