Continual Reassessment Method Design Research Articles

The 3 + 3 design in dose-finding studies with small sample sizes: Pitfalls and possible remedies.

In the last few years, numerous novel designs have been proposed to improve the efficiency and accuracy of phase I trials to identify the maximum-tolerated dose (MTD) or the optimal biological dose (OBD) for noncytotoxic agents. However, the conventional 3+3 approach, known for its and poor performance, continues to be an attractive choice for many trials despite these alternative suggestions. The article seeks to underscore the importance of moving beyond the 3+3 design by highlighting a different key element in trial design: the estimation of sample size and its crucial role in predicting toxicity and determining the MTD. We use simulation studies to compare the performance of the most used phase I approaches: 3+3, Continual Reassessment Method (CRM), Keyboard and Bayesian Optimal Interval (BOIN) designs regarding three key operating characteristics: the percentage of correct selection of the true MTD, the average number of patients allocated per dose level, and the average total sample size. The simulation results consistently show that the 3+3 algorithm underperforms in comparison to model-based and model-assisted designs across all scenarios and metrics. The 3+3 method yields significantly lower (up to three times) probabilities in identifying the correct MTD, often selecting doses one or even two levels below the actual MTD. The 3+3 design allocates significantly fewer patients at the true MTD, assigns higher numbers to lower dose levels, and rarely explores doses above the target dose-limiting toxicity (DLT) rate. The overall performance of the 3+3 method is suboptimal, with a high level of unexplained uncertainty and significant implications for accurately determining the MTD. While the primary focus of the article is to demonstrate the limitations of the 3+3 algorithm, the question remains about the preferred alternative approach. The intention is not to definitively recommend one model-based or model-assisted method over others, as their performance can vary based on parameters and model specifications. However, the presented results indicate that the CRM, Keyboard, and BOIN designs consistently outperform the 3+3 and offer improved efficiency and precision in determining the MTD, which is crucial in early-phase clinical trials.

Local continual reassessment methods for dose finding and optimization in drug-combination trials.

Due to the limited sample size and large dose exploration space, obtaining a desirable dose combination is a challenging task in the early development of combination treatments for cancer patients. Most existing designs for optimizing the dose combination are model-based, requiring significant efforts to elicit parameters or prior distributions. Model-based designs also rely on intensive model calibration and may yield unstable performance in the case of model misspecification or sparse data. We propose to employ local, underparameterized models for dose exploration to reduce the hurdle of model calibration and enhance the design robustness. Building upon the framework of the partial ordering continual reassessment method, we develop local data-based continual reassessment method designs for identifying the maximum tolerated dose combination, using toxicity only, and the optimal biological dose combination, using both toxicity and efficacy, respectively. The local data-based continual reassessment method designs only model the local data from neighboring dose combinations. Therefore, they are flexible in estimating the local space and circumventing unstable characterization of the entire dose-exploration surface. Our simulation studies show that our approach has competitive performance compared to widely used methods for finding maximum tolerated dose combination, and it has advantages over existing model-based methods for optimizing optimal biological dose combination.

A phase (Ph) I/II trial of abiraterone acetate in combination with tildrakizumab (anti-IL23 monoclonal antibody) in patients with metastatic castration-resistant prostate cancer (mCRPC).

