Hybrid-control arm construction using historical trial data for an early-phase, randomized controlled trial in metastatic colorectal cancer.

Background: Treatment for metastatic colorectal cancer patients beyond the second line remains challenging, highlighting the need for early phase trials of combination therapies for patients who had disease progression during or following two prior lines of therapy. Leveraging hybrid control design in these trials may preserve the benefits of randomization while strengthening evidence by integrating historical trial data. Few examples have been established to assess the applicability of such design in supporting early phase metastatic colorectal cancer trials.
Methods: MORPHEUS-CRC is an umbrella, multicenter, open-label, phase Ib/II, randomized, controlled trial (NCT03555149), with active experimental arms ongoing. Patients enrolled were assigned to a control arm (regorafenib, 15 patients randomized and 13 analysed) or multiple experimental arms for immunotherapy-based treatment combinations. One experimental arm (atezolizumab + isatuximab, 15 patients randomized and analysed) was completed and included in the hybrid-control study, where the hybrid-control arm was constructed by integrating data from the IMblaze370 phase 3 trial (NCT02788279). To estimate treatment efficacy, Cox and logistic regression models were used in a frequentist framework with standardized mortality ratio weighting or in a Bayesian framework with commensurate priors. The primary endpoint is objective response rate, while disease control rate, progression-free survival, and overall survival were the outcomes assessed in the hybrid-control study.
Results: The experimental arm showed no efficacy signal, yet a well-tolerated safety profile in the MORPHEUS-CRC trial. Treatment effects estimated in hybrid control design were comparable to those in the MORPHEUS-CRC trial using either frequentist or Bayesian models. Conclusions: Hybrid control provides comparable treatment-effect estimates with generally improved precision, and thus can be of value to inform early-phase clinical development in metastatic colorectal cancer.

Introduction

Randomized controlled trials are regarded as the gold standard for evaluating effectiveness of treatments, yet regulatory agencies are becoming more receptive to supplementing or replacing a control arm with historical data from previously completed trials, especially in rare and pediatric diseases or for life-threatening cancer indications with few treatment options[1,2]. In such scenarios, randomizing patients to control arms may be less acceptable due to ethical or feasibility considerations, leading to a higher proportion of patients dropping out when randomized to control arms or less likely to consent if there are higher odds of being randomized to control arms[3]. Moreover, even in trials of more-prevalent diseases or with specific eligibility criteria, challenges may be found during patient recruitment—for instance, in late-stage cancer trials with requirements for specific biomarker status[4]. Hybrid-control design using relevant individual patient data from historical clinical trials is being explored as a way to achieve more patient-centric, cost-effective, and accelerated clinical development, since fewer patients are needed for standard-of-care or placebo-control arms[5,6]. How to determine the amount of borrowing for the control arm is based on comparability between historical- and concurrent-control arms, a key question for implementing a hybrid-control design[7], and few examples have been established to assess the applicability of such design in supporting early-trial development.

Treatment for metastatic colorectal cancer (mCRC) patients beyond the second line remains challenging, despite the success of single-agent checkpoint inhibition in the patient population with microsatellite instability-high status. mCRC patients are mostly microsatellite stable, and thus do not respond to the single-agent checkpoint inhibition, highlighting the need for combination therapies. The MORPHEUS platform consists of multiple randomized umbrella phase 1b/2 trials designed to identify early efficacy signals in small cohorts and accelerate development of treatment combinations across a wide scope of cancer indications[8]. In the MORPHEUS mCRC trial, patients with microsatellite stable tumors who had been refractory to the first and second line of therapies were randomized to either experimental arms or a control arm with regorafenib, a standard-of-care therapy in this disease setting. The relatively small sample size inherent to early-phase trials can limit their potential to detect a treatment effect. Here we report the primary results of the experimental arm (atezolizumab + isatuximab) and the control arm (regorafenib) and investigate the hybrid control trial design with data integrated from historical control arm data of the IMblaze370 trial. The combination of atezolizumab plus isatuximab lacks efficacy, while the safety profile of the experimental arm is consistent with that of the control arm. The use of hybrid control design improves precision while maintains accuracy of estimates from a randomized trial.

