Finding the (biomarker-defined) subgroup of patients who benefit from a novel therapy: No time for a game of hide and seek.

An important element of precision medicine is the ability to identify, for a specific therapy, those patients for whom benefits of that therapy meaningfully exceed the risks. To achieve this goal, treatment effect usually is examined across subgroups defined by a variety of factors, including demographic, clinical, or pathologic characteristics or by molecular attributes of patients or their disease. Frequently such subgroups are defined by the measurement of biomarkers. Even though such examination is necessary when pursuing this goal, the evaluation of treatment effect across a variety of subgroups is statistically fraught due to both the danger of inflated false-positive error rate from multiple testing and the inherent insensitivity to how treatment effects differ across subgroups.Pre-specification of subgroup analyses with appropriate control of false-positive (i.e. type I) error is recommended when possible. However, when subgroups are specified by biomarkers, which could be measured by different assays and might lack established interpretation criteria, such as cut-offs, it might not be possible to fully specify those subgroups at the time a new therapy is ready for definitive evaluation in a Phase 3 trial. In these situations, further refinement and evaluation of treatment effect in biomarker-defined subgroups might have to take place within the trial. A common scenario is that evidence suggests that treatment effect is a monotone function of a biomarker value, but optimal cut-offs for therapy decisions are not known. In this setting, hierarchical testing strategies are widely used, where testing is first conducted in a particular biomarker-positive subgroup and then is conducted in the expanded pool of biomarker-positive and biomarker-negative patients, with control for multiple testing. A serious limitation of this approach is the logical inconsistency of excluding the biomarker-negatives when evaluating effects in the biomarker-positives, yet allowing the biomarker-positives to drive the assessment of whether a conclusion of benefit could be extrapolated to the biomarker-negative subgroup.Examples from oncology and cardiology are described to illustrate the challenges and pitfalls. Recommendations are provided for statistically valid and logically consistent subgroup testing in these scenarios as alternatives to reliance on hierarchical testing alone, and approaches for exploratory assessment of continuous biomarkers as treatment effect modifiers are discussed.

Innovations in Pediatric Therapeutics Development: Principles for the Use of Bridging Biomarkers in Pediatric Extrapolation.

Even with recent substantive improvements in health care in pediatric populations, considerable need remains for additional safe and effective interventions for the prevention and treatment of diseases in children. The approval of prescription drugs and biological products for use in pediatric settings, as in adults, requires demonstration of substantial evidence of effectiveness and favorable benefit-to-risk. For diseases primarily affecting children, such evidence predominantly would be obtained in the pediatric setting. However, for conditions affecting both adults and children, pediatric extrapolation uses scientific evidence in adults to enable more efficiently obtaining a reliable evaluation of an intervention's effects in pediatric populations. Bridging biomarkers potentially have an integral role in pediatric extrapolation. In a setting where an intervention reliably has been established to be safe and effective in adults, and where there is substantive evidence that disease processes in pediatric and adult settings are biologically similar, a 'bridging biomarker' should satisfy three additional criteria: effects on the bridging biomarker should capture effects on the principal causal pathway through which the disease process meaningfully influences 'feels, functions, survives' measures; secondly, the experimental intervention should not have important unintended effects on 'feels, functions, survives' measures not captured by the bridging biomarker; and thirdly, in statistical analyses in adults, the intervention's net effect on 'feels, functions, survives' measures should be consistent with what would be predicted by its level of effect on the bridging biomarker. A validated bridging biomarker has considerable potential utility, since an intervention's efficacy could be extrapolated from adult to pediatric populations if evidence in children establishes the intervention not only to be safe but also to have substantive effects on that bridging biomarker. Proper use of bridging biomarkers could increase availability of reliably evaluated therapies approved for use in pediatric settings, enabling children and their caregivers to make informed choices about health care.

U.S. Food and Drug Administration approval summary: omacetaxine mepesuccinate as treatment for chronic myeloid leukemia.

