Clinical trial designs to assess treatment effects on glomerular filtration rate decline.

Glomerular filtration rate (GFR) decline is used as surrogate endpoint for kidney failure. Interventions that reduce chronic kidney disease (CKD) progression often exert acute GFR reductions which differ from their long-term benefits and complicate the estimation of long-term benefit. Here, we assessed the utility of two alternative trial designs (wash-out design and active run-in randomized withdrawal design) that attempt to exclude the impact of acute effects. Post-hoc analyses of two clinical trials that characterized the effect of an intervention with acute reductions in GFR were conducted. The two trials included a wash-out period (EMPA-REG Outcome testing empagliflozin vs placebo) or an active run-in period with a randomized withdrawal (SONAR testing atrasentan vs placebo). We compared the drug effect on GFR decline calculated from the first on-treatment visit to the end of treatment (chronic slope in a standard randomized trial design) with GFR change calculated from randomization to end of wash out, or GFR change from treatment-specific baseline GFR values (GFR at start-of-run-in for placebo and end-of-run-in for atrasentan) until end-of-treatment. The effect of empagliflozin versus placebo on chronic GFR slope was 1.72 (95% confidence interval 1.49-1.94) mL/min/1.73 m2/year, similar to total GFR decline from baseline to the end of wash-out period using a linear mixed model 1.64 (1.44-1.85) mL/min/1.73 m2/year). The effect of atrasentan versus placebo on chronic GFR slope was 0.72 (0.32-1.11) mL/min/1.73 m2/year, similar to total slope from a single slope model when estimated from treatment specific baseline GFR values 0.77 (0.39-1.14) mL/min/1.73 m2/year). Statistical power of the two designs outperformed the standard randomized design. Thus, wash-out and active-run-in randomized-withdrawal trial designs are appropriate models to compute treatment effects on GFR decline.

The Role of AI in Drug Discovery.

The emergence of Artificial Intelligence (AI) in drug discovery marks a pivotal shift in pharmaceutical research, blending sophisticated computational techniques with conventional scientific exploration to break through enduring obstacles. This review paper elucidates the multifaceted applications of AI across various stages of drug development, highlighting significant advancements and methodologies. It delves into AI's instrumental role in drug design, polypharmacology, chemical synthesis, drug repurposing, and the prediction of drug properties such as toxicity, bioactivity, and physicochemical characteristics. Despite AI's promising advancements, the paper also addresses the challenges and limitations encountered in the field, including data quality, generalizability, computational demands, and ethical considerations. By offering a comprehensive overview of AI's role in drug discovery, this paper underscores the technology's potential to significantly enhance drug development, while also acknowledging the hurdles that must be overcome to fully realize its benefits.

Longitudinal course of neurofilament light chain levels in amyotrophic lateral sclerosis-insights from a completed randomized controlled trial with rasagiline.

BACKGROUND AND PURPOSE: Rasagiline might be disease modifying in patients with amyotrophic lateral sclerosis (ALS). The aim was to evaluate the effect of rasagiline 2 mg/day on neurofilament light chain (NfL), a prognostic biomarker in ALS. METHODS: In 65 patients with ALS randomized in a 3:1 ratio to rasagiline 2 mg/day (n = 48) or placebo (n = 17) in a completed randomized controlled multicentre trial, NfL levels in plasma were measured at baseline, month 6 and month 12. Longitudinal changes in NfL levels were evaluated regarding treatment and clinical parameters. RESULTS: Baseline NfL levels did not differ between the study arms and correlated with disease progression rates both pre-baseline (r = 0.64, p < 0.001) and during the study (r = 0.61, p < 0.001). NfL measured at months 6 and 12 did not change significantly from baseline in both arms, with a median individual NfL change of +1.4 pg/mL (interquartile range [IQR] -5.6, 14.2) across all follow-up time points. However, a significant difference in NfL change at month 12 was observed between patients with high and low NfL baseline levels treated with rasagiline (high [n = 13], -6.9 pg/mL, IQR -20.4, 6.0; low [n = 18], +5.9 pg/mL, IQR -1.4, 19.7; p = 0.025). Additionally, generally higher longitudinal NfL variability was observed in patients with high baseline levels, whereas disease progression rates and disease duration at baseline had no impact on the longitudinal NfL course. CONCLUSION: Post hoc NfL measurements in completed clinical trials are helpful in interpreting NfL data from ongoing and future interventional trials and could provide hypothesis-generating complementary insights. Further studies are warranted to ultimately differentiate NfL response to treatment from other factors.

