Phase II Study to Determine the Antitumor Activity and Safety of Simlukafusp Alfa (FAP-IL2v) Combined with Atezolizumab in Esophageal Cancer.

PURPOSE: In this study, we report the results from the esophageal squamous cell carcinoma (SCC) cohort of a phase II, noncomparative, basket study evaluating the antitumor activity and safety of fibroblast activation protein-IL2 variant (FAP-IL2v) plus atezolizumab in patients with advanced/metastatic solid tumors (NCT03386721). PATIENTS AND METHODS: Eligible patients had an Eastern Cooperative Oncology Group performance status of 0 to 1; measurable metastatic, persistent, or recurrent esophageal SCC; progression on ≥1 prior therapy; and were checkpoint inhibitor-naïve. Patients received FAP-IL2v 10 mg plus atezolizumab 1,200 mg intravenously every 3 weeks, or FAP-IL2v weekly for 4 weeks and then every 2 weeks plus atezolizumab 840 mg intravenously every 2 weeks. The primary endpoint was investigator-assessed objective response rate (ORR). RESULTS: In the response-evaluable population (N = 34), the best confirmed ORR was 20.6% [95% confidence interval (CI), 10.4-36.8], with a complete response seen in 1 patient and partial responses in 6 patients. The disease control rate was 44.1% (complete response = 2.9%; partial response = 17.6%; stable disease = 23.5%), and the median duration of response was 10.1 mon/ths (95% CI, 5.6-26.7). The median progression-free survival was 1.9 months (95% CI, 1.8-3.7). Analysis of response by PDL1 expression (Ventana SP263) resulted in an ORR of 26.7% for patients with PDL1-positive tumors (tumor area positivity cutoff ≥1%; n = 15) and 7.1% for patients with PDL1-negative tumors (tumor area positivity cutoff <1%; n = 14). Overall, the treatment combination was tolerable, and adverse events were consistent with the known safety profiles of each drug. CONCLUSIONS: FAP-IL2v plus atezolizumab demonstrated clinical activity and was tolerable in patients with previously treated esophageal SCC.

Safety, Pharmacokinetics, Pharmacodynamics, and Antitumor Activity from a Phase I Study of Simlukafusp Alfa (FAP-IL2v) in Advanced/Metastatic Solid Tumors.

PURPOSE: Simlukafusp alfa [fibroblast activation protein α-targeted IL2 variant (FAP-IL2v)], a tumor-targeted immunocytokine, comprising an IL2 variant moiety with abolished CD25 binding fused to human IgG1, is directed against fibroblast activation protein α. This phase I, open-label, multicenter, dose-escalation, and extension study (NCT02627274) evaluated the safety, pharmacokinetics, pharmacodynamics, and antitumor activity of FAP-IL2v in patients with advanced/metastatic solid tumors. PATIENTS AND METHODS: Participants received FAP-IL2v intravenously once weekly. Dose escalation started at 5 mg; flat dosing (≤25 mg) and intraparticipant uptitration regimens (15/20, 20/25, 20/20/35, and 20/35/35 mg) were evaluated. Primary objectives were dose-limiting toxicities, maximum tolerated dose, recommended expansion dose, and pharmacokinetics. RESULTS: Sixty-one participants were enrolled. Dose-limiting toxicities included fatigue (flat dose 20 mg: n = 1), asthenia (25 mg: n = 1), drug-induced liver injury (uptitration regimen 20/25 mg: n = 1), transaminase increase (20/25 mg: n = 1), and pneumonia (20/35/35 mg: n = 1). The uptitration regimen 15/20 mg was determined as the maximum tolerated dose and was selected as the recommended expansion dose. Increases in peripheral blood absolute immune cell counts were seen for all tested doses [NK cells, 13-fold; CD4+ T cells (including regulatory T cells), 2-fold; CD8+ T cells, 3.5-fold] but without any percentage change in regulatory T cells. Clinical activity was observed from 5 mg [objective response rate, 5.1% (n = 3); disease control rate, 27.1% (n = 16)]. Responses were durable [n = 3, 2.8 (censored), 6.3, and 43.4 months]. CONCLUSIONS: FAP-IL2v had a manageable safety profile and showed initial signs of antitumor activity in advanced/metastatic solid tumors.

Obinutuzumab Pretreatment as a Novel Approach to Mitigate Formation of Anti-Drug Antibodies Against Cergutuzumab Amunaleukin in Patients with Solid Tumors.

