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Biomedical subjects

Tim Friede

Publications and source records attributed to Tim Friede.

11 recordsLinked to original sources
PubMed2007

Planning and analysis of three-arm non-inferiority trials with binary endpoints.

Three-arm trials including an experimental treatment, an active control and a placebo group are frequently preferred for the assessment of non-inferiority. In contrast to two-arm non-inferiority studies, these designs allow a direct proof of efficacy of a new treatment by comparison with placebo. As a further advantage, the test problem for establishing non-inferiority can be formulated in such a way that rejection of the null hypothesis assures that a pre-defined portion of the (unknown) effect the reference shows versus placebo is preserved by the treatment under investigation. We present statistical methods for this study design and the situation of a binary outcome variable. Asymptotic test procedures are given and their actual type I error rates are calculated. Approximate sample size formulae are derived and their accuracy is discussed. Furthermore, the question of optimal allocation of the total sample size is considered. Power properties of the testing strategy including a pre-test for assay sensitivity are presented. The derived methods are illustrated by application to a clinical trial in depression.

Controlled Clinical Trials as Topic↗
PubMed2006

Sample size recalculation in internal pilot study designs: a review.

The adequacy of sample size is important to clinical trials. In the planning phase of a trial, however, the investigators are often quite uncertain about the sizes of parameters which are needed for sample size calculations. A solution to this problem is mid-course recalculation of the sample size during the ongoing trial. In internal pilot study designs, nuisance parameters are estimated on the basis of interim data and the sample size is adjusted accordingly. This review attempts to give an overview on the available methods. It is written not only for biometricians who are already familar with the the topic and wish to update their knowledge but also for users new to the subject.

Clinical Trials as Topic↗
PubMed2005

Randomized, controlled trial of cannabis-based medicine in central pain in multiple sclerosis.

BACKGROUND: Central pain in multiple sclerosis (MS) is common and often refractory to treatment. METHODS: We conducted a single-center, 5-week (1-week run-in, 4-week treatment), randomized, double-blind, placebo-controlled, parallel-group trial in 66 patients with MS and central pain states (59 dysesthetic, seven painful spasms) of a whole-plant cannabis-based medicine (CBM), containing delta-9-tetrahydrocannabinol:cannabidiol (THC:CBD) delivered via an oromucosal spray, as adjunctive analgesic treatment. Each spray delivered 2.7 mg of THC and 2.5 of CBD, and patients could gradually self-titrate to a maximum of 48 sprays in 24 hours. RESULTS: Sixty-four patients (97%) completed the trial, 34 received CBM. In week 4, the mean number of daily sprays taken of CBM (n = 32) was 9.6 (range 2 to 25, SD = 6.0) and of placebo (n = 31) was 19.1 (range 1 to 47, SD = 12.9). Pain and sleep disturbance were recorded daily on an 11-point numerical rating scale. CBM was superior to placebo in reducing the mean intensity of pain (CBM mean change -2.7, 95% CI: -3.4 to -2.0, placebo -1.4 95% CI: -2.0 to -0.8, comparison between groups, p = 0.005) and sleep disturbance (CBM mean change -2.5, 95% CI: -3.4 to -1.7, placebo -0.8, 95% CI: -1.5 to -0.1, comparison between groups, p = 0.003). CBM was generally well tolerated, although more patients on CBM than placebo reported dizziness, dry mouth, and somnolence. Cognitive side effects were limited to long-term memory storage. CONCLUSIONS: Cannabis-based medicine is effective in reducing pain and sleep disturbance in patients with multiple sclerosis related central neuropathic pain and is mostly well tolerated.

Administration, Oral↗
PubMed2005

Effect of the left internal mammary artery to the left anterior descending artery on mortality and morbidity after combined coronary and valve operations.

