Statistical methods for assessing differential vaccine protection against human immunodeficiency virus types

The human immunodeficiency virus type 1 (HIV-1) is extremely diverse. In assessing the utility of an HIV-1 vaccine, an important issue is the possibility of differential protection. We discuss statistical methods of inferring how the vaccine efficacy may vary with viral type from data that would be collected from a randomized, double-blind, placebo-controlled preventive vaccine efficacy trial. Detailed characterization of virus isolated from individuals infected during the trial will be available. We focus on the highly simplified case in which the viral characteristics are summarized by a single feature, which may be nominal, or a scalar quantity that represents distance between the isolate and the prototype virus or viruses used in the vaccine preparation. We consider discrete categorical and continuous response models for this quantity and identify models whose parameters can be interpreted as log ratios of strain-specific relative risks of infection in a prospective model for HIV-1 exposure and transmission. Methods of inference are described for the multinomial logistic regression (MLR) model for discrete categorical response, and a new semiparametric model which can be viewed as a continuous analog of the MLR model is introduced. The methods are illustrated by application to HIV-1 and hepatitis B vaccine trial data.

Evaluation and follow-up of patients with N1-3 M0 or NXM1 prostate cancer in phase III trials

OBJECTIVES

The aim of this discussion is to review the design and conduct of phase III trials in metastatic prostate cancer, to seek ways of improving their study design, accuracy, relevance to clinical practice, acceptability to patients, and ease of participation by clinicians. We also aim to try to set uniform definitions for the evaluation of the different endpoints used in clinical trials on metastasized prostate cancer.

METHODS

The work was started by correspondence between the participants in the group for the year before the consensus meeting. Two comprehensive questionnaires were circulated and the answers were distributed to all the members of the group. The statements were finalized during the consensus meeting.

RESULTS

There were some differing opinions concerning the methods of evaluation of endpoints for follow-up, such as time to tumor progression and time to treatment failure. After the consensus conference, there were no major disagreements within the group.

CONCLUSIONS

The aim of phase III trials is to influence clinical management. To obtain a credible result they require a sound statistical basis with appropriate power and encompassing patients from small urologic practices as well as large or academic institutions. However, deviation from routine practice may affect the accrual rate, and the trial procedure should therefore be as similar as possible to routine management. Trials inevitably involve extra work and cost. Both should be kept to a minimum to encourage participation and hasten a timely conclusion. It is mandatory to create uniform ways of designing and evaluating clinical trials in prostate cancer.

Is good clinical research practice for clinical trials good clinical practice?

This article presents results of monitoring of the recruitment process for a phase III study of a new antidepressant drug in elderly patients with depressive disorders, focusing on the peculiarities of recruitment posed by the presence of comorbidity and coadministration of medications. Data are derived from screening of 188 patients, the majority of whom lived at home, referred for trial inclusion. One hundred and seventy-one (91%) had Hamilton Rating Scale score in excess of 18 and met inclusion criteria. Only eight (4.2%) elderly depressed subjects could be recruited, after application of exclusion criteria. The trial data so obtained may be scientifically credible, but the conclusions reached by trials with very stringent exclusion criteria do not reflect the practice environment in which the product will be prescribed by clinicians. This raises questions of the relevance of good clinical research practice and good clinical practice guidelines to the reality of good clinical practice beyond the trial situation.

An introduction to the statistical design of phase III cancer clinical trials

Unless a phase III clinical trial is properly designed, it may be impossible to draw valid conclusions concerning the relative efficacy of the treatments being studied. The purpose of this paper is to present the basic principles of trial design as related to treatment assignment by randomization, the stratification for prognostic factors, the number of treatments to be compared and the determination of the sample size. Emphasis is placed on the distinction between the number of events and the number of patients required in time to event analyses and between trials designed to detect a difference and trials attempting to show treatment equivalence.

Placebo washout in trials of antipsychotic drugs

For antipsychotic phase 3 clinical trials, we compare the relative merits of a placebo washout period with an alternate design strategy using a low-dose antipsychotic treatment. Evaluations are made with respect to the achievement of specific clinical trial design goals including the effect on power for detecting between-treatment and within-treatment pre-post differences. The relative merits of these two designs are discussed separately for those patients who enter the initial leadin period after withdrawal from previous antipsychotic medication and for those not on medication immediately before that period.

[Introduction to the statistical aspects of planning clinical oncologic phase III studies]

A phase III clinical trial is a comparative study in which one assesses the relative efficacy of a treatment or treatments. It generally has one of the following objectives: 1. To determine the effectiveness of a new treatment relative to the natural history of the disease, for example when comparing a new treatment to not treatment or to placebo in an adjuvant setting. 2. To determine if a new treatment is more effective than the best current standard therapy (at the risk of increasing the toxicity). 3. To determine if a new treatment is as effective as the best current standard therapy but is associated with less severe toxicity or a better quality of life (equivalence trial). Clinical trials must be properly designed in order to answer such questions with a high degree of certainty. The purpose of this paper is to present several concepts which must be taken into account during the process of designing a clinical trial.