TPS5105 Background: Tumor-infiltrating inflammatory myeloid cells promote prostate cancer (PC) growth and therapeutic resistance. Myeloid inflammatory cells release interleukin-23 (IL-23) to fuel tumor growth via JAK2-STAT3 signalling and facilitate tumor-promoting T helper 17 (TH17) differentiation in PC models in vivo. IL-23 blockade reverses resistance to AR-targeting in vivo; we hypothesise that targeting IL-23 can be an effective therapeutic strategy for CRPC. Tildrakizumab, an anti-IL-23 (p19) monoclonal antibody, is FDA/EMA approved for treating moderate-severe psoriasis. In progress is the first clinical trial to combining IL-23 and AR signalling blockade in humans. Methods: This is an open-label, single-arm, Ph 1/2, dose-escalation and expansion study evaluating safety and tolerability of tildrakizumab and abiraterone acetate combination therapy in patients with mCRPC. Eligible patients must have progressed on androgen deprivation therapy, plus abiraterone and/or enzalutamide. The Ph 1 trial will adopt a one-stage Bayesian Continual Reassessment Method design exploring escalating doses of 4-weekly, IV tildrakizumab (100 mg, 300 mg, and 600 mg), in combination with standard fixed doses of abiraterone acetate and methylprednisolone, with the aim of determining the maximum tolerated dose (MTD) and recommended phase 2 dose (RP2D). Depending on the number of responses observed, tolerable dose levels may be expanded up to 10 patients after review by the Safety Review Committee (SRC). The RP2D and MTD determination will be based on the rate of toxicity and efficacy, reviewed by the SRC. Once RP2D is determined, the Ph 2 study will enrol up to 25 response-evaluable patients using a Simon’s two-stage design. Primary endpoint of the Ph 2 trial is overall response rate. Adverse events are assessed according to CTCAE v5. Tumor response is determined according to RECIST v1.1, confirmed PSA decline of at least 50%, and/or CTC conversion. PK analyses is being performed for both drugs to identify potential drug-drug interactions. PD analyses is being performed on archival and serial tumour biopsies and blood samples to investigate putative predictive biomarkers and confirm on-target and downstream effector modulation. The trial began enrolling in January 2021 in the United Kingdom and Switzerland. As of January 22th 2023, 12 patients were included in the study. Clinical trial information: NCT04458311 .

Phase I study of intravesical anti-CD40 agonist antibody 2141-V11 for non-muscle invasive bladder cancer unresponsive to Bacillus Calmette-Guerin (BCG) therapy.

TPS4616 Background: CD40 is an immune-stimulatory receptor centrally involved in activating antigen-presenting cells and downstream anti-tumor immunity. Multiple agonistic anti-CD40 antibodies have been investigated clinically for cancer therapy, but have thus far shown limited efficacy and notable systemic toxicity. Our group has previously demonstrated that the ability of the Fc domain of anti-CD40 agonist antibodies to engage the FcγRIIB receptor, needed for optimal CD40 crosslinking, is critical for CD40 agonist activity. We engineered a fully-human anti-CD40 agonist antibody (2141-V11) with optimized Fc binding to FcγRIIB, which demonstrates significantly enhanced CD40 agonist activity. Non-muscle invasive bladder cancer (NMIBC), which remains an area of significant unmet need, represents an attractive clinical context to pursue CD40 agonist therapy given strong enrichment of CD40 in the bladder tumor microenvironment and routine use of local intravesical delivery as a potential strategy to mitigate systemic toxicity. Our preclinical studies, including in immunocompetent orthotopic murine models of bladder cancer humanized for CD40 and Fcγ receptors, revealed that intravesical delivery of 2141-V11 induced potent and durable anti-tumor immunity in both front-line and BCG-unresponsive settings without associated systemic toxicity (Garris and Wong, et al., Sci Transl Med, 2021;13:eabd1346). These data provide rationale to investigate intravesical 2141-V11 for the treatment of BCG-unresponsive NMIBC. Methods: This is a phase 1, open-label, dose-escalation study (NCT05126472) to evaluate the safety and tolerability of intravesically-delivered 2141-V11 in patients with BCG-unresponsive NMIBC who are considered ineligible for or have elected not to undergo radical cystectomy. Key inclusion criteria include adults with high-grade NMIBC (Ta, CIS, and/or T1) of urothelial histology that is unresponsive to adequate BCG therapy per consensus 2018 FDA guidelines. The primary objectives are to evaluate the safety and tolerability of 2141-V11 and to define the maximum tolerated dose and/or recommended phase 2 dose. The secondary objectives are to characterize the pharmacokinetics and evaluate the preliminary clinical activity of 2141-V11. Exploratory objectives include assessment of biomarkers of biological activity and disease resistance, their potential associations with clinical outcome measures, and patient-reported outcomes/quality of life measures. The 2141-V11 antibody is administered intravesically once weekly for 3 doses. Depending on disease status at week 13 and week 25 evaluations, patients may be eligible for re-treatment (once weekly for 3 doses) at these time points. Dose exploration utilizes a modified continual reassessment method design. Enrollment began in November 2021 and is ongoing. Clinical trial information: NCT05126472.