Methods, design, and initial results of an angiographic core lab from VOYAGER-PAD.

Background: Anatomy is critical in risk stratification and therapeutic decision making in coronary disease. The relationship between anatomy and outcomes is not well described in PAD. We sought to develop an angiographic core lab within the VOYAGER-PAD trial. The current report describes the methods of creating this core lab, its study population, and baseline anatomic variables. Methods: Patients undergoing lower-extremity revascularization for symptomatic PAD were randomized in VOYAGER-PAD. The median follow up was 2.25 years. Events were adjudicated by a blinded Clinical Endpoint Committee. Angiograms were collected from study participants; those with available angiograms formed this core lab cohort. Angiograms were scored for anatomic and flow characteristics by trained reviewers blinded to treatment. Ten percent of angiograms were evaluated independently by two reviewers; inter-rater agreement was assessed. Clinical characteristics and the treatment effect of rivaroxaban were compared between the core lab cohort and noncore lab participants. Anatomic data by segment were analyzed. Results: Of 6564 participants randomized in VOYAGER-PAD, catheter-based angiograms from 1666 patients were obtained for this core lab. Anatomic and flow characteristics were collected across 16 anatomic segments by 15 reviewers. Concordance between reviewers for anatomic and flow variables across segments was 90.5% (24,417/26,968). Clinical characteristics were similar between patients in the core lab and those not included. The effect of rivaroxaban on the primary efficacy and safety outcomes was also similar. Conclusions: The VOYAGER-PAD angiographic core lab provides an opportunity to correlate PAD anatomy with independently adjudicated outcomes and provide insights into therapy for PAD. (ClinicalTrials.gov Identifier: NCT02504216).

Applications of the partial-order continual reassessment method in the early development of treatment combinations.

Combination therapy is increasingly being explored as a promising approach for improving cancer treatment outcomes. However, identifying effective dose combinations in early oncology drug development is challenging due to limited sample sizes in early-phase clinical trials. This task becomes even more complex when multiple agents are being escalated simultaneously, potentially leading to a loss of monotonic toxicity order with respect to the dose. Traditional single-agent trial designs are insufficient for this multi-dimensional problem, necessitating the development and implementation of dose-finding methods specifically designed for drug combinations. While, in practice, approaches to this problem have focused on preselecting combinations with a known toxicity order and applying single-agent designs, this limits the number of combinations considered and may miss promising dose combinations. In recent years, several novel designs have been proposed for exploring partially ordered drug combination spaces with the goal of identifying a maximum tolerated dose combination, based on safety, or an optimal dose combination, based on toxicity and efficacy. However, their implementation in clinical practice remains limited. In this article, we describe the application of the partial order continual reassessment method and its extensions for combination therapies in early-phase clinical trials. We present completed trials that use safety endpoints to identify maximum tolerated dose combinations and adaptively use both safety and efficacy endpoints to determine optimal treatment strategies. We discuss the effectiveness of the partial-order continual reassessment method and its extensions in identifying optimal treatment strategies and provide our experience with executing these novel adaptive designs in practice. By utilizing innovative dose-finding methods, researchers and clinicians can more effectively navigate the challenges of combination therapy development, ultimately improving patient outcomes in the treatment of cancer.

Optimizing the doses of cancer drugs after usual dose finding.

