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.

Active-control trials with binary data: a comparison of methods for testing superiority or non-inferiority using the odds ratio

This paper considers methods for testing for superiority or non-inferiority in active-control trials with binary data, when the relative treatment effect is expressed as an odds ratio. Three asymptotic tests for the log-odds ratio based on the unconditional binary likelihood are presented, namely the likelihood ratio, Wald and score tests. All three tests can be implemented straightforwardly in standard statistical software packages, as can the corresponding confidence intervals. Simulations indicate that the three alternatives are similar in terms of the Type I error, with values close to the nominal level. However, when the non-inferiority margin becomes large, the score test slightly exceeds the nominal level. In general, the highest power is obtained from the score test, although all three tests are similar and the observed differences in power are not of practical importance. Copyright (C) 2007 John Wiley & Sons, Ltd.

Comparison of methods for analysis of proteolysis by plasmin in milk

Sensitive methods that are currently used to monitor proteolysis by plasmin in milk are limited due to 7 their high cost and lack of standardisation for quality assurance in the various dairy laboratories. In 8 this study, four methods, trinitrobenzene sulphonic acid (TNBS), reverse phase high pressure liquid 9 chromatography (RP-HPLC), gel electrophoresis and fluorescamine, were selected to assess their 10 suitability for the detection of proteolysis in milk by plasmin. Commercial UHT milk was incubated 11 with plasmin at 37 °C for one week. Clarification was achieved by isoelectric precipitation (pH 4·6 12 soluble extracts)or 6% (final concentration) trichloroacetic acid (TCA). The pH 4·6 and 6% TCA 13 soluble extracts of milk showed high correlations (R2 > 0·93) by the TNBS, fluorescamine and 14 RP-HPLC methods, confirming increased proteolysis during storage. For gel electrophoresis,15 extensive proteolysis was confirmed by the disappearance of α- and β-casein bands on the seventh 16 day, which was more evident in the highest plasmin concentration. This was accompanied by the 17 appearance of α- and β-casein proteolysis products with higher intensities than on previous days, 18 implying that more products had been formed as a result of casein breakdown. The fluorescamine 19 method had a lower detection limit compared with the other methods, whereas gel electrophoresis 20 was the best qualitative method for monitoring β-casein proteolysis products. Although HPLC was the 21 most sensitive, the TNBS method is recommended for use in routine laboratory analysis on the basis 22 of its accuracy, reliability and simplicity.

Automatic keyphrase extraction: a comparison of methods

There are many published methods available for creating keyphrases for documents. Previous work in the field has shown that in a significant proportion of cases author selected keyphrases are not appropriate for the document they accompany. This requires the use of such automated methods to improve the use of keyphrases. Often the keyphrases are not updated when the focus of a paper changes or include keyphrases that are more classificatory than explanatory. The published methods are all evaluated using different corpora, typically one relevant to their field of study. This not only makes it difficult to incorporate the useful elements of algorithms in future work but also makes comparing the results of each method inefficient and ineffective. This paper describes the work undertaken to compare five methods across a common baseline of six corpora. The methods chosen were term frequency, inverse document frequency, the C-Value, the NC-Value, and a synonym based approach. These methods were compared to evaluate performance and quality of results, and to provide a future benchmark. It is shown that, with the comparison metric used for this study Term Frequency and Inverse Document Frequency were the best algorithms, with the synonym based approach following them. Further work in the area is required to determine an appropriate (or more appropriate) comparison metric.

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.

Intercomparison of methods of coupling between convection and large-scale circulation: 1. Comparison over uniform surface conditions

As part of an international intercomparison project, a set of single column models (SCMs) and cloud-resolving models (CRMs) are run under the weak temperature gradient (WTG) method and the damped gravity wave (DGW) method. For each model, the implementation of the WTG or DGW method involves a simulated column which is coupled to a reference state defined with profiles obtained from the same model in radiative-convective equilibrium. The simulated column has the same surface conditions as the reference state and is initialized with profiles from the reference state. We performed systematic comparison of the behavior of different models under a consistent implementation of the WTG method and the DGW method and systematic comparison of the WTG and DGW methods in models with different physics and numerics. CRMs and SCMs produce a variety of behaviors under both WTG and DGW methods. Some of the models reproduce the reference state while others sustain a large-scale circulation which results in either substantially lower or higher precipitation compared to the value of the reference state. CRMs show a fairly linear relationship between precipitation and circulation strength. SCMs display a wider range of behaviors than CRMs. Some SCMs under the WTG method produce zero precipitation. Within an individual SCM, a DGW simulation and a corresponding WTG simulation can produce different signed circulation. When initialized with a dry troposphere, DGW simulations always result in a precipitating equilibrium state. The greatest sensitivities to the initial moisture conditions occur for multiple stable equilibria in some WTG simulations, corresponding to either a dry equilibrium state when initialized as dry or a precipitating equilibrium state when initialized as moist. Multiple equilibria are seen in more WTG simulations for higher SST. In some models, the existence of multiple equilibria is sensitive to some parameters in the WTG calculations.

