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Cell therapies comprise one of the most important advances in oncology. One of the biggest challenges in the early development of cell therapies is to recommend safe and feasible doses to carry forward to middle development. The treatment involves extracting cells from a patient, expanding the cells and infusing the cells back into the patient. Each dose level being studied is defined by the number of cells infused into the trial participant. The manufacturing process may not generate enough cells for a given patient to receive their assigned dose level, making it infeasible to administer their intended dose. The primary design challenge is to efficiently use accumulated data from participants treated away from their assigned dose to efficiently allocate future trial participants and recommend a feasible maximum tolerated dose (FMTD) at the study conclusion. Currently, there are few available options for designing and implementing Phase I trials of cell therapies that can incorporate a dose feasibility endpoint. Moreover, the application of these designs is limited to a traditional dose-finding framework, where the dose-limiting toxicity (DLT) endpoint is observed in early cycles of therapy. This paper presents a novel phase I trial design for adoptive cell therapy that simultaneously accounts for dose feasibility and late-onset toxicities. We apply our design to a phase I dose-escalation trial of Rituximab-based bispecific activated T-cells combined with a fixed dose of Nivolumab. Our simulation results demonstrate that our proposed method can reduce trial duration without significantly hindering trial accuracy. [ABSTRACT FROM AUTHOR]

AbstractThis article considers the concept of designing Phase I clinical trials using both clinician- and patient-reported outcomes to adaptively allocate study participants to tolerable doses and determine the maximum tolerated dose (MTD) at the study conclusion. We describe a new isotonic patient-reported outcome (PRO-ISO) Phase I design with the flexibility of allocating patients to lower, more tolerable regimens if a large number of PRO-DLT events are seen at higher doses. We conduct simulation studies of the operating characteristics of the design and compared them to the patient-reported outcomes continual reassessment method (PRO-CRM). We illustrate that the PRO-ISO makes appropriate dose assignments during the study to give investigators and reviewers an idea of how the method behaves. In simulation studies, the PRO-ISO demonstrates comparable performance to the PRO-CRM in terms of recommending target doses and allocating patients to these doses. It also performs well relative to a nonparametric optimal benchmark applied to the PRO setting. Finally, we extend our methodology to account for the problem of late-onset toxicities. [ABSTRACT FROM AUTHOR]

This article addresses the problem of identifying the maximum tolerated dose (MTD) in Phase I dose-finding clinical trials with late-onset toxicities. The main design challenge is how best to adaptively allocate study participants to tolerable doses when the evaluation window for the toxicity endpoint is long relative to the accrual rate of new participants. We propose a new design framework based on order-restricted statistical inference that addresses this challenge in sequential dose assignments. We illustrate the proposed method on real data from a Phase I trial of bortezomib in lymphoma patients and apply it to a Phase I trial of radiotherapy in prostate cancer patients. We conduct extensive simulation studies to compare our design's operating characteristics to existing published methods. Overall, our proposed design demonstrates good performance relative to existing methods in allocating participants at and around the MTD during the study and accurately recommending the MTD at the study conclusion. [ABSTRACT FROM AUTHOR]

In recent years, the landscape in clinical trial development has changed to involve many molecularly targeted agents, immunotherapies, or radiotherapy, as a single agent or in combination. Given their different mechanisms of action and lengths of administration, these agents have different toxicity profiles, which has resulted in numerous challenges when applying traditional designs such as the 3 + 3 design in dose-finding clinical trials. Novel methods have been proposed to address these design challenges such as combinations of therapies or late-onset toxicities. However, their design and implementation require close collaboration between clinicians and statisticians to ensure that the appropriate design is selected to address the aims of the study and that the design assumptions are pertinent to the study drug. The goal of this paper is to provide guidelines for appropriate questions that should be considered early in the design stage to facilitate the interactions between clinical and statistical teams and to improve the design of dose-finding clinical trials for novel anticancer agents. [ABSTRACT FROM AUTHOR]

Purpose: The phase 1 portion of this multicenter, phase 1/2 study of hypofractionated (HypoFx) prostate bed radiation therapy (RT) as salvage or adjuvant therapy aimed to identify the shortest dose-fractionation schedule with acceptable toxicity. The phase 2 portion aimed to assess the health-related quality of life (QoL) of using this HypoFx regimen.Methods and Materials: Eligibility included standard adjuvant or salvage prostate bed RT indications. Patients were assigned to receive 1 of 3 daily RT schedules: 56.6 Gy in 20 Fx, 50.4 Gy in 15 Fx, or 42.6 Gy in 10 Fx. Regional nodal irradiation and androgen deprivation therapy were not allowed. Participants were followed for 2 years after treatment with outcome measures based on prostate-specific antigen levels, toxicity assessments (Common Terminology Criteria for Adverse Events, v4.0), QoL measures (the Expanded Prostate Cancer Index Composite [EPIC] and EuroQol EQ-5D instruments), and out-of-pocket costs.Results: There were 32 evaluable participants, and median follow-up was 3.53 years. The shortest dose-fractionation schedule with acceptable toxicity was determined to be 42.6 Gy in 10 Fx, with most patients (23) treated with this schedule. Grade 3 genitourinary (GU) and gastrointestinal (GI) toxicities occurred in 3 patients and 1 patient, respectively. There was 1 grade 4 sepsis event. Higher dose to the hottest 25% of the rectum was associated with increased risk of grade 2+ GI toxicity; no dosimetric factors were found to predict for GU toxicity. There was a significant decrease in the mean bowel, but not bladder, QoL score at 1 year compared with baseline. Prostate-specific antigen failure occurred in 34.3% of participants, using a definition of nadir plus 2 ng/mL. Metastases were more likely to occur in regional lymph nodes (5 of 7) than in bones (2 of 7). The mean out-of-pocket cost for patients during treatment was $223.90.Conclusions: We identified 42.6 Gy in 10 fractions as the shortest dose-fractionation schedule with acceptable toxicity in this phase 1/2 study. There was a higher than expected rate of grade 2 to 3 GU and GI toxicity and a decreased EPIC bowel QoL domain with this regimen. Future studies are needed to explore alternative adjuvant/salvage HypoFx RT schedules after radical prostatectomy. [ABSTRACT FROM AUTHOR]

