Historical Controls in Randomized Clinical Trials: Opportunities and Challenges

Alzheimer's Disease: Combination Therapies and Clinical Trials for Combination Therapy Development

Alzheimer's disease (AD) is a complex multifaceted disease. Recently approved anti-amyloid monoclonal antibodies slow disease progression by approximately 30%, and combination therapy appears necessary to prevent the onset of AD or produce greater slowing of cognitive and functional decline. Combination therapies may address core features, non-specific co-pathology commonly occurring in patients with AD (e.g., inflammation), or non-AD pathologies that may co-occur with AD (e.g., α-synuclein). Combination therapies may be advanced through co-development of more than one new molecular entity or through add-on strategies including an approved agent plus a new molecular entity. Addressing add-on combination therapy is currently urgent since patients on anti-amyloid monoclonal antibodies may be included in clinical trials for experimental agents. Phase 1 information must be generated for each agent in combination drug development. Phase 2 and Phase 3 of add-on therapies may contrast the new molecular entity, the approved agent as standard of care, and the combination. More complex development programs including standard or modified combinatorial designs are required for co-development of two or more new molecular entities. Biomarkers are markedly affected by anti-amyloid monoclonal antibodies, and these effects must be anticipated in add-on trials. Examining target engagement biomarkers and comparing the magnitude and sequence of biomarker changes in those receiving more than one therapy, compared with those on monotherapy, may be informative. Using network-based medicine approaches, computational strategies may identify rational combinations using disease and drug effect network mapping.

Long-Term Nicotinamide Riboside Use Improves Coordination and Eye Movements in Ataxia Telangiectasia

BACKGROUND

Supplementation of nicotinamide riboside (NR) ameliorates neuropathology in animal models of ataxia telangiectasia (A-T). In humans, short-term NR supplementation showed benefits in neurological outcome.

OBJECTIVES

The study aimed to investigate the safety and benefits of long-term NR supplementation in individuals with A-T.

METHODS

A single-arm, open-label clinical trial was performed in individuals with A-T, receiving NR over a period of 2 years. Biomarkers and clinical examinations were used to assess safety parameters. Standardized and validated neuromotor tests were used to monitor changes in neurological symptoms. Using generalized mixed models, test results were compared to expected disease progression based on historical data.

RESULTS

NAD+ concentrations increased rapidly in peripheral blood and stabilized at a higher level than baseline. NR supplementation was well tolerated for most participants. The total scores in the neuromotor test panels, as evaluated at the 18-month time point, improved for all but one participant, primarily driven by improvements in coordination subscores and eye movements. A comparison with historical data revealed that the progression of certain neuromotor symptoms was slower than anticipated.

CONCLUSIONS

Long-term use of NR appears to be safe and well tolerated, and it improves motor coordination and eye movements in patients with A-T of all ages. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Placebo analgesia and nocebo hyperalgesia in patients with Alzheimer disease and healthy participants

ABSTRACT

The role of placebo analgesia and nocebo hyperalgesia in patients with Alzheimer disease (AD) is largely unknown, with only few studies in the area. Therefore, this study aims to investigate to which extent placebo analgesia and nocebo hyperalgesia effects are present in patients experiencing mild-to-moderate AD. Twenty-one patients with AD (test population) and 26 healthy participants (HP; design validation) were exposed to thermal pain stimulation on 3 test days: Lidocaine condition (open/hidden lidocaine administration), capsaicin condition (open/hidden capsaicin administration), and natural history (no treatment), in a randomized, within-subject design. Open lidocaine and open capsaicin were accompanied by verbal suggestions for pain relief and pain increase, respectively. Expected pain and actual pain intensity were measured on a numerical rating scale (0-10). Placebo and nocebo effects were calculated as pain differences in open-hidden lidocaine and capsaicin, respectively, controlled for no treatment. Healthy participants obtained a placebo effect ( P = 0.01) and a trend for a nocebo effect ( P = 0.07). Patients with AD did not obtain a placebo effect ( P = 0.44) nor a significant nocebo effect ( P = 0.86). Healthy participants expected lower and higher pain with open vs hidden lidocaine and capsaicin, respectively ( P < 0.001). The same expectation effects were seen in patients with AD (open vs hidden lidocaine, P = 0.008; open vs hidden capsaicin, P < 0.001). With a well-controlled experimental setting, this study suggests that patients with AD may not experience placebo analgesia effects. Nocebo hyperalgesia effects in patients with AD needs further research. These findings may have implications for the conduction of clinical trials and the treatment of patients with AD in clinical practice.