A Phase Ib Study to Assess the Safety and Tolerability of Ruxolitinib in Combination with Azacitidine in Patients with Advanced Phase Myeloproliferative Neoplasms (MPN), Including Myelodysplastic Syndromes (MDS) or Acute Myeloid Leukaemia (AML) Arising from MPN (The Bloodwise / TAP PHAZAR Study on Behalf of the UK MPN CSG)

A Phase Ib Study to Assess the Safety and Tolerability of Ruxolitinib in Combination with Azacitidine in Patients with Advanced Phase Myeloproliferative Neoplasms (MPN), Including Myelodysplastic Syndromes (MDS) or Acute Myeloid Leukaemia (AML) Arising from MPN (The Bloodwise / TAP PHAZAR Study on Behalf of the UK MPN CSG)

Combined Azacitidine and High Dose Lenalidomide Therapy Is Well Tolerated and Clinically Active in Patients Who Relapse after Allogeneic Stem Cell Transplantation for Actue Myeloid Leukemia: Results of the Uk Trials Acceleration Programme Viola Trial

▪Introduction: The outcome for patients who relapse after allogeneic stem cell transplantation (allo-SCT) remains extremely poor and the development of novel salvage regimens represents a major unmet clinical need. Intensive chemotherapy is not only frequently ineffective in this population but also associated with substantial toxicity which substantially limits its utilization in practice. Both azacitidine (AZA) and lenalidomide (LEN) represent promising salvage agents post allograft not only because they demonstrate significant anti-tumor activity as monotherapy in AML and MDS but also because they have the potential to augment the graft-versus-leukemia effect. AZA is well tolerated post-transplant and results in a reduced risk of graft-versus-host disease (GVHD) in animal models but is associated with only modest clinical activity in patients who relapse after allo-SCT. LEN, however, results in excessive rates of severe GVHD when administered post-transplant which has limited its assessment as a salvage therapy in this setting. Reasoning that AZA may reduce the GVHD risk associated with LEN administration we evaluated the safety and efficacy of combined LEN and AZA therapy in patients with relapsed AML post allo-SCT. Patients and Methods: 29 patients with morphological evidence of disease relapse at a median of 10 months after allo-SCT were treated with escalating doses of LEN (0 mg, 2.5mg, 5 mg, 10 mg, 15 mg, 25 mg, 35 mg) in combination with AZA (75 mg/m2) x 7 days in 28 day cycles. 24 patients were transplanted for AML and 5 for MDS using a matched sibling (n = 13) or unrelated donor (n=16). Patients received a median of 3 cycles of LEN/AZA combination therapy.The maximum tolerated dose (MTD) of LEN/AZA combination therapy was estimated using a modified continual reassessment method (CRM) based on occurrence of dose-limiting toxicities observed within the first cycle. Clinical response was assessed after every 3rd cycle using modified Cheson criteria. The frequency of CD3+ T cells and their expression of PD1, LAG3, and TIM3 exhaustion markers was analyzed in all samples by flow cytometry. T cell activation status was determined by PMA and ionomycin stimulation followed by cytokine profile analyzing bead-array flow cytometry. Results: Using an efficient CRM model a dose of 25 mg LEN (days 10-30) in combination with AZA 75 mg/m2 x 7 days (days 1-5, 8-9) was established as the MTD. Only one patient developed Grade 3-4 GVHD during LEN/AZA combined therapy. Major clinical responses were observed in 7 of the 15 patients who received three or more cycles of combined LEN/AZA treatment: CR/CRi n=6, PR n=1. Acquisition of a major clinical response was associated with prolonged overall survival (OS): median OS 17.3 versus 3.2 months (p<0.001). Increased levels of PD1 and LAG3 expression were present on CD3+ T cells at baseline compared with healthy controls (p=0.0025 and p=0.0177 respectively) consistent with a T cell exhaustion phenotype. T cells demonstrated impaired IFN-γ/TNF-α production at relapse and this was not reversed during LEN/AZA therapy. Conclusion: High doses of LEN can be safely delivered post-allograft when co-administered with AZA. Assessment of the MTD in this very high risk patient population was accelerated by the adoption of a CRM design which coped effectively with the challenges of cohort variation and early patient drop out. LEN/AZA combination therapy demonstrates promising clinical activity supporting further prospective evaluation as a novel salvage strategy post-transplant. Preliminary data supports combined LEN/AZA therapy exerting an anti-leukemia effect through a PD1 independent pathway. DisclosuresCavenagh:Amgen: Honoraria; Janssen: Honoraria; Celgene: Honoraria. Christina:Celgene: Honoraria.

