Early-phase Oncology Clinical Trials Research Articles

Abstract B036: Trends in disparities in clinical trial accrual: An analysis of National Cancer Institute (NCI)-sponsored early phase clinical trials over the last 22 years

Abstract Using the NCI Cancer Therapy Evaluation Program (CTEP)-sponsored early phase oncology clinical trials database, we evaluated trends in disparities in patient enrollment over the last 22 years. Counts and percentages of enrolled patients were calculated directly from the full population of patients enrolled to CTEP-sponsored Phase 1, 2, and 1/2 trials during 2000-22. Trends in enrollment were assessed based on single-year data, four-year periods, and using a three-year rolling average. Analyses of patient residential ZIP code were restricted to patients residing and enrolled at institutions within the United States. Geographical data corresponding to patient ZIP codes was obtained using the zipcodeR package, including geographical region and median household income corresponding to each ZIP, and distance between patient residential and enrolling institution ZIPs. A total of 14,877 patients were enrolled in CTEP-sponsored early phase trials evaluated during 2000-22, with 14,342 residing and enrolled within the US. The proportion of patients aged 40-64 at enrollment decreased from 59.8% in 2000-03 to 47.5% in 2020-22, with corresponding increases in ages 65-74 (24.2% to 32.9%) and 75-84 (5.9% to 12.3%). There were fluctuations in gender, most likely based on the specific agents being studied in clinical trials enrolling at a given time. In 2020-22, 72.9% of the population was non-Hispanic white when compared to 2000-03 when enrollment of non-Hispanic whites was 83.7%. Hispanic/Latino population enrollment increased from 4.2% in years 2000-03 to 6.9% in years 2020-22. Asian/Pacific Islander population increased from 2.5% in 2000-03 to 5.4% in 2020-22. Enrollment of non-Hispanic Black patients increased slightly over the last 20 years (6.3% to 7.1%), as did the proportion with unknown or unspecified race/ethnicity (3.3% to 7.6%). Trial enrollment trends by geographic regions revealed that enrollment in South and West overall increased (29.1% to 40.9%; 7.9% to 18.2%), Northeast representation remained static (23.9% to 20.8%) and Midwest representation decreased (24.4% to 19.4%) from 2000-03 to 2020-22. Most early phase participants in our database were from localities with a moderate median household income ($52,200 - $156,600; 51.9% to 59.4%), with an increase in representation from low-income localities (income < $52,000; 31.1% to 37.7%) over the last 22 years. We observed an overall increase in patients enrolling within a 50-mile radius of their residence over the 22-year period (46.5% to 64.5%) and an overall decrease in patients traveling over 200 miles to enroll in clinical trials (16.1% to 8.3%). We also examined trends in disparities during the COVID-19 pandemic and saw no significant differences in trial enrollment by race/ethnicity and gender when compared to pre-pandemic enrollment. Disparities in patients enrolled in early-phase clinical trials have marginally improved over the span of two decades, and outreach and inclusion efforts for enrollment of underrepresented patients should be continued to sustain these observed trends. Citation Format: Maria Farooq, Elad Sharon, Naoko Takebe, Ana F. Best, Shanda Finnigan. Trends in disparities in clinical trial accrual: An analysis of National Cancer Institute (NCI)-sponsored early phase clinical trials over the last 22 years [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr B036.

CONSENT: Randomized controlled trial of enhanced informed consent compared to standard informed consent to improve patient understanding of early phase oncology clinical trials.