Methods

Study design

This study established a hybrid-control arm for the MORPHEUS-CRC trial using historical control data from the IMblaze370 trial. MORPHEUS-CRC (ClinicalTrials.gov Identifier: NCT03555149) is an ongoing, phase 1b/2, open-label, multicenter, randomized study designed to identify early signals of safety and efficacy of immunotherapy-based treatment combinations in patients with refractory microsatellite-stable mCRC[8,9]. Patients in the MORPHEUS-CRC trial were randomly assigned to different treatment arms with a permuted-block randomization method; study sites obtained patients’ identification numbers and treatment assignments from an interactive voice or web-based response system (IxRS). The control arm (regorafenib) and the experimental arm (atezolizumab + isatuximab) were included in this study and were enrolled between September 2018 and August 2019 (Supplementary Fig. 1). IMblaze370 (ClinicalTrials.gov Identifier: NCT02788279) is a completed, phase 3, multicenter, open-label, randomized trial study that enrolled patients with mCRC who had disease progression with at least 2 previous systemic chemotherapy regimens between July 2016 and January 2017[10]. Patients in the IMblaze370 control arm who met the MORPHEUS-CRC eligibility criteria were selected to build an external-control arm (Supplementary Note 2). A detailed comparison of eligibility criteria in the IMblaze370 and MORPHEUS-CRC trials is in Supplementary Data File 1. The external-control arm was incorporated into the MORPHEUS-CRC concurrent-control arm to construct a hybrid-control arm using a frequentist model with propensity score (PS) weighting or a Bayesian dynamic borrowing method. An overview of the study design is shown in Fig. 1. MORPHEUS-CRC trial was reviewed by the institutional review board at each site (Supplementary Note 4), as well as the IMblaze370 trial[10]. All participants provided informed written consent. The present hybrid-control study was not prespecified in the MORPHEUS-CRC trial protocol. The study followed the Consolidated Standards of Reporting Trials (CONSORT) reporting guideline (Supplementary Fig. 3).

Fig. 1

Study overview.

Patients from the IMblaze370 trial control arm (regorafenib) who received regorafenib as the third-line treatment and met the MORPHEUS-CRC trial eligibility criteria were selected for the external-control cohort and incorporated in the MORPHEUS concurrent control arm to construct a hybrid-control cohort. DCR disease control rate, EC external control, HC hybrid control, I/E inclusion/exclusion, mCRC metastatic colorectal cancer, OS overall survival, PFS progression-free survival, PS propensity score, R randomization.

Outcome assessment

Investigator-assessed objective response rate (ORR) was the primary endpoint for MORPHEUS-CRC. For hybrid control analyses, the key secondary endpoints of disease control rate (DCR), investigator-assessed progression-free survival (PFS), and overall survival (OS) were the outcomes evaluated. ORR was not evaluated in the hybrid control analyses, because no response was observed in either of the arms. DCR was defined as the proportion of patients with complete or partial response at any time during the trial or stable disease for at least 12 weeks in the MORPHEUS-CRC. Similar definition of DCR was applied in the IMblaze370 trial, but with stable disease for at least 16 weeks. As the time interval for response assessment was every 6 weeks in the MORPHEUS-CRC and every 8 weeks in the IMblaze370 trial, the DCR in the IMblaze370 trial at 12 weeks was inferred using tumor overall response assessment at 8 and 16 weeks. Specifically, if a patient showed progressive disease at 8 weeks in the IMblaze370 trial, then the response for that patient at 12 weeks was defined as progressive disease; if a patient showed stable disease at both 8 and 16 weeks, then the response for that patient at 12 weeks was defined as stable disease; otherwise, a patient’s response was set as unknown. Disease progression was determined by clinical investigators according to the Response Evaluation Criteria in Solid Tumors (RECIST) v1.1[11]. PFS was defined as the time from trial randomization to the occurrence of disease progression or death (whichever occurs first) or end of trial follow-up. OS was defined as the time from trial randomization to the occurrence of death or end-of-trial follow-up. PFS and OS time in the external-control arm were truncated to match with the maximum PFS and OS time of the MORPHEUS-CRC trial, respectively. Safety was also reported for the MORPHEUS-CRC using the National Cancer Institute’s The Common Terminology Criteria for Adverse Events, version 4.0.

Propensity score estimation

Potential imbalance of predefined baseline characteristic and prognostic factors (hereafter referred to as baseline covariates) between the MORPHEUS experimental arm and the external-control arm were adjusted using PS with standardized mortality ratio weighting (SMRW) method. The SMRW method was preferred to the inverse probability of treatment weighting (IPTW) method in this scenario, due to considerations given in the Supplementary Note 1. PS was estimated using a multivariate logistic regression model adjusted for predefined covariates. This model assumed a linear relationship between each baseline covariate and the log-odds of the group assignment (being in the MORPHEUS-CRC experimental arm vs external-control arm). PS was calculated for each patient, representing a patient’s probability of being in the MORPHEUS-CRC experimental arm, conditioning on all baseline covariates.