Decoupling power and type I error rate considerations when incorporating historical control data using a test-then-pool approach

To accelerate a randomized controlled trial, historical control data may be used after ensuring little heterogeneity between the historical and current trials. The test-then-pool approach is a simple frequentist borrowing method that assesses the similarity between historical and current control data using a two-sided test. A limitation of the conventional test-then-pool method is the inability to control the type I error rate and power for the primary hypothesis separately and flexibly for heterogeneity between trials. This is because the two-sided test focuses on the absolute value of the mean difference between the historical and current controls. In this paper, we propose a new test-then-pool method that splits the two-sided hypothesis of the conventional method into two one-sided hypotheses. Testing each one-sided hypothesis with different significance levels allows for the separate control of the type I error rate and power for heterogeneity between trials. We also propose a significance-level selection approach based on the maximum type I error rate and the minimum power. The proposed method prevented a decrease in power even when there was heterogeneity between trials while controlling type I error at a maximum tolerable type I error rate larger than the targeted type I error rate. The application of depression trial data and hypothetical trial data further supported the usefulness of the proposed method.

In Silico Clinical Trials: Is It Possible?

Modeling and simulation (M&S), including in silico (clinical) trials, helps accelerate drug research and development and reduce costs and have coined the term "model-informed drug development (MIDD)." Data-driven, inferential approaches are now becoming increasingly complemented by emerging complex physiologically and knowledge-based disease (and drug) models, but differ in setup, bottlenecks, data requirements, and applications (also reminiscent of the different scientific communities they arose from). At the same time, and within the MIDD landscape, regulators and drug developers start to embrace in silico trials as a potential tool to refine, reduce, and ultimately replace clinical trials. Effectively, silos between the historically distinct modeling approaches start to break down. Widespread adoption of in silico trials still needs more collaboration between different stakeholders and established precedence use cases in key applications, which is currently impeded by a shattered collection of tools and practices. In order to address these key challenges, efforts to establish best practice workflows need to be undertaken and new collaborative M&S tools devised, and an attempt to provide a coherent set of solutions is provided in this chapter. First, a dedicated workflow for in silico clinical trial (development) life cycle is provided, which takes up general ideas from the systems biology and quantitative systems pharmacology space and which implements specific steps toward regulatory qualification. Then, key characteristics of an in silico trial software platform implementation are given on the example of jinkō.ai (nova's end-to-end in silico clinical trial platform). Considering these enabling scientific and technological advances, future applications of in silico trials to refine, reduce, and replace clinical research are indicated, ranging from synthetic control strategies and digital twins, which overall shows promise to begin a new era of more efficient drug development.

Hybrid Controlled Clinical Trials Using Concurrent Registries in Amyotrophic Lateral Sclerosis: A Feasibility Study

