Randomized Clinical Trial Representativeness and Outcomes in Real-World Patients: Comparison of 6 Hallmark Randomized Clinical Trials of Relapsed/Refractory Multiple Myeloma

Background: Multiple myeloma (MM) is a plasma cell disorder and demonstrates overexpression of B cell maturation antigen (BCMA). Our objective is to evaluate the safety and efficacy of chimeric antigen receptor T cells (CAR-T) against BCMA in patients with relapsed/refractory multiple myeloma (RRMM). Methods: We conducted a systematic literature search using PubMed, Cochrane, Clinicaltrials.gov, and Embase databases. We also searched for data from society meetings. A total of 935 articles were identified, and 610 were screened for relevance. Results: Data from thirty-one original studies with a total of 871 patients (pts) were included based on defined eligibility criteria, see Table 1. Hu et al. reported an overall response rate (ORR) of 100% in 33 pts treated with BCMA CAR-T cells including 21 complete response (CR), 7 very good partial response (VGPR), 4 partial response (PR). Moreover, 32 pts achieved minimal residual disease (MRD) negative status. Chen et al. reported ORR of 88%, 14% CR, 6% VGPR, and 82% MRD negative status with BCMA CAR-T therapy in 17 RRMM pts. In another clinical trial by Han et al. BCMA CAR-T therapy demonstrated an ORR of 100% among 7 evaluable pts with 43% pts having ≥ CR and 14% VGPR. An ORR of 100% with 64% stringent CR (sCR) and 36% VGPR was reported with novel anti-BCMA CART cells (CT103A). Similarly, Li et al. reported ORR of 87.5%, sCR of 50%, VGPR 12.5%, and PR 25% in 16 pts. BCMA targeting agent, JNJ-4528, showed ORR of 91%, including 4sCR, 2CR, 10MRD, and 7VGPR. CAR-T- bb2121 demonstrated ORR of 85%, sCR 36%, CR 9%, VGPR 57%, and MRD negativity of 100% (among 16 responsive pts). GSK2857916, a BCMA targeting CAR-T cells yielded ORR of 60% in both clinical trials. Three studies utilizing bispecific CART cells targeting both BCMA & CD38 (LCARB38M) reported by Zhao et al., Wang et al., and Fan et al. showed ORR of 88%, 88%, & 100% respectively. Topp et al. reported ORR of 31% along with 5 ≥CR and 5 MRD negative status in 42 pts treated with Bi T-cells Engager BiTE® Ab BCMA targeting antigen (AMG420). One clinical trial presented AUTO2 CART cells therapy against BCMA with an ORR of 43%, VGPR of 14%, and PR of 28%. CT053CAR-BCMA showed 14sCR and 5CR with a collective ORR of 87.5% and MRD negative status of 85% in 24 and 20 evaluable pts, respectively. Likewise, Mikkilineni et al. reported an ORR of 83%, sCR of 16.7%, and VGPR & PR of 25% and 41% in 12 pts treated with FHVH-BCMA T cells. Similar results are also reported in other clinical trials of BCMA targeting CART therapy (Table 1). The most common adverse effects exhibited were grade 1-3 hematologic (cytopenia) and cytokine release syndrome (CRS) (mostly reversible with tocilizumab). Conclusion: Initial data from ongoing clinical trials using BCMA targeting CAR-T therapy have yielded promising results both in terms of improved outcome and tolerable toxicity profiles. Although two phase 3 trails are ongoing, additional data is warranted to further ensure the safety and efficacy of anti-BCMA CAR-T cells therapy in pts with RRMM for future use. Disclosures Anwer: Incyte, Seattle Genetics, Acetylon Pharmaceuticals, AbbVie Pharma, Astellas Pharma, Celegene, Millennium Pharmaceuticals.: Honoraria, Research Funding, Speakers Bureau.