On October 26, 2012, the U.S. Food and Drug Administration (FDA) granted accelerated approval to omacetaxine mepesuccinate (Synribo; Teva Pharmaceuticals USA, Inc., North Wales, PA, http://www.tevausa.com) for the treatment of adult patients with chronic phase (CP) or accelerated phase (AP) chronic myeloid leukemia (CML) with resistance and/or intolerance to two or more tyrosine kinase inhibitors (TKIs). The approval was based on the FDA review of data from 111 patients with CML in CP or in AP who had received two or more prior TKIs, including imatinib. Major cytogenetic response was achieved in 18% of patients with CP, with a median response duration of 12.5 months. Major hematologic response was achieved in 14% of patients with AP, with a median response duration of 4.7 months. The FDA safety evaluation was based on submitted data from 163 patients with CP or AP CML who had received at least one dose of omacetaxine mepesuccinate. The safety evaluation was limited by the single-arm design of the clinical trials as conducted in a small number of previously treated patients. The most common (≥20%) adverse reactions of any grade in enrolled patients included thrombocytopenia, anemia, neutropenia, diarrhea, nausea, fatigue, asthenia, injection site reaction, pyrexia, and infection. The FDA concluded that omacetaxine mepesuccinate has shown activity and a favorable benefit-to-risk profile for the studied population of adult patients with CML (CP or AP) with resistance and/or intolerance to two or more TKIs. Further evidence of response durability to verify clinical benefit is pending.

U.s. Food and Drug Administration approval: carfilzomib for the treatment of multiple myeloma.

The U.S. Food and Drug Administration (FDA) review leading to accelerated approval of carfilzomib is described. A single-arm trial enrolled 266 patients with multiple myeloma refractory to the most recent therapy who had received prior treatment with bortezomib and an immunomodulatory agent (IMID). Patients received carfilzomib by intravenous infusion over 2 to 10 minutes at a dose of 20 mg/m2 on days 1, 2, 8, 9, 15, and 16 of the 28 days of cycle 1, and at a dose of 27 mg/m2 on the same schedule in cycle 2 and subsequent cycles. The primary efficacy endpoint was overall response rate (ORR) as determined by an independent review committee using International Myeloma Working Group Uniform Response Criteria. The safety of carfilzomib was evaluated in 526 patients with multiple myeloma treated with various dosing regimens. The ORR was 23%. The median duration of response was 7.8 months. The most common adverse reactions associated with carfilzomib infusion were fatigue, anemia, nausea, thrombocytopenia, dyspnea, diarrhea, and fever. The most common serious adverse events were pneumonia, acute renal failure, fever, and congestive heart failure. Infusion reactions to carfilzomib could be reduced by pretreatment with dexamethasone and intravenous fluids. On July 20, 2012, the FDA granted accelerated approval of carfilzomib for the treatment of patients with multiple myeloma who have received at least two prior therapies including bortezomib and an IMID and who have shown disease progression while on therapy or within 60 days of completion of the last therapy.

Testing in a Prespecified Subgroup and the Intent-to-Treat Population.

In many settings, testing has been proposed to assess the effect of an experimental regimen within a biomarker-positive subgroup where it is biologically plausible that benefit is stronger in such patients, and in the overall population that also includes biomarker-negative subjects less likely to benefit from that regimen. A statistically favorable result in the biomarker-positive subgroup would lead to a claim for that subgroup, whereas a statistically favorable result for the overall population would lead to a claim that includes both biomarker subgroups. The latter setting is problematic when biomarker-negative patients truly do not benefit from the experimental regimen. When it is prespecified that biomarker-negative patients should not be included in the primary analysis of treatment effect in biomarker-positive patients because of the likelihood that treatment effects would differ between the 2 subgroups, it is logically inconsistent to include biomarker-positive patients in the primary analysis of treatment effect in biomarker-negative patients.

U.S. Food and Drug Administration approval: ruxolitinib for the treatment of patients with intermediate and high-risk myelofibrosis.

