Abdul J. Sankoh

Telaprevir for Previously Untreated Chronic Hepatitis C Virus Infection

BACKGROUND In phase 2 trials, telaprevir, a hepatitis C virus (HCV) genotype 1 protease inhibitor, in combination with peginterferon-ribavirin, as compared with peginterferon-ribavirin alone, has shown improved efficacy, with potential for shortening the duration of treatment in a majority of patients. METHODS In this international, phase 3, randomized, double-blind, placebo-controlled trial, we assigned 1088 patients with HCV genotype 1 infection who had not received previous treatment for the infection to one of three groups: a group receiving telaprevir combined with peginterferon alfa-2a and ribavirin for 12 weeks (T12PR group), followed by peginterferon-ribavirin alone for 12 weeks if HCV RNA was undetectable at weeks 4 and 12 or for 36 weeks if HCV RNA was detectable at either time point; a group receiving telaprevir with peginterferon-ribavirin for 8 weeks and placebo with peginterferon-ribavirin for 4 weeks (T8PR group), followed by 12 or 36 weeks of peginterferon-ribavirin on the basis of the same HCV RNA criteria; or a group receiving placebo with peginterferon-ribavirin for 12 weeks, followed by 36 weeks of peginterferon-ribavirin (PR group). The primary end point was the proportion of patients who had undetectable plasma HCV RNA 24 weeks after the last planned dose of study treatment (sustained virologic response). RESULTS Significantly more patients in the T12PR or T8PR group than in the PR group had a sustained virologic response (75% and 69%, respectively, vs. 44%; P<0.001 for the comparison of the T12PR or T8PR group with the PR group). A total of 58% of the patients treated with telaprevir were eligible to receive 24 weeks of total treatment. Anemia, gastrointestinal side effects, and skin rashes occurred at a higher incidence among patients receiving telaprevir than among those receiving peginterferon-ribavirin alone. The overall rate of discontinuation of the treatment regimen owing to adverse events was 10% in the T12PR and T8PR groups and 7% in the PR group. CONCLUSIONS Telaprevir with peginterferon-ribavirin, as compared with peginterferon-ribavirin alone, was associated with significantly improved rates of sustained virologic response in patients with HCV genotype 1 infection who had not received previous treatment, with only 24 weeks of therapy administered in the majority of patients. (Funded by Vertex Pharmaceuticals and Tibotec; ADVANCE ClinicalTrials.gov number, NCT00627926.).

Response-Guided Telaprevir Combination Treatment for Hepatitis C Virus Infection

BACKGROUND Patients with chronic infection with hepatitis C virus (HCV) genotype 1 often need 48 weeks of peginterferon-ribavirin treatment for a sustained virologic response. We designed a noninferiority trial (noninferiority margin, -10.5%) to compare rates of sustained virologic response among patients receiving two treatment durations. METHODS We enrolled patients with chronic infection with HCV genotype 1 who had not previously received treatment. All patients received telaprevir at a dose of 750 mg every 8 hours, peginterferon alfa-2a at a dose of 180 μg per week, and ribavirin at a dose of 1000 to 1200 mg per day, for 12 weeks (T12PR12), followed by peginterferon-ribavirin. Patients who had an extended rapid virologic response (undetectable HCV RNA levels at weeks 4 and 12) were randomly assigned after week 20 to receive the dual therapy for 4 more weeks (T12PR24) or 28 more weeks (T12PR48). Patients without an extended rapid virologic response were assigned to T12PR48. RESULTS Of the 540 patients, a total of 352 (65%) had an extended rapid virologic response. The overall rate of sustained virologic response was 72%. Among the 322 patients with an extended rapid virologic response who were randomly assigned to a study group, 149 (92%) in the T12PR24 group and 140 (88%) in the T12PR48 group had a sustained virologic response (absolute difference, 4 percentage points; 95% confidence interval, -2 to 11), establishing noninferiority. Adverse events included rash (in 37% of patients, severe in 5%) and anemia (in 39%, severe in 6%). Discontinuation of all the study drugs was based on adverse events in 18% of patients overall, as well as in 1% of patients (all of whom were randomly assigned) in the T12PR24 group and 12% of the patients randomly assigned to the T12PR48 group (P<0.001). CONCLUSIONS In this study, among patients with chronic HCV infection who had not received treatment previously, a regimen of peginterferon-ribavirin for 24 weeks, with telaprevir for the first 12 weeks, was noninferior to the same regimen for 48 weeks in patients with undetectable HCV RNA at weeks 4 and 12, with an extended rapid virologic response achieved in nearly two thirds of patients. (Funded by Vertex Pharmaceuticals and Tibotec; ILLUMINATE ClinicalTrials.gov number, NCT00758043.).