Hybrid designs with both randomized arms and an external control cohort preserve key features of randomization and utilize external information to augment clinical trials. In this study, we propose to leverage high-quality, patient-level concurrent registries to enhance clinical trials and illustrate the impact on trial design for amyotrophic lateral sclerosis. The proposed methodology was evaluated in a randomized, placebo-controlled clinical trial. We used patient-level information from a well-defined, population-based registry, that was running parallel to the randomized clinical trial, to identify concurrently nonparticipating, eligible patients who could be matched with trial participants, and integrate them into the statistical analysis. We assessed the impact of the addition of the external controls on the treatment effect estimate, precision, and time to reach a conclusion. During the runtime of the trial, a total of 1,141 registry patients were alive; 473 (41.5%) of them fulfilled the eligibility criteria and 133 (11.7%) were enrolled in the study. A matched control population could be identified among the nonparticipating patients. Augmenting the randomized controls with matched external controls could have avoided unnecessary randomization of 17 patients (-12.8%) as well as reducing the study duration from 30.1 months to 22.6 months (-25.0%). Matching eligible external controls from a different calendar period led to bias in the treatment effect estimate. Hybrid trial designs utilizing a concurrent registry with rigorous matching can minimize bias due to a mismatch in calendar time and differences in standard of care, and may accelerate the development of new treatments.

Efficacy and safety of first-line immunotherapy plus chemotherapy in treating patients with extensive-stage small cell lung cancer: a Bayesian network meta-analysis

Background

Despite numerous immunotherapy and chemotherapy regimens available for patients with extensive-stage small cell lung cancer (ES-SCLC), it remains unclear which regimen is the most effective and safest; relative studies comparing such regimens are scarce.

Objective

The aim of this study was to investigate the efficacy and safety of first-line immunotherapy combinations with chemotherapy for patients with extensive-stage small cell lung cancer. In addition, for the first time, comparisons among the first-line systemic regimens on OS and PFS in ES-SCLC by each time node were made.

Methods

Databases including PubMed, Embase, Cochrane Library, Scopus, Google Scholars, and ClinicalTrials.gov, and major international conferences were searched for randomized controlled trials (RCTs) regarding comparing immunotherapy combinations with chemotherapy as first-line treatments for patients with advanced ES-SCLC from inception to 1 November. Hazard ratios (HRs) and odds ratios (ORs) were generated for dichotomous variants by RStudio 4.2.1. The outcomes comprised overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and adverse events of grade 3 or higher (Grade ≥ 3 AEs).

Results

Eventually, a total of nine RCTs reporting 4,352 individuals with nine regimens were enrolled. The regimens were ipilimumabnu (Ipi), atezolizumab (Atez), durvalumab plus tremelimumab (Durv-Trem), durvalumab (Durv), pembrolizumab (Pemb), adebrelimab (Adeb), serplulimab (Serp), atezolizumab plus tiragolumab (Atez-Tira), and nivolumab (Nivo). With regard to OS, serplulimab (HR = 0.63, 95% CI: 0.49 to 0.81) was found to yield the best OS benefit when compared with chemotherapy. Meanwhile, serplulimab had the highest probability (46.11%) for better OS. Furthermore, compared with chemotherapy, serplulimab significantly increased the OS rate from the 6th to the 21st month. With regard to PFS, serplulimab (HR = 0.47, 95% CI: 0.38 to 0.59) was found to yield the best PFS benefit when compared with chemotherapy. Simultaneously, serplulimab had the highest probability (94.48%) for better PFS. Serplulimab was also a long-lasting first-line regimen in both OS and PFS from a longitudinal perspective. In addition, there was no significant difference among the various treatment options for ORR and grade ≥3 AEs.

Conclusion

Considering OS, PFS, ORR, and safety profiles, serplulimab with chemotherapy should be recommended as the best therapy for patients with ES-SCLC. Certainly, more head-to-head studies are needed to confirm these findings.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022373291.

Dynamic use of historical controls in clinical trials for rare disease research: A re-evaluation of the MILES trial

BACKGROUND

Randomized controlled trials offer the best design for eliminating bias in estimating treatment effects but can be slow and costly in rare disease research. Additionally, an equal randomization approach may not be optimal in studies in which prior evidence of superiority of one or more treatments exist. Supplementing prospectively enrolled, concurrent controls with historical controls can reduce recruitment requirements and provide patients a higher likelihood of enrolling in a new and possibly superior treatment arm. Appropriate methods need to be employed to ensure comparability of concurrent and historical controls to minimize bias and variability in the treatment effect estimates and reduce the chances of drawing incorrect conclusions regarding treatment benefit.

