Evolution of clinical trial design in early drug development: systematic review of expansion cohort use in single-agent phase I cancer trials

Proportion of patients in phase 2 oncology trials receiving treatments that are ultimately approved

BACKGROUND

Many patients enroll in phase 1 dose expansion cohorts or phase 2 clinical trials (together referred to below as "phase 2") seeking access to novel treatments. Little is known about the extent to which they benefit by enrolling. Herein, we use a novel metric of benefit-therapeutic proportion-to assess the probability that patients in phase 2 trials receive treatment that eventually advances to FDA (Food and Drug Administration) approval for their condition.

METHODS

We randomly sampled 400 trials identified in a search of Clinicaltrials.gov for cancer phase 2 trials initiated between November 1, 2012 and November 1, 2015. We determined whether the drug/dose/indication tested in each trial advanced to FDA approval within 7.5 years. We determined whether the drug/dose/indication presented substantial clinical benefit using the ESMO-MCBS (European Society for Medical Oncology - Magnitude of Clinical Benefit Scale), or whether it received off-label recommendation in NCCN (National Comprehensive Cancer Network) guidelines.

RESULTS

Collectively, trials in our sample enrolled 25 002 patient-participants in 608 specific treatment cohorts. A total of 4045 patients received a treatment that advanced to FDA approval (16.2%; 95% CI = 10.3 to 22.7). The therapeutic proportion increased to 19.4% (95% CI = 14.1 to 25.8) when considering NCCN off-label recommendations and decreased to 9.3% (95% CI = 4.7 to 14.6) for FDA-approved regimens considered being of substantial clinical benefit by ESMO-MCBS. Bootstrap test of mean difference showed no statistical difference in proportions based on drug class, trial phase, or sponsorship.

CONCLUSION

One in 6 patients in phase 2 clinical trials receives treatments that are eventually approved. This represents a higher therapeutic value than phase 1 trials.

Integrating artificial intelligence in drug discovery and early drug development: a transformative approach

Artificial intelligence (AI) can transform drug discovery and early drug development by addressing inefficiencies in traditional methods, which often face high costs, long timelines, and low success rates. In this review we provide an overview of how to integrate AI to the current drug discovery and development process, as it can enhance activities like target identification, drug discovery, and early clinical development. Through multiomics data analysis and network-based approaches, AI can help to identify novel oncogenic vulnerabilities and key therapeutic targets. AI models, such as AlphaFold, predict protein structures with high accuracy, aiding druggability assessments and structure-based drug design. AI also facilitates virtual screening and de novo drug design, creating optimized molecular structures for specific biological properties. In early clinical development, AI supports patient recruitment by analyzing electronic health records and improves trial design through predictive modeling, protocol optimization, and adaptive strategies. Innovations like synthetic control arms and digital twins can reduce logistical and ethical challenges by simulating outcomes using real-world or virtual patient data. Despite these advancements, limitations remain. AI models may be biased if trained on unrepresentative datasets, and reliance on historical or synthetic data can lead to overfitting or lack generalizability. Ethical and regulatory issues, such as data privacy, also challenge the implementation of AI. In conclusion, in this review we provide a comprehensive overview about how to integrate AI into current processes. These efforts, although they will demand collaboration between professionals, and robust data quality, have a transformative potential to accelerate drug development.

Seamless trials in oncology: A cross-sectional analysis of characteristics and reporting

OBJECTIVES

Seamless clinical trials have received much attention as a possible way to expedite drug development. The growing importance of seamless design can be seen in oncology research, especially in the early stages of drug development. Our objective is to examine the basic characteristics of seamless early-phase oncology trials registered on the ClinicalTrials.gov database and to determine their results reporting rates. We also aim to identify factors associated with results reporting.

METHODS

Cross-sectional study. We defined seamless early-phase trials as either those registered as Phase 1/2 or Phase 1 with planned expansion cohort(s). Using the ClinicalTrials.gov registry, we searched for interventional cancer clinical trials with primary completion date (PCD) between 2016 and 2020. After trial selection, we performed manual data extraction based on the trial record description and the results posted in the trial registry. We used logistic regression to search for predictors of results reporting. Protocol: https://osf.io/m346x/.

RESULTS

We included 1051 seamless early-phase oncology trials reported as completed (PCD) between 2016 and 2020. We provided descriptive statistics including the number of patients enrolled, study start date, primary completion date, funding, type of intervention, cancer type, design details, type of endpoints, recruitment regions, and number of trial sites. Overall, only 34.7% trials reported results on ClinicalTrials.gov. The results reporting rates for 24 months was 24.0%. The overall reporting rate for Phase 1/2 studies was over three times higher than for seamless Phase 1.

CONCLUSIONS

Our study provides cross-sectional data on seamless early-phase oncology trials registered on ClinicalTrials.gov. We highlight the challenges of the evolving clinical trial design landscape and the problem of missing results in the seamless design context, which raises serious ethical concerns. Efforts should be made to adapt the functionality of the ClinicalTrials.gov database to emerging clinical trial models.