6560 Background: Early phase oncology clinical trials have become increasingly complicated in terms of patient selection and trial procedures. Informed consent has been contentious due to potential ethical issues associated with performing experimental research on patients with advanced cancer who lack standard treatment options. Prior research has shown significant gaps in patient understanding regarding the nature and intent of these trials. CONSENT aimed to test whether enhanced informed consent can improve clinical trial comprehension. Methods: We randomized patients eligible to participate in one of four investigator-initiated early phase oncology clinical trials at the Royal Marsden Drug Development Unit to either a control arm or an experimental arm, stratified by age and educational level. The control arm received the full-length trial PIS, followed by electronic or paper administration of the Quality of Informed Consent Questionnaire Parts A (QuIC-A). The experimental arm received the full-length trial PIS, exposure to a two-page study specific aid and 10 online educational videos (both co-designed with patients and clinicians), followed by administration of the QuIC-A. The primary endpoint was the difference in the QuIC-A score between the control and experimental arm. The accrual target was at least 17 evaluable patients per arm to detect an 8-point difference (80% power, alpha 0.05). Results: 23 patients were accrued to the control arm (17 evaluable) and 22 patients (18 evaluable) were accrued to the experimental arm. Patients were evaluable if they had completed the QuIC-A. 38% of the participants were over the age of 65, 91% identified as White, 56% had completed a university degree and 97% spoke English at home. We did not observe a significant improvement in the primary endpoint in evaluable patients – control (QuIC-A - 76.5/100) vs experimental arm (QuIC-A - 77.4/100), p value = 0.39 (one sided, two sample t-test). 20 participants provided feedback on the enhanced consent materials via a study questionnaire –75% found both the 2-page study aid and the videos not at all distressing or uncomfortable and 85% found them either quite useful or very useful. Conclusions: This is the first prospective randomized trial evaluating the impact of communication interventions on informed consent in advanced cancer patients considering early phase oncology clinical trials. The co-designed interventions were deliverable online and were acceptable and useful for patients. We did not demonstrate an improvement in the primary endpoint with a high QuIC-A score observed in the control arm- this could be explained by the study population which was highly educated, White and spoke English at home. Future studies should focus on groups with lower literacy and from culturally and linguistically diverse backgrounds. Clinical trial information: NCT04407676 .

Concurrent dose-finding of a novel cancer drug with and without a second agent.

More complex research questions are being posed in early-phase oncology clinical trials, necessitating design strategies tailored to contemporary study objectives. This paper describes the proposed design of a Phase I trial concurrently evaluating the safety of a hematopoietic progenitor kinase-1 inhibitor (Agent A) as a single agent and in combination with an anti-PD-1 agent in patients with advanced malignancies. The study's primary objective was to concurrently determine the maximum tolerated dose (MTD) of Agent A with and without anti-PD-1 therapy among seven possible study dose levels. Our solution to this challenge was to apply a continual reassessment method shift model to meet the research objectives of the study. The application of this method is described herein, and a simulation study of the design's operating characteristics is conducted. This work was developed through collaboration and mentoring between the authors at the American Association for Cancer Research (AACR) and the American Society of Clinical Oncology (ASCO) annual AACR/ASCO Methods in Clinical Cancer Research Workshop. The aim of this manuscript is to highlight examples of novel design applications as a means of augmenting the implementation of innovative designs in the future and to demonstrate the flexibility of adaptive designs in satisfying modern design conditions. Although the design is presented using an investigation of Agent A with and without anti-PD-1 therapy as an illustrative example, the approach described is not specific to these agents and could be applied to other concurrent monotherapy and combination therapy studies with well-defined binary safety endpoints.

Early phase oncology clinical trials in Malaysia: current status and future perspectives.

Historically, the majority of oncology clinical trials are conducted in Western Europe and North America. Globalization of drug development has resulted in sponsors shifting their focus to the Asia-Pacific region. In Malaysia, implementation of various government policies to promote clinical trials has been initiated over a decade ago and includes the establishment of Clinical Research Malaysia, which functions as a facilitator and enabler of industry-sponsored clinical trials on a nationwide basis. Although oncology clinical trials in Malaysia have seen promising growth, there are still only a limited number of early phase oncology studies being conducted. Hence, the Phase 1 Realization Project was initiated to develop Malaysia's early phase clinical trial capabilities. In addition, the adaptation of good practices from other countries contribute to the effective implementation of existing initiatives to drive progress in the development of early phase drug development set up in Malaysia. Furthermore, holistic approaches with emphasis in training and education, infrastructure capacities, strategic alliances, reinforcement of upstream activities in the value chain of drug development, enhanced patient advocacy, coupled with continued commitment from policy makers are imperative in nurturing a resilient clinical research ecosystem in Malaysia.

