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Susan Todd

Publications and source records attributed to Susan Todd.

11 recordsLinked to original sources

A 25-year review of sequential methodology in clinical studies.

This paper explores the theoretical developments and subsequent uptake of sequential methodology in clinical studies in the 25 years since Statistics in Medicine was launched. The review examines the contributions which have been made to all four phases into which clinical trials are traditionally classified and highlights major statistical advancements, together with assessing application of the techniques. The vast majority of work has been in the setting of phase III clinical trials and so emphasis will be placed here. Finally, comments are given indicating how the subject area may develop in the future.

Clinical Trials as Topic↗

Comparing correlations of continuous observations from two independent populations using a sequential approach.

A sequential study design generally makes more efficient use of available information than a fixed sample counterpart of equal power. This feature is gradually being exploited by researchers in genetic and epidemiological investigations that utilize banked biological resources and in studies where time, cost and ethics are prominent considerations. Recent work in this area has focussed on the sequential analysis of matched case-control studies with a dichotomous trait. In this paper, we extend the sequential approach to a comparison of the associations within two independent groups of paired continuous observations. Such a comparison is particularly relevant in familial studies of phenotypic correlation using twins. We develop a sequential twin method based on the intraclass correlation and show that use of sequential methodology can lead to a substantial reduction in the number of observations without compromising the study error rates. Additionally, our approach permits straightforward allowance for other explanatory factors in the analysis. We illustrate our method in a sequential heritability study of dysplasia that allows for the effect of body mass index and compares monozygotes with pairs of singleton sisters.

Data Interpretation, Statistical↗

The Acute Care Undergraduate TEaching (ACUTE) Initiative: consensus development of core competencies in acute care for undergraduates in the United Kingdom.

BACKGROUND: The care of the acutely ill patient in hospital is often sub-optimal. Poor recognition of critical illness combined with a lack of knowledge, failure to appreciate the clinical urgency of a situation, a lack of supervision, failure to seek advice and poor communication have been identified as contributory factors. At present the training of medical students in these important skills is fragmented. The aim of this study was to use consensus techniques to identify the core competencies in the care of acutely ill or arrested adult patients that medical students should possess at the point of graduation. DESIGN: Healthcare professionals were invited to contribute suggestions for competencies to a website as part of a modified Delphi survey. The competency proposals were grouped into themes and rated by a nominal group comprised of physicians, nurses and students from the UK. The nominal group rated the importance of each competency using a 5-point Likert scale. RESULTS: A total of 359 healthcare professionals contributed 2,629 competency suggestions during the Delphi survey. These were reduced to 88 representative themes covering: airway and oxygenation; breathing and ventilation; circulation; confusion and coma; drugs, therapeutics and protocols; clinical examination; monitoring and investigations; team-working, organisation and communication; patient and societal needs; trauma; equipment; pre-hospital care; infection and inflammation. The nominal group identified 71 essential and 16 optional competencies which students should possess at the point of graduation. CONCLUSIONS: We propose these competencies form a core set for undergraduate training in resuscitation and acute care.

Acute Disease↗

Design considerations in the sequential analysis of matched case-control data.

A role for sequential test procedures is emerging in genetic and epidemiological studies using banked biological resources. This stems from the methodology's potential for improved use of information relative to comparable fixed sample designs. Studies in which cost, time and ethics feature prominently are particularly suited to a sequential approach. In this paper sequential procedures for matched case-control studies with binary data will be investigated and assessed. Design issues such as sample size evaluation and error rates are identified and addressed. The methodology is illustrated and evaluated using both real and simulated data sets.

Breast Neoplasms↗

An adaptive group sequential design for phase II/III clinical trials that select a single treatment from several.

There is increasing interest in combining Phases II and III of clinical development into a single trial in which one of a small number of competing experimental treatments is ultimately selected and where a valid comparison is made between this treatment and the control treatment. Such a trial usually proceeds in stages, with the least promising experimental treatments dropped as soon as possible. In this paper we present a highly flexible design that uses adaptive group sequential methodology to monitor an order statistic. By using this approach, it is possible to design a trial which can have any number of stages, begins with any number of experimental treatments, and permits any number of these to continue at any stage. The test statistic used is based upon efficient scores, so the method can be easily applied to binary, ordinal, failure time, or normally distributed outcomes. The method is illustrated with an example, and simulations are conducted to investigate its type I error rate and power under a range of scenarios.