Since the middle of the 20th century, oncology's dose-finding paradigm has been oriented toward identifying a drug's maximum tolerated dose, which is then carried forward into phase 2 and 3 trials and clinical practice. For most modern precision medicines, however, maximum tolerated dose is far greater than the minimum dose needed to achieve maximal benefit, leading to unnecessary side effects. Regulatory change may decrease maximum tolerated dose's predominance by enforcing dose optimization of new drugs. Dozens of already approved cancer drugs require re-evaluation, however, introducing a new methodologic and ethical challenge in cancer clinical trials. In this article, we assess the history and current landscape of cancer drug dose finding. We provide a set of strategic priorities for postapproval dose optimization trials of the future. We discuss ethical considerations for postapproval dose optimization trial design and review three major design strategies for these unique trials that would both adhere to ethical standards and benefit patients and funders. We close with a discussion of financial and reporting considerations in the realm of dose optimization. Taken together, we provide a comprehensive, bird's eye view of the postapproval dose optimization trial landscape and offer our thoughts on the next steps required of methodologies and regulatory and funding regimes.

A comparison of alternative ranking methods in two-stage clinical trials with multiple interventions: An application to the anxiolysis for laceration repair in children trial.

BACKGROUND/AIMS: Multi-arm, multi-stage trials frequently include a standard care to which all interventions are compared. This may increase costs and hinders comparisons among the experimental arms. Furthermore, the standard care may not be evident, particularly when there is a large variation in standard practice. Thus, we aimed to develop an adaptive clinical trial that drops ineffective interventions following an interim analysis before selecting the best intervention at the final stage without requiring a standard care. METHODS: We used Bayesian methods to develop a multi-arm, two-stage adaptive trial and evaluated two different methods for ranking interventions, the probability that each intervention was optimal (Pbest) and using the surface under the cumulative ranking curve (SUCRA), at both the interim and final analysis. The proposed trial design determines the maximum sample size for each intervention using the Average Length Criteria. The interim analysis takes place at approximately half the pre-specified maximum sample size and aims to drop interventions for futility if either Pbest or the SUCRA is below a pre-specified threshold. The final analysis compares all remaining interventions at the maximum sample size to conclude superiority based on either Pbest or the SUCRA. The two ranking methods were compared across 12 scenarios that vary the number of interventions and the assumed differences between the interventions. The thresholds for futility and superiority were chosen to control type 1 error, and then the predictive power and expected sample size were evaluated across scenarios. A trial comparing three interventions that aim to reduce anxiety for children undergoing a laceration repair in the emergency department was then designed, known as the Anxiolysis for Laceration Repair in Children Trial (ALICE) trial. RESULTS: As the number of interventions increases, the SUCRA results in a higher predictive power compared with Pbest. Using Pbest results in a lower expected sample size when there is an effective intervention. Using the Average Length Criterion, the ALICE trial has a maximum sample size for each arm of 100 patients. This sample size results in a 86% and 85% predictive power using Pbest and the SUCRA, respectively. Thus, we chose Pbest as the ranking method for the ALICE trial. CONCLUSION: Bayesian ranking methods can be used in multi-arm, multi-stage trials with no clear control intervention. When more interventions are included, the SUCRA results in a higher power than Pbest. Future work should consider whether other ranking methods may also be relevant for clinical trial design.

External Control Arms in Idiopathic Pulmonary Fibrosis Using Clinical Trial and Real-World Data Sources.

Rationale: Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease for which novel therapies are needed. External controls (ECs) could enhance IPF trial efficiency, but the direct comparability of ECs versus concurrent controls is unknown. Objectives: To develop IPF ECs by fit-for-purpose data standards to historical randomized clinical trial (RCT), multicenter registry (Pulmonary Fibrosis Foundation Patient Registry), and electronic health record (EHR) data and to evaluate endpoint comparability among ECs and the phase II RCT of BMS-986020. Methods: After data curation, the rate of change in FVC from baseline to 26 weeks among participants receiving BMS-986020 600 mg twice daily was compared with the BMS-placebo arm and ECs using mixed-effects models with inverse probability weights. Measurements and Main Results: At 26 weeks, the rates of change in FVC were -32.71 ml for BMS-986020 and -130.09 ml for BMS-placebo (difference, 97.4 ml; 95% confidence interval [CI], 24.6-170.2), replicating the original BMS-986020 RCT. RCT ECs showed treatment effect point estimates within the 95% CI of the original BMS-986020 RCT. Pulmonary Fibrosis Foundation Patient Registry ECs and EHR ECs experienced a slower rate of FVC decline compared with the BMS-placebo arm, resulting in treatment-effect point estimates outside of the 95% CI of the original BMS-986020 RCT. Conclusions: IPF ECs generated from historical RCT placebo arms result in comparable primary treatment effects to that of the original clinical trial, whereas ECs from real-world data sources, including registry or EHR data, do not. RCT ECs may serve as a potentially useful supplement to future IPF RCTs.