Rolling continual reassessment method with overdose control: An efficient and safe dose escalation design

In phase 1 dose escalation studies, dose limiting toxicities (DLTs) are defined as adverse events of concern occurring during a predefined time window after first dosing of patients. Standard dose escalation designs, such as the continual reassessment method (CRM), only utilize this binary DLT information. Thus, late-onset DLTs are usually not accounted for when CRM guiding the dose escalation and finally defining the maximum tolerated dose (MTD) of the drug, which brings safety concerns for patients. Previously, several extensions of CRMs, such as the time-to-event CRM (TITE-CRM), fractional CRM (fCRM) and the data augmented CRM (DA-CRM), have been proposed to handle this issue without prolonging trial duration. However, among the model-based designs, none of the designs have explicitly controlled the risk of overdosing as in the escalation with overdose control (EWOC) design. Here we propose a novel dose escalation with overdose control design using a two-parameter logistic regression model for the probability of DLT depending on the dose and a piecewise exponential model for the time to DLT distribution, which we call rolling-CRM design. A comprehensive simulation study has been conducted to compare the performance of the rolling-CRM design with other dose escalation designs. Of note, the trial duration is significantly shorter compared to traditional CRM designs. The proposed design also retains overdose control characteristics, but might require a larger sample size compared to traditional CRM designs.

A Bayesian dose-finding design for outcomes evaluated with uncertainty.

In some phase I trial settings, there is uncertainty in assessing whether a given patient meets the criteria for dose-limiting toxicity. We present a design which accommodates dose-limiting toxicity outcomes that are assessed with uncertainty for some patients. Our approach could be utilized in many available phase I trial designs, but we focus on the continual reassessment method due to its popularity. We assume that for some patients, instead of the usual binary dose-limiting toxicity outcome, we observe a physician-assessed probability of dose-limiting toxicity specific to a given patient. Data augmentation is used to estimate the posterior probabilities of dose-limiting toxicity at each dose level based on both the fully observed and partially observed patient outcomes. A simulation study is used to assess the performance of the design relative to using the continual reassessment method on the true dose-limiting toxicity outcomes (available in simulation setting only) and relative to simple thresholding approaches. Among the designs utilizing the partially observed outcomes, our proposed design has the best overall performance in terms of probability of selecting correct maximum tolerated dose and number of patients treated at the maximum tolerated dose. Incorporating uncertainty in dose-limiting toxicity assessment can improve the performance of the continual reassessment method design.

A simulation-free approach to assessing the performance of the continual reassessment method.

The continual reassessment method (CRM) is an adaptive design for Phase I trials whose operating characteristics, including appropriate sample size, probability of correctly identifying the maximum tolerated dose, and the expected proportion of participants assigned to each dose, can only be determined via simulation. The actual time to determine a final "best" design can take several hours or days, depending on the number of scenarios that are examined. The computational cost increases as the kernel of the one-parameter CRM design is expanded to other settings, including additional parameters, monitoring of both toxicity and efficacy, and studies of combinations of two agents. For a given vector of true DLT probabilities, we have developed an approach that replaces a simulation study of thousands of hypothetical trials with a single simulation. Our approach, which is founded on the consistency of the CRM, very accurately reflects the results produced by the simulation study, but does so in a fraction of time required by the simulation study. Relative to traditional simulations, we extensively examine how our method is able to assess the operating characteristics of a CRM design for a hypothetical trial whose characteristics are based upon a previously published Phase I trial. We also provide a metric of nonconsistency and demonstrate that although nonconsistency can impact the operating characteristics of our method, the degree of over- or under-estimation is unpredictable. As a solution, we provide an algorithm for maintaining the consistency of a chosen CRM design so that our method is applicable for any trial.