Granulocyte-macrophage colony-stimulating factor as adjunct therapy in relapsed lymphoid malignancy: implications for economic analyses of phase III clinical trials

With the increasing concern over the high cost of health care, policy makers have incorporated economic analyses into phase III clinical trials as the randomized clinical trials can provide important information on the efficacy and potential cost-effectiveness of new pharmaceutical agents. Economic analyses of single-hospital experience during phase III trials of granulocyte-macrophage colony-stimulating factor (GM-CSF) as adjunct therapy for high dose chemotherapy with autologous stem cell support found significant shortening of neutropenia with GM-CSF at each hospital, but shortened hospitalization (and lower costs) at only two of three hospitals. In this study, we added data from three additional hospitals and found that the 103 patients who received GM-CSF had, on average, 5.7 days shorter durations of severe neutropenia than the 95 patients who received placebo (p < 0.0001) and 3.4 days shorter in hospitalization (p = 0.06). However, the duration of hospitalization, the primary determinant of health care costs, was shorter for GM-CSF patients in only four of the six centers and the duration of hospitalization of placebo patients was shorter at the other two centers. Careful analyses must be carried out when phase III clinical trial results are used to derive estimates of cost-effectiveness of new pharmaceutical agents. The interpretation of economic analyses of phase III clinical trials raises issues related to the perspective of the investigators, study design, collection of data on resource utilization, learning curve effects and generalizability of the results to other settings.

Inferring systemic exposure from a pharmacokinetic screen: model-free and model-based approaches

To infer patterns of average systemic exposure and to estimate individual exposures in phase III clinical trials of a new anxiolytic, two statistical methodologies were applied and compared: non-linear mixed-effect modelling, and a model-free approach based on quartiles of dose-normalized plasma concentrations of the drug. Although the model-based approach provides more quantitative insight about relationships between average exposure and demographic covariates, the model-free approach provides qualitatively similar results about average clearance and quantitatively similar results about individual exposures, and the model-free approach is easy and inexpensive to implement.

An application of Bayesian population pharmacokinetic/pharmacodynamic models to dose recommendation

Population pharmacokinetic data consists of dose histories, individual covariates and measured drug concentrations with associated sampling times. Population pharmacodynamic data consist of dose histories, covariates and some response measure. Population analyses, whether they be pharmacokinetic or pharmacodynamic attempt to explain the variability observed in the recorded measurements and are increasingly being seen as an important aid in drug development. In this paper a general Bayesian population pharmacokinetic/pharmacodynamic model is described and an analysis of data for the drug recombinant hirudin is presented. The model we use allows for both outliers and censoring in the concentration data and outlying individual pharmacokinetic parameters. We attempt to address directly important questions such as recommended dose size using predictive distributions for response.

Dose finding strategies involving interim analyses and unbalanced treatment allocation

Dose finding studies usually require the application of multiple test procedures (MTP). A variety of procedures is available for data analyses. Focusing on testing only subset hypotheses of interest requires only limited alpha-adjustment. Specific strategies based on MTP, in particular closed test procedures, which also consider dropping dose groups and unequal group sizes, lead to substantial reduction in total sample size. Of course, strategies discussed here can be extended to comparisons of more than five groups, and they may be generalized to cover equivalence tests, too. For example, one may want to demonstrate therapeutical equivalence of two dose regimens like b.i.d. and o.d. administrations of the drug.

The case for cross-over trials in phase III

There is a common belief that cross-over trials should not be used in phase III of drug development. This was reinforced by a statement in the draft CPMP Note for Guidance on biostatistical methodology in clinical trials which was circulated for review in March 1993: 'Hence crossover trials in patients should be avoided as far as possible'. We do not share this belief. Historically, many successful drug developments in indications such as hypertension and asthma have depended heavily on cross-over trials in their phase III programmes, leading to regulatory approval for a number of well established medicines. The evidence on which these developments were based appeared sound at the time, and has not been questioned by later experiences with these medicines. Furthermore, the general level of understanding of these medical indications is now even more well developed, and hence the circumstances under which cross-over trials may be used to advantage for new drugs in phase III are even more likely to be correctly identified. There are some well-known disadvantages of cross-over trials relative to parallel group trials. These are reviewed and the ways in which early indications of such problems might be detected in phases I and II or elsewhere will be discussed. However, there are also two key advantages, the well-known one of study size and a less well-known one arising in the context of treatment-by-patient interaction. In phases I and II these advantages lead routinely to the use of the cross-over design. Some methods of analysing cross-over trials have been criticized in a number of recent articles. We compare the properties of a number of alternative analysis strategies by means of simulation and conclude that these concerns about methods of analysis do not imply that cross-over trials should be avoided, especially if baseline measurements can be included in the design. Any small risks attached to their use should not normally concern the regulator as they will tend to diminish estimates of treatment effects rather than enhance them. In summary, cross-over trials remain a potentially valuable research tool in the development of new medicines at all stages including phase III. It is unnecessary and counterproductive to exclude them from use.