Factors Influencing Willingness to Participate in Clinical Studies in Pediatric Anesthesia (FILIPPA): A vignette-based, structured interview study.

BACKGROUND: Informed consent is a relevant backdrop for conducting clinical trials, particularly those involving children. While several factors are known to influence the willingness to consent to pediatric anesthesia studies, the influence of study design on consenting behavior is unknown. AIMS: To quantify the impact of study complexity on willingness to consent to pediatric anesthesia studies. METHODS: We conducted a vignette-based interview study by presenting three hypothetical studies to 106 parents or legal guardians whose children were scheduled to undergo anesthesia. These studies differed in level of complexity and included an example of a prospective observational study, a randomized controlled trial, and a phase-II-pharmacological study. Primary outcome was the willingness to consent, using a 5-point Likert scale ranging from "absolutely consent" to "absolutely decline". Secondary outcomes were the effects of child-related (such as sex, age, previous anesthesia, research exposure) and proxy-related factors. RESULTS: Response probabilities for "absolute consent" were 90.9% [95% CI 85.3-96.5] for the observational study, 48.6% [95% CI 38.3-58.9] for the randomized controlled trial, and 32.7% [95% CI 23.9-41.6] for the phase-II-pharmacological study. Response probabilities for "absolutely decline" were 1.6% [95% CI 0.3-2.8], 14.4% [95% CI 8.3-20.5], and 24.7% [95% CI 16.6-32.7], respectively. Significant effects were found for previous research exposure (OR = 0.486 [95% CI 0.256-0.923], p = .027), older age (OR = 0.963 [95% CI 0.927-0.999], p = .045) and the gender of the parent or legal guardian, as mothers were less willing to consent (OR = 0.234 [95% CI 0.107-0.512], p < .001). CONCLUSIONS: Willingness to consent decreased with increasing level of study complexity. When conducting more complex studies, greater efforts need to be made to increase the enrollment of pediatric patients.

A conservative approach to leveraging external evidence for effective clinical trial design.

Prior probabilities of clinical hypotheses are not systematically used for clinical trial design yet, due to a concern that poor priors may lead to poor decisions. To address this concern, a conservative approach to Bayesian trial design is illustrated here, requiring that the operational characteristics of the primary trial outcome are stronger than the prior. This approach is complementary to current Bayesian design methods, in that it insures against prior-data conflict by defining a sample size commensurate to a discrete design prior. This approach is ethical, in that it requires designs appropriate to achieving pre-specified levels of clinical equipoise imbalance. Practical examples are discussed, illustrating design of trials with binary or time to event endpoints. Moderate increases in phase II study sample size are shown to deliver strong levels of overall evidence for go/no-go clinical development decisions. Levels of negative evidence provided by group sequential confirmatory designs are found negligible, highlighting the importance of complementing efficacy boundaries with non-binding futility criteria.

Efficient Study Design and Analysis of Longitudinal Dose-Response Data Using Fractional Polynomials.

Correctly characterising the dose-response relationship and taking the correct dose forward for further study is a critical part of the drug development process. We use optimal design theory to compare different designs and show that using longitudinal data from all available timepoints in a continuous-time dose-response model can substantially increase the efficiency of estimation of the dose-response compared to a single timepoint model. We give theoretical results to calculate the efficiency gains for a large class of these models. For example, a linearly growing Emax dose-response in a population with a between/within-patient variance ratio ranging from 0.1 to 1 measured at six visits can be estimated with between 1.43 and 2.22 times relative efficiency gain, or equivalently, with 30% to a 55% reduced sample size, compared to a single model of the final timepoint. Fractional polynomials are a flexible way to incorporate data from repeated measurements, increasing precision without imposing strong constraints. Longitudinal dose-response models using two fractional polynomial terms are robust to mis-specification of the true longitudinal process while maintaining, often large, efficiency gains. These models have applications for characterising the dose-response at interim or final analyses.

