Point estimation for adaptive trial designs I: A methodological review

Recent FDA guidance on adaptive clinical trial designs defines bias as "a systematic tendency for the estimate of treatment effect to deviate from its true value," and states that it is desirable to obtain and report estimates of treatment effects that reduce or remove this bias. The conventional end-of-trial point estimates of the treatment effects are prone to bias in many adaptive designs, because they do not take into account the potential and realized trial adaptations. While much of the methodological developments on adaptive designs have tended to focus on control of type I error rates and power considerations, in contrast the question of biased estimation has received relatively less attention. This article is the first in a two-part series that studies the issue of potential bias in point estimation for adaptive trials. Part I provides a comprehensive review of the methods to remove or reduce the potential bias in point estimation of treatment effects for adaptive designs, while part II illustrates how to implement these in practice and proposes a set of guidelines for trial statisticians. The methods reviewed in this article can be broadly classified into unbiased and bias-reduced estimation, and we also provide a classification of estimators by the type of adaptive design. We compare the proposed methods, highlight available software and code, and discuss potential methodological gaps in the literature.

Treatment of Middle East respiratory syndrome with a combination of lopinavir/ritonavir and interferon-β1b (MIRACLE trial): statistical analysis plan for a recursive two-stage group sequential randomized controlled trial

The MIRACLE trial (MERS-CoV Infection tReated with A Combination of Lopinavir/ritonavir and intErferon-β1b) investigates the efficacy of a combination therapy of lopinavir/ritonavir and recombinant interferon-β1b provided with standard supportive care, compared to placebo provided with standard supportive care, in hospitalized patients with laboratory-confirmed MERS. The MIRACLE trial is designed as a recursive, two-stage, group sequential, multicenter, placebo-controlled, double-blind randomized controlled trial. The aim of this article is to describe the statistical analysis plan for the MIRACLE trial. The primary outcome is 90-day mortality. The primary analysis will follow the intention-to-treat principle. The MIRACLE trial is the first randomized controlled trial for MERS treatment. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02845843. Registered on 27 July 2016.

Comparing the MAMS framework with the combination method in multi-arm adaptive trials with binary outcomes

In multi-arm adaptive trials, several treatments are assessed simultaneously and accumulating data are used to inform decisions about the trial, such as whether treatments are dropped or continued. Different methodological approaches have been developed for such trials and research has compared the performance of different subsets of these. One particular approach, for which we use the acronym MAMS(R), has generally not been included in these comparisons because control of the family-wise error rate (FWER) could not be guaranteed. Recently, the MAMS(R) approach has been extended to facilitate the generation of efficient designs which strongly control the FWER. We consider multi-arm two-stage trials with binary outcomes and propose parameterising treatment effects using the log odds ratio. We conduct a simulation study comparing the extended MAMS(R) framework with the well-established combination method both for trials where a different outcome is used for mid-trial analysis and for trials where the same outcome is used throughout. We show how the MAMS(R) framework compares favourably only in scenarios where the same outcome is used. We propose a hybrid selection rule within MAMS(R) methodology and demonstrate that this makes it possible to use the MAMS(R) framework in trials incorporating comparative treatment selection.

Data-Driven Analysis Strategies for Proportion Studies in Adaptive Group Sequential Test Designs

Using multistage adaptive group sequential test designs, the investigator may perform data-driven changes in the design during the course of the trial without inflation of the Type I error rate. This is possible, for example, through the use of the inverse normal method of combining the p-values from the separate stages of the trial. Generally, conditional error functions are useful instruments for midtrial design modifications of clinical trials. Particularly, it is worthwhile to consider sample size reassessment strategies based on conditional power arguments. In this paper, approximate techniques will be proposed for the application of the inverse normal combination testing principle in superiority and noninferiority proportion studies. Planning facilities and the adaptive analysis strategies will be discussed in terms of the Type I error rate, the necessary sample size, and the power within the adaptive design. Furthermore, how to calculate confidence intervals and overall p-values will be shown.

