Exploring the validity of a synthetic control arm (SCA) for augmentation or replacement of a randomized control in difficult-to-study indications: A case study in relapsed or refractory multiple myeloma (R/R MM).

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e20521-e20521
Author(s):  
Ruthie Davi ◽  
Xiang Yin ◽  
Mark Stewart
Keyword(s):  
Clinical Trials ◽  
Drug Development ◽  
Treatment Effect ◽  
Tipping Point ◽  
Patient Level Data ◽  
Patient Level ◽  
Level Data ◽  
Randomized Control ◽  
Baseline Characteristics

e20521 Background: The randomized clinical trial (RCT) is the gold standard in drug development. However, for indications where patients have a strong preference for the investigational product, such as many oncology and rare diseases, the use of a SCA may improve drug development and reduce patient burden. SCA is an external control constructed from patient-level data from previous clinical trials to match the baseline characteristics of the patients in an investigational group and can augment a single-arm trial or a RCT compromised by control arm early withdrawal or noncompliance in order to estimate treatment effects. This research explores whether the treatment effect (difference between arms) based on an SCA can mimic the treatment effect from a RCT. Tipping point analyses were explored to assess the impact of unobserved confounders on the SCA-based demonstration of efficacy. Methods: This case study is based on patient-level data from previous clinical trials in R/R MM. The SCA patients satisfied key eligibility criteria of the target RCT and were further selected using propensity score methods to balance the baseline characteristics in the SCA with the target randomized treatment group (TRT) from the original RCT. Sensitivity analyses utilizing methods proposed by Lin (1998) illustrate the robustness of the treatment effect to unobserved covariate(s). Results: Comparable balance was achieved in observed baseline characteristics between SCA and the matched patients from TRT. The treatment effect utilizing SCA is similar to the original RCT. The Kaplan Meier curve of overall survival for the SCA overlaps with that of the randomized control and the quantified differences between SCA and the matched patients from TRT are very similar to the original RCT. Tipping point analyses show changes in HRs under representative sets of assumptions regarding the unobserved confounder (results not shown). Conclusions: This case study demonstrates an SCA built from previous clinical trials, can be well-balanced at baseline with TRT and can provide similar treatment effect estimates as a RCT. Tipping point analyses can elucidate whether treatment effects are reliable despite a reasonable degree of confounding expected in a clinical setting. This suggests, in some settings, SCA can be used to augment or replace a randomized control in future trials without loss of understanding of the treatment effect. [Table: see text]

Non-small cell lung cancer (NSCLC) case study examining whether results in a randomized control arm are replicated by a synthetic control arm (SCA).

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 9108-9108 ◽  
Author(s):  
Ruthie Davi ◽  
Mark Chandler ◽  
Barbara Elashoff ◽  
Andrea Stern Ferris ◽  
Andrew Howland ◽  
...  
Keyword(s):  
Treatment Effect ◽  
Surrogate Endpoint ◽  
Drop Out ◽  
Rank Test ◽  
Synthetic Control ◽  
Eligibility Criteria ◽  
Randomized Control ◽  
Baseline Characteristics ◽  
Positive Effect

9108 Background: The FDA’s accelerated approval (AA) pathway provides conditional approval for an investigational product (IP) after positive effect on a surrogate endpoint has been provided, allowing patients earlier access to the therapy. Confirmation of a positive effect on the clinical endpoint after conditional approval is required and usually includes a randomized trial. However, such a trial is challenged by availability of the IP outside the trial. Recruitment becomes more difficult, and patients assigned to control are more likely to drop-out and use the non-assigned IP, which may bias the observed treatment effect. In AA settings we propose a SCA composed of patient level data from previous clinical trials to augment or replace the randomized control. Validity of this approach in one case study is assessed by examining if a SCA can replicate the outcomes of a target randomized control (TRC) from a recent NSCLC trial. Methods: The patients for the NSCLC SCA were required to have satisfied the key eligibility criteria of the target trial and were further selected using a propensity score-based approach to balance the baseline characteristics in the SCA and TRC. All patient selections were made without knowledge of patient outcomes. Results: The results show comparable balance in observed baseline characteristics of the SCA and TRC was achieved. Overall survival (OS) in TRC was replicated by SCA. The Kaplan Meier curves for OS in the SCA and TRC visually overlap. In addition, the log rank test (p = 0.65) and hazard ratio of 1.04 (95% CI: (0.88, 1.23)) were not statistically significant. Conclusions: If the SCA had been in place of the randomized control in this study, conclusions about the treatment effect would have been the same. While this may not hold when it is not possible to balance the groups on all confounders, this suggests that in some settings, SCA could augment or replace the randomized control in future trials easing recruitment, retention, and crossover challenges without compromising the understanding of the treatment effect. Future work should examine in what settings SCA is appropriate and consider the implications of potential unobserved confounders.