PURPOSE: The immunocytokine cergutuzumab amunaleukin (CEA-IL2v) showed manageable safety and favorable pharmacodynamics in phase I/Ib trials in patients with advanced/metastatic carcinoembryonic antigen-positive (CEA+) solid tumors, but this was accompanied by a high incidence of anti-drug antibodies (ADA). We examined B-cell depletion with obinutuzumab as a potential mitigation strategy. EXPERIMENTAL DESIGN: Preclinical data comparing B-cell depletion with rituximab versus obinutuzumab are summarized. Substudies of phase I/Ib trials investigated the effect of obinutuzumab pretreatment on ADA development, safety, pharmacodynamics, and antitumor activity of CEA-IL2v ± atezolizumab in patients with advanced/metastatic or unresectable CEA+ solid tumors who had progressed on standard of care. RESULTS: Preclinical data showed superior B-cell depletion with obinutuzumab versus rituximab. In clinical studies, patients received CEA-IL2v monotherapy with (n = 16) or without (n = 6) obinutuzumab pretreatment (monotherapy study), or CEA-IL2v + atezolizumab + obinutuzumab pretreatment (n = 5; combination study). In the monotherapy study, after four cycles (every 2 weeks treatment), 0/15 evaluable patients administered obinutuzumab pretreatment had ADAs versus 4/6 patients without obinutuzumab. Obinutuzumab pretreatment with CEA-IL2v monotherapy showed no new safety signals and pharmacodynamic data suggested minimal impact on T cells and natural killer cells. Conversely, increased liver toxicity was observed in the combination study (CEA-IL2v + atezolizumab + obinutuzumab pretreatment). CONCLUSIONS: These preliminary findings suggest that obinutuzumab pretreatment before CEA-IL2v administration in patients with CEA+ solid tumors may be a feasible and potent ADA mitigation strategy, with an acceptable safety profile, supporting broader investigation of obinutuzumab pretreatment for ADA mitigation in other settings.

A Composite Decision Rule of CD8+ T-cell Density in Tumor Biopsies Predicts Efficacy in Early-stage, Immunotherapy Trials.

PURPOSE: To examine whether CD8+ T-cell numbers in paired tumor biopsies in early-stage clinical trials can be used as an early indicator of clinical benefit for cancer immunotherapies. EXPERIMENTAL DESIGN: Paraffin sections of tumor biopsies were stained immunohistochemically for CD8+ T cells, which were digitally enumerated. The tumor biopsies were from cancer patients in early-phase trials testing novel immunotherapeutic agents. Paired biopsies taken before the start of treatment and on-treatment were compared. A total of 155 patients were used as the training set and an additional 221 patients were used as the validation set. RESULTS: Using the Cox proportional hazard model, a ≥0.9- increase in fold change (FC) on a ln scale in CD8+ T cells (corresponding to a 2.5-fold increase on the linear scale), from baseline, demonstrated a greater association with prolonged progression-free survival and allowed improved differentiation between groups above and below the threshold. Similarly, a ≥6.2 threshold in geometric mean of the on-treatment density (OTD) of T cells, which approximately corresponds to 500 cells/mm2, correlated with longer PFS. The combination of both criteria (FC and OTD) provided the best discrimination between clinically nonactive and active compounds. CONCLUSIONS: We propose that a composite score of CD8+ T-cell density in paired biopsies taken before and on-treatment may be a new biomarker to inform on clinical outcomes in early immunotherapy clinical trials.

Predictive biomarkers for PD-1/PD-L1 checkpoint inhibitor response in NSCLC: an analysis of clinical trial and real-world data.

BACKGROUND: Many biomarkers have been proposed to be predictive of response to anti-programmed cell death protein-1 (PD-1)/anti-programmed death ligand-1 (PD-L1) checkpoint inhibitors (CPI). However, conflicting observations and lack of consensus call for an assessment of their clinical utility in a large data set. Using a combined data set of clinical trials and real-world data, we assessed the predictive and prognostic utility of biomarkers for clinical outcome of CPI in non-small cell lung cancer (NSCLC). METHODS: Retrospective cohort study using 24,152 patients selected from 71,850 patients with advanced NSCLC from electronic health records and 9 Roche atezolizumab trials. Patients were stratified into high and low biomarker groups. Correlation with treatment outcome in the different biomarker groups was investigated and compared between patients treated with CPI versus chemotherapy. Durable response was defined as having complete response/partial response without progression during the study period of 270 days. RESULTS: Standard blood analytes (eg, albumin and lymphocyte) were just prognostic, having correlation with clinical outcome irrespective of treatment type. High expression of PD-L1 on tumors (≥50% tumor cell staining) were specifically associated with response to CPI (OR 0.20; 95% CI 0.13 to 0.30; p<0.001). The association was stronger in patients with non-squamous than squamous histology, with smoking history than non-smokers, and with prior chemotherapy than first-line CPI. Higher tumor mutational burden (TMB) (≥10.44 mut/Mb) was also specifically associated with durable response to CPI (OR=0.40; 95% CI 0.29 to 0.54; p<0.001). The combination of high TMB and PD-L1 expression was the strongest predictor of durable response to CPI (OR=0.04; 95% CI 0.00 to 0.18; p<0.001). There was no significant association between PD-L1 or TMB levels with response to chemotherapy, suggesting a CPI-specific predictive effect. CONCLUSIONS: Standard blood analytes had just prognostic utility, whereas tumor PD-L1 and TMB specifically predicted response to CPI in NSCLC. The combined high TMB and PD-L1 expression was the strongest predictor of durable response. PD-L1 was also a stronger predictor in patients with non-squamous histology, smoking history or prior chemotherapy.

