A practical comparison of blinded methods for sample size reviews in survival data clinical trials.

This paper presents practical approaches to the problem of sample size re-estimation in the case of clinical trials with survival data when proportional hazards can be assumed. When data are readily available at the time of the review, on a full range of survival experiences across the recruited patients, it is shown that, as expected, performing a blinded re-estimation procedure is straightforward and can help to maintain the trial's pre-specified error rates. Two alternative methods for dealing with the situation where limited survival experiences are available at the time of the sample size review are then presented and compared. In this instance, extrapolation is required in order to undertake the sample size re-estimation. Worked examples, together with results from a simulation study are described. It is concluded that, as in the standard case, use of either extrapolation approach successfully protects the trial error rates. Copyright © 2012 John Wiley & Sons, Ltd.

Normative modeling for personalized clinical pathway using organizational semiotics methods

Clinical pathways are widely adopted by many large hospitals around the world in order to provide high-quality patient treatment and reduce the length and cost of hospital stay. However, nowadays most of them are static and nonpersonalized. Our objective is to capture and represent clinical pathway using organizational semiotics method including Semantic Analysis which determines semantic units in clinical pathway, their relationship and their patterns of behavior, and Norm Analysis which extracts and specifies the norms that establish how and when these medical behaviors will occur. Finally, we propose a method to develop clinical pathway ontology based on the results of Semantic Analysis and Norm analysis. This approach will give a contribution to design personalized clinical pathway by defining a set of possible patterns of behavior and theClinical pathways are widely adopted by many large hospitals around the world in order to provide high-quality patient treatment and reduce the length and cost of hospital stay. However, nowadays most of them are static and nonpersonalized. Our objective is to capture and represent clinical pathway using organizational semiotics method including Semantic Analysis which determines semantic units in clinical pathway, their relationship and their patterns of behavior, and Norm Analysis which extracts and specifies the norms that establish how and when these medical behaviors will occur. Finally, we propose a method to develop clinical pathway ontology based on the results of Semantic Analysis and Norm analysis. This approach will give a contribution to design personalized clinical pathway by defining a set of possible patterns of behavior and the norms that govern the behavior based on patient’s condition.

A comparison of methods for constructing confidence intervals after phase II/III clinical trials

Recently, in order to accelerate drug development, trials that use adaptive seamless designs such as phase II/III clinical trials have been proposed. Phase II/III clinical trials combine traditional phases II and III into a single trial that is conducted in two stages. Using stage 1 data, an interim analysis is performed to answer phase II objectives and after collection of stage 2 data, a final confirmatory analysis is performed to answer phase III objectives. In this paper we consider phase II/III clinical trials in which, at stage 1, several experimental treatments are compared to a control and the apparently most effective experimental treatment is selected to continue to stage 2. Although these trials are attractive because the confirmatory analysis includes phase II data from stage 1, the inference methods used for trials that compare a single experimental treatment to a control and do not have an interim analysis are no longer appropriate. Several methods for analysing phase II/III clinical trials have been developed. These methods are recent and so there is little literature on extensive comparisons of their characteristics. In this paper we review and compare the various methods available for constructing confidence intervals after phase II/III clinical trials.

A comparison of methods for treatment selection in seamless phase II/III clinical trials incorporating information on short-term endpoints

In an adaptive seamless phase II/III clinical trial interim analysis, data are used for treatment selection, enabling resources to be focused on comparison of more effective treatment(s) with a control. In this paper, we compare two methods recently proposed to enable use of short-term endpoint data for decision-making at the interim analysis. The comparison focuses on the power and the probability of correctly identifying the most promising treatment. We show that the choice of method depends on how well short-term data predict the best treatment, which may be measured by the correlation between treatment effects on short- and long-term endpoints.

Treatment of written verb and written sentence production in an individual with aphasia: A clinical study

Background: Although the efficacy of treatments for spoken verb and sentence production deficits in aphasia has been documented widely, less is known about interventions for written verb and written sentence production deficits. Aims: This study documents a treatment aiming to improve production of (a) written subject-verb sentences (involving intransitive verbs) and (b) written subject-verb-object sentences (involving transitive verbs). Methods & Procedures: The participant, a 63-year-old female aphasic speaker, had a marked language comprehension deficit, apraxia of speech, relatively good spelling abilities, and no hemiplegia. The treatment involved intransitive verbs producing subject-verb active sentences and transitive verbs producing subject-verb-object active non-reversible sentences. The treatment was undertaken in the context of current UK clinical practice. Outcomes & Results: Statistical improvements were noted for the trained sets of verbs and sentences. Other improvements were also noted in LW's ability to retrieve some non-treated verbs and construct written sentences. Treatment did not generalise to sentence comprehension and letter spelling to dictation. Conclusions: Our participant's ability to write verbs and sentences improved as a result of the treatment.