Evaluation of methods of detecting cell reactive oxygen species production for drug screening and cell cycle studies

Intracellular reactive oxygen species (ROS) production is essential to normal cell function. However, excessive ROS production causes oxidative damage and cell death. Many pharmacological compounds exert their effects on cell cycle progression by changing intracellular redox state and in many cases cause oxidative damage leading to drug cytotoxicity. Appropriate measurement of intracellular ROS levels during cell cycle progression is therefore crucial in understanding redox-regulation of cell function and drug toxicity and for the development of new drugs. However, due to the extremely short half-life of ROS, measuring the changes in intracellular ROS levels during a particular phase of cell cycle for drug intervention can be challenging. In this article, we have provided updated information on the rationale, the applications, the advantages and limitations of common methods for screening drug effects on intracellular ROS production linked to cell cycle study. Our aim is to facilitate biomedical scientists and researchers in the pharmaceutical industry in choosing or developing specific experimental regimens to suit their research needs.

Intercomparison of methods of coupling between convection and large-scale circulation. 2: Comparison over non-uniform surface conditions

As part of an international intercomparison project, the weak temperature gradient (WTG) and damped gravity wave (DGW) methods are used to parameterize large-scale dynamics in a set of cloud-resolving models (CRMs) and single column models (SCMs). The WTG or DGW method is implemented using a configuration that couples a model to a reference state defined with profiles obtained from the same model in radiative-convective equilibrium. We investigated the sensitivity of each model to changes in SST, given a fixed reference state. We performed a systematic comparison of the WTG and DGW methods in different models, and a systematic comparison of the behavior of those models using the WTG method and the DGW method. The sensitivity to the SST depends on both the large-scale parameterization method and the choice of the cloud model. In general, SCMs display a wider range of behaviors than CRMs. All CRMs using either the WTG or DGW method show an increase of precipitation with SST, while SCMs show sensitivities which are not always monotonic. CRMs using either the WTG or DGW method show a similar relationship between mean precipitation rate and column-relative humidity, while SCMs exhibit a much wider range of behaviors. DGW simulations produce large-scale velocity profiles which are smoother and less top-heavy compared to those produced by the WTG simulations. These large-scale parameterization methods provide a useful tool to identify the impact of parameterization differences on model behavior in the presence of two-way feedback between convection and the large-scale circulation.

Methods to assess the effectiveness of naturally ventilated classrooms in Gauteng, South Africa

There is a tendency to reduce ventilation rates and natural or hybrid ventilation systems to ensure the conservation of energy in school buildings. However, high indoor pollutant concentration, due to natural or hybrid ventilation systems may have a significant adverse impact on the health and academic performance of pupils and students. Reviewed evidence shows that this can be detrimental to health and wellbeing in schools because of the learner density within a small area, eventually indicating that CO2 concentrations can rise to very high levels (about 4000 ppm) in classrooms during occupancy periods. In South Africa’s naturally ventilated classrooms, it is not clear whether the environmental conditions are conducive for learning. In addition, natural ventilation will be minimized given the fact that in cold, wet or windy weather, doors and windows will commonly remain closed. Evidence from literature based studies indicates that the significance of ventilation techniques is not understood satisfactorily and additional information concerning naturally ventilated schools has to be provided for better design and policy formulation. To develop a thorough understanding of the environments in classrooms, many other parameters have to be considered as well, such as outdoor air quality, CO2 concentrations, temperature and relative humidity and safety issues that may be important drawbacks for naturally ventilated schools. The aim of this paper is to develop a conceptual understanding of methods that can be implemented to assess the effectiveness of naturally ventilated classrooms in Gauteng, South Africa. A theoretical concept with an embedded practical methodology have been proposed for the research programme to investigate the relationship between ventilation rates and learning in schools in Gauteng , a province in South Africa. It is important that existing and future school buildings must include adequate outdoor ventilation, control of moisture, and avoidance of indoor exposures to microbiologic and chemical substances considered likely to have adverse effects in South Africa. Adequate ventilation in classrooms is necessary to reduce and/or eradicate the transmission of indoor pollutants.