scholarly journals Prospective comparison of Bayesian and frequentist adaptive clinical trials : The SHADOW - SHINE project

2021 ◽  
Author(s):  
Kristine Broglio ◽  
William Meurer ◽  
Valerie Durkalski ◽  
Qi Pauls ◽  
Jason Connor ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Acute Stroke ◽  
Sample Size ◽  
Trial Design ◽  
Interim Analyses ◽  
Patient Level Data ◽  
Patient Level ◽  
Prospective Comparison ◽  
Level Data

Importance: Bayesian adaptive trial design has the potential to create more efficient clinical trials. However, one of the barriers to the uptake of Bayesian adaptive designs for confirmatory trials is limited experience with how they may perform compared to a frequentist design. Objective: Compare the performance of a Bayesian and a frequentist adaptive clinical trial design. Design: Prospective observational study comparing two trial designs using individual patient level data from a completed stroke trial, including the timing and order of enrollments and outcome ascertainment. The implemented frequentist design had group sequential boundaries for efficacy and futility interim analyses when 90-days post-randomization was met for 500, 700, 900, and 1,100 patients. The Bayesian alternative utilized predictive probability of trial success to govern early termination for efficacy and futility with a first interim analysis at 500 randomized patients, and subsequent interims after every 100 randomizations. Setting: Multi-center, acute stroke study conducted within a National Institutes of Health neurological emergencies clinical trials network. Participants: Patient level data from 1,151 patients randomized in a clinical trial comparing intensive insulin therapy to standard in acute stroke patients with hyperglycemia. Main Outcome(s) and Measure(s): Sample size at end of study. This was defined as the sample size at which each of the studies stopped accrual of patients. Results: As conducted, the frequentist design passed the futility boundary after 936 participants were randomized. Using the same sequence and timing of randomization and outcome data, the Bayesian alternative crossed the futility boundary about 3 months earlier after 800 participants were randomized. Conclusions and Relevance: Both trial designs stopped for futility prior to reaching the planned maximum sample size. In both cases, the clinical community and patients would benefit from learning the answer to the trial's primary question earlier. The common feature across the two designs was frequent interim analyses to stop early for efficacy or for futility. Differences between how this was implemented between the two trials resulted in the differences in early stopping.

scholarly journals Single-Agent Ibrutinib Versus Real-World (RW) Treatments for Patients with Previously Untreated Chronic Lymphocytic Leukemia (CLL): Adjusted Comparison of Resonate-2™ with the Cllear and Lyon-Sud Rw Databases

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 4679-4679
Author(s):  
Michael Doubek ◽  
Mudr. Lukas Smolej ◽  
Martin Šimkovič ◽  
Anna Panovska ◽  
Renata Urbanova ◽  
...  
Keyword(s):  
Research Funding ◽  
Single Agent ◽  
Eastern Cooperative Oncology Group ◽  
Average Treatment Effect ◽  
Disease Stage ◽  
Phase 3 ◽  
Patient Level Data ◽  
Patient Level ◽  
Level Data ◽  
Baseline Characteristics