Contributions of the ADNI Biostatistics Core.

The goal of the Biostatistics Core of the Alzheimer's Disease Neuroimaging Initiative (ADNI) has been to ensure that sound study designs and statistical methods are used to meet the overall goals of ADNI. We have supported the creation of a well-validated and well-curated longitudinal database of clinical and biomarker information on ADNI participants and helped to make this accessible and usable for researchers. We have developed a statistical methodology for characterizing the trajectories of clinical and biomarker change for ADNI participants across the spectrum from cognitively normal to dementia, including multivariate patterns and evidence for heterogeneity in cognitive aging. We have applied these methods and adapted them to improve clinical trial design. ADNI-4 will offer us a chance to help extend these efforts to a more diverse cohort with an even richer panel of biomarker data to support better knowledge of and treatment for Alzheimer's disease and related dementias. HIGHLIGHTS: The Alzheimer's Disease Neuroimaging Initiative (ADNI) Biostatistics Core provides study design and analytic support to ADNI investigators. Core members develop and apply novel statistical methodology to work with ADNI data and support clinical trial design. The Core contributes to the standardization, validation, and harmonization of biomarker data. The Core serves as a resource to the wider research community to address questions related to the data and study as a whole.

Comparative review of novel model-assisted designs for phase I/II clinical trials.

In recent years, both model-based and model-assisted designs have emerged to efficiently determine the optimal biological dose (OBD) in phase I/II trials for immunotherapy and targeted cellular agents. Model-based designs necessitate repeated model fitting and computationally intensive posterior sampling for each dose-assignment decision, limiting their practical application in real trials. On the other hand, model-assisted designs employ simple statistical models and facilitate the precalculation of a decision table for use throughout the trial, eliminating the need for repeated model fitting. Due to their simplicity and transparency, model-assisted designs are often preferred in phase I/II trials. In this paper, we systematically evaluate and compare the operating characteristics of several recent model-assisted phase I/II designs, including TEPI, PRINTE, Joint i3+3, BOIN-ET, STEIN, uTPI, and BOIN12, in addition to the well-known model-based EffTox design, using comprehensive numerical simulations. To ensure an unbiased comparison, we generated 10,000 dosing scenarios using a random scenario generation algorithm for each predetermined OBD location. We thoroughly assess various performance metrics, such as the selection percentages, average patient allocation to OBD, and overdose percentages across the eight designs. Based on these assessments, we offer design recommendations tailored to different objectives, sample sizes, and starting dose locations.

Protocol-in-a-Day Workshop: Expediting IRB Approval for Junior and Senior Faculty.

Delays in research protocol development may be a single factor that hinders the career progression of academic faculty. Structured educational guidance during this phase proves crucial in mitigating setbacks in Institutional Review Board (IRB) approval and expediting trial implementation. To address this, the Protocol-in-a-Day (PIAD) workshop, a comprehensive 1-day event involving members from six critical facets of RO clinical trial implementation, was established, offering significant input to individual protocols. Efficacy and satisfaction of the PIAD workshop were assessed through a 5-question survey and the average time from submission to IRB initial approval. The normality of the data was analyzed using the Shapiro-Wilk Test. Nonparametric data was analyzed using a Mann-Whitney U test for significance. A total of 18 protocols that went through the PIAD workshop were activated. The mean time to IRB approval for protocols that went through PIAD was 39.8 days compared to 58.4 days for those that did not go through the PIAD workshop. Based on survey results, 100% of PIAD participants said the PIAD workshop was useful and 94% of participants stated that the PIAD workshop improved the overall quality of their protocol. Participant surveys further highlighted substantial improvements in trial quality, language, and statistical design and revealed that all participants found the workshop helpful. Therefore, both junior and senior faculty benefitted from this educational program during protocol development, as both groups demonstrated shorter times to IRB approval than non-participants. This acceleration not only fosters efficient trial implementation but also supports academic faculty in their career development.

Clinical recommendations for posttransplant assessment of anti-HLA (Human Leukocyte Antigen) donor-specific antibodies: A Sensitization in Transplantation: Assessment of Risk consensus document.