Planning and analyzing adaptive group sequential survival trials

The use of adaptive methods has experienced increasing interest in the current literature on group sequential designs. Group sequential analysis in survival trials usually apply the error spending function approach due to the unpredictable amount of information available in an interim analysis. An alternative way is to apply adaptive methods where additionally the maximum amount of information and other designing parameters can be changed based on the information available at the interim stage. In this paper, it is shown how the inverse normal method can be used within a survival design using the log-rank test for comparing two survival functions. This method allows for many kinds of design modifications. In case of no modifications, the inverse normal method coincides with the commonly used analysis strategy. It is straightforward to specify effect estimates. Confidence intervals for the hazard ratio that can be calculated at each stage of the trial and intervals that can only be computed by the end of the trial are proposed. The latter also enables the calculation of median unbiased estimates. Overall p-values can be defined analogously. Properties of the analyses techniques are investigated and compared with alternative approaches. It is shown that the proposed analysis technique might help to rescue an underpowered study and opens the way to other types of changes in design. The proposed technique is implemented in the software ADDPLAN Adaptive Design, Plans and Analyses (http://www.addplan.com).

Using the partitioning principle to adaptively design dose-response studies

An adaptive two-stage design is proposed for dose-response studies to find the minimum effective dose. The procedure is conducted in a stepwise fashion based on the partition testing principle with familywise error rate controlled strongly. We examine a wide dose range vs. a placebo in the first stage. Then an interim analysis is conducted with potential modification of design features of the experiment. Ineffective and/or unsafe dose treatments are terminated, and selected doses are further investigated in the second stage. Inference is based on a pre-chosen conditional error function. Several conditional error functions are discussed and compared.

Treatment of acute bronchitis in adults with a pelargonium sidoides preparation (EPs 7630): a randomized, double-blind, placebo-controlled trial

BACKGROUND

Acute bronchitis is a widespread medical problem, and, although predominantly caused by viruses, antibiotics are still prescribed unnecessarily. Therefore, it is of utmost importance to evaluate the use of alternative treatments for acute bronchitis.

OBJECTIVE

To evaluate the efficacy and safety of a Pelargonium sidoides preparation (EPs 7630 is a registered trademark of Dr. Willmar Schwabe GmbH & Co. KG, Karlsruhe, Germany) compared with placebo in patients with acute bronchitis.

DESIGN

Randomized, double-blind, placebo-controlled trial using a design with planned interim analyses.

SETTING

Six outpatient clinics.

PATIENTS

One hundred twenty-four adults with acute bronchitis present </=48 hours, Bronchitis Severity Score (BSS) >/=five points, and informed consent.

INTERVENTION

EPs 7630 or placebo (30 drops three times daily) for seven days.

MEASUREMENTS

The primary outcome criterion was the change of BSS on day seven.

RESULTS

The decrease of BSS from baseline to day seven was 7.2 +/- 3.1 points with EPs 7630 (n = 64) and 4.9 +/- 2.7 points with placebo (n = 60). The 95% confidence interval for the difference of effects between the two treatment groups (EPs 7630 minus placebo) was calculated as (1.21, 3.56) showing a significant improvement of EPs 7630 compared with placebo on day seven (P < .0001). For each of the five individual symptoms, rates of complete recovery were considerably higher in the EPs 7630 group. Within the first four days, onset of treatment effect was recognized in 68.8% of patients in the EPs 7630 group compared with 33.3% of patients in the placebo group (P < .0001). Health-related quality of life improved more in patients treated with EPs 7630 compared with placebo-treated patients. Adverse events occurred in 25 of 124 patients (EPs 7630: 15/64 patients, placebo: 10/60 patients). All adverse events were assessed as nonserious.

CONCLUSIONS

EPs 7630 was superior in efficacy compared with placebo in the treatment of adults with acute bronchitis. It may therefore offer an effective alternative for acute bronchitis unless antibiotics are clearly indicated.