SEQPWR and SEQOPR: computer programs for design of maximum information trials based on group sequential logrank tests

The maximum information trial paradigm for clinical trials with failure time data was recognized and has been investigated. With the maximum information trial paradigm, a study is concluded when a prespecified maximum number of events of interest, thus maximum information, has been accrued if there was no early stopping due to treatment difference or lack thereof. We present two interactive FORTRAN programs for use in designing maximum information trials based on group sequential logrank tests. The program SEQPWR computes the attainable power of group sequential logrank tests given the combinations of the accrual and follow-up durations. The program SEQOPR allows the users to investigate the operating characteristics of the maximum information trial given the information fractions of interim analyses. A clinical trial from the Eastern Cooperative Oncology Group is provided to illustrate the usage and features of the programs.

Preparation for phase III HIV vaccine efficacy trials: methods for the determination of HIV incidence

OBJECTIVE

Accurate estimates of HIV incidence that reflect the effect of non-vaccine interventions (education, counselling, condom promotion, and possibly sexually transmitted disease treatment) and that may be provided in a Phase III vaccine efficacy trial, are needed so that vaccine trial population sample sizes can be accurately determined. In order to avoid delays in the implementation of efficacy trials, well characterized cohorts must also be developed and available to participate in such trials. We reviewed the potential study populations, the epidemiologic methods for the determination of HIV incidence (using open cohort, closed cohort, and seroprevalence data methods), and the need for the development of population cohorts in preparation for Phase III HIV vaccine efficacy trials.

SETTING

Phase III trials in developed and developing countries.

METHODS

Comparison of open and closed cohorts and those using seroprevalence data to estimate HIV incidence.

RESULTS

Open and closed cohorts each have disadvantages and advantages. However, the open cohort may be more suitable for determining estimates of HIV incidence that reflect non-vaccine interventions and for the development of a well characterized cohort available to participate in efficacy trials.

CONCLUSION

Careful preparation of research infrastructures and population cohorts will help ensure the successful conduct of scientifically and ethically sound HIV vaccine efficacy trials in the future.

Cerebral intraarterial fibrinolysis at the crossroads: is a phase III trial advisable at this time?

PURPOSE

To describe the rationale for fibrinolysis, review the state of the art in cerebral fibrinolysis, and discuss whether it is time for phase III studies of cerebral intraarterial fibrinolysis.

METHODS

Critical review of the literature with statistical reevaluation of significant clinical data.

RESULTS

There are abundant phase III data supporting the use of thrombolysis in the cardiovascular system. However, there are no published phase III trials of intraarterial fibrinolysis in stroke. All reports of cerebral intraarterial fibrinolysis are case series. The studies are typically small with variable treatment protocols and designs that are susceptible to bias. The only analysis comparing cerebral intraarterial fibrinolysis with conventional therapy is based on nonconcurrent controls.

CONCLUSIONS

Stroke is common and costly. Acute stroke intervention with fibrinolytic drugs is theoretically justified. Studies done to date have significant, inferential limitations. The data suggest an association between thrombolysis, recanalization, and prognosis. However, imprecision and inadequate control of systematic error preclude conclusions regarding clinical outcomes. Randomized, controlled trials are needed to establish the clinical value of cerebral local intraarterial fibrinolysis. However, cerebral local intraarterial fibrinolysis availability, the cerebral local intraarterial arterial fibrinolysis learning curve, anticipated technological advances, unresolved procedural controversies, and ethical and fiscal considerations make a large phase III trial impractical and ill-advised at the present time. Additional basic research is needed to set the stage for a successful clinical trial.

Data Monitoring Committees and early stopping guidelines: the Southwest Oncology Group experience

Data Monitoring Committees in the Southwest Oncology Group comprise the study leadership and the leadership of the Group, augmented by some outside representation. The early stopping guidelines used by these committees are explicit in each protocol, and can be characterized as specifying a few interim analyses at conservative statistical levels. We describe our ten years of experience with this system, and give examples of different trials which have stopped either for positive or negative results.