A comparison of phase I dose-finding designs in clinical trials with monotonicity assumption violation.

In oncology, new combined treatments make it difficult to order dose levels according to monotonically increasing toxicity. New flexible dose-finding designs that take into account uncertainty in dose levels ordering were compared with classical designs through simulations in the setting of the monotonicity assumption violation. We give recommendations for the choice of dose-finding design. Motivated by a clinical trial for patients with high-risk neuroblastoma, we considered designs that require a monotonicity assumption, the Bayesian Continual Reassessment Method, the modified Toxicity Probability Interval, the Bayesian Optimal Interval design, and designs that relax monotonicity assumption, the Bayesian Partial Ordering Continual Reassessment Method and the No Monotonicity Assumption design. We considered 15 scenarios including monotonic and non-monotonic dose-toxicity relationships among six dose levels. The No Monotonicity Assumption and Partial Ordering Continual Reassessment Method designs were robust to the violation of the monotonicity assumption. Under non-monotonic scenarios, the No Monotonicity Assumption design selected the correct dose level more often than alternative methods on average. Under the majority of monotonic scenarios, the Partial Ordering Continual Reassessment Method selected the correct dose level more often than the No Monotonicity Assumption design. Other designs were impacted by the violation of the monotonicity assumption with a proportion of correct selections below 20% in most scenarios. Under monotonic scenarios, the highest proportions of correct selections were achieved using the Continual Reassessment Method and the Bayesian Optimal Interval design (between 52.8% and 73.1%). The costs of relaxing the monotonicity assumption by the No Monotonicity Assumption design and Partial Ordering Continual Reassessment Method were decreases in the proportions of correct selections under monotonic scenarios ranging from 5.3% to 20.7% and from 1.4% to 16.1%, respectively, compared with the best performing design and were higher proportions of patients allocated to toxic dose levels during the trial. Innovative oncology treatments may no longer follow monotonic dose levels ordering which makes standard phase I methods fail. In such a setting, appropriate designs, as the No Monotonicity Assumption or Partial Ordering Continual Reassessment Method designs, should be used to safely determine recommended for phase II dose.

Practicalities in running early-phase trials using the time-to-event continual reassessment method (TiTE-CRM) for interventions with long toxicity periods using two radiotherapy oncology trials as examples

BackgroundAwareness of model-based designs for dose-finding studies such as the Continual Reassessment Method (CRM) is now becoming more commonplace amongst clinicians, statisticians and trial management staff. In some settings toxicities can occur a long time after treatment has finished, resulting in extremely long, interrupted, CRM design trials. The Time-to-Event CRM (TiTE-CRM), a modification to the original CRM, accounts for the timing of late-onset toxicities and results in shorter trial duration. In this article, we discuss how to design and deliver a trial using this method, from the grant application stage through to dissemination, using two radiotherapy trials as examples.MethodsThe TiTE-CRM encapsulates the dose-toxicity relationship with a statistical model. The model incorporates observed toxicities and uses a weight to account for the proportion of completed follow-up of participants without toxicity. This model uses all available data to determine the next participant’s dose and subsequently declare the maximum tolerated dose.We focus on two trials designed by the authors to illustrate practical issues when designing, setting up, and running such studies.ResultsIn setting up a TiTE-CRM trial, model parameters need to be defined and the time element involved might cause complications, therefore looking at operating characteristics through simulations is essential. At the grant application stage, we suggest resources to fund statisticians’ time before funding is awarded and make recommendations for the level of detail to include in funding applications. While running the trial, close contact of all involved staff is required as a dose decision is made each time a participant is recruited. We suggest ways of capturing data in a timely manner and give example code in R for design and delivery of the trial. Finally, we touch upon dissemination issues while the trial is running and upon completion.ConclusionModel-based designs can be complex. We hope this paper will help clinical trial teams to demystify the conduct of TiTE-CRM trials and be a starting point for using this methodology in practice.