Abstract Introduction Ibrutinib, a once-daily oral Bruton's tyrosine kinase inhibitor, has shown progression-free survival (PFS) or overall-survival (OS) benefit over chemoimmunotherapy (CIT) in multiple phase 3 studies in previously untreated patients with CLL, and significantly longer time to next treatment compared with CIT in previously untreated high-risk patients in a RW setting. We conducted an adjusted comparison of ibrutinib versus RW treatment for previously untreated CLL using patient-level data from the phase 3 RESONATE-2™ (NCT01722487) trial and RW databases from 2 countries. Methods Previously untreated patients with CLL, fulfilling RESONATE-2™ eligibility criteria (age ≥ 65, no del17p) were selected from 2 RW data sources containing electronic medical records for patients with CLL: Centre Hospitalier Lyon-Sud, France; CLLEAR CLL registry from 7 academic centers in the Czech Republic. PFS and OS were compared between patients from the ibrutinib arm of RESONATE-2™ with a median follow-up of 60 months, and those receiving physicians' choice (PC) treatment other than ibrutinib from the RW database, adjusting for differences in baseline characteristics including age, gender, del11q, IGHV status, RAI/BINET disease stage, and Eastern Cooperative Oncology Group (ECOG) score. Hazard ratios (HRs) for ibrutinib versus RW PC treatment were estimated using a multivariable Cox proportional hazards model including available baseline characteristics as covariates, and using an inverse probability weighted (IPW) Cox model with average treatment effect for treatment (ATT) weights derived from propensity scores estimated from a logistic regression including the same covariates. Results The analysis included 136 patients from the RESONATE-2™ study receiving ibrutinib and 920 previously untreated RW patients receiving PC treatment (Lyon-Sud n = 162, CLLEAR n = 758). Baseline characteristics were generally balanced between treatment groups. The most common PC regimens contained CIT and were fludarabine + cyclophosphamide + rituximab (FCR) (n = 227), bendamustine + rituximab (BR) (n = 201), and rituximab + chlorambucil (R + Chlor) (n = 116). Older age, male gender, del11q and advanced disease stage were independent risk factors for PFS and OS. When comparing ibrutinib versus the overall PC cohort, the adjusted HR (95% confidence interval [CI]) was 0.24 (0.16-0.34) for PFS and 0.33 (0.21-0.52) for OS (both p < 0.0001). IPW-based comparative estimates were highly consistent for both PFS (HR = 0.27 [0.18-0.39]) and OS (HR = 0.39 [0.24-0.62]). ATT-weighted survival curves estimating PFS and OS for the RESONATE-2™ population as if treated with PC, showed a median value of 32.1 months and 72.5 months, respectively, while median values for Ibrutinib were not reached. When comparing ibrutinib versus FCR, BR, and R + Chlor, the adjusted HRs (95% CI) were 0.26 (0.17-0.38), 0.27 (0.18-0.41), and 0.27 (0.17-0.42), respectively, for PFS and 0.34 (0.20-0.56), 0.28 (0.16-0.49), and 0.61 (0.32-1.13), respectively, for OS (Figure). Concl usions Adjusted comparisons of the RESONATE-2™ trial and RW patient-level data demonstrates significantly improved PFS and OS for ibrutinib versus physician's choice treatment (predominantly CIT) in previously untreated patients with CLL. PFS and OS benefit for ibrutinib was consistent across a range of common regimens: FCR, BR, and R + Chlor. These results are consistent with data from phase 3 studies and support the use of ibrutinib for first-line CLL treatment. Funding Source: Sponsored by Janssen Pharmaceutica NV, and Pharmacyclics LLC, an AbbVie Company. The RW databases are independently owned. Writing assistance was provided by Emma Fulkes and Liqing Xiao of Parexel and funded by Janssen Pharmaceutica NV. Figure 1 Figure 1. Disclosures Doubek: Janssen-Cilag, AbbVie, AstraZeneca, Amgen, Gilead, Novartis: Honoraria, Research Funding. Smolej: AbbVie, AstraZeneca, Gilead, Janssen-Cilag, and Roche: Consultancy, Honoraria, Other: Travel Grants. Šimkovič: AbbVie, AstraZeneca, Janssen-Cilag, Gilead, Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Grants. Lysak: Novartis, Janssen-Cilag, AbbVie; AstraZeneca: Honoraria, Research Funding. Bachy: Kite, a Gilead Company: Honoraria; Novartis: Honoraria; Daiishi: Research Funding; Roche: Consultancy; Takeda: Consultancy; Incyte: Consultancy. Ferrant: AbbVie: Honoraria, Other: Travel, Accommodations, Expenses; AstraZeneca: Honoraria; Janssen: Other: Travel, Accommodations, Expenses. Diels: Janssen: Current Employment. Cabrieto: Janssen: Current Employment. Nielsen: Janssen: Current Employment. Salles: Allogene: Consultancy; Regeneron: Consultancy, Honoraria; Velosbio: Consultancy; Takeda: Consultancy; Rapt: Consultancy; Genentech/Roche: Consultancy; Epizyme: Consultancy, Honoraria; Debiopharm: Consultancy; Genmab: Consultancy; Incyte: Consultancy; Ipsen: Consultancy; Janssen: Consultancy; Kite/Gilead: Consultancy; Loxo: Consultancy; Miltneiy: Consultancy; Morphosys: Consultancy, Honoraria; Novartis: Consultancy; BMS/Celgene: Consultancy; Beigene: Consultancy; Abbvie: Consultancy, Honoraria; Bayer: Honoraria.

185-OR: Efficacy and Safety of Bempedoic Acid in Patients with Diabetes, Prediabetes, and Normoglycemia: Analysis of Pooled Patient-Level Data from Four Phase 3 Clinical Trials

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 185-OR
Author(s):  
LAWRENCE A. LEITER ◽  
MACIEJ BANACH ◽  
ALBERICO L. CATAPANO ◽  
P. BARTON DUELL ◽  
ANTONIO GOTTO ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Efficacy And Safety ◽  
Phase 3 ◽  
Patient Level Data ◽  
Patient Level ◽  
Level Data ◽  
Patients With Diabetes

scholarly journals Protecting patient privacy when sharing patient-level data from clinical trials

2016 ◽  
Vol 16 (S1) ◽  
Author(s):  
Katherine Tucker ◽  
Janice Branson ◽  
Maria Dilleen ◽  
Sally Hollis ◽  
Paul Loughlin ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Patient Privacy ◽  
Patient Level Data ◽  
Patient Level ◽  
Level Data
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