A multistate model for early decision-making in oncology.

The development of oncology drugs progresses through multiple phases, where after each phase, a decision is made about whether to move a molecule forward. Early phase efficacy decisions are often made on the basis of single-arm studies based on a set of rules to define whether the tumor improves ("responds"), remains stable, or progresses (response evaluation criteria in solid tumors [RECIST]). These decision rules are implicitly assuming some form of surrogacy between tumor response and long-term endpoints like progression-free survival (PFS) or overall survival (OS). With the emergence of new therapies, for which the link between RECIST tumor response and long-term endpoints is either not accessible yet, or the link is weaker than with classical chemotherapies, tumor response-based rules may not be optimal. In this paper, we explore the use of a multistate model for decision-making based on single-arm early phase trials. The multistate model allows to account for more information than the simple RECIST response status, namely, the time to get to response, the duration of response, the PFS time, and time to death. We propose to base the decision on efficacy on the OS hazard ratio (HR) comparing historical control to data from the experimental treatment, with the latter predicted from a multistate model based on early phase data with limited survival follow-up. Using two case studies, we illustrate feasibility of the estimation of such an OS HR. We argue that, in the presence of limited follow-up and small sample size, and making realistic assumptions within the multistate model, the OS prediction is acceptable and may lead to better early decisions within the development of a drug.

Modified power prior with multiple historical trials for binary endpoints.

Including historical data may increase the power of the analysis of a current clinical trial and reduce the sample size of the study. Recently, several Bayesian methods for incorporating historical data have been proposed. One of the methods consists of specifying a so-called power prior whereby the historical likelihood is downweighted with a weight parameter. When the weight parameter is also estimated from the data, the modified power prior (MPP) is needed. This method has been used primarily when a single historical trial is available. We have adapted the MPP for incorporating multiple historical control arms into a current clinical trial, each with a separate weight parameter. Three priors for the weights are considered: (1) independent, (2) dependent, and (3) robustified dependent. The latter is developed to account for the possibility of a conflict between the historical data and the current data. We analyze two real-life data sets and perform simulation studies to compare the performance of competing Bayesian methods that allow to incorporate historical control patients in the analysis of a current trial. The dependent power prior borrows more information from comparable historical studies and thereby can improve the statistical power. Robustifying the dependent power prior seems to protect against prior-data conflict.

Use of a historical control group in a noninferiority trial assessing a new antibacterial treatment: A case study and discussion of practical implementation aspects.

When recruitment into a clinical trial is limited due to rarity of the disease of interest, or when recruitment to the control arm is limited due to ethical reasons (eg, pediatric studies or important unmet medical need), exploiting historical controls to augment the prospectively collected database can be an attractive option. Statistical methods for combining historical data with randomized data, while accounting for the incompatibility between the two, have been recently proposed and remain an active field of research. The current literature is lacking a rigorous comparison between methods but also guidelines about their use in practice. In this paper, we compare the existing methods based on a confirmatory phase III study design exercise done for a new antibacterial therapy with a binary endpoint and a single historical dataset. A procedure to assess the relative performance of the different methods for borrowing information from historical control data is proposed, and practical questions related to the selection and implementation of methods are discussed. Based on our examination, we found that the methods have a comparable performance, but we recommend the robust mixture prior for its ease of implementation.

Including historical data in the analysis of clinical trials: Is it worth the effort?

Data of previous trials with a similar setting are often available in the analysis of clinical trials. Several Bayesian methods have been proposed for including historical data as prior information in the analysis of the current trial, such as the (modified) power prior, the (robust) meta-analytic-predictive prior, the commensurate prior and methods proposed by Pocock and Murray et al. We compared these methods and illustrated their use in a practical setting, including an assessment of the comparability of the current and the historical data. The motivating data set consists of randomised controlled trials for acute myeloid leukaemia. A simulation study was used to compare the methods in terms of bias, precision, power and type I error rate. Methods that estimate parameters for the between-trial heterogeneity generally offer the best trade-off of power, precision and type I error, with the meta-analytic-predictive prior being the most promising method. The results show that it can be feasible to include historical data in the analysis of clinical trials, if an appropriate method is used to estimate the heterogeneity between trials, and the historical data satisfy criteria for comparability.