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Guidelines on how to assess the validity of results presented in subgroup analysis of clinical trials

Revista do Hospital das Clínicas ◽

10.1590/s0041-87812002000200007 ◽

2002 ◽

Vol 57 (2) ◽

pp. 83-88 ◽

Cited By ~ 5

Author(s):

Edson Duarte Moreira ◽

Ezra Susser

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Randomized Clinical Trial ◽

Subgroup Analysis ◽

Observational Studies ◽

Randomized Clinical Trials ◽

Usual Method ◽

Validity Of Results ◽

Results Of Treatment ◽

Trial Participants

In observational studies, identification of associations within particular subgroups is the usual method of investigation. As an exploratory method, it is the bread and butter of epidemiological research. Nearly everything that has been learned in epidemiology has been derived from the analysis of subgroups. In a randomized clinical trial, the entire purpose is the comparison of the test subjects and the controls, and when there is particular interest in the results of treatment in a certain section of trial participants, a subgroup analysis is performed. These subgroups are examined to see if they are liable to a greater benefit or risk from treatment. Thus, analyzing patient subsets is a natural part of the process of improving therapeutic knowledge through clinical trials. Nevertheless, the reliability of subgroup analysis can often be poor because of problems of multiplicity and limitations in the numbers of patients studied. The naive interpretation of the results of such examinations is a cause of great confusion in the therapeutic literature. We emphasize the need for readers to be aware that inferences based on comparisons between subgroups in randomized clinical trials should be approached more cautiously than those based on the main comparison. That is, subgroup analysis results derived from a sound clinical trial are not necessarily valid; one must not jump to conclusions and accept the validity of subgroup analysis results without an appropriate judgment.

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Extracorporeal Membrane Oxygenation and the Play the Winner Rule

PEDIATRICS ◽

10.1542/peds.76.4.622 ◽

1985 ◽

Vol 76 (4) ◽

pp. 622-623

Author(s):

NIGEL PANETH ◽

SYLVAN WALLENSTEIN

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Extracorporeal Membrane Oxygenation ◽

Randomized Clinical Trial ◽

Conventional Treatment ◽

Randomized Clinical Trials ◽

Ethical Problem ◽

Therapeutic Trial ◽

Membrane Oxygenation ◽

Treatment Comparisons

The therapeutic trial comparing extracorporeal membrane oxygenation with conventional treatment in neonatal respiratory failure reported by Bartlett et al (Pediatrics 1985;76:479-487) uses a method of comparing treatments unlikely to be familiar to most pediatricians. Known as the "randomized play the winner" method, it has thus far been little used in clinical research. Most clinical investigators consider the conventional randomized clinical trial to be the last word in treatment comparisons. But randomized clinical trials are costly, cumbersome, and to some observers less than ideal ethically. The ethical problem arises from the fact that during a "successful" randomized clinical trial (ie, one that demonstrates a significant advantage to one treatment) about half of the trial subjects will receive a treatment which, at the end of the trial, will be known to be inferior.

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Simulation Modeling as a Decision-Making Aid in Economic Evaluation for Randomized Clinical Trials

Clinical Technologies ◽

10.4018/978-1-60960-561-2.ch609 ◽

2011 ◽

pp. 1738-1758

Author(s):

Tillal Eldabi ◽

Robert D. Macredie ◽

Ray J. Paul

Keyword(s):

Clinical Trial ◽

Decision Making ◽

Clinical Trials ◽

Economic Evaluation ◽

Simulation Model ◽

Randomized Clinical Trial ◽

Simulation Modeling ◽

Randomized Clinical Trials ◽

Healthcare Systems ◽

Modeling Process

This chapter reports on the use of simulation in supporting decision-making about what data to collect in a randomized clinical trial (RCT). We show how simulation also allows the identification of critical variables in the RCT by measuring their effects on the simulation model’s “behavior.” Healthcare systems pose many of the challenges, including difficulty in understanding the system being studied, uncertainty over which data to collect, and problems of communication between problem owners. In this chapter we show how simulation also allows the identification of critical variables in the RCT by measuring their effects on the simulation model’s “behavior.” The experience of developing the simulation model leads us to suggest simple but extremely valuable lessons. The first relates to the inclusion of stakeholders in the modeling process and the accessibility of the resulting models. The ownership and confidence felt by stakeholders in our case is, we feel, extremely important and may provide an example to others developing models.

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Survival among metastatic colorectal patients in clinical trials compared to the real world.