On November 16, 2011, the U.S. Food and Drug Administration (FDA) granted full approval to ruxolitinib, (Jakafi; Incyte Corp.), an inhibitor of the Janus kinases 1 and 2, for the treatment of patients with intermediate- or high-risk myelofibrosis, including primary myelofibrosis, postpolycythemia vera myelofibrosis, and postessential thrombocythemia myelofibrosis. This approval was based on the results of 2 large randomized phase III trials that enrolled patients with intermediate-2 or high-risk myelofibrosis and compared ruxolitinib with placebo (study 1) or best available therapy (study 2). The primary efficacy endpoint was the proportion of patients who experienced a reduction in spleen volume of ≥ 35% at 24 weeks (study 1) or 48 weeks (study 2). The key secondary endpoint in study 1 was the proportion of patients who experienced a ≥ 50% improvement from baseline in myelofibrosis total symptom score at 24 weeks. The results of these studies showed that a greater proportion of patients treated with ruxolitinib experienced a ≥ 35% reduction in spleen volume as compared with those treated with placebo (42% vs. 1%, P < 0.0001) or best available therapy (29% vs. 0%, P < 0.0001). A greater proportion of patients in study 1 experienced a ≥ 50% reduction in the myelofibrosis total symptom score during treatment with ruxolitinib than with placebo (46% vs. 5%, P < 0.0001). Ruxolitinib treatment was associated with an increased incidence of grades III and IV anemia, thrombocytopenia, and neutropenia. This is the first drug approved for myelofibrosis.

Some essential considerations in the design and conduct of non-inferiority trials.

BACKGROUND: Suppose a standard therapy (Standard) has been established to provide a clinically important reduction in risk of irreversible morbidity or mortality. In that setting, the safety and efficacy of an experimental intervention likely would be assessed in a clinical trial providing a comparison with Standard rather than a placebo arm. Such a trial often is designed to assess whether the efficacy of the experimental intervention is not unacceptably worse than that of Standard, and is called a non-inferiority trial. Formally, the non-inferiority trial usually is designed to rule out a non-inferiority margin, defined as the minimum threshold for what would constitute an unacceptable loss of efficacy. PURPOSE: Even though the literature has many important articles identifying various approaches to the design and conduct of non-inferiority trials, confusion remains especially regarding key considerations for selecting the non-inferiority margin. The purpose of this article is to provide improved clarity regarding these considerations. METHODS: We present scientific insights into many factors that should be addressed in the design and conduct of non-inferiority trials to enhance their integrity and reliability, and provide motivation for key considerations that guide the selection of non-inferiority margins. We also provide illustrations and insights from recent experiences. RESULTS: Two considerations are essential, and should be addressed in separate steps, in the formulation of the non-inferiority margin. First, the margin should be formulated using adjustments to account for bias or lack of reliability in the estimate of the effect of Standard in the non-inferiority trial setting. Second, the non-inferiority margin should be formulated to achieve preservation of an appropriate percentage of the effect of Standard. LIMITATIONS: The considerations, in particular regarding the importance of preservation of effect, might not apply to settings where it would be ethical as well as clinically relevant to include both Standard and placebo arms in the trial for direct comparisons with the experimental intervention arm. CONCLUSIONS: Non-inferiority trials with non-rigorous margins allow substantial risk for accepting inadequately effective experimental regimens, leading to the risk of erosion in quality of health care. The design and conduct of non-inferiority trials, including selection of non-inferiority margins, should account for many factors that can induce bias in the estimated effect of Standard in the non-inferiority trial and thus lead to bias in the estimated effect of the experimental treatment, for the need to ensure the experimental treatment preserves a clinically acceptable fraction of Standard's effect, and for the particular vulnerability of the integrity of a non-inferiority trial to the irregularities in trial conduct. Due to the inherent uncertainties in non-inferiority trials, alternative designs should be pursued whenever possible.

U.S. Food and drug administration approval: rituximab in combination with fludarabine and cyclophosphamide for the treatment of patients with chronic lymphocytic leukemia.

PURPOSE: To describe the clinical studies that led to the FDA approval of rituximab in combination with fludarabine and cyclophosphamide (FC) for the treatment of patients with chronic lymphocytic leukemia (CLL). MATERIALS AND METHODS: The results of two multinational, randomized trials in CLL patients comparing rituximab combined with fludarabine and cyclophosphamide versus FC were reviewed. The primary endpoint of both studies was progression-free survival (PFS). RESULTS: The addition of rituximab to FC decreased the risk of a PFS event by 44% in 817 previously untreated patients and by 24% in 552 previously treated patients. Median survival times could not be estimated. Exploratory analysis in patients older than 70 suggested that there was no benefit to patients when rituximab was added to FC. The safety profile observed in both trials was consistent with the known toxicity profile of rituximab, FC, or CLL. CONCLUSIONS: On the basis of the demonstration of clinically meaningful prolongation of PFS, the FDA granted regular approval to rituximab in combination with FC for the treatment of patients with CLL. The magnitude of the treatment effect in patients 70 years and older is uncertain.