Although anti-HLA (Human Leukocyte Antigen) donor-specific antibodies (DSAs) are commonly measured in clinical practice and their relationship with transplant outcome is well established, clinical recommendations for anti-HLA antibody assessment are sparse. Supported by a careful and critical review of the current literature performed by the Sensitization in Transplantation: Assessment of Risk 2022 working group, this consensus report provides clinical practice recommendations in kidney, heart, lung, and liver transplantation based on expert assessment of quality and strength of evidence. The recommendations address 3 major clinical problems in transplantation and include guidance regarding posttransplant DSA assessment and application to diagnostics, prognostics, and therapeutics: (1) the clinical implications of positive posttransplant DSA detection according to DSA status (ie, preformed or de novo), (2) the relevance of posttransplant DSA assessment for precision diagnosis of antibody-mediated rejection and for treatment management, and (3) the relevance of posttransplant DSA for allograft prognosis and risk stratification. This consensus report also highlights gaps in current knowledge and provides directions for clinical investigations and trials in the future that will further refine the clinical utility of posttransplant DSA assessment, leading to improved transplant management and patient care.

Infection and clinical xenotransplantation: Guidance from the Infectious Disease Community of Practice of the American Society of Transplantation.

This guidance was developed to summarize current approaches to the potential transmission of swine-derived organisms to xenograft recipients, health care providers, or the public in clinical xenotransplantation. Limited specific data are available on the zoonotic potential of pig pathogens. It is anticipated that the risk of zoonotic infection in xenograft recipients will be determined by organisms present in source animals and relate to the nature and intensity of the immunosuppression used to maintain xenograft function. Based on experience in allotransplantation and with preclinical models, viral infections are of greatest concern, including porcine cytomegalovirus, porcine lymphotropic herpesvirus, and porcine endogenous retroviruses. Sensitive and specific microbiological assays are required for routine microbiological surveillance of source animals and xenograft recipients. Archiving of blood samples from recipients, contacts, and hospital staff may provide a basis for microbiological investigations if infectious syndromes develop. Carefully implemented infection control practices are required to prevent zoonotic pathogen exposures by clinical care providers. Informed consent practices for recipients and their close contacts must convey the lack of specific data for infectious risk assessment. Available data suggest that infectious risks of xenotransplantation are manageable and that clinical trials can advance with carefully developed protocols for pretransplant assessment, syndrome evaluation, and microbiological monitoring.

A decision-theoretic approach to Bayesian clinical trial design and evaluation of robustness to prior-data conflict.

Bayesian clinical trials allow taking advantage of relevant external information through the elicitation of prior distributions, which influence Bayesian posterior parameter estimates and test decisions. However, incorporation of historical information can have harmful consequences on the trial's frequentist (conditional) operating characteristics in case of inconsistency between prior information and the newly collected data. A compromise between meaningful incorporation of historical information and strict control of frequentist error rates is therefore often sought. Our aim is thus to review and investigate the rationale and consequences of different approaches to relaxing strict frequentist control of error rates from a Bayesian decision-theoretic viewpoint. In particular, we define an integrated risk which incorporates losses arising from testing, estimation, and sampling. A weighted combination of the integrated risk addends arising from testing and estimation allows moving smoothly between these two targets. Furthermore, we explore different possible elicitations of the test error costs, leading to test decisions based either on posterior probabilities, or solely on Bayes factors. Sensitivity analyses are performed following the convention which makes a distinction between the prior of the data-generating process, and the analysis prior adopted to fit the data. Simulation in the case of normal and binomial outcomes and an application to a one-arm proof-of-concept trial, exemplify how such analysis can be conducted to explore sensitivity of the integrated risk, the operating characteristics, and the optimal sample size, to prior-data conflict. Robust analysis prior specifications, which gradually discount potentially conflicting prior information, are also included for comparison. Guidance with respect to cost elicitation, particularly in the context of a Phase II proof-of-concept trial, is provided.

Challenges and strategies for clinical trials in propionic and methylmalonic acidemias.