How to design a dose-finding study using the continual reassessment method

IntroductionThe continual reassessment method (CRM) is a model-based design for phase I trials, which aims to find the maximum tolerated dose (MTD) of a new therapy. The CRM has been shown to be more accurate in targeting the MTD than traditional rule-based approaches such as the 3 + 3 design, which is used in most phase I trials. Furthermore, the CRM has been shown to assign more trial participants at or close to the MTD than the 3 + 3 design. However, the CRM’s uptake in clinical research has been incredibly slow, putting trial participants, drug development and patients at risk. Barriers to increasing the use of the CRM have been identified, most notably a lack of knowledge amongst clinicians and statisticians on how to apply new designs in practice. No recent tutorial, guidelines, or recommendations for clinicians on conducting dose-finding studies using the CRM are available. Furthermore, practical resources to support clinicians considering the CRM for their trials are scarce.MethodsTo help overcome these barriers, we present a structured framework for designing a dose-finding study using the CRM. We give recommendations for key design parameters and advise on conducting pre-trial simulation work to tailor the design to a specific trial. We provide practical tools to support clinicians and statisticians, including software recommendations, and template text and tables that can be edited and inserted into a trial protocol. We also give guidance on how to conduct and report dose-finding studies using the CRM.ResultsAn initial set of design recommendations are provided to kick-start the design process. To complement these and the additional resources, we describe two published dose-finding trials that used the CRM. We discuss their designs, how they were conducted and analysed, and compare them to what would have happened under a 3 + 3 design.ConclusionsThe framework and resources we provide are aimed at clinicians and statisticians new to the CRM design. Provision of key resources in this contemporary guidance paper will hopefully improve the uptake of the CRM in phase I dose-finding trials.

A pragmatic approach to the design and calibration of a Bayesian CRM dose finding trial

The Continual Reassessment Method (CRM) is not widely used in early phase dose finding trials partly because the logistics of development and implementation are perceived as complex and time consuming. Details are presented of the steps involved when designing such a trial using an adaptation of a Bayesian CRM calibration algorithm proposed by Cheung [1]. In addition to clinician centred parameters including target toxicity probability and number of test doses, the Bayesian CRM requires specification of the prior probability of toxicity associated with each of the test doses and the prior SD of the single model parameter. Cheung’s simple pragmatic approach is used to aid selection of these parameters. Competing designs are assessed in terms of risk-adjusted accuracy and trial specific requirements including the mean number of patients treated above the maximum tolerated dose. Performance measures are estimated by Monte Carlo simulation across a range of scenarios chosen solely upon the target toxicity level and the number of test doses. We demonstrate that following this pragmatic approach to CRM design calibration, design of CRM trials need not be overly complex or time-consuming.

A statistical evaluation of dose expansion cohorts in phase I clinical trials.

Phase I trials often include a dose expansion cohort (DEC), in which additional patients are treated at the estimated maximum tolerated dose (MTD) after dose escalation, with the goal of ensuring that data are available from more than six patients at a single dose level. However, protocols do not always detail how, or even if, the additional toxicity data will be used to reanalyze the MTD or whether observed toxicity in the DEC will warrant changing the assigned dose. A DEC strategy has not been statistically justified. We conducted a simulation study of two phase I designs: the "3+3" and the Continual Reassessment Method (CRM). We quantified how many patients are assigned the true MTD using a 10 to 20 patient DEC and how a sensible reanalysis using the DEC changes the probability of selecting the true MTD. We compared these results with those from an equivalently sized larger CRM that does not include a DEC. With either the 3+3 or CRM, reanalysis with the DEC increased the probability of identifying the true MTD. However, a large CRM without a DEC was more likely to identify the true MTD while still treating 10 or 15 patients at this dose level. Where feasible, a CRM design with no explicit DEC is preferred to designs that fix a dose for all patients in a DEC.