In recent years, the landscape in clinical trial development has changed to involve many molecularly targeted agents, immunotherapies, or radiotherapy, as a single agent or in combination. Given their different mechanisms of action and lengths of administration, these agents have different toxicity profiles, which has resulted in numerous challenges when applying traditional designs such as the 3 + 3 design in dose-finding clinical trials. Novel methods have been proposed to address these design challenges such as combinations of therapies or late-onset toxicities. However, their design and implementation require close collaboration between clinicians and statisticians to ensure that the appropriate design is selected to address the aims of the study and that the design assumptions are pertinent to the study drug. The goal of this paper is to provide guidelines for appropriate questions that should be considered early in the design stage to facilitate the interactions between clinical and statistical teams and to improve the design of dose-finding clinical trials for novel anticancer agents. [ABSTRACT FROM AUTHOR]

This paper studies the notion of coherence in interval‐based dose‐finding methods. An incoherent decision is either (a) a recommendation to escalate the dose following an observed dose‐limiting toxicity or (b) a recommendation to deescalate the dose following a non–dose‐limiting toxicity. In a simulated example, we illustrate that the Bayesian optimal interval method and the Keyboard method are not coherent. We generated dose‐limiting toxicity outcomes under an assumed set of true probabilities for a trial of n=36 patients in cohorts of size 1, and we counted the number of incoherent dosing decisions that were made throughout this simulated trial. Each of the methods studied resulted in 13/36 (36%) incoherent decisions in the simulated trial. Additionally, for two different target dose‐limiting toxicity rates, 20% and 30%, and a sample size of n=30 patients, we randomly generated 100 dose‐toxicity curves and tabulated the number of incoherent decisions made by each method in 1000 simulated trials under each curve. For each method studied, the probability of incurring at least one incoherent decision during the conduct of a single trial is greater than 75%. Coherency is an important principle in the conduct of dose‐finding trials. Interval‐based methods violate this principle for cohorts of size 1 and require additional modifications to overcome this shortcoming. Researchers need to take a closer look at the dose assignment behavior of interval‐based methods when using them to plan dose‐finding studies. [ABSTRACT FROM AUTHOR]

Introduction: In contemporary oncology drug development, implementation of novel early-phase designs with the ability to address multiple research objectives is needed to better refine regimens. This paper describes an adaptive design strategy for identifying a range of optimal regimens based on two endpoints within multiple cohorts. The proposed design was developed to address objectives in an early-phase trial of cancer vaccines in combination with agonistic antibodies to CD40 and CD27. Materials and methods: We describe a model-based design strategy that was developed for a trial evaluating the safety and immunogenicity of vaccination with (1) peptides plus CD40 antibody and TLR3 ligand, (2) systemic administration of an agonistic CD27 antibody, and (3) to assess immune response from (1) and (2) compared to optimal controls in participants with stage IIB-IV melanoma. Results and conclusions: The proposed design is a practical adaptive method for use with combined immunotherapy regimens with multiple objectives within multiple cohorts of interest. Further advances in the effectiveness of cancer immunotherapies will require new approaches that include redefining optimal strategies to take multiple regimens forward into later phases, incorporating additional endpoints in the dose selection process and testing drug combination therapies to improve efficacy and reduce toxicity. Our goal is to facilitate the acceptance and application of more novel designs in contemporary early development trials. [ABSTRACT FROM AUTHOR]

In this article, we propose and evaluate three alternative randomization strategies to the adaptive randomization (AR) stage used in a seamless Phase I/II dose-finding design. The original design was proposed by Wages and Tait in 2015 for trials of molecularly targeted agents in cancer treatments, where dose-efficacy assumptions are not always monotonically increasing. Our goal is to improve the design's overall performance regarding the estimation of optimal dose as well as patient allocation to effective treatments. The proposed methods calculate randomization probabilities based on the likelihood of every candidate model as opposed to the original design which selects the best model and then randomizes doses based on estimations from the selected model. Unlike the original method, our proposed adaption does not require an arbitrarily specified sample size for the adaptive randomization stage. Simulations are used to compare the proposed strategies and a final strategy is recommended. Under most scenarios, our recommended method allocates more patients to the optimal dose while improving accuracy in selecting the final optimal dose without increasing the overall risk of toxicity. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The primary endpoint of most dose-finding cancer trials is patient toxicity, and the primary goal is to identify the maximum tolerated dose (MTD), that is, the highest dose that falls below or within a pre-specified toxicity tolerability threshold. Conventionally, dose-finding methods have utilized a binary toxicity endpoint based on whether or not a patient experiences a dose limiting-toxicity (DLT). Improving upon this, in recent years several methods have been developed for modeling toxicity scores, a novel continuous endpoint designed to more precisely estimate patient toxicity burden. Separately, drug-combination trials have become increasingly prevalent, and due to added complexities regarding estimating 'true' dose ordering and potential for more complex patient toxicity profiles, provide an ideal setting which may benefit from the improved precision of toxicity scores. In this paper, we merge two frameworks based on the Continual Reassessment Method (CRM) - the Quasi-CRM and the Partial Order CRM (POCRM) – to propose a novel approach for modeling toxicity scores in a combination-trial setting. We demonstrate that utilizing toxicity scores has the potential to greatly improve correct dose-selection over a variety of trial scenarios. We further present a simple adaptation to the toxicity-score model to control for potential over-dosing issues such that it adheres to the conventional DLT definition and will, at worst, perform equivalently to that of the traditional binary DLT framework. We demonstrate that extending toxicity scores to the combination-trial setting offers potential for improvement over the conventional binary endpoint models. [ABSTRACT FROM AUTHOR]