Understanding the processes governing climate variability and change, climate predictability and the probability of extreme events

The purpose of Research Theme 4 (RT4) was to advance understanding of the basic science issues at the heart of the ENSEMBLES project, focusing on the key processes that govern climate variability and change, and that determine the predictability of climate. Particular attention was given to understanding linear and non-linear feedbacks that may lead to climate surprises,and to understanding the factors that govern the probability of extreme events. Improved understanding of these issues will contribute significantly to the quantification and reduction of uncertainty in seasonal to decadal predictions and projections of climate change. RT4 exploited the ENSEMBLES integrations (stream 1) performed in RT2A as well as undertaking its own experimentation to explore key processes within the climate system. It was working at the cutting edge of problems related to climate feedbacks, the interaction between climate variability and climate change � especially how climate change pertains to extreme events, and the predictability of the climate system on a range of time-scales. The statisticalmethodologies developed for extreme event analysis are new and state-of-the-art. The RT4-coordinated experiments, which have been conducted with six different atmospheric GCMs forced by common timeinvariant sea surface temperature (SST) and sea-ice fields (removing some sources of inter-model variability), are designed to help to understand model uncertainty (rather than scenario or initial condition uncertainty) in predictions of the response to greenhouse-gas-induced warming. RT4 links strongly with RT5 on the evaluation of the ENSEMBLES prediction system and feeds back its results to RT1 to guide improvements in the Earth system models and, through its research on predictability, to steer the development of methods for initialising the ensembles

Construction management research: a field of application

Research in construction management is diverse in content and in quality. There is much to be learned from more fundamental disciplines. Construction is a sub-set of human experience rather than a completely separate phenomenon. Therefore, it is likely that there are few problems in construction requiring the invention of a completely new theory. If construction researchers base their work only on that of other construction researchers, our academic community will become less relevant to the world at large. The theories that we develop or test must be of wider applicability to be of any real interest. In undertaking research, researchers learn a lot about themselves. Perhaps the only difference between research and education is that if we are learning about something which no-one else knows, then it is research, otherwise it is education. Self-awareness of this will help to reduce the chances of publishing work which only reveals a researcher’s own learning curve. Scientific method is not as simplistic as non-scientists claim and is the only real way of overcoming methodological weaknesses in our work. The reporting of research may convey the false impression that it is undertaken in the sequence in which it is written. Construction is not so unique and special as to require a completely different set of methods from other fields of enquiry. Until our research is reported in mainstream journals and conferences, there is little chance that we will influence the wider academic community and a concomitant danger that it will become irrelevant. The most useful insights will come from research which challenges the current orthodoxy rather than research which merely reports it.

Construction research: a field of application

Research in construction management is diverse in content and in quality. There is much to be learned from more fundamental disciplines. Construction is a sub-set of human experience rather than a completely separate phenomenon. Therefore, it is likely that there are few problems in construction requiring the invention of a completely new theory. If construction researchers base their work only on that of other construction researchers, our academic community will become less relevant to the world at large. The theories that we develop or test must be of wider applicability to be of any real interest. In undertaking research, researchers learn a lot about themselves. Perhaps the only difference between research and education is that if we are learning about something which no-one else knows, then it is research, otherwise it is education. Self-awareness of this will help to reduce the chances of publishing work which only reveals a researcher’s own learning curve. Scientific method is not as simplistic as non-scientists claim and is the only real way of overcoming methodological weaknesses in our work. The reporting of research may convey the false impression that it is undertaken in the sequence in which it is written. Construction is not so unique and special as to require a completely different set of methods from other fields of enquiry. Until our research is reported in mainstream journals and conferences, there is little chance that we will influence the wider academic community and a concomitant danger that it will become irrelevant. The most useful insights will come from research which challenges the current orthodoxy rather than research which merely reports it.