Dose-Finding Trial Designs for Combination Therapies in Oncology

Dose-Finding Trial Designs for Combination Therapies in Oncology

Implementation of adaptive dose-finding designs in two early phase haematological trials: clinical, operational, and methodological challenges

The majority of Phase I dose-finding trials in oncology have been dominated by the traditional up-and-down designs, such as 3+3 designs. However, in recent years, there is an emerging interest in more innovative model-based dose finding methods such as the Continual Reassessment Method (CRM), though examples of implementing such adaptive designs in the medical literature remain limited. In this paper, we discuss three main challenges faced in the implementation of CRM in a Phase I trial in Acute Myeloid Leukaemia and a Phase I/II trial in T-cell Lymphoma, and possible solutions. Despite the mounting evidence of the CRM's superior performance in identifying the maximum tolerated dose, it remains a challenge to communicate to clinicians the rationale for using a method with such a greater level of statistical complexity. Operational challenges include trialists' impression that dose-recommendations come from a black-box, which contrast unfavourably with the transparent simple rules of a 3+3 design; and concerns that possible delays that might result. Methodological challenges include the different variants of a CRM design that could be considered, both from Bayesian and Maximum Likelihood frameworks, and how to choose an appropriate design that could be adapted to specific requirements of a trial. We discuss proposed solutions to challenges encountered and introduce the use of Dose Transition Sample Paths, demonstrating how this can be used to aid understanding in the working of such adaptive designs. We will show that it is a valuable planning tool to achieve a seamless, clear transition for each dose-recommendation.

Fractional Dose-Finding Methods with Late-Onset Toxicity in Phase I Clinical Trials

In Phase I clinical trials, the algorithm-based dose-finding methods, such as the 3 + 3 and up-and-down designs, do not impose any dose-toxicity curve. In contrast, model-based designs, such as the continual reassessment method (CRM), assume a parametric model to borrow information from all the doses under consideration. For these conventional dose-finding methods, toxicity outcomes need to be observed shortly after the treatment, so that newly enrolled patients can be treated without delay. However, in the case of late-onset toxicity, patients’ outcomes may not be observed quickly enough to keep up with the speed of enrollment, and thus toxicity data may not be available when that information is needed. Patients who have not experienced toxicity by the decision-making time may yet experience toxicity later during the rest of the follow-up. Ignoring such late-onset toxicity information may lead to biased estimation of the dose toxicity probabilities and thus compromise the trial's performance. To expand the applicability of the 3 + 3, up-and-down, and CRM designs with late-onset toxicity, we propose to redistribute the mass of the censored observation to the right and utilize the fractional contribution for the unobserved toxicity outcome. We evaluate the operating characteristics of the proposed fractional designs through extensive simulation studies. The fractional designs satisfactorily resolve the issues associated with late-onset toxicity, and are compared favorably with other available methods.

Specifications of a continual reassessment method design for phase I trials of combined drugs

In studies of combinations of agents in phase I oncology trials, the dose-toxicity relationship may not be monotone for all combinations, in which case the toxicity probabilities follow a partial order. The continual reassessment method for partial orders (PO-CRM) is a design for phase I trials of combinations that leans upon identifying possible complete orders associated with the partial order. This article addresses some practical design considerations not previously undertaken when describing the PO-CRM. We describe an approach in choosing a proper subset of possible orderings, formulated according to the known toxicity relationships within a matrix of combination therapies. Other design issues, such as working model selection and stopping rules, are also discussed. We demonstrate the practical ability of PO-CRM as a phase I design for combinations through its use in a recent trial designed at the University of Virginia Cancer Center.

Abstract 2412: Phase 1, open-label, dose-escalation studies of SGN-CD19A in patients with relapsed or refractory B-lineage acute leukemia and non-Hodgkin lymphoma.