There has been constant development of novel statistical methods in the design of early-phase clinical trials since the introduction of model-based designs, yet the traditional or modified 3+3 algorithmic design remains the most widely used approach in dose-finding studies. Research has shown the limitations of this traditional design compared with more innovative approaches yet the use of these model-based designs remains infrequent. This can be attributed to several causes including a poor understanding from clinicians and reviewers into how the designs work, and how best to evaluate the appropriateness of a proposed design. These barriers are likely to be enhanced in the coming years as the recent paradigm of drug development involves a shift to more complex dose-finding problems. This article reviews relevant information that should be included in clinical trial protocols to aid in the acceptance and approval of novel methods. We provide practical guidance for implementing these efficient designs with the aim of augmenting a broader transition from algorithmic to adaptive model-guided designs. In addition we highlight issues to consider in the actual implementation of a trial once approval is obtained. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The majority of phase I methods for multi-agent trials have focused on identifying a single maximum tolerated dose combination (MTDC) among those being investigated. Some published methods in the area have been based on the notion that there is no unique MTDC and that the set of dose combinations with acceptable toxicity forms an equivalence contour in two dimensions. Therefore, it may be of interest to find multiple MTDCs for further testing for efficacy in a phase II setting. In this paper, we present a new dose-finding method that extends the continual reassessment method to account for the location of multiple MTDCs. Operating characteristics are demonstrated through simulation studies and are compared with existing methodology. Some brief discussion of implementation and available software is also provided. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Toxicity probability interval designs have received increasing attention as a dose-finding method in recent years. In this study, we compared the two-stage, likelihood-based continual reassessment method (CRM), modified toxicity probability interval (mTPI), and the Bayesian optimal interval design (BOIN) in order to evaluate each method's performance in dose selection for phase I trials. We use several summary measures to compare the performance of these methods, including percentage of correct selection (PCS) of the true maximum tolerable dose (MTD), allocation of patients to doses at and around the true MTD, and an accuracy index. This index is an efficiency measure that describes the entire distribution of MTD selection and patient allocation by taking into account the distance between the true probability of toxicity at each dose level and the target toxicity rate. The simulation study considered a broad range of toxicity curves and various sample sizes. When considering PCS, we found that CRM outperformed the two competing methods in most scenarios, followed by BOIN, then mTPI. We observed a similar trend when considering the accuracy index for dose allocation, where CRM most often outperformed both mTPI and BOIN. These trends were more pronounced with increasing number of dose levels. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

We propose a new design for dose finding for cytotoxic agents in two ordered groups of patients. By ordered groups, we mean that prior to the study there is clinical information that would indicate that for a given dose one group would be more susceptible to toxicities than patients in the other group. The designs are evaluated relative to two previously proposed designs for ordered groups over a range of scenarios generated randomly from a family of dose-toxicity curves. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Introduction: Infiltration of non-small-cell lung cancer (NSCLC) by CD8 T lymphocytes predicts improved patient survival; however, heterogeneity of intratumoral localization complicates this assessment. Strategies for tumor sampling may not accurately represent the whole tumor. We hypothesized that sampling strategies may alter the identification of tumors with high CD8 density and affect the prognostic significance. Patients and methods: Twenty-three primary NSCLC tumors were immunohistochemically stained for CD8 and were assessed using automated software with eight different sampling strategies or the whole tumor. Results of all sampling strategies were compared to the whole tumor counts (paired t tests, Pearson's r). Associations between CD8 densities and overall survival were assessed (log-rank test). Results: Counts from all eight sampling strategies significantly correlated with whole tumor counts ( p ≤ 0.001). However, the magnitude of CD8 cell counts and categorization into high vs low infiltrate groups were affected by the sampling strategy. The most concordant values were derived from random sampling of 20 % of the tumor, a simulated core biopsy, or from sampling the tumor center. TIL infiltration was associated with survival when sampling the center ( p = 0.038), but not the invasive margin ( p > 0.2) or other strategies. Conclusion: Different tumor sampling strategies may yield discordant TIL density results and different stratification for risk assessment. Small biopsies may be particularly unrepresentative. Random sampling of larger tumor areas is recommended. Enumerating CD8 T cells in the tumor center may have prognostic value. [ABSTRACT FROM AUTHOR]

Introduction: Infiltration of cancers by T cells is associated with improved patient survival and response to immune therapies; however, optimal approaches to induce T cell infiltration of tumors are not known. This study was designed to assess whether topical treatment of melanoma metastases with the TLR7 agonist imiquimod plus administration of a multipeptide cancer vaccine will improve immune cell infiltration of melanoma metastases. Patients and methods: Eligible patients were immunized with a vaccine comprised of 12 melanoma peptides and a tetanus toxoid-derived helper peptide, and imiquimod was applied topically to metastatic tumors daily. Adverse events were recorded, and effects on the tumor microenvironment were evaluated from sequential tumor biopsies. T cell responses were assessed by IFNγ ELIspot assay and T cell tetramer staining. Patient tumors were evaluated for immune cell infiltration, cytokine and chemokine production, and gene expression. Results and conclusions: Four eligible patients were enrolled, and administration of imiquimod and vaccination were well tolerated. Circulating T cell responses to the vaccine was detected by ex vivo ELIspot assay in 3 of 4 patients. Treatment of metastases with imiquimod induced immune cell infiltration and favorable gene signatures in the patients with circulating T cell responses. This study supports further study of topical imiquimod combined with vaccines or other immune therapies for the treatment of melanoma. [ABSTRACT FROM AUTHOR]

Introduction: Optimal approaches to induce T cell infiltration of tumors are not known. Chemokines CXCL9, CXCL10, and CXCL11 support effector T cell recruitment and may be induced by IFN. This study tests the hypothesis that intratumoral administration of IFNγ will induce CXCL9-11 and will induce T cell recruitment and anti-tumor immune signatures in melanoma metastases. Patients and methods: Nine eligible patients were immunized with a vaccine comprised of 12 class I MHC-restricted melanoma peptides and received IFNγ intratumorally. Effects on the tumor microenvironment were evaluated in sequential tumor biopsies. Adverse events (AEs) were recorded. T cell responses to vaccination were assessed in PBMC by IFNγ ELISPOT assay. Tumor biopsies were evaluated for immune cell infiltration, chemokine protein expression, and gene expression. Results: Vaccination and intratumoral administration of IFNγ were well tolerated. Circulating T cell responses to vaccine were detected in six of nine patients. IFNγ increased production of chemokines CXCL10, CXCL11, and CCL5 in patient tumors. Neither vaccination alone, nor the addition of IFNγ promoted immune cell infiltration or induced anti-tumor immune gene signatures. Conclusion: The melanoma vaccine induced circulating T cell responses, but it failed to infiltrate metastases, thus highlighting the need for combination strategies to support T cell infiltration. A single intratumoral injection of IFNγ induced T cell-attracting chemokines; however, it also induced secondary immune regulation that may paradoxically limit immune infiltration and effector functions. Alternate dosing strategies or additional combinatorial treatments may be needed to promote trafficking and retention of tumor-reactive T cells in melanoma metastases. [ABSTRACT FROM AUTHOR]