An overview of practical approaches for handling missing data in clinical trials.

For a variety of reasons including poorly designed case report forms (CRFs), incomplete or invalid CRF data entries, and premature treatment or study discontinuations, missing data is a common phenomenon in controlled clinical trials. With the widely accepted use of the intent-to-treat (ITT) analysis dataset as the primary analysis dataset for the analysis of controlled clinical trial data, the presence of missing data could lead to complicated data analysis strategies and subsequently to controversy in the interpretation of trial results. In this article, we review the mechanisms of missing data and some common approaches to analyzing missing data with an emphasis on study dropouts. We discuss the importance of understanding the reasons for study dropouts with ways to assess the mechanisms of missingness. Finally, we discuss the results of a comparative Monte Carlo investigation of the performance characteristics of commonly utilized statistical methods for the analysis of clinical trial data with dropouts. The methods investigated include the mixed effects model for repeated measurements (MMRM), weighted and unweighted generalized estimating equations (GEE) method for the available case data, multiple-imputation-based GEE (MI-GEE), complete case (CC) analysis of covariance (ANCOVA), and last observation carried forward (LOCF) ANCOVA. Simulation experiments for the repeated measures model with missing at random (MAR) dropout, under varying dropout rates and intrasubject correlation, show that the LOCF, ANCOVA, and weighted GEE methods perform poorly in terms of percent relative bias for estimating a difference in means effect, while the MI-GEE and weighted GEE methods both have less power for rejecting a zero difference in means hypothesis.

Use of composite endpoints in clinical trials.

The success of a confirmatory clinical trial designed to demonstrate the efficacy of a new treatment is highly dependent on the choice of valid primary efficacy endpoint(s). The optimal clinical and statistical situation for the design of such a trial is one that starts with the selection of a single primary efficacy endpoint that completely characterizes the disease under study, admits the most efficient clinical and statistical evaluation of treatment effect, and provides clear and broad interpretation of drug effect. For diseases with multidimensional presentations, however, the selection of such an endpoint may not be possible, and so drug effectiveness is often characterized by the use of composite or multiple efficacy endpoint(s). The use of a composite endpoint with components that are only slightly correlated but not quite dissimilar in their recognized clinical relevance could lead to a more sensitive statistical test and thus, adequately powered trials with smaller sample size. This note discusses the utility of composite endpoints in clinical trials and some of the common approaches for dealing with multiplicity arising from their use.

Extension of adaptive alpha allocation methods for strong control of the family-wise error rate

With recent advancements in clinical trial design and the availability of rigorous statistical methods that provide strong control of the family-wise type I error rate for multiple testing of hypotheses, it is now common for sponsors to design clinical trials with prospectively specified multiple testing of hypotheses of both primary and secondary endpoints and with the intent to obtain labeling claims for secondary endpoints. One of these recent advancements in multiple testing techniques is the adaptive alpha allocation approach (4A) proposed by Li and Mehrotra (Statistics in Medicine 2008; 27:5377-5391), which groups the hypotheses into two families on the basis of perceived trial power and allows the significance level for the second family to be set adaptively on the basis of the largest observed p-value in the first family. We introduce a class of flexible functions that generalize the 4A procedure and can lead to relatively more powerful test statistics. In the case when the test statistics are correlated, we introduce well-defined functions to calculate the significance level for the second family. The numerical computation for our methods is straightforward, making application in practice easy.

Composite and multicomponent end points in clinical trials

In January 2017, the FDA released the draft guidance to industry on multiple end points in clinical trials. A class of multiplicity problems arise from the testing of individual or subset of components of a composite or multicomponent end point. This commentary attempts to further clarify these problems. Discussions include general consideration on the use of the composite and multicomponent end points, situations when multiplicity adjustments are needed, and the relevant multiple testing methods. Copyright

Evaluation of Overall Treatment Effect in MMRM

In longitudinal clinical trials for drug development, the study objective is often to evaluate overall treatment effect across all visits. Despite careful planning and study conduct, the occurrence of incomplete data cannot be completely eliminated. As a direct likelihood method, the mixed-effects model for repeated measures (MMRM) has become one of the preferred approaches for handling missing data in such designs. MMRM is a full multivariate model in nature, which avoids potential bias as a predetermined model, and operates in a more general missing-at-random (MAR) framework. However, if treatment effect is constant over time, overparameterization of treatment by time interaction in MMRM could result in loss of power. In this article, we utilize MMRM estimates and propose an optimal weighting method for combining visit-specific estimates to maximize the power under MAR mechanism. For a special case where the underlying covariance is compound symmetry, we show that the optimal weighting method is asymptotically equal to MMRM. In other words, MMRM has optimal power under this special case. When the underlying covariance is of an unstructured pattern, the optimal weighting method has increased power under MAR and missing-not-at-random (MNAR) mechanisms, and can lead to bias reduction under MNAR. This is especially true when the variance is greater at later time point, which could lead to a smaller weight. We present practical examples using the optimal weighting method to analyze two cystic fibrosis clinical trial data sets.

