A study of using epigenetic modulators to enhance response to pembrolizumab (MK-3475) in microsatellite stable advanced colorectal cancer.

BACKGROUND: Approximately 95% of advanced colorectal cancer patients (CRC) have mismatch repair MMR-proficient (MMRp) tumors, which do not respond to PD1 blockade alone. Preclinical studies have shown that combined histone deacetylases (HDAC) and/or DNA methyltransferases (DNMT) inhibition can induce susceptibility to immune checkpoint therapy and inhibit tumor growth. We conducted a pilot trial evaluating PD-1 immune checkpoint inhibitor therapy in combination with DNMT and HDAC inhibitors in MMRp CRC. The study was designed with a biological endpoint of change in immune cell infiltration, to determine the optimal epigenetic combination that optimizes the tumor microenvironment. This trial was designed to test that hypothesis. RESULTS: From January 2016 to November 2018, 27 patients were enrolled with median age of 57 (range 40-69) years. Median progression-free survival and overall survival were 2.79 months and 9.17, respectively. One patient in Arm C achieved a durable partial response by RECIST criteria, lasting for approximately 19 months. The most common treatment-related hematological adverse events in all arms were anemia (62%), lymphopenia (54%) and thrombocytopenia (35%), and non-hematological AEs were anorexia (65%), nausea (77%), and vomiting (73%). CONCLUSIONS: The combination of 5-azacitidine and romidepsin with pembrolizumab was safe and tolerable in patients with advanced MMRp CRC, but with a minimal activity. Further mechanistic investigations are needed to understand epigenetic-induced immunologic shift and to expand the potential applicability of checkpoint inhibitors in this setting.

Bayesian modelling of response to therapy and drug-sensitivity in acute lymphoblastic leukemia.

Acute lymphoblastic leukemia (ALL) is a heterogeneous haematologic malignancy involving the abnormal proliferation of immature lymphocytes and accounts for most paediatric cancer cases. The management of ALL in children has seen great improvement in the last decades thanks to greater understanding of the disease leading to improved treatment strategies evidenced through clinical trials. Common therapy regimens involve a first course of chemotherapy (induction phase), followed by treatment with a combination of anti-leukemia drugs. A measure of the efficacy early in the course of therapy is the presence of minimal residual disease (MRD). MRD quantifies residual tumor cells and indicates the effiectiveness of the treatment over the course of therapy. MRD positivity is defined for values of MRD greater than 0.01%, yielding left-censored MRD observations. We propose a Bayesian model to study the relationship between patient features (leukemia subtype, baseline characteristics, and drug sensitivity profile) and MRD observed at two time points during the induction phase. Specifically, we model the observed MRD values via an auto-regressive model, accounting for left-censoring of the data and for the fact that some patients are already in remission after the first stage of induction therapy. Patient characteristics are included in the model via linear regression terms. In particular, patient-specific drug sensitivity based on ex vivo assays of patient samples is exploited to identify groups of subjects with similar profiles. We include this information as a covariate in the model for MRD. We adopt horseshoe priors for the regression coefficients to perform variable selection to identify important covariates. We fit the proposed approach to data from three prospective paediatric ALL clinical trials carried out at the St. Jude Children's Research Hospital. Our results highlight that drug sensitivity profiles and leukemic subtypes play an important role in the response to induction therapy as measured by serial MRD measures.

Pharmacotypes across the genomic landscape of pediatric acute lymphoblastic leukemia and impact on treatment response.

