Composite endpoints are often used in clinical trials in order to increase the overall event rates, reduce the sizes of the trials and achieve desired power. For example, in a trial to study the effect of a treatment ...
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Composite endpoints are often used in clinical trials in order to increase the overall event rates, reduce the sizes of the trials and achieve desired power. For example, in a trial to study the effect of a treatment on the prevention of venous thromboembolic events after a major orthopaedic surgery of the lower limbs, the primary endpoint is usually a composite endpoint consisting of any deep vein thrombosis identified by venography of lower limbs, symptomatic and well-documented non-fatal pulmonary embolism, and death from all causes. Just as any endpoints, missing data can occur in the components of the composite endpoint. If a patient has missing data on some of the components but not all the components, this patient may not have complete data but partial data for the composite endpoint. To be consistent with the intention-to-treat principle, the patient should not be discarded from the analysis. In this research, we propose an approach for the analysis of a composite endpoint with missing data in components. The main idea is to first derive the probabilities of all possible study outcomes based on the appropriate model and then to construct the overall rate for the composite endpoint. Simulations are conducted to compare the approach with several naive methods. A data example is used to illustrate the application of the approach. Copyright (C) 2007 John Wiley & Sons, Ltd.
In monitoring a clinical trial or other observational study with a survivalendpoint, sometimes the numbers of patients entering and dying at each time point are presented, butthe connections between them are kept conf...
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In monitoring a clinical trial or other observational study with a survivalendpoint, sometimes the numbers of patients entering and dying at each time point are presented, butthe connections between them are kept confidential. Hence, the exact time to failure or censoringfor each individual is missing. We refer to such a study monitoring table with missing pairinginformation between the entry and death times as a 'broken' survival data set. In this paper westudy the problem of estimating the survival distribution from a broken survival data set. We havedeveloped two methods, likelihood-based estimation and self-consistency estimation, to estimate thesurvival curve parametrically and empirically, respectively. We use simulations to study theproperties of these methods, and illustrate them with data from the STELLAR-3 trial.
Introduction: Generalized anxiety disorder (GAD) is a chronic illness with psychic and somatic symptoms that do not respond uniformly in the first weeks of treatment. Methods: A post-hoc analysis of pooled data from f...
Introduction: Generalized anxiety disorder (GAD) is a chronic illness with psychic and somatic symptoms that do not respond uniformly in the first weeks of treatment. Methods: A post-hoc analysis of pooled data from five placebo-controlled, double-blind, randomized studies in non-depressed GAD patients treated with venlafaxine extended release (ER) or placebo was performed to determine the temporal response of psychic and somatic symptoms to treatment over 8 weeks. Two of the studies included extension phases of up to 6 months, the results of which were also analyzed here. Results:The earliest symptoms to respond included both psychic symptoms (anxious mood, tension, behavior at interview) and somatic muscular, cardiovascular, and respiratory symptoms. The last symptoms to respond included the psychic symptoms of insomnia and fear and the somatic sensory, gastrointestinal and autonomic symptoms, perhaps in part because of drug-related side effects. Continuing treatment beyond 8 weeks in venlafaxine ER responders for up to 6 months of total treatment results not only in additional improvement in early-responding symptoms, but also in the improvement of late-responding symptoms, perhaps due in part to the development of tolerance to antidepressant side effects. Conclusion: Serious consideration should be given to maintaining partial responders to venlafaxine ER treatment on the same treatment for >= 3-6 months.
Subgroup analysis is an important part in the design and analysis of clinical trials. The importance arises from the scientific and commercial implications of such analysis. The predominant concerns about subgroup ana...