Evolving or immutable - phase I solid tumor trials in the era of precision oncology

In the era of precision oncology (PO), systemic therapies for patients (pts) with solid tumors have shifted from chemotherapy (CT) to targeted therapy (TT) and immunotherapy (IO). This systematic survey describes features of trials enrolling between 2010 and 2020, focusing on inclusion criteria, type of dose escalation scheme (DES) utilized, and use of expansion cohorts (ECs). A literature search identified phase I studies in adults with solid tumors published January 1, 2000- December 31, 2020 from 12 journals. We included only studies enrolling between 2010 and 2020 to better capture the PO era. Two reviewers abstracted data; a third established concordance. Of 10,744 studies, 10,195 were non-topical or enrolled prior to 2010; 437 studies were included. The most common drug classes were TT (47.6%), IO (22%), and CT (6.9%). In studies which reported race, patients were predominantly white (61.7%) or Asian (25.7%), followed by black (6.5%) or other (6.1%). Heterogeneity was observed in the reporting and specification of study inclusion criteria. Only 40.1% of studies utilized ECs, and among the studies which used ECS, 46.6% were defined by genomic selection. Rule-based DES were used in 89% of trials; a 3+3 design was used in 80.5%. Of all drugs tested, 37.5% advanced to phase II, while 10.3% garnered regulatory licensure (for an indication tested in phase I). In the era of PO, TT and IO have emerged as the most studied agents in phase I trials. Rule-based DES, which are more relevant for escalating CT, are still chiefly utilized.

The 3 + 3 design in dose-finding studies with small sample sizes: Pitfalls and possible remedies

In the last few years, numerous novel designs have been proposed to improve the efficiency and accuracy of phase I trials to identify the maximum-tolerated dose (MTD) or the optimal biological dose (OBD) for noncytotoxic agents. However, the conventional 3+3 approach, known for its and poor performance, continues to be an attractive choice for many trials despite these alternative suggestions. The article seeks to underscore the importance of moving beyond the 3+3 design by highlighting a different key element in trial design: the estimation of sample size and its crucial role in predicting toxicity and determining the MTD. We use simulation studies to compare the performance of the most used phase I approaches: 3+3, Continual Reassessment Method (CRM), Keyboard and Bayesian Optimal Interval (BOIN) designs regarding three key operating characteristics: the percentage of correct selection of the true MTD, the average number of patients allocated per dose level, and the average total sample size. The simulation results consistently show that the 3+3 algorithm underperforms in comparison to model-based and model-assisted designs across all scenarios and metrics. The 3+3 method yields significantly lower (up to three times) probabilities in identifying the correct MTD, often selecting doses one or even two levels below the actual MTD. The 3+3 design allocates significantly fewer patients at the true MTD, assigns higher numbers to lower dose levels, and rarely explores doses above the target dose-limiting toxicity (DLT) rate. The overall performance of the 3+3 method is suboptimal, with a high level of unexplained uncertainty and significant implications for accurately determining the MTD. While the primary focus of the article is to demonstrate the limitations of the 3+3 algorithm, the question remains about the preferred alternative approach. The intention is not to definitively recommend one model-based or model-assisted method over others, as their performance can vary based on parameters and model specifications. However, the presented results indicate that the CRM, Keyboard, and BOIN designs consistently outperform the 3+3 and offer improved efficiency and precision in determining the MTD, which is crucial in early-phase clinical trials.

Evolving or Immutable - Phase I Solid Tumor Trials in the Era of Precision Oncology

Purpose

In the era of precision oncology (PO), systemic therapies for patients (pts) with solid tumors have shifted from chemotherapy (CT) to targeted therapy (TT) and immunotherapy (IO). This systematic survey describes features of trials enrolling between 2010-2020, focusing on inclusion criteria, type of dose escalation scheme (DES) utilized, and use of expansion cohorts (ECs).

Methods

A literature search identified phase I studies in adults with solid tumors published January 1, 2000 - December 31, 2020 from 12 journals. We included only studies enrolling between 2010-2020 to better capture the PO era. Two reviewers abstracted data; a third established concordance.

Results

Of 10,744 studies, 10,195 were non-topical or enrolled prior to 2010; 437 studies were included. The most common drug classes were TT (47.6%), IO (22%), and CT (6.9%). In studies which reported race, patients were predominantly white (61.7%) or Asian (25.7%), followed by black (6.5%) or other (6.1%). Heterogeneity was observed in the reporting and specification of study inclusion criteria. Only 40.1% of studies utilized ECs, and among the studies which used ECS, 46.6% were defined by genomic selection. Rule-based DES were used in 89% of trials; a 3+3 design was used in 80.5%. Of all drugs tested, 37.5% advanced to phase II, while 10.3% garnered regulatory licensure (for an indication tested in phase I).

Conclusion

In the era of PO, TT and IO have emerged as the most studied agents in phase I trials. Rule-based DES, which are more relevant for escalating CT, are still chiefly utilized.

Profile and outcome of cancer patients enrolled in contemporary phase I trials

BACKGROUND

Phase I trials historically involved heavily pretreated patients (pts) with no more effective therapeutic options available and with poor expected outcomes. There are scare data regarding profile and outcomes of pts enrolled into modern phase I trials. Here, we sought to provide an overview of pts' profile and outcome into phase I trials at Gustave Roussy (GR).