CONSENT - A Randomised Controlled Trial of Enhanced Informed Consent Compared to Standard Informed Consent to Improve Patient Understanding of Early Phase Oncology Clinical Trials – GBM Cohort (Nonrandomised) Analysis

Abstract AIMS Early phase cancer clinical trials have become more complicated and patients often misunderstand their nature and purpose. CONSENT (NCT04407676) is a randomised controlled trial testing whether enhanced informed consent for patient education can improve comprehension – since patients with glioblastoma multiforme (GBM) have a higher rate of baseline cognitive impairment, we studied this group separately. METHOD GBM patients (from the ICE-CAP Phase 1 study - NCT03673787), underwent the schedule for the standard CONSENT arm - full length trial PIS, Quality of Informed Consent Questionnaire Parts A and B (QuIC-A and QuIC-B), experimental intervention (2 page study aid and 10 educational videos), and a repeat QuIC-A and QuIC-B. The primary endpoint for this subgroup was the difference in QuIC-A scores before and after the intervention using a paired t-test. RESULTS 6 patients with GBM were recruited - 3 did not complete any study questionnaires. The three pre intervention QuIC-A scores were 70, 81, 88, with a mean of 75 (unit reference 76). The three pre intervention QuIC-B scores were 69, 62, 75 with a mean of 69 (unit reference is 91). Only one patient completed the post intervention questionnaire - their QuIC-A score moved from 88 to 100. CONCLUSION This study demonstrates the significant difficulties in studying comprehension in patients with GBM considering early phase trials. There is a need for creative multi-modality solutions to provide information to GBM patients considering clinical trials, and novel tools to assess the effectiveness of these solutions.

Natural Language Processing for Patient Selection in Phase I or II Oncology Clinical Trials.

Early discontinuation affects more than one third of patients enrolled in early-phase oncology clinical trials. Early discontinuation is deleterious both for the patient and for the study, by inflating its duration and associated costs. We aimed at predicting the successful screening and dose-limiting toxicity period completion (SSD) from automatic analysis of consultation reports. We retrieved the consultation reports of patients included in phase I and/or phase II oncology trials for any tumor type at Gustave Roussy, France. We designed a preprocessing pipeline that transformed free text into numerical vectors and gathered them into semantic clusters. These document-based semantic vectors were then fed into a machine learning model that we trained to output a binary prediction of SSD status. Between September 2012 and July 2020, 56,924 consultation reports were used to build the dictionary and 1,858 phase I or II inclusion reports were used to train (72%), validate (14%), and test (14%) a random forest model. Preprocessing could efficiently cluster words with semantic proximity. On the unseen test cohort of 264 consultation reports, the performances of the model reached: F1 score 0.80, recall 0.81, and area under the curve 0.88. Using this model, we could have reduced the screen fail rate (including dose-limiting toxicity period) from 39.8% to 12.8% (relative risk, 0.322; 95% CI, 0.209 to 0.498; P < .0001) within the test cohort. Most important semantic clusters for predictions comprised words related to hematologic malignancies, anatomopathologic features, and laboratory and imaging interpretation. Machine learning with semantic conservation is a promising tool to assist physicians in selecting patients prone to achieve SSD in early-phase oncology clinical trials.

Compliance with dietary guidelines and its relationship with symptoms and clinical outcomes in patients with advanced cancer in early-phase oncology clinical trials.