Journal of Clinical Oncology ◽

10.1200/jco.2015.33.3_suppl.673 ◽

2015 ◽

Vol 33 (3_suppl) ◽

pp. 673-673

Author(s):

Ziwei Wang ◽

Lindsay Hwang ◽

James Don Murphy

Keyword(s):

Colorectal Cancer ◽

Clinical Trial ◽

Clinical Trials ◽

Metastatic Colorectal Cancer ◽

Median Survival ◽

Real World ◽

Randomized Clinical Trials ◽

Phase Iii ◽

The Real ◽

Clinical Trial Results

673 Background: Randomized clinical trials play a central role in clinical research though only a small fraction of patients partake in clinical studies. Questions thus arise regarding the generalizability of clinical trial results to the remainder of the population. This study evaluated whether patient survival from randomized clinical trials in metastatic colorectal cancer reflects real world outcomes. Methods: A Pubmed search was used to identify randomized phase III clinical trials of first-line treatment for metastatic colorectal cancer published between 2005 and 2010. We excluded secondary or pooled analyses, second-line treatments, non-metastatic patients, non-English language, and non-randomized studies. Thirty-one clinical trials met these criteria, comprised of 79 distinct clinical trial arms. Overall survival among clinical trial patients was compared to metastatic colorectal cancer patients within the Surveillance, Epidemiology, and End Results (SEER) program. Within SEER, we restricted the analysis time-period and age of patients to match the enrollment period and age of patients within each individual clinical trial. Results: The clinical trials enrolled a total of 16,614 patients. Among all clinical trial arms the median survival ranged from 6.7-62 months, 1-year survival ranged from 30-97%, and 2-year survival ranged from 6-88%. Compared to SEER, the median survival was higher in 95% of the individual clinical trial arms by an average of 5.4 months (p<0.0001). The 1-year survival was higher in 94% of the clinical trial arms by an average of 16.7% (p<0.0001). The 2-year survival was higher in 71% of the clinical trial arms by an average of 7.2% (p<0.0001). Conclusions: This study found substantially improved survival among clinical trial participants compared to patients in the SEER database suggesting that survival estimates from clinical trials may not generalize to the “real world.” Potential patient factors such as differences in underlying comorbidity, performance status, disease burden, as well as variation in treatment could not be addressed in this study, though these factors likely explain some of the observed survival differences.

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The real-world outcomes of multiple myeloma patients treated with daratumumab

PLoS ONE ◽

10.1371/journal.pone.0258487 ◽

2021 ◽

Vol 16 (10) ◽

pp. e0258487

Author(s):

Agoston Gyula Szabo ◽

Tobias Wirenfeldt Klausen ◽

Mette Bøegh Levring ◽

Birgitte Preiss ◽

Carsten Helleberg ◽

...

Keyword(s):

Multiple Myeloma ◽

Clinical Trials ◽

Real World ◽

Randomized Clinical Trials ◽

Proteasome Inhibitors ◽

Median Number ◽

The Real ◽

Treatment Timing ◽

Risk Patients ◽

Standard Risk

Most patients cannot be included in randomized clinical trials. We report real-world outcomes of all Danish patients with multiple myeloma (MM) treated with daratumumab-based regimens until 1 January 2019. Methods Information of 635 patients treated with daratumumab was collected retrospectively and included lines of therapy (LOT), hematologic responses according to the International Myeloma Working Group recommendations, time to next treatment (TNT) and the cause of discontinuation of treatment. Baseline characteristics were acquired from the validated Danish Multiple Myeloma Registry (DMMR). Results Daratumumab was administrated as monotherapy (Da-mono) in 27.7%, in combination with immunomodulatory drugs (Da-IMiD) in 57.3%, in combination with proteasome inhibitors (Da-PI) in 11.2% and in other combinations (Da-other) in 3.8% of patients. The median number of lines of therapy given before daratumumab was 5 for Da-mono, 3 for Da-IMiD, 4 for Da-PI, and 2 for Da-other. In Da-mono, overall response rate (ORR) was 44.9% and median time to next treatment (mTNT) was 4.9 months. In Da-IMiD, ORR was 80.5%, and mTNT was 16.1 months. In Da-PI, OOR was 60.6% and mTNT was 5.3 months. In patients treated with Da-other, OOR was 54,2% and mTNT was 5.6 months. The use of daratumumab in early LOT was associated with longer TNT (p<0.0001). Patients with amplification 1q had outcome comparable to standard risk patients, while patients with t(4;14), t(14;16) or del17p had worse outcome (p = 0.0001). Multivariate analysis indicated that timing of treatment (timing of daratumumab in the sequence of all LOT that the patients received throughout the course of their disease) was the most important factor for outcome (p<0.0001). Conclusion The real-world outcomes of multiple myeloma patients treated with daratumumab are worse than the results of clinical trials. Outcomes achieved with daratumumab were best when daratumumab was used in combination with IMIDs and in early LOT. Patients with high-risk CA had worse outcomes, but patients with amp1q had similar outcomes to standard-risk patients.