Clinical Trials, Phase II as Topic↗

A practical comparison of group-sequential and adaptive designs.

Sequential methods provide a formal framework by which clinical trial data can be monitored as they accumulate. The results from interim analyses can be used either to modify the design of the remainder of the trial or to stop the trial as soon as sufficient evidence of either the presence or absence of a treatment effect is available. The circumstances under which the trial will be stopped with a claim of superiority for the experimental treatment, must, however, be determined in advance so as to control the overall type I error rate. One approach to calculating the stopping rule is the group-sequential method. A relatively recent alternative to group-sequential approaches is the adaptive design method. This latter approach provides considerable flexibility in changes to the design of a clinical trial at an interim point. However, a criticism is that the method by which evidence from different parts of the trial is combined means that a final comparison of treatments is not based on a sufficient statistic for the treatment difference, suggesting that the method may lack power. The aim of this paper is to compare two adaptive design approaches with the group-sequential approach. We first compare the form of the stopping boundaries obtained using the different methods. We then focus on a comparison of the power of the different trials when they are designed so as to be as similar as possible. We conclude that all methods acceptably control type I error rate and power when the sample size is modified based on a variance estimate, provided no interim analysis is so small that the asymptotic properties of the test statistic no longer hold. In the latter case, the group-sequential approach is to be preferred. Provided that asymptotic assumptions hold, the adaptive design approaches control the type I error rate even if the sample size is adjusted on the basis of an estimate of the treatment effect, showing that the adaptive designs allow more modifications than the group-sequential method.

Algorithms↗

Erythropoietin mimics the acute phase response in critical illness.

BACKGROUND: In a prospective observational study, we examined the temporal relationships between serum erythropoietin (EPO) levels, haemoglobin concentration and the inflammatory response in critically ill patients with and without acute renal failure (ARF). PATIENTS AND METHOD: Twenty-five critically ill patients, from general and cardiac intensive care units (ICUs) in a university hospital, were studied. Eight had ARF and 17 had normal or mildly impaired renal function. The comparator group included 82 nonhospitalized patients with normal renal function and varying haemoglobin concentrations. In the patients, levels of haemoglobin, serum EPO, C-reactive protein, IL-1beta, IL-6, serum iron, ferritin, vitamin B12 and folate were measured, and Coombs test was performed from ICU admission until discharge or death. Concurrent EPO and haemoglobin levels were measured in the comparator group. RESULTS: EPO levels were initially high in patients with ARF, falling to normal or low levels by day 3. Thereafter, almost all ICU patients demonstrated normal or low EPO levels despite progressive anaemia. IL-6 exhibited a similar initial pattern, but levels remained elevated during the chronic phase of critical illness. IL-1beta was undetectable. Critically ill patients could not be distinguished from nonhospitalized anaemic patients on the basis of EPO levels. CONCLUSION: EPO levels are markedly elevated in the initial phase of critical illness with ARF. In the chronic phase of critical illness, EPO levels are the same for patients with and those without ARF, and cannot be distinguished from noncritically ill patients with varying haemoglobin concentrations. Exogenous EPO therapy is unlikely to be effective in the first few days of critical illness.

Acute Kidney Injury↗

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.

Alzheimer Disease↗

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, rho between test statistics monitored as part of the sequential test. It can be difficult to quantify rho 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 rho 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.

Biometry↗

A sequential procedure for comparing two experimental treatments with a control.

A procedure is described in which patients are randomized between two experimental treatments and a control. At a series of interim analyses, each experimental treatment is compared with control. One of the experimental treatments might then be found sufficiently superior to the control for it to be declared the best treatment, and the trial stopped. Alternatively, experimental treatments might be eliminated from further consideration at any stage. It is shown how the procedure can be conducted while controlling overall error probabilities. Data concerning evaluation of different doses of riluzole in the treatment of motor neurone disease are used for illustration.

Analysis of Variance↗