Contemporary chemotherapy for childhood acute lymphoblastic leukemia (ALL) is risk-adapted based on clinical features, leukemia genomics and minimal residual disease (MRD); however, the pharmacological basis of these prognostic variables remains unclear. Analyzing samples from 805 children with newly diagnosed ALL from three consecutive clinical trials, we determined the ex vivo sensitivity of primary leukemia cells to 18 therapeutic agents across 23 molecular subtypes defined by leukemia genomics. There was wide variability in drug response, with favorable ALL subtypes exhibiting the greatest sensitivity to L-asparaginase and glucocorticoids. Leukemia sensitivity to these two agents was highly associated with MRD although with distinct patterns and only in B cell ALL. We identified six patient clusters based on ALL pharmacotypes, which were associated with event-free survival, even after adjusting for MRD. Pharmacotyping identified a T cell ALL subset with a poor prognosis that was sensitive to targeted agents, pointing to alternative therapeutic strategies. Our study comprehensively described the pharmacological heterogeneity of ALL, highlighting opportunities for further individualizing therapy for this most common childhood cancer.

A Phase 1 Trial of Durvalumab in Combination with Bacillus Calmette-Guerin (BCG) or External Beam Radiation Therapy in Patients with BCG-unresponsive Non-muscle-Invasive Bladder Cancer: The Hoosier Cancer Research Network GU16-243 ADAPT-BLADDER Study.

BACKGROUND: Novel treatments and trial designs remain a high priority for bacillus Calmette-Guerin (BCG)-unresponsive non-muscle-invasive bladder cancer (NMIBC) patients. OBJECTIVE: To evaluate the safety and preliminary efficacy of anti-PD-L1 directed therapy with durvalumab (D), durvalumab plus BCG (D + BCG), and durvalumab plus external beam radiation therapy (D + EBRT). DESIGN, SETTING, AND PARTICIPANTS: A multicenter phase 1 trial was conducted at community and academic sites. INTERVENTION: Patients received 1120 mg of D intravenously every 3 wk for eight cycles. D + BCG patients also received full-dose intravesical BCG weekly for 6 wk with BCG maintenance recommended. D + EBRT patients received concurrent EBRT (6 Gy × 3 in cycle 1 only). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Post-treatment cystoscopy and urine cytology were performed at 3 and 6 -mo, with bladder biopsies required at the 6-mo evaluation. The recommended phase 2 dose (RP2D) for each regimen was the primary endpoint. Secondary endpoints included toxicity profiles and complete response (CR) rates. RESULTS AND LIMITATIONS: Twenty-eight patients were treated in the D (n = 3), D + BCG (n = 13), and D + EBRT (n = 12) cohorts. Full-dose D, full-dose BCG, and 6 Gy fractions × 3 were determined as the RP2Ds. One patient (4%) experienced a grade 3 dose limiting toxicity event of autoimmune hepatitis. The 3-mo CR occurred in 64% of all patients and in 33%, 85%, and 50% within the D, D + BCG, and D + EBRT cohorts, respectively. Twelve-month CRs were achieved in 46% of all patients and in 73% of D + BCG and 33% of D + EBRT patients. CONCLUSIONS: D combined with intravesical BCG or EBRT proved feasible and safe in BCG-unresponsive NMIBC patients. Encouraging preliminary efficacy justifies further study of combination therapy approaches. PATIENT SUMMARY: Durvalumab combination therapy can be safely administered to non-muscle-invasive bladder cancer patients with the goal of increasing durable response rates.

A Bayesian model with application for adaptive platform trials having temporal changes.

Temporal changes exist in clinical trials. Over time, shifts in patients' characteristics, trial conduct, and other features of a clinical trial may occur. In typical randomized clinical trials, temporal effects, that is, the impact of temporal changes on clinical outcomes and study analysis, are largely mitigated by randomization and usually need not be explicitly addressed. However, temporal effects can be a serious obstacle for conducting clinical trials with complex designs, including the adaptive platform trials that are gaining popularity in recent medical product development. In this paper, we introduce a Bayesian robust prior for mitigating temporal effects based on a hidden Markov model, and propose a particle filtering algorithm for computation. We conduct simulation studies to evaluate the performance of the proposed method and provide illustration examples based on trials of Ebola virus disease therapeutics and hemostat in vascular surgery.

Changes in Circulating Tumor DNA Reflect Clinical Benefit Across Multiple Studies of Patients With Non-Small-Cell Lung Cancer Treated With Immune Checkpoint Inhibitors.