The baseline covariates selected included age, sex, presence of liver metastasis, time from metastatic diagnosis to baseline (> vs ≤18 months), and Eastern Cooperative Oncology Group (ECOG) performance score (0 vs 1). Covariate selection was based on data availability, model convergence, and potential clinical importance with respect to their prognostic impact in the metastatic refractory setting[12]. Balance was assessed with standardized mean difference (SMD), where covariates with SMD < 0.25 were deemed as sufficiently balanced[13,14].

Hybrid-control modeling

Bayesian borrowing

Combining randomized- and historical-control arms in a Bayesian framework allows a dynamic proportion of the historical-control arm to be used in the hybrid-control arm in a data-driven manner. The proportion was determined by commensurability between the external-control and the concurrent-control arm. This was derived firstly based on one’s subjective determination via the prior setting on a value for the variance of difference between mean treatment-effect sizes of the two control arms, then updated with data likelihood, to produce a posterior belief for the proportion of borrowing[7]. A prior setting for the variance incorporates one’s initial guidance for the degree of borrowing; by increasing values of the prior, one places more emphasis on the randomized control and less on the historical control, i.e., discouraging the borrowing, and vice versa.

For the DCR analyses, given there were only two levels observed, stable disease (SD) and progressive disease (PD), we assumed DCR for a patient i (y) to follow a Bernoulli distribution y ~ Bernoulli(p), with p referring to the probability of SD for the patient i. We defined γ0, γ1, and γ2 to be the logit function of p in the MORPHEUS-CRC experimental arm, the concurrent-control arm, and the external-control arm, respectively; γ1 follows a normal distribution with a mean of γ2 and a variance of 1/τ, where τ follows a gamma(1,1) distribution; γ0 and γ1 are both non-informative vague priors with the Gaussian normal distribution.

For the PFS and OS analyses, we assumed survival time for a patient i (t) to follow a Weibull distribution t ~ Weibull(r, μ), with a shape of r ~ exp(10), and a scale parameter of μ. By setting the natural logarithm of hazards to be β0, β1, and β2 in the MORPHEUS-CRC experimental arm, the concurrent-control arm, and the external-control arm, respectively, we derived μ = eβ0, eβ1, eβ2 in each corresponding arm; β1 follows a normal distribution with a mean of β2 and a variance of 1/τ, where τ parametrizes commensurability and determines the degree of borrowing, which follows a half-Cauchy (0, 25) distribution; β0 and β1 are set to be noninformative, following standard normal distributions[15].

When evidence for commensurability is weak, τ is forced toward zero, increasing the prior variance of β1 by 1/τ, thereby discouraging borrowing from external data[5]. To assess the potential impact of the prior choices of τ on the results, we performed sensitivity analyses with different τ distributions. For the PFS and OS, results were consistent across different prior distributions; for the DCR, results changed slightly with priors (1/τ) of larger variances, partially due to the very small sample size and thus very large standard deviations of the result estimates (Supplementary Table 1). Moreover, we assessed the amount of prior-data conflict by visualising prior and posterior distributions of β coefficients for all three outcomes (Supplementary Fig. 2).

The implementation was written in JAGS[16] using Markov chain Monte Carlo with 3 parallel chains, each run for a 1000-iteration burn-in period followed by a 20,000-iteration production run.

Frequentist with SMRW

Logistic regression was implemented for the binary endpoint of DCR; Cox proportional hazards models were implemented for the time-to-event endpoints, PFS and OS; each model contained only one exposure variable, the group of treatment (experimental vs control treatment), and was weighted with SMRW to balance baseline covariates through the PS method. Robust variance estimator was applied for weighted models to account of within-subject correlations in the weighted pseudo-population, because a lack of independence between subjects can cause a naive model‐based variance estimator more likely to be biased, and such robust method has been shown to be an option for unbiased variance estimation in this setting[17].