Adaptive, model-based, dose-finding methods, such as the continual reassessment method, have been shown to have good operating characteristics. One school of thought argues in favor of the use of parsimonious models, not modeling all aspects of the problem, and using a strict minimum number of parameters. In particular, for the standard situation of a single homogeneous group, it is common to appeal to a one-parameter model. Other authors argue for a more classical approach that models all aspects of the problem. Here, we show that increasing the dimension of the parameter space, in the context of adaptive dose-finding studies, is usually counter productive and, rather than leading to improvements in operating characteristics, the added dimensionality is likely to result in difficulties. Among these are inconsistency of parameter estimates, lack of coherence in escalation or de-escalation, erratic behavior, getting stuck at the wrong level, and, in almost all cases, poorer performance in terms of correct identification of the targeted dose. Our conclusions are based on both theoretical results and simulations. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Phase I trials evaluating the safety of multidrug combinations are becoming more common in oncology. Despite the emergence of novel methodology in the area, it is rare that innovative approaches are used in practice. In this article, we review three methods for Phase I combination studies that are easy to understand and straightforward to implement. We demonstrate the operating characteristics of the designs through illustration in a single trial, as well as through extensive simulation studies, with the aim of increasing the use of novel approaches in Phase I combination studies. Design specifications and software capabilities are also discussed. [ABSTRACT FROM AUTHOR]

Background: The impacts of patient age and gender on immune response (IR) and clinical outcome after cancer vaccines are not known. We hypothesized younger and female patients would have higher IR rates and better survival. Methods: Patients with resected stage IIB-IV melanoma in three clinical trials (Mel43, Mel44, Mel48) were vaccinated with 12 melanoma-associated peptides restricted by class I MHC. The cumulative incidence rate of CD8 T cell responses (direct interferon-gamma ELIspot assay) by week 7 was compared by age and gender. Overall survival (OS) and disease-free survival (DFS) landmark analyses were compared by Kaplan-Meier estimates and in multivariate analyses. Results: T cell responses were evaluated in 327 patients and detected in 50 % of males and 48 % of females, with no difference in IR by gender or menopausal status. Males had trends toward longer DFS ( p = 0.12) and OS ( p = 0.09). Cumulative incidence of IR was higher in patients <64 years of age versus older patients ( p = 0.03). OS and DFS were similar by age group ( p > 0.50). In multivariate modeling, younger age was associated with better IR (OR 0.40, p value 0.003), without an impact of age or gender on clinical outcomes. Conclusion: These data support the hypothesis that older patients are less likely to develop T cell responses to a cancer vaccine. Nonetheless, significant proportions of older patients mount immune responses with comparable survival outcomes. Thus, these data support including older patients in cancer vaccine trials, but suggest value in stratifying patients by age 64 years. [ABSTRACT FROM AUTHOR]

Little is known about the relative performance of competing model-based dose-finding methods for combination phase I trials. In this study, we focused on five model-based dose-finding methods that have been recently developed. We compared the recommendation rates for true maximum-tolerated dose combinations (MTDCs) and over-dose combinations among these methods under 16 scenarios for 3 × 3, 4 × 4, 2 × 4, and 3 × 5 dose combination matrices. We found that performance of the model-based dose-finding methods varied depending on (1) whether the dose combination matrix is square or not; (2) whether the true MTDCs exist within the same group along the diagonals of the dose combination matrix; and (3) the number of true MTDCs. We discuss the details of the operating characteristics and the advantages and disadvantages of the five methods compared. [ABSTRACT FROM AUTHOR]

In dose-finding trials of chemotherapeutic agents, the goal of identifying the maximum tolerated dose is usually determined by considering information on toxicity only, with the assumption that the highest safe dose also provides the most promising outlook for efficacy. Trials of molecularly targeted agents challenge accepted dose-finding methods because minimal toxicity may arise over all doses under consideration and higher doses may not result in greater response. In this article, we propose a new early-phase method for trials investigating targeted agents. We provide simulation results illustrating the operating characteristics of our design. [ABSTRACT FROM PUBLISHER]

Dose-finding studies that aim to evaluate the safety of single agents are becoming less common, and advances in clinical research have complicated the paradigm of dose finding in oncology. A class of more complex problems, such as targeted agents, combination therapies and stratification of patients by clinical or genetic characteristics, has created the need to adapt early-phase trial design to the specific type of drug being investigated and the corresponding endpoints. In this article, we describe the implementation of an adaptive design based on a continual reassessment method for heterogeneous groups, modified to coincide with the objectives of a Phase I/II trial of stereotactic body radiation therapy in patients with painful osseous metastatic disease. Operating characteristics of the Institutional Review Board approved design are demonstrated under various possible true scenarios via simulation studies. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

REFERENCES 1 Ratain MJ: Designing dose-finding phase I clinical trials: Top questions that should be discussed with your clinical pharmacologist. Dr Ratain attributes inappropriate dosing of approved drugs to a reliance on toxicity end points to determine the dose. Incorporating pharmacokinetic (PK) information in the dose-finding process can better estimate the dose-toxicity curve while maintaining MTD selection performance. [Extracted from the article]

Incorporating pharmacokinetic (PK) information in the dose-finding process can better estimate the dose-toxicity curve while maintaining MTD selection performance. REFERENCES 1 Ratain MJ: Designing dose-finding phase I clinical trials: Top questions that should be discussed with your clinical pharmacologist. Dr Ratain attributes inappropriate dosing of approved drugs to a reliance on toxicity end points to determine the dose. [Extracted from the article]