199 Background: We examined compliance with the Dietary Guidelines for Americans and its association with symptom burden and clinical outcomes in patients with advanced cancer in early-phase clinical trials testing novel immunotherapeutic and targeted agents. Methods: Patients starting an early-phase clinical trial (ECOG-PS = 0-1) were recruited into a prospective, longitudinal design with assessments at baseline and at the end of Cycle 1. Diet and symptom burden were assessed using the validated National Cancer Institute Diet History Questionnaire (NCI-DHQ) and the MD Anderson Symptom Inventory, respectively. Compliance with the Dietary Guidelines for Americans recommendations was measured via the Healthy Eating Index (HEI) (a measure of dietary intake per total energy), computed from NCI-DHQ food group and nutrient scores; higher HEI scores indicate greater compliance with dietary guidance recommendations (possible range = 0–100). Statistical tests included Spearman rank correlations (rho), and Cox proportional hazards models. Results: Among early-phase clinical trial patients [N = 40; 50% female; 80% Non-Hispanic White; 80% ECOG = 1; 36% on trials including an immunotherapeutic agent and 64% on targeted therapy trials; mean age = 55y; mean BMI = 28], mean HEI was 69, compared to 59 for the US general population. The proportion of phase I clinical trial patients who met adequacy guidelines were 80% for whole fruit, 73% for total protein foods, 55% for seafood and plant proteins, 55% for total fruit, 50% for greens and beans, 28% for total vegetables, 15% for fatty acids [(PUFAs + MUFAs)/SFAs ≥2.5], 13% for dairy, and 0% for whole grains. The proportion of patients who met moderation guidelines were 28% for refined grains, 28% for added sugar, 13% for saturated fat, and 0% for sodium. Female patients had higher HEI scores than male patients (73 vs. 65, P = 0.004). Patients who were normal weight (BMI &lt; 25) had higher scores for meeting the moderation in sugar intake guideline than overweight patients (BMI≥25) (7.7 vs. 5.5, P = 0.031). Higher intakes of cooked lean meat from beef, pork, veal, lamb, and game were linked to prolonged overall survival (HR = 0.5, 95%CI = 0.26, 0.96, P = 0.039). In immunotherapy patients, greater compliance with seafood and plant protein recommendations was associated with less fatigue at end of Cycle 1 (rho = -0.7, P = 0.008); in targeted therapy patients, higher glycemic load was associated with worse pain (rho = 0.7, P = 0.004). Conclusions: Diets of these early-phase clinical trial patients overall were congruent with recommendations in the Dietary Guidelines for Americans. However, increasing intakes of whole grains and reducing sodium intakes may be useful dietary goals for this population. Also, dietary factors may influence symptoms, such as fatigue and pain, in early-phase clinical trial patients with advanced cancer.

Abstract 153: Development of a workflow to handle the quality control and analysis of Olink protein biomarker data in early phase oncology clinical trials

Abstract INTRODUCTION: Olink is a high-throughput targeted biomarker platform based on Proximity Extension Assay (PEA) technology using oligonucleotide-labeled antibody pairs. At AbbVie RWC, we have primarily utilized the 96-plex Immune-Oncology (IO) panel measuring 92 proteins to support our early-phase oncology clinical trials. As we analyzed batches of specimens from ongoing trials, we set out to develop a workflow to control data quality and streamline analysis. METHODS: Prior to sample shipment to Olink, we randomize sample position onto plates to ensure key factors such as dose and cohort are balanced within and across plates. This prevents plate or location effects from becoming a confounder. If the study specimens are analyzed in more than one batch, subsequent batches require bridging samples from the first batch to allow us to detect and remove batch effects if necessary. Our workflow thus identifies bridging samples and recommends the optimal number. Upon receiving the data, we evaluate its quality by calculating inter- and intra-plate coefficients of variation (CVs) and visualizing it in multiple ways. The next step in our workflow is analysis, including pharmacodynamic (PD) analysis and association with clinical response. In the PD analysis, we identify biomarkers that significantly change across time and/or exhibit a dose effect. To help interpret the results, enrichment analysis is performed to identify biological processes enriched in the significantly modulated biomarkers. Heatmaps and volcano plots are also generated. For analysis of association with clinical response, we examine how each biomarkers' baseline value and modulation over time associates with progression free survival (PFS) and best overall response (BOR). RESULTS: We successfully created a workflow that handles quality control and analysis of Olink protein biomarker data. The workflow starts from experimental design quality control. Upon receiving the data, we conduct data quality assessment and examination and removal of potential batch effects. Finally, we perform analysis of the data to identify potential biomarkers of interest. We used elements of this workflow on data from M15-891 (ABBV-181) and have now applied the full workflow to multiple batches of data from three early-phase oncology trials (M15-862 (ABBV-927), M16-074 (ABBV-368) and M19-345 (ABBV-151)), with plans to incorporate this methodology into several additional upcoming trials. CONCLUSIONS: We have developed a comprehensive workflow that manages Olink quality control and analysis and can potentially be implemented to all early-phase oncology clinical trials using Olink. It allows us to standardize and streamline Olink data handling and provide robust and efficient analyses that enable rapid biomarker data interpretation, hypothesis generation, and decision making for our trials. Citation Format: Claire J. Guo, Mary Saltarelli, Stacie Lambert, Hua Fang, Chun Zhang. Development of a workflow to handle the quality control and analysis of Olink protein biomarker data in early phase oncology clinical trials [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 153.

Radiological Patterns of Drug-induced Interstitial Lung Disease (DILD) in Early-phase Oncology Clinical Trials.