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The impact of newly approved drugs on clinical and operational strategies for multiple myeloma clinical trials.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.15_suppl.e19511 ◽

2019 ◽

Vol 37 (15_suppl) ◽

pp. e19511-e19511

Author(s):

Bhavani Krishnan ◽

Bernadette Collins ◽

Michael Jeffrey Cho ◽

Tanya Partridge ◽

Durga Vighnay ◽

...

Keyword(s):

Clinical Trial ◽

Multiple Myeloma ◽

Clinical Trials ◽

Real World ◽

Operational Strategies ◽

Clinical Trial Enrollment ◽

Near Term ◽

Approved Drugs ◽

The Impact ◽

The U.S

e19511 Background: The global burden of multiple myeloma (MM) has increased steadily in last 3 decades. The IARC reports there were ~160,000 new cases worldwide in 2018. There has been an increase in the development and approval of more effective targeted therapy options (new immunomodulatory agents, proteasome inhibitors, and monoclonal antibodies); this, coupled with high adoption of these therapies presents a major challenge in enrollment of current ongoing clinical trials. We assessed the impact of near-term regulatory approvals on clinical trial enrollment. Methods: Public domain clinical trial enrollment data from MM studies (Phase I, I/II, II) closed/completed between 2011-2018 were used to determine enrollment trends pre and post 2014. We leveraged real-world medical claims data to project/model adoption of recently approved drugs in the U.S.; additionally, drug sales volume data was used to evaluate ex-US national adoption trends. The utilization rates of 5 recently approved drugs by regimen and line of treatment was determined. Results: In the U.S., there is a 13% increase in median enrollment duration with a corresponding 25% decrease in median p/s/m enrollment in MM studies, irrespective of phase, where enrollment was completed between 2015 -2018 compared to 2011-2014. We hypothesize that one of the factors for this increase in enrollment timeline is the approval and adoption of newly approved therapies post 2014. Two of the five recently approved drugs show a steady increase in the number of patients treated over 2016, 2017 and 2018, while one of the drugs plateaus over the same period. Outside of the U.S., our analysis confirms the existence of gaps in time to approval /adoption of recently approved drugs; for example, we observe a two-year delay in approval/adoption for one of the drugs in France compared to the other countries in Western Europe. Conclusions: There are over 10 investigational MM drugs currently in development which are anticipated to be granted approval between 2019-2021. Factoring the real-world adoption of near-term drug approval into global clinical and operational strategies offers insights into mitigating potential future enrollment challenges.

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Simulation Modeling as a Decision-Making Aid in Economic Evaluation for Randomized Clinical Trials

Simulation and Modeling ◽

10.4018/978-1-59904-198-8.ch008 ◽

2008 ◽

pp. 219-243 ◽

Cited By ~ 1

Author(s):

Tillal Eldabi ◽

Robert D. Macredie ◽

Ray J. Paul

Keyword(s):

Clinical Trial ◽

Decision Making ◽

Clinical Trials ◽

Economic Evaluation ◽

Simulation Model ◽

Randomized Clinical Trial ◽

Simulation Modeling ◽

Randomized Clinical Trials ◽

Healthcare Systems ◽

Modeling Process

This chapter reports on the use of simulation in supporting decision-making about what data to collect in a randomized clinical trial (RCT). We show how simulation also allows the identification of critical variables in the RCT by measuring their effects on the simulation model’s “behavior.” Healthcare systems pose many of the challenges, including difficulty in understanding the system being studied, uncertainty over which data to collect, and problems of communication between problem owners. In this chapter we show how simulation also allows the identification of critical variables in the RCT by measuring their effects on the simulation model’s “behavior.” The experience of developing the simulation model leads us to suggest simple but extremely valuable lessons. The first relates to the inclusion of stakeholders in the modeling process and the accessibility of the resulting models. The ownership and confidence felt by stakeholders in our case is, we feel, extremely important and may provide an example to others developing models.

Download Full-text