Abstract Background. CD19 is a member of the immunoglobulin superfamily that regulates B-lineage cell development and differentiation. It is not known to be expressed by any cell outside of the B-lineage and expression is maintained upon malignant transformation. Due to its restricted normal tissue expression profile, CD19 is an attractive target for antibody-based therapeutics for the treatment of B-lineage malignancies. SGN-CD19A is a novel antibody-drug conjugate composed of a humanized anti-CD19 monoclonal antibody conjugated to the microtubule-disrupting agent monomethyl auristatin F (MMAF) via a maleimidocaproyl (mc) linker. Upon binding to CD19, SGN-CD19A internalizes and releases cys-mcMMAF, which binds to tubulin and induces G2/M arrest and apoptosis in the targeted cells. We describe two first-in-human, dose-escalation studies of SGN-CD19A. Methods. The objectives of both studies include evaluation of safety, tolerability, the pharmacokinetic (PK) profile, and antitumor activity of SGN-CD19A in patients with relapsed or refractory B-lineage malignancies. SGN19A-001 will evaluate a weekly (days 1 and 8 of 21-day cycles) and an every 3 week (q3wk) IV dosing schedule in adult and pediatric patient populations with B-lineage acute lymphoblastic leukemia and aggressive lymphoma. SGN19A-002 will enroll adult patients with B-lineage non-Hodgkin lymphoma and will test a q3wk IV dosing schedule. Both trials will employ a modified continual reassessment method (CRM) to estimate the dose-toxicity relationship, estimate the maximum tolerated dose (MTD), and allocate patients to dose levels. Each trial has an additional dose-finding expansion phase that can be initiated to further evaluate multiple doses and schedules to help identify a recommended phase 2 dose based on a utility score that weighs both toxicity and efficacy in different patient populations. The CRM algorithm estimates the efficacy and toxicity of each patient population and disease subgroup by borrowing information across groups (age and disease). Exploratory analyses will include correlation of target (CD19) expression, target saturation, and apoptotic cellular markers with clinical response and clearance of leukemic blasts; dose and PK of SGN-CD19A will also be correlated with target saturation and intracellular levels of cys-mcMMAF. These studies are scheduled to be initiated by late 2012. Expected Results. The CRM design will allow the MTDs to be identified with high probability. As designed, we expect 10 pediatric and/or 20 adult patients to be treated at or around the estimated MTDs during dose escalation. During the dose-finding expansion portions, refined estimates of the MTDs and estimates of antitumor activity at multiple dose levels will provide rationale for the best dosing regimen for future phase 2 trials. Citation Format: Tina M. Albertson, Lali Sandalic, Che-Leung Law, Kristine Broglio, Scott Berry. Phase 1, open-label, dose-escalation studies of SGN-CD19A in patients with relapsed or refractory B-lineage acute leukemia and non-Hodgkin lymphoma. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2412. doi:10.1158/1538-7445.AM2013-2412

A Generalized Continual Reassessment Method for Two-Agent Phase I Trials

Numerous models have been suggested for Phase I adaptive designs for identifying the maximum tolerated combination (MTC) of two agents. However, these designs have yet to be adopted as the standard approach to use in actual clinical trials, which we posit is mostly due to the complexity of the models that are used. Given that the continual reassessment method (CRM) is gradually being adopted as a standard for single-agent Phase I trials, we propose a generalized version of the CRM, which we denote by gCRM, in hopes of providing such a standard for two-agent trials. For each dose of one agent, we apply the traditional CRM to study doses of the other agent; each of these CRM designs assumes the same dose-toxicity model, as well as the value of the parameter used in the model. However, each model includes a second parameter that varies among the models in an effort to allow flexibility when modeling the probability of dose-limiting toxicity (DLT) of all combinations, yet borrow strength among neighboring combinations as well. We incorporate an adaptive Bayesian algorithm to sequentially assign each patient to the most appropriate dose combination, as well as focus patient assignments to a dose combination that has a DLT probability closest to a prespecified target rate. We test the performance of our method via extensive simulations in various scenarios that are likely to arise in two-agent Phase I trials. We also directly compare the operating characteristics of our model to the alternate published models.