PURPOSE: As immune checkpoint inhibitors (ICI) become increasingly used in frontline settings, identifying early indicators of response is needed. Recent studies suggest a role for circulating tumor DNA (ctDNA) in monitoring response to ICI, but uncertainty exists in the generalizability of these studies. Here, the role of ctDNA for monitoring response to ICI is assessed through a standardized approach by assessing clinical trial data from five independent studies. PATIENTS AND METHODS: Patient-level clinical and ctDNA data were pooled and harmonized from 200 patients across five independent clinical trials investigating the treatment of patients with non-small-cell lung cancer with programmed cell death-1 (PD-1)/programmed death ligand-1 (PD-L1)-directed monotherapy or in combination with chemotherapy. CtDNA levels were measured using different ctDNA assays across the studies. Maximum variant allele frequencies were calculated using all somatic tumor-derived variants in each unique patient sample to correlate ctDNA changes with overall survival (OS) and progression-free survival (PFS). RESULTS: We observed strong associations between reductions in ctDNA levels from on-treatment liquid biopsies with improved OS (OS; hazard ratio, 2.28; 95% CI, 1.62 to 3.20; P < .001) and PFS (PFS; hazard ratio 1.76; 95% CI, 1.31 to 2.36; P < .001). Changes in the maximum variant allele frequencies ctDNA values showed strong association across different outcomes. CONCLUSION: In this pooled analysis of five independent clinical trials, consistent and robust associations between reductions in ctDNA and outcomes were found across multiple end points assessed in patients with non-small-cell lung cancer treated with an ICI. Additional tumor types, stages, and drug classes should be included in future analyses to further validate this. CtDNA may serve as an important tool in clinical development and an early indicator of treatment benefit.

A Bayesian decision-theoretic design for simultaneous biomarker-based subgroup selection and efficacy evaluation.

The success of drug development of targeted therapy often hinges on an appropriate selection of the sensitive patient population, mostly based on patients' biomarker levels. At the planning stage of a phase II study, although a potential biomarker may have been identified, a threshold value for defining sensitive patient population is often unavailable for adopting many existing biomarker-guided designs. To address this issue, we propose a two-stage design that allows for simultaneous biomarker threshold selection and efficacy evaluation while accommodating situations where the drug is efficacious in the entire patient population. The design uses a Bayesian decision-theoretic approach and incorporates the benefit and cost considerations of the study into a utility function. The operating characteristics of the proposed design under different scenarios are investigated via simulations. We also provide a discussion on the choice of the benefit and cost parameters in practice.

Leveraging real-world evidence for determining performance goals for medical device studies.

Performance goals are numerical target values pertaining to effectiveness or safety endpoints in single-arm medical device clinical studies. Typically, performance goals are determined at the planning stage of the investigational study under consideration based on summarized outcome information from existing relevant clinical trials. In recent years, there is a growing interest in leveraging real-world evidence in medical product development. In this article, we introduce a new method for proposing performance goals by leveraging real-world evidence. The method applies entropy balancing to address possible patient dissimilarities between the study's target patient population and existing real-world patients, and can take into account operation differences between clinical studies and real-world clinical practice. An illustrative example is provided to demonstrate how to implement the proposed method for performance goal determination while leveraging real-world evidence.

Feature engineering and machine learning for causality assessment in pharmacovigilance: Lessons learned from application to the FDA Adverse Event Reporting System.