METHODS

MILES was a phase III placebo-controlled trial employing 1:1 randomization that led to US Food and Drug Administration approval of sirolimus for treating patients with lymphangioleiomyomatosis. We re-analyzed the MILES trial data to learn whether substituting concurrent controls with controls from a historical registry could have accelerated subject enrollment while leading to similar study conclusions. We used propensity score matching to identify exchangeable historical controls from a registry balancing the baseline characteristics of the two control groups. This allowed more new patients to be assigned to the sirolimus arm. We used trial data and simulations to estimate key outcomes under an array of alternative designs.

RESULTS

Borrowing information from historical controls would have allowed the trial to enroll fewer concurrent controls while leading to the same conclusion reached in the trial. Simulations showed similar statistical performance for borrowing as for the actual trial design without producing type I error inflation and preserving power for the same study size when concurrent and historical controls are comparable.

CONCLUSION

Substituting concurrent controls with propensity score-matched historical controls can allow more prospectively enrolled patients to be assigned to the active treatment and enable the trial to be conducted with smaller overall sample size, while maintaining covariate balance and study power and minimizing bias in response estimation. This approach does not fully eliminate the concern that introducing non-randomized historical controls in a trial may lead to bias in estimating treatment effects, and should be carefully considered on a case-by-case basis. Borrowing historical controls is best suited when conducting randomized controlled trials with conventional designs is challenging, as in rare disease research. High-quality data on covariates and outcomes must be available for candidate historical controls to ensure the validity of these designs. Additional precautions are needed to maintain blinding of the treatment assignment and to ensure comparability in the assessment of treatment safety.MILES ClinicalTrials.gov Number: NCT00414648.

Discovering chronic pain treatments: better animal models might help us get there

Only three classes of pain medications have made it into clinical use in the past 60 years despite intensive efforts and the need for nonaddictive pain treatments. One reason for the failure involves the use of animal models that lack mechanistic similarity to human pain conditions, with endpoint measurements that may not reflect the human pain experience. In this issue of the JCI, Ding, Fischer, and co-authors developed the foramen lacerum impingement of trigeminal nerve root (FLIT) model of human trigeminal neuralgia that has improved face, construct, and predictive validities over those of current models. They used the FLIT model to investigate the role that abnormal, hypersynchronous cortical activity contributed to a neuropathic pain state. Unrestrained, synchronous glutamatergic activity in the primary somatosensory cortex upper lip and jaw (S1ULp-S1J) region of the somatosensory cortex drove pain phenotypes. The model establishes a powerful tool to continue investigating the interaction between the peripheral and central nervous systems that leads to chronic pain.

The Randomised Controlled Trial at the Intersection of Research Ethics and Innovation

The randomised controlled trial (RCT) has been considered for a long time as the gold standard for evidence generation to support regulatory decision making for medicines. The randomisation procedure involves an ethical dilemma since it means leaving the treatment choice to chance. Although currently contested, the ethical justification for the RCT that has gained widespread acceptance is the notion of 'clinical equipoise'. This state exists when "there is no consensus within the expert clinical community about the comparative merits of the alternatives to be tested"; it is argued that this confers the ethical grounds for the conduct of an RCT. The prominent position of the RCT is being challenged by new therapeutic modalities for which this study design may be unsuitable. Moreover, alternative approaches to evidence generation represent another area where innovation may have implications for the relevance of the RCT. Against the backdrop of the debate around the equipoise principle and some recent therapeutic and data analytical innovations, the aim of this article is to explore the current standing of the RCT from a regulatory perspective.