A randomized phase I Bayesian dose escalation design for the combination of anti-cancer drugs.

Nowadays, treatment regimens for cancer often involve a combination of drugs. The determination of the doses of each of the combined drugs in phase I dose escalation studies poses methodological challenges. The most common phase I design, the classic '3+3' design, has been criticized for poorly estimating the maximum tolerated dose (MTD) and for treating too many subjects at doses below the MTD. In addition, the classic '3+3' is not able to address the challenges posed by combinations of drugs. Here, we assume that a control drug (commonly used and well-studied) is administered at a fixed dose in combination with a new agent (the experimental drug) of which the appropriate dose has to be determined. We propose a randomized design in which subjects are assigned to the control or to the combination of the control and experimental. The MTD is determined using a model-based Bayesian technique based on the difference of probability of dose limiting toxicities (DLT) between the control and the combination arm. We show, through a simulation study, that this approach provides better and more accurate estimates of the MTD. We argue that this approach may differentiate between an extreme high probability of DLT observed from the control and a high probability of DLT of the combination. We also report on a fictive (simulation) analysis based on published data of a phase I trial of ifosfamide combined with sunitinib.

Stochastic EM algorithm for doubly interval-censored data.

In clinical trials, it is frequently of interest to estimate the time between the onset of two events (e.g. duration of response in oncology). Here, we consider the case where subjects are assessed at fixed visits but the initial event and the terminating event occur in between visits. This type of data, called doubly interval censored, is often analyzed with standard survival techniques, assuming either that the survival time (between initial and terminating event) is known exactly or is single interval censored. We introduce a motivating dataset in which the interest is to evaluate the impact of the treatment on the duration of response endpoint. We review the existing approaches and discuss their limitations with respect to the characteristics of our motivating dataset. Furthermore, we propose a stochastic EM algorithm that overcomes the problems in the existing approaches. We show by simulations the finite sample properties of our approach.

Joint modeling of progression-free survival and death in advanced cancer clinical trials.

Progression-related endpoints (such as time to progression or progression-free survival) and time to death are common endpoints in cancer clinical trials. It is of interest to study the link between progression-related endpoints and time to death (e.g. to evaluate the degree of surrogacy). However, current methods ignore some aspects of the definitions of progression-related endpoints. We review those definitions and investigate their impact on modeling the joint distribution. Further, we propose a multi-state model in which the association between the endpoints is modeled through a frailty term. We also argue that interval-censoring needs to be taken into account to more closely match the latent disease evolution. The joint distribution and an expression for Kendall's tau are derived. The model is applied to data from a clinical trial in advanced metastatic ovarian cancer.

Dasatinib or high-dose imatinib for chronic-phase chronic myeloid leukemia resistant to imatinib at a dose of 400 to 600 milligrams daily: two-year follow-up of a randomized phase 2 study (START-R).

BACKGROUND: In patients with chronic-phase chronic myeloid leukemia (CP-CML), imatinib resistance is of increasing importance. Imatinib dose escalation was the main treatment option before dasatinib, which has 325-fold more potent inhibition than imatinib against unmutated Bcr-Abl in vitro. Data with a minimum of 2 years of follow-up were available for the current study of dasatinib and high-dose imatinib in CP-CML resistant to imatinib at daily doses from 400 mg to 600 mg. METHODS: A phase 2, open-label study was initiated of 150 patients with imatinib-resistant CP-CML who were randomized (2:1) to receive either dasatinib 70 mg twice daily (n=101) or high-dose imatinib 800 mg (400 mg twice daily; n=49). RESULTS: At a minimum follow-up of 2 years, dasatinib demonstrated higher rates of complete hematologic response (93% vs 82%; P=.034), major cytogenetic response (MCyR) (53% vs 33%; P=.017), and complete cytogenetic response (44% vs 18%; P=.0025). At 18 months, the MCyR was maintained in 90% of patients on the dasatinib arm and in 74% of patients on the high-dose imatinib arm. Major molecular response rates also were more frequent with dasatinib than with high-dose imatinib (29% vs 12%; P=.028). The estimated progression-free survival also favored dasatinib (unstratified log-rank test; P=.0012). CONCLUSIONS: After 2 years of follow-up, dasatinib demonstrated durable responses and improved response and progression-free survival rates relative to high-dose imatinib.