BACKGROUND: Tubular carcinoma (TC) of the breast is an uncommon, well-differentiated subtype of breast cancer with an excellent prognosis, but ambiguity in how it should be defined and treated. OBJECTIVE: To determine the clinicopathologic characteristics and survival outcomes of patients with TC. METHODS: The University of Virginia (UVA) Breast Cancer Database and the Surveillance, Epidemiology and End Results (SEER) databases were queried for patients with either grade 1 TC or grade 1 ductal (G1D) breast cancer. RESULTS: Nineteen institutional TC cases were identified and compared to 54 G1D cases. Flat epithelial atypia frequently was found with TC and not with G1D. There was no difference in overall or progression free survival. In SEER 18, 9,565 cases of TC were found. Most cases were stage I and patient characteristics were nearly identical. Both cause specific survival and overall survival were significantly longer for TC when compared to G1D. CONCLUSIONS: This review shows TC to have favorable behavior, with similar features to, but superior survival compared to low-grade ductal carcinoma of the breast. This suggests the adequacy of histopathologic review while reinforcing the designation of TC as a unique subtype. [ABSTRACT FROM AUTHOR]

In oncology, vaccine-based immunotherapy often investigates regimens that demonstrate minimal toxicity overall and higher doses may not correlate with greater immune response. Rather than determining the maximum tolerated dose, the goal of the study becomes locating the optimal biological dose, which is defined as a safe dose demonstrating the greatest immunogenicity, based on some predefined measure of immune response. Incorporation of adjuvants, new or optimized peptide vaccines, and combining vaccines with immune modulators may enhance immune response, with the aim of improving clinical response. Innovative dose escalation strategies are needed to establish the safety and immunogenicity of new immunologic combinations. We describe the implementation of an adaptive design for identifying the optimal treatment strategy in a multi-site, FDA-approved, phase I/II trial of a novel vaccination approach using long-peptides plus TLR agonists for resected stage IIB-IV melanoma. Operating characteristics of the design are demonstrated under various possible true scenarios via simulation studies. Overall performance indicates that the design is a practical Phase I/II adaptive method for use with combined immunotherapy agents. The simulation results demonstrate the method's ability to effectively recommend optimal regimens in a high percentage of trials with manageable sample sizes. The numerical results presented in this work include the type of simulation information that aid review boards in understanding design performance, such as average sample size and frequency of early trial termination, which we hope will augment early-phase trial design in cancer immunotherapy. [ABSTRACT FROM AUTHOR]

The aim of this investigation is to characterize vaginal apex "dog ears" and their association with patterns of treatment failure in patients with endometrial cancer treated with adjuvant high-dose-rate (HDR) single-channel vaginal cuff brachytherapy (VCB). A retrospective review of patients treated with HDR VCB from 2012 to 2021 for medically operable endometrial cancer at a single institution was conducted. Dog ears, defined as tissue at the apex extending at least 10 mm from the brachytherapy applicator were identified on CT simulation images. Fisher exact test and a multivariate logistic regression model evaluated the association between factors of interest with treatment failure. Vaginal cuff failure free survival (VCFFS) was calculated from first brachytherapy to vaginal cuff recurrence (VCR). A total of 219 patients were reviewed. In this sample, 57.5% of patients met criteria for having dog ears. In total, 13 patients (5.9%) developed a VCR. There was no statistically significant difference in the rate of VCR between patients with and without dog ears (7.1% vs. 4.3%, p = 0.56). There was a trend toward increased risk of recurrence with higher grade histology identified in the multivariate logistic regression model (p = 0.085). The estimated 3-year probability of VCFFS was 86%. Vaginal apex dog ears are prevalent but are not found to statistically increase the risk of VCR after VCB in our single institution experience. However, while local failure remains low in this population, we report an absolute value of over twice as many VCRs in patients with dog ears, indicating that with improved dog ear characterization this may remain a relevant parameter for consideration in treatment planning. [ABSTRACT FROM AUTHOR]

Existing statistical methodology on dose finding for combination chemotherapies has focused on toxicity considerations alone in finding a maximum tolerated dose combination to recommend for further testing of efficacy in a phase II setting. Recently, there has been increasing interest in integrating phase I and phase II trials in order to facilitate drug development. In this article, we propose a new adaptive phase I/II method for dual-agent combinations that takes into account both toxicity and efficacy after each cohort inclusion. The primary objective, both within and at the conclusion of the trial, becomes finding a single dose combination with an acceptable level of toxicity that maximizes efficacious response. We assume that there exist monotone dose-toxicity and dose-efficacy relationships among doses of one agent when the dose of other agent is fixed. We perform extensive simulation studies that demonstrate the operating characteristics of our proposed approach, and we compare simulated results to existing methodology in phase I/II design for combinations of agents. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The majority of methods for the design of phase I trials in oncology are based upon a single course of therapy, yet in actual practice, it may be the case that there is more than one treatment schedule for any given dose. Therefore, the probability of observing a dose-limiting toxicity may depend upon both the total amount of the dose given, as well as the frequency with which it is administered. The objective of the study then becomes to find an acceptable combination of both dose and schedule. Past literature on designing these trials has entailed the assumption that toxicity increases monotonically with both dose and schedule. In this article, we relax this assumption for schedules and present a dose-schedule finding design that can be generalized to situations in which we know the ordering between all schedules and those in which we do not. We present simulation results that compare our method with other suggested dose-schedule finding methodology. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the R package pocrm for implementing and simulating the partial order continual reassessment method (PO-CRM; [1,2]) in Phase I trials of combinations of agents. The aim of this article is to illustrate, through examples of the pocrm package, how the PO-CRM works and how its operating characteristics can inform clinical trial investigators. This should promote the use of the PO-CRM in designing and conducting dose-finding Phase I trials of combinations of agents. [Copyright &y& Elsevier]

