Controlled clinical trials最新文献

The primary aim of this randomized clinical trial is to evaluate whether a standardized modified Burch colposuspension, when added to planned abdominal sacrocolpopexy for the treatment of pelvic organ prolapse, improves the rate of urinary stress continence in subjects without preoperative symptoms of stress urinary incontinence. Secondary aims include comparison of immediate and short-term complications, overall urinary tract function, and other aspects of pelvic health between subjects with and without a concomitant Burch. The value of preoperative urodynamic testing with prolapse reduction will also be compared between subjects with and without a concomitant Burch. This trial is performed through the Pelvic Floor Disorders Network, which is funded by the National Institutes of Health–National Institute of Child Health and Human Development. Subjects will be enrolled at seven clinical centers across the United States and data will be analyzed by the central data coordinating center. Standardized questionnaires and physical observations and measurements will be obtained. The surgical team is masked to the preoperative urodynamic findings, and the patient and research coordinator are masked to treatment assignment. The primary outcome will be determined at 3 months after surgery. Stress continence is defined as absence of stress incontinence symptoms by questionnaire, a negative standardized stress test, and no treatment for stress incontinence other than the study intervention. Additional follow-up occurs at 6, 12, and 24 months. Accrual began in April 2002 and is projected to take 3 years. As of March 6, 2003, 91 patients have been randomized. This article highlights the scientific aspects of trial design for this pivotal clinical trial. The optimal approach to the urinary tract in women treated surgically for prolapse is not known. This trial is designed to provide pelvic surgeons and their patients with scientific data regarding the utility of urodynamics with and without prolapse reduction and the role of colposuspension with sacrocolpopexy.

Microalbuminuria is an early marker of diabetic nephropathy and its prevention is considered key for the primary prevention of diabetic nephropathy. Angiotensin-converting enzyme (ACE) inhibitors and nondihydropyridine calcium channel blockers (CCBs) have specific renoprotective properties in diabetes, and preliminary evidence is available that they are more effective in combination than either of the two agents alone in limiting albuminuria either in micro- or macroalbuminuric type 2 diabetic patients. The BErgamo NEphrologic DIabetes Complications Trial (BENEDICT) is a prospective, randomized, double-blind parallel-group study primarily aimed at evaluating the possibility of preventing the progression to microalbuminuria (urinary albumin excretion [UAE] rate 20–200 μg/min, i.e., incipient nephropathy) in 1209 hypertensive, type 2 diabetic patients with a normal UAE rate (<20 μg/min). During phase A of the study, patients are randomized to a 3-year treatment with one of the following: (1) a nondihydropyridine CCB (verapamil SR 240 mg/day); (2) an ACE inhibitor (trandolapril 2 mg/day); (3) the combination of the above study drugs (verapamil SR 180 mg/day plus trandolapril 2 mg/day); or (4) placebo. Phase B of the study evaluates the progression to macroalbuminuria (UAE⩾200 μg/min) in patients who progress to microalbuminuria in phase A or are found with microalbuminuria during the screening phase; these patients are randomized to a 2-year treatment with either trandolapril (2 mg/day) alone or verapamil SR (180 mg/day) plus trandolapril (2 mg/day). BENEDICT final results are expected to be available by the end of 2003 for phase A and 2 years later for phase B. The BENEDICT study, in addition to exploring whether primary prevention of diabetic nephropathy is an achievable goal, will also offer an opportunity to study prospectively risk factors of nephropathy and other chronic complications of type 2 diabetes. Here we provide an overview of the protocol and summarize the main baseline demographic, biochemical, and clinical characteristics of randomized participants.

Osteoarthritis (OA) of the knee leads to restrictions of physical activity and ability to perform activities of daily living. Obesity is a risk factor for knee OA and it appears to exacerbate knee pain and disability. The Arthritis, Diet, and Activity Promotion Trial (ADAPT) was developed to test the efficacy of lifestyle behavioral changes on physical function, pain, and disability in obese, sedentary older adults with knee OA. This controlled trial randomized 316 sedentary overweight and obese older adults in a two-by-two factorial design into one of four 18-month duration intervention groups: Healthy Lifestyle Control; Dietary Weight Loss; Structured Exercise; or Combined Exercise and Dietary Weight Loss. The weight-loss goal for the diet groups was a 5% loss at 18 months. The intervention was modeled from principles derived from the group dynamics literature and social cognitive theory. Exercise training consisted of aerobic and strength training for 60 minutes, three times per week in a group and home-based setting. The primary outcome measure was self-report of physical function using the Western Ontario and McMaster University Osteoarthritis Index. Other measurements included timed stair climb, distance walked in 6 minutes, strength, gait, knee pain, health-related quality of life, knee radiographs, body weight, dietary intake, and cost-effectiveness of the interventions. We report baseline data stratified by level of overweight and obesity focusing on self-reported physical function and physical performance tasks. The results from ADAPT will provide approaches clinicians should recommend for behavioral therapies that effectively reduce the incidence of disability associated with knee OA.