On model-based time trend adjustments in platform trials with non-concurrent controls

BACKGROUND

Platform trials can evaluate the efficacy of several experimental treatments compared to a control. The number of experimental treatments is not fixed, as arms may be added or removed as the trial progresses. Platform trials are more efficient than independent parallel group trials because of using shared control groups. However, for a treatment entering the trial at a later time point, the control group is divided into concurrent controls, consisting of patients randomised to control when that treatment arm is in the platform, and non-concurrent controls, patients randomised before. Using non-concurrent controls in addition to concurrent controls can improve the trial's efficiency by increasing power and reducing the required sample size, but can introduce bias due to time trends.

METHODS

We focus on a platform trial with two treatment arms and a common control arm. Assuming that the second treatment arm is added at a later time, we assess the robustness of recently proposed model-based approaches to adjust for time trends when utilizing non-concurrent controls. In particular, we consider approaches where time trends are modeled either as linear in time or as a step function, with steps at time points where treatments enter or leave the platform trial. For trials with continuous or binary outcomes, we investigate the type 1 error rate and power of testing the efficacy of the newly added arm, as well as the bias and root mean squared error of treatment effect estimates under a range of scenarios. In addition to scenarios where time trends are equal across arms, we investigate settings with different time trends or time trends that are not additive in the scale of the model.

RESULTS

A step function model, fitted on data from all treatment arms, gives increased power while controlling the type 1 error, as long as the time trends are equal for the different arms and additive on the model scale. This holds even if the shape of the time trend deviates from a step function when patients are allocated to arms by block randomisation. However, if time trends differ between arms or are not additive to treatment effects in the scale of the model, the type 1 error rate may be inflated.

CONCLUSIONS

The efficiency gained by using step function models to incorporate non-concurrent controls can outweigh potential risks of biases, especially in settings with small sample sizes. Such biases may arise if the model assumptions of equality and additivity of time trends are not satisfied. However, the specifics of the trial, scientific plausibility of different time trends, and robustness of results should be carefully considered.

Bayesian Design of Superiority Trials: Methods and Applications

In this paper, we lay out the basic elements of Bayesian sample size determination (SSD) for the Bayesian design of a two-arm superiority clinical trial. We develop a flowchart of the Bayesian SSD that highlights the critical components of a Bayesian design and provides a practically useful roadmap for designing a Bayesian clinical trial in real world applications. We empirically examine the amount of borrowing, the choice of noninformative priors, and the impact of model misspecification on the Bayesian type I error and power. A formal and statistically rigorous formulation of conditional borrowing within the decision rule framework is developed. Moreover, by extending the partial borrowing power priors, a new borrowing-by-parts power prior for incorporating historical data is proposed. Computational algorithms are also developed to calculate the Bayesian type I error and power. Extensive simulation studies are carried out to explore the operating characteristics of the proposed Bayesian design of a superiority trial.

NHLBI-CMREF Workshop Report on Pulmonary Vascular Disease Classification: JACC State-of-the-Art Review

The National Heart, Lung, and Blood Institute and the Cardiovascular Medical Research and Education Fund held a workshop on the application of pulmonary vascular disease omics data to the understanding, prevention, and treatment of pulmonary vascular disease. Experts in pulmonary vascular disease, omics, and data analytics met to identify knowledge gaps and formulate ideas for future research priorities in pulmonary vascular disease in line with National Heart, Lung, and Blood Institute Strategic Vision goals. The group identified opportunities to develop analytic approaches to multiomic datasets, to identify molecular pathways in pulmonary vascular disease pathobiology, and to link novel phenotypes to meaningful clinical outcomes. The committee suggested support for interdisciplinary research teams to develop and validate analytic methods, a national effort to coordinate biosamples and data, a consortium of preclinical investigators to expedite target evaluation and drug development, longitudinal assessment of molecular biomarkers in clinical trials, and a task force to develop a master clinical trials protocol for pulmonary vascular disease.