Drug-induced interstitial lung disease (DILD) is a rare, but potentially fatal toxicity. Clinical and radiological features of DILD in the early experimental setting are poorly described. A total of 2,499 consecutive patients with advanced cancer on phase I clinical trials were included. DILD was identified by a dedicated radiologist and investigators, categorized per internationally recognized radiological patterns, and graded per Common Terminology Criteria for Adverse Events (CTCAE) and the Royal Marsden Hospital (RMH) DILD score. Clinical and radiological features of DILD were analyzed. Sixty patients overall (2.4%) developed DILD. Median time to onset of DILD was 63 days (range, 14-336 days). A total of 45% of patients who developed DILD were clinically asymptomatic. Incidence was highest in patients receiving drug conjugates (7.4%), followed by inhibitors of the PI3K/AKT/mTOR pathway (3.9%). The most common pattern seen was hypersensitivity pneumonitis (33.3%), followed by nonspecific interstitial pneumonia (30%), and cryptogenic organizing pneumonia (26.7%). A higher DILD score [OR, 1.47, 95% confidence interval (CI), 1.19-1.81; P < 0.001] and the pattern of DILD (OR, 5.83 for acute interstitial pneumonia; 95% CI, 0.38-90.26; P = 0.002) were significantly associated with a higher CTCAE grading. The only predictive factor for an improvement in DILD was an interruption of treatment (OR, 0.05; 95% CI, 0.01-0.35; P = 0.01). DILD in early-phase clinical trials is a toxicity of variable onset, with diverse clinical and radiological findings. Radiological findings precede clinical symptoms. The extent of the affected lung parenchyma, scored by the RMH DILD score, correlates with clinical presentation. Most events are low grade, and improve with treatment interruption, which should be considered early.

Clinical implications of drug-induced liver injury in early-phase oncology clinical trials.

Data on drug-induced liver injury (DILI) and acute liver failure (ALF) in modern phase 1 oncology trials are limited, specifically with respect to the incidence and resolution of DILI and the safety of drug rechallenge. This study reviewed all patients who were recruited to phase 1 oncology trials between 2013 and 2017 at Memorial Sloan Kettering Cancer Center. Clinicopathologic data were extracted to characterize DILI, and attribution was assessed on the basis of data prospectively generated during the studies. Logistic regression models were used to explore factors related to DILI and DILI recurrence after drug rechallenge. Among 1670 cases recruited to 85 phase 1 trials, 81 (4.9%) developed DILI. The rate of DILI occurrence was similar for patients in immune-based trials and patients in targeted therapy trials (5.0% vs 4.9%), as was the median time to DILI (5.5 vs 6.5 weeks; P=.48). Two patients (0.12%) met the criteria of Hy's law, although none developed ALF. The DILI resolved in 96% of the patients. Pretreatment factors were not predictive for DILI development. Thirty-six of the 81 patients underwent a drug rechallenge, and 28% of these patients developed DILI recurrence. Peak alanine aminotransferase during the initial DILI was associated with DILI recurrence (odds ratio, 1.04; 95% confidence interval, 1.0-1.09; P=.035). In modern phase 1 oncology trials, DILI is uncommon, may occur at any time, and often resolves with supportive measures. Rechallenging after DILI is feasible; however, the high rate of DILI recurrence suggests that clinicians should consider the severity of the DILI episode and treatment alternatives.

Patient-reported out-of-pocket costs and financial toxicity during early-phase oncology clinical trials.