Statistical methods for examining genetic influences of resistance to anti-epileptic drugs

It is generally accepted that genetics may be an important factor in explaining the variation between patients’ responses to certain drugs. However, identification and confirmation of the responsible genetic variants is proving to be a challenge in many cases. A number of difficulties that maybe encountered in pursuit of these variants, such as non-replication of a true effect, population structure and selection bias, can be mitigated or at least reduced by appropriate statistical methodology. Another major statistical challenge facing pharmacogenetics studies is trying to detect possibly small polygenic effects using large volumes of genetic data, while controlling the number of false positive signals. Here we review statistical design and analysis options available for investigations of genetic resistance to anti-epileptic drugs.

A randomised controlled trial of cognitive behaviour therapy for psychosis in a routine clinical service

Objective: To evaluate CBTp delivered by non-expert therapists, using CBT relevant measures. Methods: Participants (N=74) were randomised into immediate therapy or waiting list control groups. The therapy group was offered six months of therapy and followed up three months later. The waiting list group received therapy after waiting nine months (becoming the delayed therapy group). Results: Depression improved in the combined therapy group at both the end of therapy and follow-up. Other significant effects were found in only one of the two therapy groups (positive symptoms; cognitive flexibility; uncontrollability of thoughts) or one of the two timepoints (end of therapy: PANSS general symptoms, anxiety, suicidal ideation, social functioning, resistance to voices; follow-up: power beliefs about voices, negative symptoms). There was no difference in costs between the groups. Conclusions: The only robust improvement was in depression. Nevertheless, there were further encouraging but modest improvements in both emotional and cognitive variables, in addition to psychotic symptoms.

Clinical and subclinical mastitis in smallholder dairy farms in Tanzania: Risk, intervention and knowledge transfer

In a cross-sectional study of 400 randomly selected smallholder dairy farms in the Tanga and Iringa regions of Tanzania, 14.2% (95% confidence interval (CI) = 11.6-17.3) of cows had developed clinical mastitis during the previous year. The point prevalence of subclinical mastitis, defined as a quarter positive by the California Mastitis Test (CMT) or by bacteriological culture, was 46.2% (95% Cl = 43.6-48.8) and 24.3% (95% Cl = 22.2-26.6), respectively. In a longitudinal disease study in Iringa, the incidence of clinical mastitis was 31.7 cases per 100 cow-years. A randomised intervention trial indicated that intramammary antibiotics significantly reduced the proportion of bacteriologically positive quarters in the short-term (14 days post-infusion) but teat dipping had no detectable effect on bacteriological infection and CMT positive quarters. Other risk and protective factors were identified from both the cross-sectional and longitudinal included animals with Boran breeding (odds ratio (OR) = 3,40, 95% CI = 1.00-11.57, P < 0.05 for clinical mastitis, and OR = 3.51, 95% CI = 1.299.55, P < 0.01 for a CMT positive quarter), while the practice of residual calf suckling was protective for a bacteriologically positive quarter (OR = 0.63, 95% Cl = 0.48-0.81, P <= 0.001) and for a CMT positive quarter (OR = 0.69, 95% Cl = 0.63-0.75, P < 0.001). A mastitis training course for farmers and extension officers was held, and the knowledge gained and use of different methods of dissemination were assessed over time. In a subsequent randomised controlled trial, there were strong associations between knowledge gained and both the individual question asked and the combination of dissemination methods (village meeting, video and handout) used. This study demonstrated that both clinical and subclinical mastitis is common in smallholder dairying in Tanzania, and that some of the risk and protective factors for mastitis can be addressed by practical management of dairy cows following effective knowledge transfer. (c) 2006 Elsevier B.V. All rights reserved.

Clinical and subclinical mastitis in smallholder dairy farms in Tanzania: Risk, intervention and knowledge transfer

In a cross-sectional study of 400 randomly selected smallholder dairy farms in the Tanga and Iringa regions of Tanzania, 14.2% (95% confidence interval (CI) = 11.6-17.3) of cows had developed clinical mastitis during the previous year. The point prevalence of subclinical mastitis, defined as a quarter positive by the California Mastitis Test (CMT) or by bacteriological culture, was 46.2% (95% Cl = 43.6-48.8) and 24.3% (95% Cl = 22.2-26.6), respectively. In a longitudinal disease study in Iringa, the incidence of clinical mastitis was 31.7 cases per 100 cow-years. A randomised intervention trial indicated that intramammary antibiotics significantly reduced the proportion of bacteriologically positive quarters in the short-term (14 days post-infusion) but teat dipping had no detectable effect on bacteriological infection and CMT positive quarters. Other risk and protective factors were identified from both the cross-sectional and longitudinal included animals with Boran breeding (odds ratio (OR) = 3,40, 95% CI = 1.00-11.57, P < 0.05 for clinical mastitis, and OR = 3.51, 95% CI = 1.299.55, P < 0.01 for a CMT positive quarter), while the practice of residual calf suckling was protective for a bacteriologically positive quarter (OR = 0.63, 95% Cl = 0.48-0.81, P <= 0.001) and for a CMT positive quarter (OR = 0.69, 95% Cl = 0.63-0.75, P < 0.001). A mastitis training course for farmers and extension officers was held, and the knowledge gained and use of different methods of dissemination were assessed over time. In a subsequent randomised controlled trial, there were strong associations between knowledge gained and both the individual question asked and the combination of dissemination methods (village meeting, video and handout) used. This study demonstrated that both clinical and subclinical mastitis is common in smallholder dairying in Tanzania, and that some of the risk and protective factors for mastitis can be addressed by practical management of dairy cows following effective knowledge transfer. (c) 2006 Elsevier B.V. All rights reserved.