BACKGROUND: The effect of using the left internal mammary artery in combined coronary and valve operations have not been fully investigated. We aimed to quantify the impact of the left internal mammary artery to the left anterior descending artery on early and mid-term outcomes in these patients. METHODS: Data was collected prospectively on 630 consecutive patients who underwent revascularization of the left anterior descending artery with concomitant valve operations between April 1997 and March 2003. Multivariate logistic regression and Cox proportional hazards analyses were used to adjust in-hospital outcomes and Kaplan-Meier survival curves. A propensity score for left internal mammary artery use was constructed to control for selection bias. RESULTS: The left internal mammary artery was used in 478 (75.9%) patients. Univariate analyses found left internal mammary artery patients had significantly lower in-hospital mortality (6.3% versus 13.2%; p < 0.01) and postoperative renal failure (8.2% versus 13.8%; p = 0.038). After adjusting for treatment selection bias, in-hospital mortality (adjusted odds ratio, 0.77; p = 0.45) and renal failure (adjusted odds ratio, 0.94; p = 0.86) were no longer significantly different. A total of 171 (27.1%) deaths occurred during the follow-up, with a total follow-up of 2,325 patient-years. The crude relative risk for the left internal mammary artery was 0.67 (p = 0.015). After adjusting for the propensity score, the adjusted relative risk was 0.91 (p = 0.62). CONCLUSIONS: The left internal mammary artery does not adversely affect the short-term and medium-term outcomes in patients undergoing concomitant coronary and valve operations. Survival at 7 years was similar with or without the use of the left internal mammary artery.

Aged↗
PubMed2005

Pro-active call center treatment support (PACCTS) to improve glucose control in type 2 diabetes: a randomized controlled trial.

OBJECTIVE: To determine whether Pro-Active Call Center Treatment Support (PACCTS), using trained nonmedical telephonists supported by specially designed software and a diabetes nurse, can effectively improve glycemic control in type 2 diabetes. RESEARCH DESIGN AND METHODS: A randomized controlled implementation trial of 1-year duration was conducted in Salford, U.K. The trial comprised 591 randomly selected individuals with type 2 diabetes. By random allocation, 197 individuals were assigned to the usual care (control) group and 394 to the PACCTS (intervention) group. Lifestyle advice and drug treatment in both groups followed local guidelines. PACCTS patients were telephoned according to a protocol with the frequency of calls proportional to the last HbA(1c) level. The primary outcome was absolute reduction in HbA(1c), and the secondary outcome was the proportion of patients reducing HbA(1c) by at least 1%. RESULTS: A total of 332 patients (84%) in the PACCTS group and 176 patients (89%) in the control group completed the study. Final HbA(1c) values were available in 374 patients (95%) in the PACCTS group and 180 patients (92%) in the usual care group. Compared with usual care, HbA(1c) improved by 0.31% (95% CI 0.11-0.52, P = 0.003) overall in the PACCTS patients. For patients with baseline HbA(1c) >7%, the improvement increased to 0.49% (0.21-0.77, P < 0.001), whereas in patients with baseline HbA(1c) <7% there was no change. The difference in the proportions of patients achieving a >/=1% reduction in HbA(1c) significantly favored the PACCTS intervention: 10% (4-16, P < 0.001) overall and 15% (7-24, P < 0.001) for patients with baseline HbA(1c) >7%. CONCLUSIONS: In an urban Caucasian trial population with blood glucose HbA(1c) >7%, PACCTS facilitated significant improvement in glycemic control. Further research should extend the validity of findings to rural communities and other ethnic groups, as well as to smoking and lipid and blood pressure control.

Adult↗
PubMed2004

Power and sample size determination when assessing the clinical relevance of trial results by 'responder analyses'.

A fundamental issue in regulatory decision making is the assessment of the benefit/risk profile of a compound. In order to do this, establishing the existence of a treatment effect by a significance test is not sufficient, but the clinical relevance of a potential benefit must also be taken into account. A number of regulatory guidelines propose that clinical relevance should be assessed by considering the rate of responders, i.e. the proportion of patients who are observed to achieve an apparently meaningful benefit. In this paper, we present methods for planning clinical trials that aim at demonstrating both statistical and clinical significance in superiority trials. Procedures based on analytical calculations are derived for normally distributed data and the case of a single endpoint as well as multiple primary outcomes. A bootstrap procedure is proposed that can be applied to non-normal data. Application is illustrated by a clinical trial in Alzheimer's disease.

Activities of Daily Living↗
PubMed2003

Intervention effects in observational survival studies with an application in total hip replacements.