7082 Background: Clinical trials are an important therapeutic option for cancer patients (pts). Although financial burden in cancer treatment is well-documented, the financial burden associated with clinical trials is not well understood, especially for pts with lower income. Methods: We conducted a survey regarding economic burden and financial toxicity in cancer pts who had been on Phase I clinical trials for ≥1 month. Financial Toxicity Score (FTS) was assessed using the validated COmprehensive Score for Financial Toxicity (COST) survey (scale 0-44, lower scores indicate worse toxicity). Pts also reported monthly out-of-pocket (OOP) medical and non-medical expenses. We applied multivariable logistic regression to analyze risk of financial toxicity, and unanticipated expenses. Results: Early-phase clinical trial pts (N = 213, median age = 59y; 59% female; 74% White, 45% w/ annual income ≤$60K; 50% lived &gt; 300 miles from the clinic; 40% required air travel; 37% had Medicare, 54% had employer sponsored insurance) had a median FTS of 20, with interquartile range of 12. Median monthly OOP costs for non-medical expenses was $1075, and for medical expenses was $475. Median total monthly OOP costs was $1750. 55% and 64% of pts reported that actual medical and non-medical expenses were higher than expected, respectively. Worse financial toxicity (≤ median FTS) in pts was associated with yearly household income &lt; $60K (OR: 2.7, P = 0.008), having medical costs higher than expected (OR: 3.2, P = 0.024), participation on ≥1 Phase I clinical trial prior to their current trial (OR: 2.2, P = 0.028), and living &gt; 100 miles away from the clinical trials hospital (OR: 2.3, P = 0.043). However, 34% of pts who lived &gt; 100 miles away received partial/full reimbursement of clinical trial-related travel costs from study sponsor/other/insurance. Racial/ethnic minority (OR: 2.6, P = 0.008) and pts who were unemployed or not working outside the home (OR: 2.4, P = 0.023) were more likely to report that actual medical costs were much higher than expected. 53% of pts used savings and 18% retirement accounts to pay for treatment. Conclusions: Among cancer pts participating on clinical trials, economic burden is high, and most of pts’ OOP costs were on non-medical expenses. Financial toxicity is disproportionally higher in pts with lower income. OOP costs can be substantial and are often unexpected for pts. Furthermore, prior participation in ≥1 Phase I clinical trial and living far away from the clinical trials hospital seem to increase risk of financial toxicity.

Increasing complexity in oncology phase I clinical trials

Clinical trials in oncology have become increasingly complex because of incorporation of predictive biomarkers and patient selection based on molecular profiling of tumors. We have examined the change in procedures and work intensity in phase 1 oncology trials over the years with several parameters used as surrogates of complexity. Categories that were included as events were clinical evaluations, pharmacokinetic (PK) laboratory tests, non-PK laboratory tests, specific molecular or histological characteristics, questionnaires and subjective assessments, routine clinical and physical examinations, imaging, invasive procedures and others. The information was extracted using a standardized form including study type, tumor type, information on agent, participant characteristics and study mandated events during the first 3cycles of each protocol. A total of 102 phase I oncology and hematology study protocols that were active at a single institution in 1996, 2006 and 2016 were evaluated. In 2016, there were significantly more (P < 0.05) median number of procedures, outpatient tests, subjective assessments, PK's, molecular profiling, biopsies and medication dispensing times. There were higher median numbers of procedures in studies in hematologic malignancies, testing immunotherapies and those with over 15 inclusion or exclusion criteria. These values also differed significantly (P < .005) when the median values were compared in nonparametric tests. Our results suggest that study related procedures in cancer phase I trials have substantially increased over the last two decades. The successful conduct of early-phase oncology clinical trials in future will require additional research resources.

Novel Early Phase Clinical Trial Design in Oncology

The development of investigational medicinal products from pre-clinical package to product launch is a process that may be beset by pitfalls and expensive failures. The focus of this review is to provide an overview of how the conventional design of early phase oncology clinical trials has been modified with the advent of molecular profiling into treatment paradigms. We identify classical and alternative trial endpoints in an era of molecularly targeted agents and immunotherapy, and consider how personalised medicine has impacted on clinical trial design with reference to basket, umbrella and multi-arm expansion cohorts. Finally, we assess the impact of agile, adaptive and ‘intelligent’ trial design for patients, clinicians and trial centres, and how these challenges may be overcome to accelerate the approval of novel drugs for patient benefit.

Insurance Clearance for Early-Phase Oncology Clinical Trials Following the Affordable Care Act.

