118s Abstracts

P13 IDENTIFYING THE EFFECT OF THE LEARNING CURVE IN

CLINICAL TRIALS

Craig Ramsay University of Aberdeen

Aberdeen, Scotland

Ideally, health service innovations, such as new surgical techniques, should be evaluated before widespread use. Many of these techniques exhibit some form of learning effect, and this represents a barrier to rigorous evaluation. There is reluctance to evaluate when the technique is being learnt, yet unwillingness to admit uncertainty once it has been learnt.

Randomized controlled trials are seen as the gold standard methodology for evaluating new health technologies. Although many clinical trials acknowledge the possibility of learning, they do not collect the relevant information to allow thorough investigation. A desirable endpoint in a clinical trial may also be inlluenced by the experience of the surgeon. Operation time and complication rates for some types of minimal access surgery decrease as experience is gained; however, this rate of decrease is surgeon specific. This will under-estimate or over-estimate the parameter estimates of differences between the treatment and control groups. There is a need to assess and adjust for the learning curve associated with a new technique during evaluation. Data requirements and methods for identification of learning effects, using clinical trials of new health technologies, will be discussed.

P14 RECURRENT MISCARRIAGE STUDY: HOW SHOULD DATA FROM

WOMEN WHO DO NOT BECOME PREGNANT BE HANDLED?

Theodore Karrison and Carole Ober University of Chicago

Chicago, Illinois

The Recurrent Miscarriage (REMIS) study is a double-blind, multicenter, randomized clinical trial to evaluate the efficacy of immunization with paternal leukocytes in the prevention of miscarriages in women with three or more unexplained losses. Women entering the study receive injections of either their husband’s leukocytes or a saline control prior to becoming pregnant After achieving a pregnancy, they receive weekly ultrasound examinations and psychological support during the first trimester, and are followed until either a successful delivery (228 weeks gestation) or a miscarriage occurs.

Intent-to-Treat (TM’) analysis will be based on comparison of the proportion of “successes” in the two groups, with success defmed as achieving a pregnancy within 12 months of randomization that results in a viable offspring. Miscarriages and non-pregnancies will be counted as faihtres, owing to the possibility of very early losses prior to pregnancy detection. However, this can have a sizable effect on the power of the study and therefore a secondary analysis will be. performed in which couples who do not become pregnant within the allotted 1Zmonth period are excluded.

We examined the power of these two approaches as well as the potential bias associated with the analysis excluding non-pregnant women. As might be expected, the ITT analysis maintains the type I error rate and the analysis excluding non-pregnant women does not when delivery rates are assumed equal but pregnancy rates differ. The latter analysis is noticeably more powerful, however, for alternatives in which delivery rates differ and pregnancy rates are equal. We also examined the power of comparisons based on the 2x3 table in which outcomes are categorized as non-pregnant, miscarriages, or live births and found that it provided greater power than the ITT analysis, which collapses the first two categories. A fourth type of comparison that normalizes the diirence in birth rates based on the pregnancy