In this article, we consider the establishment of noninferiority between a reference test and a new test with respect to the ratio of sensitivity and/or specificity. We first review two (one-sided) noninferiority tests, namely the logarithmic transformation test and the Fieller-type test, and their associated sample size formulae proposed for matched-pair designs when the null hypothesis is of a specified nonunity rate ratio. Different methods for implementing these one-sided noninferiority tests are reviewed. They include (1) the sample-based method, (2) the constrained least-squares estimation method, and (3) the constrained maximum likelihood estimation method. We conduct a simple empirical study to evaluate the performance of various tests/methods. In summary, statistics based on constrained maximum likelihood estimation always control the actual type I error rate much better than other statistics. Moreover, the corresponding approximate sample size formulae are valid asymptotically in the sense that the exact powers associated with the approximate sample size formulae are generally close to the prespecified power level. Methods based on constrained maximum likelihood estimation are illustrated with a real example from a clinical laboratory study.

This paper presents a new sample size formula for Cochran's test that uses additional information on stratum-specific success rates and requires fewer subjects for an equivalence study. Equivalence studies are common in clinical trials, where unlike superiority studies, the goal is to show whether a new drug therapy is as effective as a standard one. Stratification is typically used to adjust for differences among individual clinical trial centers with different success rates. The sample size is derived for a clinical trial design where two independent binomial proportions are compared within each stratum. Implementation of the sample size formula is described when the number of centers is large and the success rates of each individual center are not known exactly. The effect of variability of the success rates on the power of Cochran's test is shown through simulation. The variability of the success rates is measured by the intracluster correlation coefficient, which can be estimated by the ANOVA estimator of Donald and Donner. The simulation results show that the new sample size formula requires fewer subjects than sample size methods, which ignore stratification. The new method provides greater savings as the variability of success rates among centers increases.

OPTIMA (OPTions In Management with Antiretrovirals) is a clinical trial with a factorial randomization to evaluate the hypotheses that mega-antiretroviral therapy (ART) consisting of five or more anti-HIV drugs compared to standard-ART consisting of four or fewer anti-HIV drugs and a 3-month antiretroviral drug-free period (ARDFP) compared to no ARDFP will delay the occurrence of new or recurrent acquired immunodeficiency syndrome events or death, and prove to be more cost-effective in treating human immunodeficiency virus-infected individuals previously exposed to ART drugs from the current three main classes. The aim is to randomize 1700 participants to four treatment strategy arms: (1) ARDFP + standard-ART; (2) ARDFP + mega-ART; (3) no ARDFP + standard-ART; (4) no ARDFP + mega-ART. The planned study duration is 3.5 years with 2.5 years of intake and a minimum 1 year of follow-up. The OPTIMA Trial was initiated in June 2001 at 30 U.S. Department of Veterans' Affairs hospitals, 22 hospitals in Canada, and 25 hospitals in the United Kingdom. This is the first large-scale, multicenter, randomized controlled trial to compare the relative efficacy of these different therapeutic strategies. We discuss the rationale behind the OPTIMA Trial design as well as the issues arising from the conduct of a trial that involves three national clinical trial agencies.

Maintaining participant adherence is a prerequisite for successful completion of randomized controlled trials requiring long-term follow-up. While patient characteristics influencing adherence are well studied, the influence of contact with clinical staff on this process has received almost no attention. To address this issue the authors evaluated the association of turnover in key clinical research staff with measures of participant adherence to protocol requirements at 40 clinical centers participating in the Women's Health Initiative (WHI), a large multicenter study. Key staff turnover in positions with potential influence on maintaining participant adherence in the Dietary Modification Clinical Trial (DM-CT) and the two Menopausal Hormone Therapy Clinical Trials (HT-CT) of the WHI was determined at each clinical center. Three prospectively established measures of participant adherence for the DM-CT and HT-CT were related to key staff turnover at each clinical center by staff category. More frequent turnover of the clinic practitioner, clinic manager, and principal investigator positions was significantly (p<0.05) associated with lower participant adherence in the HT-CT but was not associated with DM-CT participant adherence. More frequent turnover of the lead nutritionist was not associated with HT-CT participant adherence but was significantly (p<0.05) associated with one measure of decreased DM-CT participant adherence, as would be expected since the lead nutritionist did not typically see the HT-CT participants. These significant and plausible associations suggest that providing consistent contact with key staff in randomized, controlled clinical trials may facilitate long-term participant adherence. Further prospective study exploring process evaluation of the provider side of controlled trial conduct is indicated.

Subgroup analysis is a common secondary objective in clinical trials. In oncology where the outcome is often binary (such as tumor response) or time-to-event (such as survival), subgroup analysis can be formulated using an interaction term in logistic or proportional hazards regression models. We focus on a case study of planning a randomized trial in metastatic colorectal cancer possibly involving a treatment-marker interaction. We present a method that can be used to compute the power of interaction tests for a given sample size or to compute the necessary sample sizes for a desired level of power for the planned subgroup analysis. The principle idea is borrowed from analysis of variance and uses appropriate contrasts after a variance-stabilizing transformation. This method is conceptually and operationally simple. It can be applied to binary- or ordinal-marker measurements, and existing sample size tables or software can be used. The accuracy of the approximation is shown to be reasonable by simulation studies.