U.S. Food and Drug Administration approval: ofatumumab for the treatment of patients with chronic lymphocytic leukemia refractory to fludarabine and alemtuzumab.

PURPOSE: To describe the data and analyses that led to the U.S. Food and Drug Administration (FDA) approval of ofatumumab (Arzerra, GlaxoSmithKline) for the treatment of patients with chronic lymphocytic leukemia (CLL) refractory to fludarabine and alemtuzumab. EXPERIMENTAL DESIGN: The FDA reviewed the results of a planned interim analysis of a single-arm trial, enrolling 154 patients with CLL refractory to fludarabine, and a supportive dose-finding, activity-estimating trial in 33 patients with CLL. Patients in the primary efficacy study received ofatumumab weekly for eight doses, then every 4 weeks for an additional four doses; patients in the supportive trial received four weekly doses. In the primary efficacy study, endpoints were objective response rate and response duration. RESULTS: For regulatory purposes, the primary efficacy population consisted of 59 patients with CLL refractory to fludarabine and alemtuzumab. In this subgroup, the investigator-determined objective response rate was 42% [99% confidence interval (CI), 26-60], with a median duration of response of 6.5 months (95% CI, 5.8-8.3); all were partial responses. The most common adverse reactions in the primary efficacy study were neutropenia, pneumonia, pyrexia, cough, diarrhea, anemia, fatigue, dyspnea, rash, nausea, bronchitis, and upper respiratory tract infections. Infusion reactions occurred in 44% of patients with the first infusion (300 mg) and 29% with the second infusion (2,000 mg). The most common serious adverse reactions were infections, neutropenia, and pyrexia. CONCLUSIONS: On October 26, 2009, the FDA granted accelerated approval to ofatumumab for the treatment of patients with CLL refractory to fludarabine and alemtuzumab, on the basis of demonstration of durable tumor shrinkage.

Issues in using progression-free survival when evaluating oncology products.

Several challenging and often controversial issues arise in oncology trials with the use of the end point progression-free survival (PFS), defined to be the time to detection of progressive disease or death. While this end point does not directly measure how a patient feels, functions, or survives, it does provide insights about whether an intervention affects the tumor burden process, the intended mechanism through which it is hoped that most anticancer agents will provide benefit. However, simply achieving statistically significant effects on PFS is insufficient to obtaining reliable evidence of important clinical benefit, and even is insufficient to justifying the conclusion that the experimental intervention is "reasonably likely to provide clinical benefit." The magnitude of the effect on PFS in addition to the statistical strength of evidence is of great importance in interpreting the reliability of the evidence regarding clinical efficacy. PFS has several important properties, including being a direct measure of the effect of treatment on the tumor burden process, being sensitive to cytostatic as well as cytotoxic mechanisms of interventions, and incorporating the clinically relevant event of death, increasing its sensitivity to influential harmful mechanisms and avoiding substantial bias that arises when deaths are censored. To obtain reliable evidence about the effect of an intervention on PFS and patient survival, randomized trials should be conducted where all patients are followed to progression and death, and where patients in a control arm do not cross-in at progression unless the experimental regimen has already been established to be effective rescue treatment.

Missing data in biologic oncology products.

The intent-to-treat principle requires analyses according to the treatment groups to which patients were randomized and that patients be followed to the occurrence of the endpoint or the end of study. This provides unbiased comparisons with valid p values. For many trials the limitations of the data will not be known until the data are analyzed. In this article, the loss-to-follow-up with respect to the intent-to-treat principle on the most important efficacy endpoints was evaluated for clinical trials of anticancer biologic products submitted to the FDA from August 2005 to October 2008. We provide recommendations in light of the results.

