Multiple retinal detachment surgery: A functional outcome study. The Houston Vision Assessment Test-Retina (HVAT-Retina)

Retinal detachment is a common ophthalmologic procedure, and outcome is typically measured by a single factor-improvement in visual acuity. Health related functional outcome testing, which quantifies patient's self-reported perception of impairment, can be integrated with objective clinical findings. Based on the patient's self-assessed lifestyle impairment, the physician and patient together can make an informed decision on the treatment that is most likely to benefit the patient. ^ A functional outcome test (the Houston Vision Assessment Test-Retina; HVAT-Retina) was developed and validated in patients with multiple retinal detachments in the same eye. The HVAT-Retina divides an estimated total impairment into subcomponents: contribution of visual disability (potentially correctable by retinal detachment surgery) and nonvisual physical disabilities (co-morbidities not affected by retinal detachment surgery. ^ Seventy-six patients participated in this prospective multicenter study. Seven patients were excluded from the analysis because they were not certain of their answers. Cronbach's alpha coefficient was 0.91 for presurgery HVAT-Retina and 0.94 post-surgery. The item-to-total correlation ranged from 0.50 to 0.88. Visual impairment score improved by 9 points from pre-surgery (p = 0.0003). Physical impairment score also improved from pre-surgery (p = 0.0002). ^ In conclusion, the results of this study demonstrate that the instrument is reliable and valid in patients presenting with recurrent retinal detachments. The HVAT-Retina is a simple instrument and does not burden the patient or the health professional in terms of time or cost. It may be self-administrated, not requiring an interviewer. Because the HVAT-Retina was designed to demonstrate outcomes perceivable by the patient, it has the potential to guide the decision making process between patient and physician. ^

Bayesian doubly optimal group sequential designs for randomized clinical trials

When conducting a randomized comparative clinical trial, ethical, scientific or economic considerations often motivate the use of interim decision rules after successive groups of patients have been treated. These decisions may pertain to the comparative efficacy or safety of the treatments under study, cost considerations, the desire to accelerate the drug evaluation process, or the likelihood of therapeutic benefit for future patients. At the time of each interim decision, an important question is whether patient enrollment should continue or be terminated; either due to a high probability that one treatment is superior to the other, or a low probability that the experimental treatment will ultimately prove to be superior. The use of frequentist group sequential decision rules has become routine in the conduct of phase III clinical trials. In this dissertation, we will present a new Bayesian decision-theoretic approach to the problem of designing a randomized group sequential clinical trial, focusing on two-arm trials with time-to-failure outcomes. Forward simulation is used to obtain optimal decision boundaries for each of a set of possible models. At each interim analysis, we use Bayesian model selection to adaptively choose the model having the largest posterior probability of being correct, and we then make the interim decision based on the boundaries that are optimal under the chosen model. We provide a simulation study to compare this method, which we call Bayesian Doubly Optimal Group Sequential (BDOGS), to corresponding frequentist designs using either O'Brien-Fleming (OF) or Pocock boundaries, as obtained from EaSt 2000. Our simulation results show that, over a wide variety of different cases, BDOGS either performs at least as well as both OF and Pocock, or on average provides a much smaller trial. ^