BACKGROUND: Our objective was to support the automated classification of Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) reports for their usefulness in assessing the possibility of a causal relationship between a drug product and an adverse event. METHOD: We used a data set of 326 redacted FAERS reports that was previously annotated using a modified version of the World Health Organization-Uppsala Monitoring Centre criteria for drug causality assessment by a group of SEs at the FDA and supported a similar study on the classification of reports using supervised machine learning and text engineering methods. We explored many potential features, including the incorporation of natural language processing on report text and information from external data sources, for supervised learning and developed models for predicting the classification status of reports. We then evaluated the models on a larger data set of previously unseen reports. RESULTS: The best-performing models achieved recall and F1 scores on both data sets above 0.80 for the identification of assessable reports (i.e. those containing enough information to make an informed causality assessment) and above 0.75 for the identification of reports meeting at least a Possible causality threshold. CONCLUSIONS: Causal inference from FAERS reports depends on many components with complex logical relationships that are yet to be made fully computable. Efforts focused on readily addressable tasks, such as quickly eliminating unassessable reports, fit naturally in SE's thought processes to provide real enhancements for FDA workflows.

Appropriate Systemic Therapy Dosing for Obese Adult Patients With Cancer: ASCO Guideline Update.

PURPOSE: To provide recommendations for appropriate dosing of systemic antineoplastic agents in obese adults with cancer. METHODS: A systematic review of the literature collected evidence regarding dosing of chemotherapy, immunotherapy, and targeted therapies in obese adults with cancer. PubMed and the Cochrane Library were searched for randomized controlled trials, meta-analyses, or cohort studies published from November 1, 2010, through March 27, 2020. ASCO convened an Expert Panel to review the evidence and formulate recommendations. RESULTS: Sixty studies, primarily retrospective, were included in the review. Overall, the evidence supported previous findings that obese adult patients tolerate full, body-size-based dosing of chemotherapy as well as nonobese patients. Fewer studies have addressed the dosing of targeted therapies and immunotherapies in relation to safety and efficacy in obese patients. RECOMMENDATIONS: The Panel continues to recommend that full, weight-based cytotoxic chemotherapy doses be used to treat obese adults with cancer. New to this version of the guideline, the Panel also recommends that full, approved doses of immunotherapy and targeted therapies be offered to obese adults with cancer. In the event of toxicity, the consensus of the Panel is that dose modifications of systemic antineoplastic therapies should be handled similarly for obese and nonobese patients. Important areas for future research include the impact of sarcopenia and other measures of body composition on optimal antineoplastic dosing, and more customized dosing based on pharmacokinetic or pharmacogenetic factors.Additional information is available at www.asco.org/supportive-care-guidelines.

A feasibility study of combined epigenetic and vaccine therapy in advanced colorectal cancer with pharmacodynamic endpoint.

Epigenetic therapies may modulate the tumor microenvironment. We evaluated the safety and optimal sequence of combination DNA methyltransferase inhibitor guadecitabine with a granulocyte macrophage-colony-stimulating-factor (GM-CSF) secreting colon cancer (CRC) vaccine (GVAX) using a primary endpoint of change in CD45RO + T cells. 18 patients with advanced CRC enrolled, 11 underwent paired biopsies and were evaluable for the primary endpoint. No significant increase in CD45RO + cells was noted. Grade 3-4 toxicities were expected and manageable. Guadecitabine + GVAX was tolerable but demonstrated no significant immunologic activity in CRC. We report a novel trial design to efficiently evaluate investigational therapies with a primary pharmacodynamic endpoint.Trial registry Clinicaltrials.gov: NCT01966289. Registered 21 October, 2013.

A batch-effect adjusted Simon's two-stage design for cancer vaccine clinical studies.

In the development of cancer treatment vaccines, phase II clinical studies are conducted to examine the efficacy of a vaccine in order to screen out vaccines with minimal activity. Immune responses are commonly used as the primary endpoint for assessing vaccine efficacy. With respect to study design, Simon's two-stage design is a popular format for phase II cancer clinical studies because of its simplicity and ethical considerations. Nonetheless, it is not straightforward to apply Simon's two-stage design to cancer vaccine studies when performing immune assays in batches, as outcomes from multiple patients may be correlated with each other in the presence of batch effects. This violates the independence assumption of Simon's two-stage design. In this paper, we numerically explore the impact of batch effects on Simon's two-stage design, propose a batch-effect adjusted Simon's two-stage design, demonstrate the proposed design by both a simulation study and a therapeutic human papillomavirus vaccine trial, and briefly introduce a software that implements the proposed design.