Statistical analysis

Baseline demographic and clinical characteristics were summarized in the external-control (regorafenib) arm derived from the IMblaze370 trial, and the MORPHEUS-CRC concurrent-control (regorafenib) and experimental (atezolizumab + isatuximab) arms, separately. Experimental treatment efficacies were estimated by comparing the MORPHEUS-CRC experimental arm to the concurrent-control or the hybrid-control arm in a frequentist or a Bayesian framework. Survival time (PFS and OS) was determined using the Kaplan–Meier estimator with SMRW, with median point estimates and corresponding 95% CIs summarized for each arm along with the Kaplan–Meier curves. All analyses were conducted using RStudio version 1.3.0 and R version 3.6.3.

Table 1

MORPHEUS-CRC Treatment Efficacy.

	Atezolizumab + isatuximab	Regorafenib
	(n = 15)	(n = 13)
Confirmed ORR, No. (%)	0 (0.0)	0 (0.0)
% [95% CI]a	[0, 21.8]	[0, 24.7]
SD, No. (%)	3 (20.0)	8 (61.5)
% [95% CI]b	[4.3, 48.1]	[31.6, 86.1]
PD, No. (%)	10 (66.7)	3 (23.1)
% [95% CI]b,c	[38.4, 88.2]	[5.0, 53.8]
DCR, No. (%)	2 (13.3)	2 (15.4)
% [95% CI]d	[1.7, 40.0]	[1.9, 45.5]
PFS, median survival (months, 95% CI)a	1.4 (1.4–1.8)	2.8 (1.6–3.1)
OS, median survival (months, 95% CI)a	5.1 (3.1–7.8)	10.2 (4.8-NE)

Clinical cutoff: 3 March 2020. No. number of patients, DCR disease control rate, NE not estimable, ORR objective response rate, OS overall survival, PD progressive disease, PFS progression-free survival, RECIST Response Evaluation Criteria in Solid Tumors, SD stable disease, CI confidence interval.

aPer INV RECIST 1.1.

bPatients were classified as achieving stable disease or progressive disease if assessment was at least 6 weeks from randomization.

cOne patient treated with atezolizumab + isatuximab beyond progression had prolonged disease stabilization.

dCriteria for disease control is either response and/or stable disease for at least 12 weeks.

Table 2

Comparison of the Baseline Demographic and Disease Characteristics Between the External-Control Arm Derived From the IMblaze370 and the MORPHEUS-CRC Control and Experimental Arms.

	IMblaze370	MORPHEUS-CRC		P value (EC vs Atezo + Isa)	SMD (EC vs Atezo + Isa)
	Regorafenib (EC)	Atezo + Isa	Regorafenib
Total Sample size	28	15	13
Age at baseline, mean (SD)	57.0 (9.6)	52.2 (12.0)	59.5 (10.5)	0.178	0.445
Sex, No. (%)				0.859	0.058
Female	12 (42.9)	6 (40.0)	7 (53.8)
Male	16 (57.1)	9 (60.0)	6 (46.2)
Race, No. (%)				0.362	0.306
White	21 (84.0)	10 (71.4)	8 (66.7)
Non-White	4 (16.0)	4 (28.6)	4 (33.3)
Unknown	3	1	1
Region, No. (%)				0.002	1.498
North America	6 (21.4)	11 (73.3)	6 (46.2)
Europe	17 (60.7)	1 (6.7)	2 (15.4)
Asia-Pacific	5 (17.9)	3 (20.0)	5 (38.5)
Time from metastatic diagnosis to baseline, No. (%)				0.161	0.464
<18 months	7 (25.0)	7 (46.7)	4 (30.8)
≥18 months	21 (75.0)	8 (53.3)	8 (61.5)
Unknown	0	1	0
ECOG, No. (%)				0.417	0.27
0	13 (46.4)	5 (33.3)	6 (46.2)
1	15 (53.6)	10 (66.7)	7 (53.8)
RAS, No. (%)				0.924	0.032
Wild type	10 (38.5)	6 (40.0)	8 (61.5)
Mutant	16 (61.5)	9 (60.0)	5 (38.5)
Unknown	2	0	0
Liver metastases, No. (%)				0.786	0.088
No	10 (35.7)	6 (40.0)	4 (30.8)
Yes	18 (64.3)	9 (60.0)	9 (69.2)

Statistical differences between the external-control and the MORPHEUS experimental arm (atezolizumab + isatuximab) were assessed using (1) P values calculated via the 2-tailed χ2 (or Fisher exact) test for all categorical variables or the Wilcoxon rank-sum test for the age variable, and (2) standardized mean difference.

Atezo atezolizumab, EC external control, ECOG Eastern Cooperative Oncology Group, Isa isatuximab, RAS Rat Sarcoma proto-oncogene.