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. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The time-to-event continual reassessment method (TITE-CRM) was proposed to handle the problem of long trial duration in Phase 1 trials as a result of late-onset toxicities. Here, we implement the TITE-CRM in dose-finding trials of combinations of agents. When studying multiple agents, monotonicity of the dose-toxicity curve is not clearly defined. Therefore, the toxicity probabilities follow a partial order, meaning that there are pairs of treatments for which the ordering of the toxicity probabilities is not known at the start of the trial. A CRM design for partially ordered trials (PO-CRM) was recently proposed. Simulation studies show that extending the TITE-CRM to the partial order setting produces results similar to those of the PO-CRM in terms of maximum tolerated dose recommendation yet reduces the duration of the trial. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary Much of the statistical methodology underlying the experimental design of phase 1 trials in oncology is intended for studies involving a single cytotoxic agent. The goal of these studies is to estimate the maximally tolerated dose, the highest dose that can be administered with an acceptable level of toxicity. A fundamental assumption of these methods is monotonicity of the dose-toxicity curve. This is a reasonable assumption for single-agent trials in which the administration of greater doses of the agent can be expected to produce dose-limiting toxicities in increasing proportions of patients. When studying multiple agents, the assumption may not hold because the ordering of the toxicity probabilities could possibly be unknown for several of the available drug combinations. At the same time, some of the orderings are known and so we describe the whole situation as that of a partial ordering. In this article, we propose a new two-dimensional dose-finding method for multiple-agent trials that simplifies to the continual reassessment method (CRM), introduced by (1990, Biometrics 46, 33-48), when the ordering is fully known. This design enables us to relax the assumption of a monotonic dose-toxicity curve. We compare our approach and some simulation results to a CRM design in which the ordering is known as well as to other suggestions for partial orders. [ABSTRACT FROM AUTHOR]

Operating characteristics for proposed clinical trial designs provide insight into performance regarding safety and accuracy, allowing the study team and review entities to determine the design's suitability to achieve the study's proposed objectives. Advances in cancer therapeutics have augmented the needs of early phase clinical trial design. Additionally, advances in research on early-phase trial design have led to the availability of a wide range of methods that show vast improvement over outdated approaches. Three trials utilizing variations of the 3 + 3 decision rule are discussed. The protocols lacked detail, including operating characteristics and guidance for decision-making that deviated from the 3 + 3 decision rule and MTD determination. We provide a discussion of the statistical issues associated with each design and operating characteristics for the proposed design compared to alternatives better suited to achieve the aims of each trial. Our results illustrate how operating characteristics inform a design's safety and accuracy. Operating characteristics can unmask poor behavior, such as a high percentage of particiapnts exposed to overly toxic doses, a low probability of correctly identifying the MTD, and inappropriate early study termination. Selection of early-phase trial design has significant implications on a trial's ability to meet its objectives. Operating characteristics are a necessary component in the design and review of a protocol, determining if the study's objectives can be achieved and documenting the study's scientific validity. Continued use of outdated approaches due to historical acceptance hinders scientific rigor and the effort to move effective agents through the drug development process. [ABSTRACT FROM AUTHOR]

Background. Breast cancer has an unacceptably high recurrence rate when any residual disease is found following neoadjuvant treatment of high-risk disease. Based on clinical data suggesting an adjuvant role for epigenetic modifying agents in breast cancer and preclinical data suggesting synergistic activity of entinostat combined with capecitabine, we conducted a phase I, open-label study of these agents in metastatic breast cancer (MBC). Both agents have published doses for use in combination therapy, but the agents had not previously been combined with each other in a human trial. Methods. A multisite phase I dose escalation study was performed at two academic centers. Patients with pretreated, HER2-negative MBC, and measurable disease were enrolled. Dual dose escalation was performed via a Bayesian partial order continual assessment method. Dose levels ranged from entinostat 3 mg to 5 mg and capecitabine 800 mg/m2 to 1000 mg/m2. Results. Thirteen patients with MBC and a median of 4 lines of prior therapy were enrolled across four dose level combinations. The most common toxicities were neutropenia, thrombocytopenia, and palmar-plantar dysesthesia, which were expected toxicities. No new safety signals were observed. One dose-limiting toxicity was observed, which did not exceed a prespecified toxicity rate of 25%. The median treatment duration was 2.37 months. No partial nor complete responses were observed. The study was halted early prior to entering an expansion phase, due to drug supply limitations. Conclusion. The tested dosing combinations of entinostat and capecitabine are likely safe in heavily pretreated metastatic breast cancer. This study's clinical investigation of entinostat in breast cancer was halted, but drug development of this agent continues outside the US. There remains a need for postoperative adjuvant drug therapy for the subpopulation of breast cancer patients with high-risk residual cancer after curative therapy. This trial is registered with NCT03473639. [ABSTRACT FROM AUTHOR]

Background: With numerous and fast approvals of different agents including immune checkpoint inhibitors, monoclonal antibodies, or chimeric antigen receptor (CAR) T-cell therapy, immunotherapy is now an established form of cancer treatment. These agents have demonstrated impressive clinical activity across many tumor types, but also revealed different toxicity profiles and mechanisms of action. The classic assumptions imposed by cytotoxic agents may no longer be applicable, requiring new strategies for dose selection and trial design. Description: This main goal of this article is to summarize and highlight main challenges of early-phase study design of immunotherapies from a statistical perspective. We compared the underlying toxicity and efficacy assumptions of cytotoxic versus immune-oncology agents, proposed novel endpoints to be included in the dose-selection process, and reviewed design considerations to be considered for early-phase trials. When available, references to software and/or web-based applications were also provided to ease the implementation. Throughout the paper, concrete examples from completed (pembrolizumab, nivolumab) or ongoing trials were used to motivate the main ideas including recommendation of alternative designs. Conclusion: Further advances in the effectiveness of cancer immunotherapies will require new approaches that include redefining the optimal dose to be carried forward in later phases, incorporating additional endpoints in the dose selection process (PK, PD, immune-based biomarkers), developing personalized biomarker profiles, or testing drug combination therapies to improve efficacy and reduce toxicity. [ABSTRACT FROM AUTHOR]