Continuing reassessment of the risks of erythropoiesis-stimulating agents in patients with cancer.

PURPOSE: Erythropoiesis-stimulating agents (ESA) are approved for the treatment of anemia in patients with nonmyeloid malignancies whose anemia is due to the effect of concomitantly administered chemotherapy. Since the 1993 approval of epoetin alfa in patients with cancer, the risk of thrombovascular events, decreased survival, and poorer tumor control have been increasingly recognized. The risks of ESAs in patients with cancer and the design of trials to assess these risks have been the topic of discussion at two Oncologic Drugs Advisory Committees in 2004 and 2007. EXPERIMENTAL DESIGN: Evaluation of randomized clinical trials comparing use of ESAs to transfusion support alone in patients with active cancer. RESULTS: Six studies (Breast Cancer Erythropoeitin Survival Trial, Evaluation of NeoRecormon on outcome in Head And Neck Cancer in Europe, Danish Head and Neck Cancer, Lymphoid Malignancy, CAN-20, and Anemia of Cancer) investigating ESAs in oncology patients showed decreased survival, decreased duration of locoregional tumor control, and/or increased risk of thrombovascular events. In these six studies, ESA dosing was targeted to achieve and maintain hemoglobin values in excess of current recommendations, and in three of the six studies, ESAs were administered to patients not receiving chemotherapy. CONCLUSIONS: ESAs increase the risk of thrombovascular events and result in decreased survival and poorer tumor control when administered to achieve hemoglobin levels of > or =12 g/dL in patients with nonmyeloid malignancies. No completed or ongoing randomized, controlled trial has addressed safety issues of ESAs in patients with chemotherapy-associated anemia using currently approved dosing regimens in an epidermal tumor type. Additional studies are needed to better characterize these risks.

Inferences on a life distribution by sampling from the ages or the ages at death.

Consider a system where units having independent and identically distributed lifetimes enter according to a nonhomogeneous Poisson process. After the unit's life in the system, the unit departs the system. For a fixed system time, this paper relates the units' common underlying life distribution with the distribution of the ages of units in the system, the distribution for the system life of units that departed the system and the distribution for the system life of units that have recently departed the system. Results can be used to estimate the underlying life distribution or a truncated version of that distribution based on the ages and/or most recent ages at death in both one sample and two sample situations. Results include a complete characterization of the possible distribution of the ages of those units in the system, how to estimate the underlying life distribution from the most recent ages at death, and how to test for an underlying monotone failure rate function based on independent samples from the ages and most recent ages at death. Two sample inferences that involve a likelihood ratio ordering make use of the results in Dykstra et al. (1995, J Amer Statisc Assoc 90(431):1030-1040), which provides the maximum likelihood estimators and a likelihood ratio test when the two distributions satisfy a likelihood ratio ordering. For the ages of the active units and the ages at death among the departed units, limits for their distributions and strong limiting results for their empirical distributions will be provided.

On non-inferiority analysis based on delta-method confidence intervals.

For many indications where there is an effective standard therapy, active controlled trials are generally conducted when it is unethical to use a placebo. The efficacy objective of most such trials is the demonstration that the experimental therapy has superior efficacy to the active-control. The efficacy objective of a non-inferiority trial may be to rule out that the experimental treatment loses some prespecified fraction of the active-control effect. The size of the active-control effect may be based on previous trials comparing this active-control with a placebo--for example, through a meta-analysis. Delta-method 95% confidence interval procedures are among the testing procedures that have been proposed to test a non-inferiority hypothesis that an experimental treatment retains more than some prespecified fraction of the active-control effect. For time-to-event endpoints using hazard ratios, we will examine the type I error probability of such testing procedures under the assumption that the current active-control effect has been correctly modeled. Conditions are discussed for when such testing procedures maintain a desired approximate type I error rate and when such testing procedures will not. Two applications (one in Cardiorenalogy and one in Oncology) are given--one maintains the desired approximate type I error probability and the other does not. The delta-method 95% confidence interval procedures will also be contrasted with Fieller 95% confidence intervals. Testing based on Fieller 95% confidence intervals will maintain a desired approximate type I error rate.