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Subgroup analysis is an important part in the design and analysis of clinical trials. The importance arises from the scientific and commercial implications of such analysis. The predominant concerns about subgroup analysis related to the increased false-positive and false-negative rates. Much of the existing literature on subgroup analysis focuses on the former. In this article, we will concentrate on the false-negative aspect. Using theoretical derivation and simulations, we investigate factors that affect the probability of observing at least one negative subgroup result (ie, numerically negative treatment effect estimate) even though the true treatment effect is positive (ie, the new treatment is more efficacious than the comparator) and homogeneous across all subgroups. This probability, conditioning or unconditioning on a statistically significant overall treatment effect, is assessed for design scenarios that are commonly encountered in practice. In additions, we assess the probability of observing at least one statistically significant negative sub-group result, again conditioning or unconditioning on a statistically significant overall treatment effect. We submit that knowledge of such probabilities could provide clinical researchers with insight into the reliability of subgroup results and help set proper expectations vis-a-vis such analysis. The later facilitates a balanced interpretation of subgroup results.
Background: Vaginal atrophy (VA) is a prevalent disorder in postmenopausal women that is characterized by decreased epithelial thickness, reduced vaginal maturation index (VMl) and increased vaginal pH. Current medica...
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Background: Vaginal atrophy (VA) is a prevalent disorder in postmenopausal women that is characterized by decreased epithelial thickness, reduced vaginal maturation index (VMl) and increased vaginal pH. Current medical therapy consists of local or systemic replacement of estrogens. Objective: The Goal of this study was to understand, at a molecular level, the effect of estradiol (E2) on the vaginal epithelium. Methods: Nineteen women were treated with E2 delivered through a skin patch at a dose of 0.05 mg/day for 12 weeks. The diagnosis of VA was confirmed by a VMI with <= 5% superficial cells and vaginal pH > 5.0. Vaginal biopsy samples were collected at baseline and after treatment. Differentially expressed mRNA transcripts in these biopsies were determined by microarray analysis. Results: All 19 subjects had increased VMI (> 5%) and/or reduced pH (<= 5) following treatment. Most subjects also had increased serum E2 levels and reduced serum FSH levels. Transcriptional profiling of vaginal biopsies identified over 3000 E2-regulated Genes, including those involved in several key pathways known to regulate cell growth and proliferation, barrier function and pathogen defense. Conclusions: E2 controls a plethora of cellular pathways that are concordant with its profound effect on vaginal physiology. The data presented here are a useful step toward understanding the role of E2 in vaginal tissue and the development of novel therapeutics for the treatment of VA. (c) 2007 Elsevier Ireland Ltd. All rights reserved.
Objective: Wait times for cancer surgery in Ontario have increased over the last decade. We reviewed trends in wait times for endometrial cancer surgery from 1996 to 2000 and identified determinants that may need to b...
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Objective: Wait times for cancer surgery in Ontario have increased over the last decade. We reviewed trends in wait times for endometrial cancer surgery from 1996 to 2000 and identified determinants that may need to be addressed in order to reduce these wait times. Methods: The study population included women diagnosed with endometrial cancer (ICD-9 codes 179 or 182) prior to surgery. Surgical wait time was defined as the interval between date of diagnosis and hospital admission for surgery. Univariate analyses assessed demographic, treatment, and hospital factors associated with wait times. A multilevel linear regression model was created to account for clustering of patients at the hospital level and regional level defined by local health integration networks (LHINs). Effects of covariates were expressed as estimates of the median proportional change in wait time. Results: There were 2042 cases in this analysis. Mean wait time increased from 32 to 40 days (P = 0.0012). Prolonged wait times were associated with age > 70 years, presence of comorbidities, and surgery performed at a teaching hospital and by a gynaecologic oncologist. Wait times were not associated with income level or region of residence defined by LHIN. Conclusion: Wait times for endometrial cancer surgery have increased significantly in Ontario. Determinants of these prolonged wait times need to be addressed, and criteria for referral to a teaching hospital and gynaecologic oncologist should be developed to ensure that local health integration networks provide equal and timely access to care.
In this article, we give a general definition of adaptive designs, describe their structure, and provide a classification of adaptive designs, mapping them against the drug development process.
In this article, we give a general definition of adaptive designs, describe their structure, and provide a classification of adaptive designs, mapping them against the drug development process.
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