Background: Broad implementation of model-based dose-finding methods, such as the continual reassessment method (CRM), has been limited, with traditional or modified 3 + 3 designs remaining in frequent use. Part of the reason is the lack of reliable, easy-to-use, and robust software tools for designing and implementing more efficient designs.Results: With the aim of augmenting broader implementation of model-guided methods, we have developed a web application for the Bayesian CRM in the R programming language using the Shiny package. The application has two components, simulation and implementation. Within the application, one has the ability to generate simulated operating characteristics for the study design phase, and to sequentially provide the next dose recommendation for each new accrual or cohort based on the current data for the study implementation phase. At the conclusion of the study, it can be used to estimate the maximum tolerated dose (MTD). The web tool requires no programming knowledge, and it is free to access on any device with an internet browser.Conclusions: The application provides the type of simulation information that aid clinicians and reviewers in understanding operating characteristics for the accuracy and safety of the CRM, which we hope will augment phase I trial design. We believe that the development of this software will facilitate more efficient collaborations within study teams conducting single-agent dose-finding trials. [ABSTRACT FROM AUTHOR]

This article considers the problem of designing Phase I-II clinical trials with delayed toxicity and efficacy outcomes. The proposed design is motivated by a Phase I-II study evaluating all-trans retinoic acid (ATRA) in combination with a fixed dose of daratumumab in the treatment of relapsed or refractory multiple myeloma. The primary objective of the study is to identify a dose that maximizes efficacy and has an acceptable level of toxicity. The toxicity endpoint is observed in one cycle of therapy (i.e., 4 weeks) while the efficacy endpoint is assessed after 8 weeks of treatment. The difference in endpoint observation windows causes logistical challenges in conducting the trial, since it is not practical to wait until both outcomes for each patient have been fully observed before sequentially assigning the dose of a newly eligible patient. In order to avoid delays in treatment for newly enrolled patients and to accelerate trial progress, we generalize the time-to-event continual reassessment method (TITE-CRM) to bivariate outcomes. Simulation studies are conducted to evaluate the proposed method, and we found that the proposed design is able to accurately select doses that maximize efficacy and have acceptable toxicity, while using all available information in allocating patients at the time of dose assignment. We compare the proposed methodology to two existing methods in the area. [ABSTRACT FROM AUTHOR]

The vaginal cuff is a common site of tumor recurrence following surgery for endometrial cancer, and adjuvant vaginal cuff brachytherapy (VCB) is indicated to reduce the risk of local recurrence. Following hysterectomy, many patients have redundant tissue at the lateral apex of the vaginal cuff ("dog ears"). This extra tissue may extend irregularly beyond the typical cylindrical dose distribution of radiation delivered during single channel VCB and it is hypothesized that they are a potential site of local treatment failure even after VCB. The effects of the presence and size of vaginal cuff "dog ears" on tumor recurrence is not yet fully understood. The aim of this study is to evaluate the prevalence and size of extra tissue at the vaginal apex, and whether these factors predict disease recurrence in patients treated with adjuvant VCB for endometrial cancer. We retrospectively reviewed the medical records of 219 patients with early-stage endometrial cancer treated with image-guided single channel VCB at our institution from 2012 - 2021 with available brachytherapy planning CT simulation images. "Dog ears" were defined as the presence of additional soft tissue extending at least 10 mm from the apex of the vaginal cuff perpendicular to the surface of the brachytherapy applicator as defined on a coronal or axial CT simulation. Patient characteristics and outcomes including stage, size and laterality of dog ears, presence of air gaps, and patterns of failure were collected. Vaginal cuff recurrence (VCR) failure free survival was calculated from time of first brachytherapy to VCR and was estimated by the product limit method of Kaplan and Meier. Fisher's exact test was used to compare categorical variables and a multivariate logistic regression model was developed to evaluate the association of overall treatment failure with various factors of interest. We found that 57.5% of patients (n = 126) met our criteria for having "dog ears," which, on average, extended 23.8 mm (SD = 6.4) from the brachytherapy applicator. In total, 13 patients (5.9%) developed a VCR, 12 (5.5%) developed a regional recurrence, and 16 (7.3%) developed distant recurrence. There was no statistically significant difference in VCRs between patients with dog ears and those without dog ears (7.1% vs 4.3%, p=0.56). The various surgical approaches (abdominal, laparoscopic, transvaginal) did not have an increased propensity to result in dog ears (p=0.74). The 3-year probability of VCR failure-free survival is 86%. On multivariate analysis (MVA), no factors predicted for overall treatment failure including the presence of dog ears, maximum dimension of dog ears, FIGO stage, presence of air gaps at the applicator surface on post insertion CT images, or brachytherapy duration. There was a trend toward increased risk of recurrence with higher grade histology on MVA (p=0.0805). In this investigation of a single institution experience with single-channel image-guided VCB, the presence of "dog ears" at the vaginal apex is prevalent; however, VCR remains low with distant metastases being the predominant site of failure. While dog ears appear to have little impact on overall recurrence patterns, these may be a factor to consider when planning adjuvant brachytherapy including choosing alternate applicators. [ABSTRACT FROM AUTHOR]

Background: tumor-infiltrating lymphocytes are prognostic in many human cancers. However, the prognostic value of lymphocytes infiltrating glioblastoma (GBM), and roles in tumor control or progression are unclear. We hypothesized that B and T cell density, and markers of their activity, proliferation, differentiation, or function, would have favorable prognostic significance for patients with GBM. Methods: initial resection specimens from 77 patients with IDH1/2 wild type GBM who received standard-of-care treatment were evaluated with multiplex immunofluorescence histology (mIFH), for the distribution, density, differentiation, and proliferation of T cells and B cells, as well as for the presence of tertiary lymphoid structures (TLS), and IFNγ expression. Immune infiltrates were evaluated for associations with overall survival (OS) by univariate and multivariate Cox proportional hazards modeling. Results: in univariate analyses, improved OS was associated with high densities of proliferating (Ki67+) CD8+ cells (HR 0.36, p = 0.001) and CD20+ cells (HR 0.51, p = 0.008), as well as CD8+Tbet+ cells (HR 0.46, p = 0.004), and RORγt+ cells (HR 0.56, p = 0.04). Conversely, IFNγ intensity was associated with diminished OS (HR 0.59, p = 0.036). In multivariable analyses, adjusting for clinical variables, including age, resection extent, Karnofsky Performance Status (KPS), and MGMT methylation status, improved OS was associated with high densities of proliferating (Ki67+) CD8+ cells (HR 0.15, p < 0.001), and higher ratios of CD8+ cells to CD4+ cells (HR 0.31, p = 0.005). Diminished OS was associated with increases in patient age (HR 1.21, p = 0.005) and higher mean intensities of IFNγ (HR 2.13, p = 0.027). Conclusions: intratumoral densities of proliferating CD8 T cells and higher CD8/CD4 ratios are independent predictors of OS in patients with GBM. Paradoxically, higher mean intensities of IFNγ in the tumors were associated with shorter OS. These findings suggest that survival may be enhanced by increasing proliferation of tumor-reactive CD8+ T cells and that approaches may be needed to promote CD8+ T cell dominance in GBM, and to interfere with the immunoregulatory effects of IFNγ in the tumor microenvironment. [ABSTRACT FROM AUTHOR]