Brexanolone injection in post-partum depression: two multicentre, double-blind, randomised, placebo-controlled, phase 3 trials

BACKGROUND Post-partum depression is associated with substantial morbidity, and improved pharmacological treatment options are urgently needed. We assessed brexanolone injection (formerly SAGE-547 injection), a positive allosteric modulator of γ-aminobutyric-acid type A (GABAA) receptors, for the treatment of moderate to severe post-partum depression. METHODS We did two double-blind, randomised, placebo-controlled, phase 3 trials, at 30 clinical research centres and specialised psychiatric units in the USA. Eligible women were aged 18-45 years, 6 months post partum or less at screening, with post-partum depression and a qualifying 17-item Hamilton Rating Scale for Depression (HAM-D) score (≥26 for study 1; 20-25 for study 2). Women with renal failure requiring dialysis, anaemia, known allergy to allopregnanolone or to progesterone, or medical history of schizophrenia, bipolar disorder, or schizoaffective disorder were excluded. Patients were randomly assigned (1:1:1) to receive a single intravenous injection of either brexanolone 90 μg/kg per h (BRX90), brexanolone 60 μg/kg per h (BRX60), or matching placebo for 60 h in study 1, or (1:1) BRX90 or matching placebo for 60 h in study 2. Patients, the study team, site staff, and the principal investigator were masked to treatment allocation. The primary efficacy endpoint was the change from baseline in the 17-item HAM-D total score at 60 h, assessed in all patients who started infusion of study drug or placebo, had a valid HAM-D baseline assessment, and had at least one post-baseline HAM-D assessment. The safety population included all randomised patients who started infusion of study drug or placebo. Patients were followed up until day 30. The trials have been completed and are registered with ClinicalTrials.gov, numbers NCT02942004 (study 1) and NCT02942017 (study 2). FINDINGS Participants were enrolled between Aug 1, 2016, and Oct 19, 2017, in study 1, and between July 25, 2016, and Oct 11, 2017, in study 2. We screened 375 women simultaneously across both studies, of whom 138 were randomly assigned to receive either BRX90 (n=45), BRX60 (n=47), or placebo (n=46) in study 1, and 108 were randomly assigned to receive BRX90 (n=54) or placebo (n=54) in study 2. In study 1, at 60 h, the least-squares (LS) mean reduction in HAM-D total score from baseline was 19·5 points (SE 1·2) in the BRX60 group and 17·7 points (1·2) in the BRX90 group compared with 14·0 points (1·1) in the placebo group (difference -5·5 [95% CI -8·8 to -2·2], p=0·0013 for the BRX60 group; -3·7 [95% CI -6·9 to -0·5], p=0·0252 for the BRX90 group). In study 2, at 60 h, the LS mean reduction in HAM-D total score from baseline was 14·6 points (SE 0·8) in the BRX90 group compared with 12·1 points (SE 0·8) for the placebo group (difference -2·5 [95% CI -4·5 to -0·5], p=0·0160). In study 1, 19 patients in the BRX60 group and 22 patients in the BRX90 group had adverse events compared with 22 patients in the placebo group. In study 2, 25 patients in the BRX90 group had adverse events compared with 24 patients in the placebo group. The most common treatment-emergent adverse events in the brexanolone groups were headache (n=7 BRX60 group and n=6 BRX90 group vs n=7 placebo group for study 1; n=9 BRX90 group vs n=6 placebo group for study 2), dizziness (n=6 BRX60 group and n=6 BRX90 group vs n=1 placebo group for study 1; n=5 BRX90 group vs n=4 placebo group for study 2), and somnolence (n=7 BRX60 group and n=2 BRX90 group vs n=3 placebo group for study 1; n=4 BRX90 group vs n=2 placebo group for study 2). In study 1, one patient in the BRX60 group had two serious adverse events (suicidal ideation and intentional overdose attempt during follow-up). In study 2, one patient in the BRX90 group had two serious adverse events (altered state of consciousness and syncope), which were considered to be treatment related. INTERPRETATION Administration of brexanolone injection for post-partum depression resulted in significant and clinically meaningful reductions in HAM-D total score at 60 h compared with placebo, with rapid onset of action and durable treatment response during the study period. Our results suggest that brexanolone injection is a novel therapeutic drug for post-partum depression that has the potential to improve treatment options for women with this disorder. FUNDING Sage Therapeutics, Inc.