Meta-analysis of rare adverse events in randomized clinical trials: Bayesian and frequentist methods.

BACKGROUND/AIMS: Regulatory approval of a drug or device involves an assessment of not only the benefits but also the risks of adverse events associated with the therapeutic agent. Although randomized controlled trials (RCTs) are the gold standard for evaluating effectiveness, the number of treated patients in a single RCT may not be enough to detect a rare but serious side effect of the treatment. Meta-analysis plays an important role in the evaluation of the safety of medical products and has advantage over analyzing a single RCT when estimating the rate of adverse events. METHODS: In this article, we compare 15 widely used meta-analysis models under both Bayesian and frequentist frameworks when outcomes are extremely infrequent or rare. We present extensive simulation study results and then apply these methods to a real meta-analysis that considers RCTs investigating the effect of rosiglitazone on the risks of myocardial infarction and of death from cardiovascular causes. RESULTS: Our simulation studies suggest that the beta hyperprior method modeling treatment group-specific parameters and accounting for heterogeneity performs the best. Most models ignoring between-study heterogeneity give poor coverage probability when such heterogeneity exists. In the data analysis, different methods provide a wide range of log odds ratio estimates between rosiglitazone and control treatments with a mixed conclusion on their statistical significance based on 95% confidence (or credible) intervals. CONCLUSION: In the rare event setting, treatment effect estimates obtained from traditional meta-analytic methods may be biased and provide poor coverage probability. This trend worsens when the data have large between-study heterogeneity. In general, we recommend methods that first estimate the summaries of treatment-specific risks across studies and then relative treatment effects based on the summaries when appropriate. Furthermore, we recommend fitting various methods, comparing the results and model performance, and investigating any significant discrepancies among them.

The precision interventions for severe and/or exacerbation-prone asthma (PrecISE) adaptive platform trial: statistical considerations.

The Precision Interventions for Severe and/or Exacerbation-prone Asthma (PrecISE) study is an adaptive platform trial designed to investigate novel interventions to severe asthma. The study is conducted under a master protocol and utilizes a crossover design with each participant receiving up to five interventions and at least one placebo. Treatment assignments are based on the patients' biomarker profiles and precision health methods are incorporated into the interim and final analyses. We describe key elements of the PrecISE study including the multistage adaptive enrichment strategy, early stopping of an intervention for futility, power calculations, and the primary analysis strategy.

Neoadjuvant nivolumab plus ipilimumab in resectable non-small cell lung cancer.

BACKGROUND: We conducted the first trial of neoadjuvant PD-1 blockade in resectable non-small cell lung cancer (NSCLC), finding nivolumab monotherapy to be safe and feasible with an encouraging rate of pathologic response. Building on these results, and promising data for nivolumab plus ipilimumab (anti-CTLA-4) in advanced NSCLC, we expanded our study to include an arm investigating neoadjuvant nivolumab plus ipilimumab. METHODS: Patients with resectable stage IB (≥4 cm)-IIIA (American Joint Committee on Cancer Tumor Node Metastases seventh edition), histologically confirmed, treatment-naïve NSCLC received nivolumab 3 mg/kg intravenously plus ipilimumab 1 mg/kg intravenously 6 weeks prior to planned resection. Nivolumab 3 mg/kg was given again approximately 4 and 2 weeks preoperatively. Primary endpoints were safety and feasibility with a planned enrollment of 15 patients. Pathologic response was a key secondary endpoint. RESULTS: While the treatment regimen was feasible per protocol, due to toxicity, the study arm was terminated early by investigator consensus after 9 of 15 patients were enrolled. All patients received every scheduled dose of therapy and were fit for planned surgery; however, 6 of 9 (67%) experienced treatment-related adverse events (TRAEs) and 3 (33%) experienced grade ≥3 TRAEs. Three of 9 patients (33%) had biopsy-confirmed tumor progression precluding definitive surgery. Of the 6 patients who underwent resection, 3 are alive and disease-free, 2 experienced recurrence and are actively receiving systemic treatment, and one died postoperatively due to acute respiratory distress syndrome. Two patients who underwent resection had tumor pathologic complete responses (pCRs) and continue to remain disease-free over 24 months since surgery. Pathologic response correlated with pre-treatment tumor PD-L1 expression, but not tumor mutation burden. Tumor KRAS/STK11 co-mutations were identified in 5 of 9 patients (59%), of whom two with disease progression precluding surgery had tumor KRAS/STK11/KEAP1 co-mutations. CONCLUSIONS: Though treatment was feasible, due to toxicity the study arm was terminated early by investigator consensus. In light of this, and while the long-term disease-free status of patients who achieved pCR is encouraging, further investigation of neoadjuvant nivolumab plus ipilimumab in patients with resectable NSCLC requires the identification of predictive biomarkers that enrich for response.