Background: Cancer vaccines require adjuvants to induce effective immune responses; however, there is no consensus on optimal adjuvants. We hypothesized that toll-like receptor (TLR)3 agonist polyICLC or TLR4 agonist lipopolysaccharide (LPS), combined with CD4 T cell activation, would support strong and durable CD8+ T cell responses, whereas addition of an incomplete Freund's adjuvant (IFA) would reduce magnitude and persistence of immune responses. Patients and methods: Participants with resected stage IIB-IV melanoma received a vaccine comprised of 12 melanoma peptides restricted by Class I MHC (12MP), plus a tetanus helper peptide (Tet). Participants were randomly assigned 2:1 to cohort 1 (LPS dose-escalation) or cohort 2 (polyICLC). Each cohort included 3 subgroups (a-c), receiving 12MP + Tet + TLR agonist without IFA (0), or with IFA in vaccine one (V1), or all six vaccines (V6). Toxicities were recorded (CTCAE v4). T cell responses were measured with IFNγ ELIspot assay ex vivo or after one in vitro stimulation (IVS). Results: Fifty-three eligible patients were enrolled, of which fifty-one were treated. Treatment-related dose-limiting toxicities (DLTs) were observed in 0/33 patients in cohort 1 and in 2/18 patients in cohort 2 (11%). CD8 T cell responses to 12MP were detected ex vivo in cohort 1 (42%) and in cohort 2 (56%) and in 18, 50, and 72% for subgroups V0, V1, and V6, respectively. T cell responses to melanoma peptides were more durable and of highest magnitude for IFA V6. Conclusions: LPS and polyICLC are safe and effective vaccine adjuvants when combined with IFA. Contrary to the central hypothesis, IFA enhanced T cell responses to peptide vaccines when added to TLR agonists. Future studies will aim to understand mechanisms underlying the favorable effects with IFA. [ABSTRACT FROM AUTHOR]

Traditionally, drug development has evaluated dose, safety, activity, and comparative benefit in a sequence of phases using trial designs and endpoints specifically devised for each phase. Innovations in drug development seek to consolidate the phases and rapidly expand accrual with "seamless" trial designs. Although consolidation and rapid accrual may yield efficiencies, widespread use of seamless first-in-human (FiH) trials without careful consideration of objectives, statistical analysis plans, or trial oversight raises concerns. A working group formed by the National Cancer Institute convened to consider and discuss opportunities and challenges for such trials as well as encourage responsible use of these designs. We reviewed all abstracts presented at American Society of Clinical Oncology annual meetings from 2010 to 2017 for FiH trials enrolling at least 100 patients. We identified 1786 early-phase trials enrolling 57 559 adult patients. Fifty-one of the trials (2.9%) investigated 50 investigational new drugs, were seamless, and accounted for 14.6% of the total patients. The seamless trials included a median of 3 (range = 1-13) expansion cohorts. The overall risk of clinically significant treatment-related adverse events (grade 3-4) was 49.1% (range = 0.0-100%), and seven studies reported at least one toxic death. Rapid expansion of FiH trials may lead to earlier drug approval and corresponding widespread patient access to active therapeutics. Nevertheless, seamless designs must adhere to established ethical, scientific, and statistical standards. Protocols should include prospectively planned analyses of efficacy in disease- or biomarker-defined cohorts of sufficient rigor to support accelerated approval. [ABSTRACT FROM AUTHOR]

Background: Cancer vaccines require adjuvants to induce effective immune responses; however, there is no consensus on optimal adjuvants. We hypothesized that toll-like receptor (TLR)3 agonist polyICLC or TLR4 agonist lipopolysaccharide (LPS), combined with CD4 T cell activation, would support strong and durable CD8+ T cell responses, whereas addition of an incomplete Freund's adjuvant (IFA) would reduce magnitude and persistence of immune responses. Patients and methods: Participants with resected stage IIB-IV melanoma received a vaccine comprised of 12 melanoma peptides restricted by Class I MHC (12MP), plus a tetanus helper peptide (Tet). Participants were randomly assigned 2:1 to cohort 1 (LPS dose-escalation) or cohort 2 (polyICLC). Each cohort included 3 subgroups (a-c), receiving 12MP + Tet + TLR agonist without IFA (0), or with IFA in vaccine one (V1), or all six vaccines (V6). Toxicities were recorded (CTCAE v4). T cell responses were measured with IFNγ ELIspot assay ex vivo or after one in vitro stimulation (IVS). Results: Fifty-three eligible patients were enrolled, of which fifty-one were treated. Treatment-related dose-limiting toxicities (DLTs) were observed in 0/33 patients in cohort 1 and in 2/18 patients in cohort 2 (11%). CD8 T cell responses to 12MP were detected ex vivo in cohort 1 (42%) and in cohort 2 (56%) and in 18, 50, and 72% for subgroups V0, V1, and V6, respectively. T cell responses to melanoma peptides were more durable and of highest magnitude for IFA V6. Conclusions: LPS and polyICLC are safe and effective vaccine adjuvants when combined with IFA. Contrary to the central hypothesis, IFA enhanced T cell responses to peptide vaccines when added to TLR agonists. Future studies will aim to understand mechanisms underlying the favorable effects with IFA. Trial registration: The clinical trial Mel58 was performed with IRB (#15781) and FDA approval and is registered with Clinicaltrials.gov on April 25, 2012 (NCT01585350). Patients provided written informed consent to participate. Enrollment started on June 24, 2012. [ABSTRACT FROM AUTHOR]