Purpose: The Affordable Care Act (ACA) required that private insurance plans allow clinical trial participation and cover standard-of-care costs, but the impact of this provision has not been well-characterized. We assessed rates of insurance clearance for trial participation within our large early-phase clinical trials program, before and after implementation of the requirement.Experimental Design: We analyzed the departmental database for the Clinical Center for Targeted Therapy (CCTT) at MD Anderson Cancer Center (Houston, TX). Among patients referred for sponsored trials, we described rates of insurance clearance and prolonged time to clearance (at least 14 days) from July 2012 to June 2013 (baseline), July 2013-December 2013 (following CCTT staffing changes in July 2103), and January 2014-June 2015 (following implementation of the ACA). We used multivariable logistic regression models to compare rates across these time periods.Results: We identified 2,404 referrals for insurance clearance. Among privately insured patients, insurance clearance rates were higher for those referred from January 2014 to June 2015 than for those referred from July 2012 to June 2013 (OR, 4.72; 95% CI, 2.96-7.51). There was no association between referral period and clearance rates for Medicare/Medicaid patients (P = 0.25). Referral from January 2014 to June 2015 was associated with lower rates of prolonged clearance among both privately insured (OR 0.57; 95% CI, 0.38-0.86) and Medicare/Medicaid patients (OR 0.39; 95% CI, 0.19-0.83).Conclusions: Within our large early-phase clinical trials program, insurance clearance rates among privately insured patients improved following implementation of the ACA's requirement for coverage of standard-of-care costs. Clin Cancer Res; 23(15); 4155-62. ©2017 AACR.

Economic growth of BRIC nations and access to early-phase oncology clinical trials: An overview.

e17554 Background: With increasing globalization we have witnessed exponential economic growth in the BRIC (Brazil, Russia, India and China) nations. Concurrently, clinical trials have been outsourced to these countries. We sought to investigate the current status of early phase oncology clinical trials in the BRIC countries, exemplifying the impact of these emerging economies and global markets in health care. Methods: We reviewed the clinicaltrials.gov database for registered early phase trials (Phase I/II) in the BRIC countries; 2. We looked at research from these countries collectively. 3. We reviewed specific challenges and prognosticated the road ahead through a literature review. Results: We identified374 active early phase clinical trials in BRIC countries as of October 2012. China had 68% (255/374) of the trials, Brazil 14% (51/374), Russia 12% (47/374) and India 6% (21/374). Twenty-three trials were registered in more than one BRIC; therefore we analyzed 348 different trials. Gastrointestinal (20%, 70/348), lung (19%, 67/348) and breast (17%, 57/348) cancers were the most studied. Most of the trials were sponsored by universities or hospitals (51%, 176/348) and most conducted in a single country (73%, 247/348) with 70% of therapy intended to be palliative (243/348). Combined agents were most commonly studied (57%, 199/348). Among the 217 targeted-agent trials, 23% targeted the EGFR pathway, 18% the VEGFR, 11% involved multi-tyrosine kinase inhibitors and 10% the PI3K-mTOR pathway. Funding mechanisms and sponsorship of studies were disparate. Industry-sponsored studies comprised 24% (62/255) in China, 96% (45/47) in Russia, 80% (41/51) in Brazil and 57% (12/21) in India. Conclusions: Despite theeconomic explosion and shift of non-oncology clinical trials to BRIC nations, USA and Europe still lead in conducting early phase clinical trials in oncology. China accounts for 19% of world’s population and has the majority (68%) of trials while India (17% of World’s population) has only 6%. A dominance of industry-sponsored studies in BRIC countries other than China was found. Significant challenges in infrastructure and trained personnel remain, but efforts to overcome them are underway.

Tissue-Based Approaches to Study Pharmacodynamic Endpoints in Early Phase Oncology Clinical Trials

Anti-cancer clinical drug development is currently costly and slow with a high attrition rate. There is thus an urgent and unmet need to integrate pharmacodynamic biomarkers into early phase clinical trials in the framework provided by the “pharmacologic audit trail” in order to overcome this challenge. This review discusses the rationale, advantages and disadvantages, as well as the practical considerations of various tissue-based approaches to perform pharmacodynamic studies in early phase oncology clinical trials using case histories of molecular targeting agents such as PI3K, m-TOR, HSP90, HDAC and PARP inhibitors. These approaches include the use of normal “surrogate” tissues such as peripheral blood mononuclear cells, platelet-rich plasma, plucked hair follicles, skin biopsies, plasma-based endocrine assays, proteomics, metabolomics and circulating endothelial cells. In addition, the review discusses the use of neoplastic tissues including tumor biopsies, circulating tumor DNA and tumor cells and metabolomic approaches. The utilization of these tissues and technology platforms to study biomarkers will help accelerate the development of molecularly targeted agents for the treatment of cancer.