Bayesian copy number detection and association in large-scale studies.

BACKGROUND: Germline copy number variants (CNVs) increase risk for many diseases, yet detection of CNVs and quantifying their contribution to disease risk in large-scale studies is challenging due to biological and technical sources of heterogeneity that vary across the genome within and between samples. METHODS: We developed an approach called CNPBayes to identify latent batch effects in genome-wide association studies involving copy number, to provide probabilistic estimates of integer copy number across the estimated batches, and to fully integrate the copy number uncertainty in the association model for disease. RESULTS: Applying a hidden Markov model (HMM) to identify CNVs in a large multi-site Pancreatic Cancer Case Control study (PanC4) of 7598 participants, we found CNV inference was highly sensitive to technical noise that varied appreciably among participants. Applying CNPBayes to this dataset, we found that the major sources of technical variation were linked to sample processing by the centralized laboratory and not the individual study sites. Modeling the latent batch effects at each CNV region hierarchically, we developed probabilistic estimates of copy number that were directly incorporated in a Bayesian regression model for pancreatic cancer risk. Candidate associations aided by this approach include deletions of 8q24 near regulatory elements of the tumor oncogene MYC and of Tumor Suppressor Candidate 3 (TUSC3). CONCLUSIONS: Laboratory effects may not account for the major sources of technical variation in genome-wide association studies. This study provides a robust Bayesian inferential framework for identifying latent batch effects, estimating copy number, and evaluating the role of copy number in heritable diseases.

Shortened-Duration Immunosuppressive Therapy after Nonmyeloablative, Related HLA-Haploidentical or Unrelated Peripheral Blood Grafts and Post-Transplantation Cyclophosphamide.