Surrogate markers in AIDS and cancer trials

There is significant need for rapid yet reliable evaluation of promising new interventions for the treatment of patients with cancer or HIV infection. Considerable attention has been given to identifying replacement or 'surrogate' endpoints for the true clinical efficacy endpoints, in order to reduce the cost, size and duration of clinical trials. We discuss issues which affect the validity of surrogate markers. The reliability of the CD4 lymphocyte count marker is carefully considered in clinical trials of anti-retroviral agents in HIV infected individuals. The nature of surrogate markers and their reliability is discussed in cancer prevention, screening and treatment trials. Some suggested uses of marker information are also considered.

Some practical aspects of the interim monitoring of clinical trials

The decision to stop accrual early to a clinical trial is often difficult and multifaceted. Interim monitoring boundaries have been found useful in U.S. oncology trials for such decisions for reasons described here. This paper also discusses rationale that lead to more conservative approaches to early stopping decisions than are currently employed. A recent initiative of the National Cancer Institute to achieve the objectives of independent data monitoring committees in the phase III clinical trials which it sponsors is also described.

New designs for the selection of treatments to be tested in randomized clinical trials

The most important aspect of phase III randomized clinical trials is the selection of the experimental treatments to be tested. Often this decision is based on uncontrolled phase II trials. Substantial statistical attention has been focused on the design of phase III trials and for simple phase II trials, which determine whether a new drug has any anti-disease activity. Much less statistical effort has been devoted to the design and analysis of phase II trials for screening active experimental treatments to determine whether they are sufficiently active, relative to standard treatments, to warrant the conduct of a large randomized phase III trial. This problem is particularly acute in the development of drug combinations where many regimens are possible. We review several designs for such screening trials which we have developed.

Design strategies in multiple sclerosis clinical trials. The Cyclosporine Multiple Sclerosis Study Group

After analyzing our natural history data on the course of multiple sclerosis (MS) in more than 500 patients followed for 20 years and our experience in several therapeutic trials, we concluded that a phase III (full) trial for efficacy should have certain properties. For a power of 0.8, alpha of 0.05, and attrition rate of 10% per year, we think the trial should have a minimum sample size of 130 (65 in each arm; placebo versus active) if the design is based upon the proportion of subjects worsening by clinical measures. No stratification by entry Extended Disability Status Scale score is needed if worsening is defined as a change of 1.0 units (2 to 0.5 steps) maintained for 90 days for an entry score of 1 to 5.0 units; or 0.5 units (1 to 0.5 steps) if the entry score is 5.5 to 7 units. We need not stratify by course (relapsing-remitting versus relapsing-progressive) but are less certain about progression from the onset. No run-in period is required to define "activity." Minimum time for treatment is 3 years. We review the justification for our conclusions; modifications in sample size that are necessary if survival analysis is used; impact of the interferon-beta trial (future trials will have an "active" control); and alternative strategies possible if magnetic resonance imaging serves as the primary outcome.

The clinical evaluation of new drugs for sepsis. A prospective study design based on survival analysis

OBJECTIVE

To develop a survival model and severity assessment method to estimate the 28-day mortality risk for patients with sepsis syndrome entering phase 2 and 3 drug evaluations.

DESIGN

Retrospective analysis of intensive care unit admissions with sepsis syndrome by means of log-normal regression to identify risk factors for 28-day mortality. Prospective application of the model to patients with gram-negative infection meeting sepsis syndrome criteria from separate data collection (validation group).

PATIENTS

A total of 58,737 intensive care unit admissions at 107 hospitals in the United States and Western Europe screened to yield 1195 patients meeting entry criteria for the sepsis syndrome study for the original model; 295 hospitalized patients with gram-negative infection meeting criteria for sepsis syndrome for validation.

MAIN OUTCOME MEASURES

Survival time and mortality at 28 days after fulfillment of the sepsis syndrome criteria.

RESULTS

Acute physiologic abnormalities were the most important prognostic factors influencing outcome (82% of total chi 2). Specific disease resulting in intensive care unit admission and the time the patient was in the hospital and intensive care unit before qualification were also independent risks, as were age and a clinical history of cirrhosis. The model's overall classification accuracy was a Somers' Dyx of .52 (rank correlation between predicted risk and 28-day mortality) (receiver operating characteristic area, 0.76), with equal accuracy (Dyx = .59; receiver operating characteristic area, 0.80) in the independent group of patients.

CONCLUSIONS

We created an accurate independent estimate for 28-day mortality risk for patients with sepsis syndrome (severe sepsis). This estimate could improve the evaluation of new drugs by investigating whether the drug's benefit varies by patient risk and then determining the amount of benefit for individual patients.

Sparse data analysis

In recent years there has been a growing interest in techniques capable of analyzing sparse data, particularly gathered during Phase III clinical trials, and there is now pressure on manufacturers to obtain more kinetic and dynamic information from Phase III studies. Techniques for the analysis of sparse data are reviewed drawing on a number of examples taken from pharmacokinetic and pharmacodynamic experiments.