Pharmacogenomics in Early-Phase Oncology Clinical Trials: Is There a Sweet Spot in Phase II?

Many clinical trials of oncology drugs now include at least a consideration of pharmacogenomics, the study of germline or acquired genetic factors governing a drug's response and toxicity. Besides the potential benefit to patients from the consideration of personalized pharmacogenomic information when making treatment decisions, the incentive is clear for oncology drug developers to incorporate pharmacogenomic factors in the drug development process, because pharmacogenomic biomarkers may allow predictive characterization of subpopulations within a disease that may particularly respond or may allow preidentification of patients at highest risk for adverse events. There is, however, a lack of agreement in actual practice about at what point in the oncology clinical drug development process pharmacogenomic studies should be incorporated. In this article, we examine the recent growth of pharmacogenomics in oncology clinical trials, especially in early-phase studies, and examine several critical questions facing the incorporation of pharmacogenomics in early oncologic drug development. We show that phase II clinical trials, in particular, have a favorable track record for showing positive pharmacogenomic signals, worthy of additional follow-up and validation, and that the phase II setting holds significant promise for potentially accelerating and informing future phase III trials. We conclude that phase II trials offer an ideal "sweet spot" for routine incorporation of pharmacogenomic questions in oncology drug development.

A qualitative study evaluating causality attribution for serious adverse events during early phase oncology clinical trials

In early phase oncology trials, novel targeted therapies are increasingly being tested in combination with traditional agents creating greater potential for enhanced and new toxicities. When a patient experiences a serious adverse event (SAE), investigators must determine whether the event is attributable to the investigational drug or not. This study seeks to understand the clinical reasoning, tools used and challenges faced by the researchers who assign causality to SAE's. Thirty-two semi-structured interviews were conducted with medical oncologists and trial coordinators at six Canadian academic cancer centres. Interviews were recorded and transcribed verbatim. Individual interview content analysis was followed by thematic analysis across the interview set. Our study found that causality assessment tends to be a rather complex process, often without complete clinical and investigational data at hand. Researchers described using a common processing strategy whereby they gather pertinent information, eliminate alternative explanations, and consider whether or not the study drug resulted in the SAE. Many of the interviewed participants voiced concern that causality assessments are often conducted quickly and tend to be highly subjective. Many participants were unable to identify any useful tools to help in assigning causality and welcomed more objectivity in the overall process. Attributing causality to SAE's is a complex process. Clinical trial researchers apply a logical system of reasoning, but feel that the current method of assigning causality could be improved. Based on these findings, future research involving the development of a new causality assessment tool specifically for use in early phase oncology clinical trials may be useful.

Clinical Pharmacogenomics and Transcriptional Profiling in Early Phase Oncology Clinical Trials

Microarray-based expression profiling studies in the field of oncology have demonstrated encouraging correlations between tumor transcriptional profiles and eventual patient outcomes. These findings have fueled great interest in the application of transcriptional profiling to samples available from real-time clinical trials, and clinical pharmacogenomic objectives utilizing transcriptional profiling strategies are becoming increasingly incorporated into clinical trial study designs. Over the last few years several retrospective studies based on the profiling of archival tumor tissues suggest that transcriptional analysis of oncology samples may provide general prognosis measures, and in some cases may even predict response to specific therapies. Recently the FDA released a voluntary genomic data guidance meant to assist both regulatory agencies and pharmaceutical companies alike in evaluating the potential benefit of implementing expression profiling studies during the preclinical and clinical phases of drug development. Despite the great promise afforded by this technology, the ultimate benefit of applying transcriptional profiling in prospective clinical trials has yet to be realized because a number of practical impediments to this process exist. The multi-fold purpose of the current review is to highlight the increasing evidence from studies that have identified transcriptional signatures in archived tumors prognostic of patient outcome, to describe some of the drivers for the implementation of transcriptional profiling strategies in real-time drug development, to discuss the use of transcriptional profiling in the context of increasingly complex translational medicine strategies, and to highlight the practical issues and potential approaches involved in the successful application of clinical pharmacogenomic objectives during real-time clinical trials. Strategic implementation of transcriptional profiling in early oncology clinical trials can provide an opportunity to identify predictive markers of clinical response and eventually provide a substantial step forward towards the era of personalized medicine.