An adaptive approach to implementing bivariate group sequential clinical trial designs

In clinical trials, situations often arise where more than one response from each patient is of interest; and it is required that any decision to stop the study be based upon some or all of these measures simultaneously. Theory for the design of sequential experiments with simultaneous bivariate responses is described by Jennison and Turnbull (Jennison, C., Turnbull, B. W. (1993). Group sequential tests for bivariate response: interim analyses of clinical trials with both efficacy and safety endpoints. Biometrics 49:741-752) and Cook and Farewell (Cook, R. J., Farewell, V. T. (1994). Guidelines for monitoring efficacy and toxicity responses in clinical trials. Biometrics 50:1146-1152) in the context of one efficacy and one safety response. These expositions are in terms of normally distributed data with known covariance. The methods proposed require specification of the correlation, ρ between test statistics monitored as part of the sequential test. It can be difficult to quantify ρ and previous authors have suggested simply taking the lowest plausible value, as this will guarantee power. This paper begins with an illustration of the effect that inappropriate specification of ρ can have on the preservation of trial error rates. It is shown that both the type I error and the power can be adversely affected. As a possible solution to this problem, formulas are provided for the calculation of correlation from data collected as part of the trial. An adaptive approach is proposed and evaluated that makes use of these formulas and an example is provided to illustrate the method. Attention is restricted to the bivariate case for ease of computation, although the formulas derived are applicable in the general multivariate case.

Sequential designs for phase III clinical trials incorporating treatment selection

Most statistical methodology for phase III clinical trials focuses on the comparison of a single experimental treatment with a control. An increasing desire to reduce the time before regulatory approval of a new drug is sought has led to development of two-stage or sequential designs for trials that combine the definitive analysis associated with phase III with the treatment selection element of a phase II study. In this paper we consider a trial in which the most promising of a number of experimental treatments is selected at the first interim analysis. This considerably reduces the computational load associated with the construction of stopping boundaries compared to the approach proposed by Follman, Proschan and Geller (Biometrics 1994; 50: 325-336). The computational requirement does not exceed that for the sequential comparison of a single experimental treatment with a control. Existing methods are extended in two ways. First, the use of the efficient score as a test statistic makes the analysis of binary, normal or failure-time data, as well as adjustment for covariates or stratification straightforward. Second, the question of trial power is also considered, enabling the determination of sample size required to give specified power. Copyright © 2003 John Wiley & Sons, Ltd.

Incorporating data received after a sequential trial has stopped into the final analysis: implementation and comparison of methods

In a sequential clinical trial, accrual of data on patients often continues after the stopping criterion for the study has been met. This is termed “overrunning.” Overrunning occurs mainly when the primary response from each patient is measured after some extended observation period. The objective of this article is to compare two methods of allowing for overrunning. In particular, simulation studies are reported that assess the two procedures in terms of how well they maintain the intended type I error rate. The effect on power resulting from the incorporation of “overrunning data” using the two procedures is evaluated.

Meta-analysis of individual patient data from randomised trials: a review of methods used in practice

Background: Meta-analyses based on individual patient data (IPD) are regarded as the gold standard for systematic reviews. However, the methods used for analysing and presenting results from IPD meta-analyses have received little discussion. Methods We review 44 IPD meta-analyses published during the years 1999–2001. We summarize whether they obtained all the data they sought, what types of approaches were used in the analysis, including assumptions of common or random effects, and how they examined the effects of covariates. Results: Twenty-four out of 44 analyses focused on time-to-event outcomes, and most analyses (28) estimated treatment effects within each trial and then combined the results assuming a common treatment effect across trials. Three analyses failed to stratify by trial, analysing the data is if they came from a single mega-trial. Only nine analyses used random effects methods. Covariate-treatment interactions were generally investigated by subgrouping patients. Seven of the meta-analyses included data from less than 80% of the randomized patients sought, but did not address the resulting potential biases. Conclusions: Although IPD meta-analyses have many advantages in assessing the effects of health care, there are several aspects that could be further developed to make fuller use of the potential of these time-consuming projects. In particular, IPD could be used to more fully investigate the influence of covariates on heterogeneity of treatment effects, both within and between trials. The impact of heterogeneity, or use of random effects, are seldom discussed. There is thus considerable scope for enhancing the methods of analysis and presentation of IPD meta-analysis.