Clinical trial development in rare diseases poses significant study design and methodology challenges, such as disease heterogeneity and appropriate patient selection, identification and selection of key endpoints, decisions on study duration, choice of control groups, selection of appropriate statistical analyses, and patient recruitment. Therapeutic development in organic acidemias (OAs) shares many challenges with other inborn errors of metabolism, such as incomplete understanding of natural history, heterogenous disease presentations, requirement for sensitive outcome measures and difficulties recruiting a small sample of participants. Here, we review strategies for the successful development of a clinical trial to evaluate treatment response in propionic and methylmalonic acidemias. Specifically, we discuss crucial decisions that may significantly impact success of the study, including patient selection, identification and selection of endpoints, determination of the study duration, consideration of control groups including natural history controls, and selection of appropriate statistical analyses. The significant challenges associated with designing a clinical trial in rare disease can sometimes be successfully met through strategic engagement with experts in the rare disease, seeking regulatory and biostatistical guidance, and early involvement of patients and families.

Reflections from the OARSI 2022 clinical trials symposium: The pain of OA-Deconstruction of pain and patient-reported outcome measures for the benefit of patients and clinical trial design.

OBJECTIVE: Osteoarthritis (OA) drug development is hampered by a number of challenges. One of the main challenges is the apparent discordance between pain and structure, which has had a significant impact on drug development programs and has led to hesitance among stakeholders. Since 2017, the Clinical Trials Symposium (CTS) has been hosted under the Osteoarthritis Research Society International (OARSI) leadership. OARSI and the CTS steering committee yearly invite and encourage discussions on selected special subject matter between regulators, drug developers, clinicians, clinical researchers, biomarker specialists, and basic scientists to progress drug development in the OA field. METHOD: The main topic for the 2022 OARSI CTS was to elucidate the many facets of pain in OA and to enable a discussion between regulators (Food and Drug Administration (FDA) and the European Medicines Agency (EMA)) and drug developers to clarify outcomes and study designs for OA drug development. RESULTS: Signs or symptoms indicative of nociceptive pain occur in 50-70% of OA patients, neuropathic-like pain in 15-30% of patients, and nociplastic pain in 15-50% of patients. Weight-bearing knee pain is associated with bone marrow lesions and effusions. There are currently no simple objective functional tests whose improvements correlate with patient perceptions. CONCLUSIONS: The CTS participants, in collaboration with the FDA and EMA, raised several suggestions that they consider key to future clinical trials in OA including the need for more precise differentiation of pain symptoms and mechanisms, and methods to reduce placebo responses in OA trials.

A data-driven approach finds RNA polymerase III antibody and tendon friction rubs as enrichment tools for early diffuse scleroderma trials.

OBJECTIVE: Clinical trials in early diffuse SSc have consistently shown a placebo group response with a declining modified Rodnan skin score (mRSS), with negative outcomes. Our objective was to identify strategies using clinical characteristics or laboratory values to improve trial design. METHODS: We identified early diffuse SSc patients first seen at the University of Pittsburgh from 1980-2015. Eligible patients had ≥3 visits, with at least two mRSS scores within the first year of follow-up. We performed Kaplan-Meier analyses, group-based trajectory analysis of mRSS scores, followed by multivariable regression analysis and classification tree analysis. We applied the results to the abatacept in early diffuse systemic sclerosis (ASSET) trial outcome data. RESULTS: We identified 403 patients with <18 months, and 514 with <36 months disease duration. The median number of mRSS follow-up scores was 14 (interquartile range 8, 25). All methodologic approaches identified skin thickness progression rate, RNA polymerase III (RNAP3) antibody positivity and presence of tendon friction rubs (TFR) as predictors of mRSS trajectory over 5 years of follow-up, and thereby as potential enrichment variables. When applied to the ASSET data, adjustment for both RNAP3 and TFR demonstrated reduction of the placebo mRSS response, particularly at 6 months. A significant difference in the ACR Composite Response Index in Systemic Sclerosis (CRISS) score was found with adjustment by RNAP3 at 6 months, and TFR or RNAP3 at 12 months. CONCLUSION: Adjustment for both RNAP3 and TFR predicts mRSS trajectory and diminished the mRSS decline in ASSET placebo group, and identified significant differences in CRISS. RNAP3, particularly, is a stratification or enrichment approach to improve early diffuse SSc trial design.