Time to revision is a common and clinically relevant endpoint for studies of patients with total hip replacement. Because failures occur rarely within the first years after replacement, new surgical techniques and materials are often implemented without evidence of their effectiveness from randomized trials. Observational data may be available but this relies on the use of historical controls which has been heavily criticized. Instead the use of changepoint methods has been suggested to detect changes caused by successfully implemented interventions. In the setting of a proportional hazards model we develop a semi-parametric changepoint method to detect changes in baseline hazard. The procedure is motivated by and applied to a clinical study in patients with total hip replacements, where the effect of a new cement type is of interest. Power properties of the proposed method are investigated.

Adult↗
PubMed2003

Simple procedures for blinded sample size adjustment that do not affect the type I error rate.

For normally distributed data, determination of the appropriate sample size requires a knowledge of the variance. Because of the uncertainty in the planning phase, two-stage procedures are attractive where the variance is reestimated from a subsample and the sample size is adjusted if necessary. From a regulatory viewpoint, preserving blindness and maintaining the ability to calculate or control the type I error rate are essential. Recently, a number of proposals have been made for sample size adjustment procedures in the t-test situation. Unfortunately, none of these methods satisfy both these requirements. We show through analytical computations that the type I error rate of the t-test is not affected if simple blind variance estimators are used for sample size recalculation. Furthermore, the results for the expected power of the procedures demonstrate that the methods are effective in ensuring the desired power even under initial misspecification of the variance. A method is discussed that can be applied in a more general setting and that assumes analysis with a permutation test. This procedure maintains the significance level for any design situation and arbitrary blind sample size recalculation strategy.

Anxiety Disorders↗
PubMed2003

Blinded sample size reassessment in non-inferiority and equivalence trials.

Even in situations where the design and conduct of clinical trials is highly standardized, there may be a considerable between-study variation in the observed variability of the primary outcome variable. As a consequence, performing a study in a fixed sample size design implies a considerable risk of resulting in a too high or too low sample size. This difficulty can be alleviated by applying a design with internal pilot study. After a provisional sample size calculation in the planning stage, a portion of the planned sample is recruited and the sample size is recalculated on the basis of the observed variability. To comply with the requirement of some regulatory guidelines only blinded data should be used for the reassessment procedure. Furthermore, the effect on the type I error rate should be quantified. The current literature presents analytical results on the actual level in the t-test situation only for superiority trials. In these situations, blinded sample size recalculation does not lead to an inflation of the type I error rate. We extended the methodology to non-inferiority and equivalence trials with normally distributed outcome variable and hypotheses formulated in terms of the ratio and difference of means. Surprisingly, in contrast to the case of testing superiority, we observed actual type I error rates above the nominal level. The extent of inflation depends on the required sample size, the sample size of the internal pilot study, and the standardized equivalence or non-inferiority margin. It turned out that the elevation of the significance level is negligible for most practical situations. Nevertheless, the consequences of sample size reassessment have to be discussed case by case and regulatory concerns with respect to the actual size of the procedure cannot generally be refuted by referring to the fact that only blinded data were used.

Asthma↗
PubMed2002

On the inappropriateness of an EM algorithm based procedure for blinded sample size re-estimation.

When planning a clinical trial the sample size calculation is commonly based on an a priori estimate of the variance of the outcome variable. Misspecification of the variance can have substantial impact on the power of the trial. It is therefore attractive to update the planning assumptions during the ongoing trial using an internal estimate of the variance. For this purpose, an EM algorithm based procedure for blinded variance estimation was proposed for normally distributed data. Various simulation studies suggest a number of appealing properties of this procedure. In contrast, we show that (i) the estimates provided by this procedure depend on the initialization, (ii) the stopping rule used is inadequate to guarantee that the algorithm converges against the maximum likelihood estimator, and (iii) the procedure corresponds to the special case of simple randomization which, however, in clinical trials is rarely applied. Further, we show that maximum likelihood estimation leads to no reasonable results for blinded sample size re-estimation due to bias and high variability. The problem is illustrated by a clinical trial in asthma.

Administration, Inhalation↗