Perioperative granulocyte colony-stimulating factor does not prevent severe infections in patients undergoing esophagectomy for esophageal cancer: a randomized placebo-controlled clinical trial

OBJECTIVE

Esophagectomy for esophageal cancer is associated with substantial postoperative morbidity as a result of infectious complications. In a prior phase II study, granulocyte colony-stimulating factor (G-CSF) was shown to improve leukocyte function and to reduce infection rates after esophagectomy. The aim of the current randomized, placebo-controlled, multicenter phase III trial was to investigate the clinical efficacy of perioperative G-CSF administration in reducing infection and mortality after esophagectomy for esophageal cancer.

PATIENTS AND METHODS

One hundred fifty five patients with resectable esophageal cancer were randomly assigned to perioperative G-CSF at standard doses (77 patients) or placebo (76 patients), administered from 2 days before until day 7 after esophagectomy. The G-CSF and placebo groups were comparable as regards age, gender, risk, cancer stage, frequency of neoadjuvant radiochemotherapy, and type of esophagectomy (transthoracic or transhiatal esophageal resection).

RESULTS

Of 155 randomized patients, 153 were eligible for the intention-to-treat analysis. The rate of infection occurring within the first 10 days after esophagectomy was 43.4% (confidence interval 32.8-55.9%) in the placebo and 44.2% (confidence interval 32.1-55.3%) in the G-CSF group (P = 0.927). 30-day mortality amounted to 5.2% in the G-CSF group versus 5.3% in the placebo group (P = 0.985). Similar results were found in the per-protocol analysis.

CONCLUSION

Perioperative administration of G-CSF failed to reduce postoperative morbidity, infection rate, or mortality in patients with esophageal cancer who underwent esophagectomy.

Efficacy and safety of an extract of Pelargonium sidoides (EPs 7630) in adults with acute bronchitis. A randomised, double-blind, placebo-controlled trial

BACKGROUND

New evidence-based treatment options are required to avoid antibiotic overuse in acute bronchitis and to replace potentially inefficacious initial antibiotic treatment.

OBJECTIVE

To evaluate the efficacy and safety of an extract of Pelargonium sidoides (EPs 7630) compared to placebo in patients with acute bronchitis.

DESIGN

Randomized, double-blind, placebo-controlled trial using a multi-stage adaptive design.

SETTING

36 primary care physicians (investigators) at the out-patient care setting.

PATIENTS

468 adults with acute bronchitis present < or = 48 hours, Bronchitis Severity Score (BSS) > or = 5 points, and informed consent.

INTERVENTION

EPs 7630 or placebo (30 drops three times daily) for 7 days.

MEASUREMENT

The primary outcome criterion was the change of BSS on day 7.

RESULTS

The decrease of BSS from baseline to day 7 was 5.9 +/- 2.9 points under EPs 7630 (n = 233), and 3.2 +/- 4.1 points under placebo (n = 235). The 95% CI for the difference of effects between the two treatment groups (EPs 7630 minus placebo) was calculated as [-3.359; -2.060] showing a significant superiority of EPs 7630 compared to placebo on day 7 (p < 0.0001). Working inability decreased to 16% in the EPs 7630 group compared to 43% in the placebo group (p < 0.0001). In addition, the duration of illness was significantly shorter for patients treated with EPs 7630 compared to placebo (p < 0.001). Within the first four days, onset of treatment effect was recognized in 53.6% of patients under EPs 7630 compared to 36.2% of patients under placebo, only (p < 0.0001). Adverse events (AEs) occurred in 36/468 patients (EPs 7630: 20/233 patients, placebo: 16/235 patients). All events were assessed as non-serious.

CONCLUSION

EPs 7630 was superior in efficacy compared to placebo in the treatment of adults with acute bronchitis. Treatment with EPs 7630 clearly reduced the severity of symptoms and shortened the duration of working inability for nearly 2 days.

Strategies for changing the test statistic during a clinical trial

This article discusses the design of a clinical trial where a new treatment will be compared to a control. For a specific type of endpoint, there are a wide variety of test statistics that can be used. Also, the investigator must decide how many patients to accrue in each arm as well as the duration of the study. After an interim look at the data, the investigator may decide that a different test statistic would be more powerful or that more patients or longer follow-up is needed. In this article, we discuss a strategy for making these types of changes. This strategy controls the probability of making a type I error and can result in a procedure that has higher power than the test without adaptation.