With post-transplantation cyclophosphamide (PTCy) as graft-versus-host disease (GVHD) prophylaxis, nonmyeloablative (NMA) HLA-haploidentical (haplo) and HLA-matched blood or marrow transplantation (BMT) have comparable outcomes. Previous reports have shown that discontinuation of immunosuppression (IS) as early as day 60 after infusion of a bone marrow (BM) haplo allograft with PTCy is feasible. There are certain diseases in which peripheral blood (PB) may be favored over BM, but given the higher rates of GVHD with PB, excessive GVHD is of increased concern. We report a completed, prospective single-center trial of stopping IS at days 90 and 60 after NMA PB stem cell transplantation (PBSCT). Between 12/2015-7/2018, 117 consecutive patients with hematologic malignancies associated with higher rates of graft failure after NMA conditioned BMT and PTCy, received NMA PB allografts on trial. The primary objective of this study was to evaluate the safety and feasibility of reduced-duration IS (from day 5 through day 90 in the D90 cohort and through day 60 in the D60 cohort). Of the 117 patients (median age, 64 years; range, 22 to 78 years), the most common diagnoses were myelodysplastic syndrome (33%), acute myelogenous leukemia (with minimal residual disease or arising from an antecedent disorder) (32%), myeloproliferative neoplasms (19%), myeloma (9%), and chronic lymphoblastic leukemia (7%). Shortened IS was feasible in 75 patients (64%) overall. Ineligibility for shortened IS resulted most commonly from GVHD (17 patients), followed by early relapse (11 patients), nonrelapse mortality (NRM) (7 patients), patient/ physician preference (4 patients) or graft failure (3 patients). Of the 57 patients in the D90 cohort, 33 (58%) stopped IS early as planned, and among the 60 patients in the D60 cohort, 42 (70%) stopped IS early as planned. The graft failure rate was 2.6%. After IS cessation, the median time to diagnosis of grade II-IV acute GVHD was 21 days in the D90 cohort and 32 days in the D60 cohort, with almost all cases developing within 40 days. Approximately one-third of these patients resumed IS. All outcome measures were similar in the 2 cohorts and our historical outcomes with 180 days of IS. The cumulative incidence of grade III-IV acute GVHD was low, 2% in the D90 cohort and 7% in the D60 cohort. The incidence of severe chronic GVHD at 2 years was 9% in the D90 cohort and 5% in the D60 cohort. The 2-year overall survival was 67% for both the D90 and D60 cohorts. The 2-year progression-free survival was 47% for the D90 cohort and 52% for the D60 cohort, and the GVHD-free, relapse-free survival was <35% for both cohorts. These data suggest that reduced-duration IS in patients undergoing NMA PBSCT with PTCy is feasible and has an acceptable safety profile. © 2020 American Society for Transplantation and Cellular Therapy. Published by Elsevier Inc.

Phase I and Pharmacokinetic Study of Romidepsin in Patients with Cancer and Hepatic Dysfunction: A National Cancer Institute Organ Dysfunction Working Group Study.

PURPOSE: Romidepsin dosing recommendations for patients with malignancy and varying degrees of hepatic dysfunction was lacking at the time of regulatory approval for T-cell lymphoma. We conducted a multicenter phase I clinical trial (ETCTN-9008) via the NCI Organ Dysfunction Working Group to investigate safety, first cycle MTD, and pharmacokinetic profile of romidepsin in this setting. PATIENTS AND METHODS: Patients with select advanced solid tumors or hematologic malignancies were stratified according to hepatic function. Romidepsin was administered intravenously on days 1, 8, and 15 of a 28-day cycle and escalation followed a 3 + 3 design in moderate and severe impairment cohorts. Blood samples for detailed pharmacokinetic analyses were collected after the first dose. RESULTS: Thirty-one patients received one dose of romidepsin and were evaluable for pharmacokinetic analyses in normal (n = 12), mild (n = 8), moderate (n = 5), and severe (n = 6) cohorts. Adverse events across cohorts were similar, and dose-limiting toxicity occurred in two patients (mild and severe impairment cohorts). The MTD was not determined because the geometric mean AUC values of romidepsin in moderate (7 mg/m2) and severe (5 mg/m2) impairment cohort were 114% and 116% of the normal cohort (14 mg/m2). CONCLUSIONS: Data from the ETCTN-9008 trial led to changes in the romidepsin labeling to reflect starting dose adjustment for patients with cancer and moderate and severe hepatic impairment, with no adjustment for mild hepatic impairment.

Bayesian Methods in Regulatory Science.

Regulatory science comprises the tools, standards, and approaches that regulators use to assess safety, efficacy, quality, and performance of drugs and medical devices. A major focus of regulatory science is the design and analysis of clinical trials. Clinical trials are an essential part of clinical research programs that aim to improve therapies and reduce the burden of disease. These clinical experiments help us learn about what works clinically and what does not work. The results of clinical trials support therapeutic and policy decisions. When designing clinical trials, investigators make many decisions regarding various aspects of how they will carry out the study, such as the primary objective of the study, primary and secondary endpoints, methods of analysis, sample size, etc. This paper provides a brief review of the clinical development of new treatments and argues for the use of Bayesian methods and decision theory in clinical research.