METHODS

This is a monocentric retrospective study, including all pts enrolled into phase I trials at GR from 2017 to 2021. Data regarding pts' demographics, tumour types, investigational treatments and survival outcomes were collected.

RESULTS

In total, 9482 pts were referred for early phase trials; 2478 pts were screened, among which 449 (18.1%) failed screening; 1693 pts finally received at least one treatment dose as part of a phase I trial. Median age of pts was 59 years old (range, 18-88) and most common tumour types included gastrointestinal (25.3%), haematological (15%), lung (13.6%), genitourinary (10.5%) and gynaecologic cancers (9.4%). Amongst all pts treated and evaluable for response (1634 pts), objective response rate was 15.9% and disease control rate was 45.4%. Median progression-free survival and overall survival were, respectively, 2.6 months (95% confidence interval [95% CI], 2.3; 2.8) and 12.4 months (95% CI, 11.7; 13.6).

CONCLUSION

As compared with historical data, our study shows that outcomes of pts included into modern phase I trials have improved and that these trials constitute nowadays a valid and safe therapeutic option. These updated data provide facts for adapting the methodology, role and place of phase I trials over the next years.

Controlled amplification in oncology dose-finding trials

In oncology clinical trials the guiding principle of model-based dose-finding designs for cytotoxic agents is to progress as fast as possible towards, and identify, the dose level most likely to be the MTD. Recent developments with non-cytotoxic agents have broadened the scope of early phase trials to include multiple objectives. The ultimate goal of dose-finding designs in our modern era is to collect the relevant information in the study for final RP2D determination. While some information is collected on dose levels below and in the vicinity of the MTD during the escalation (using conventional tools such as the Continual Reassessment Method for example), designs that include expansion cohorts or backfill patients effectively amplify the information collected on the lower dose levels. This is achieved by allocating patients to dose levels slightly differently during the study in order to take into account the possibility that "less (dose) might be more". The objective of this paper is to study the concept of amplification. Under the heading of controlled amplification we can include dose expansion cohorts and backfill patients among others. We make some general observations by defining these concepts more precisely and study a specific design that exploits the concept of controlled amplification.

Recent advances and clinical pharmacology aspects of Chimeric Antigen Receptor (CAR) T-cellular therapy development

Advances in immuno-oncology have provided a variety of novel therapeutics that harness the innate immune system to identify and destroy neoplastic cells. It is noteworthy that acceptable safety profiles accompany the development of these targeted therapies, which result in efficacious cancer treatment with higher survival rates and lower toxicities. Adoptive cellular therapy (ACT) has shown promising results in inducing sustainable remissions in patients suffering from refractory diseases. Two main types of ACT include engineered Chimeric Antigen Receptor (CAR) T cells and T cell receptor (TCR) T cells. The application of these immuno-therapies in the last few years has been successful and has demonstrated a safe and rapid treatment regimen for solid and non-solid tumors. The current review presents an insight into the clinical pharmacology aspects of immuno-therapies, especially CAR-T cells. Here, we summarize the current knowledge of TCR and CAR-T cell immunotherapy with particular focus on the structure of CAR-T cells, the effects and toxicities associated with these therapies in clinical trials, risk mitigation strategies, dose selection approaches, and cellular kinetics. Finally, the quantitative approaches and modeling techniques used in the development of CAR-T cell therapies are described.

Early drug development in solid tumours: analysis of National Cancer Institute-sponsored phase 1 trials

BACKGROUND

The low expectation of clinical benefit from phase 1 cancer therapeutics trials might negatively affect patient and physician participation, study reimbursement, and slow the progress of oncology research. Advances in cancer drug development, meanwhile, might have favourably improved treatment responses; however, little comprehensive data exist describing the response and toxicity associated with phase 1 trials across solid tumours. The aim of the study is to evaluate the trend of toxicity and response in phase 1 trials for solid tumours over time.

METHODS

We analysed patient-level data from the Cancer Therapy Evaluation Program of the National Cancer Institute-sponsored investigator-initiated phase 1 trials for solid tumours, from Jan 1, 2000, to May 31, 2019. We assessed risks of treatment-related death (grade 5 toxicity ratings possibly, probably, or definitely attributable to treatment), all on-treatment deaths (deaths during protocol treatment regardless of attribution), grade 3-4 toxicity, and proportion of overall response (complete response and partial response) and complete response rate in the study periods of 2000-05, 2006-12, and 2013-2019, and evaluated their trends over time. We also analysed cancer type-specific and investigational agent-specific response, and analysed the trend of response in each cancer type over time. Univariate associations of overall response rates with patients' baseline characteristics (age, sex, performance status, BMI, albumin concentration, and haemoglobin concentration), enrolment period, investigational agents, and trial design were assessed using risk ratio based on the modified Poisson regression model.

FINDINGS

We analysed 465 protocols that enrolled 13 847 patients using 261 agents. 144 (31%) trials used a monotherapy and 321 (69%) used combination therapies. The overall treatment-related death rate was 0·7% (95% CI 0·5-0·8) across all periods. Risks of treatment-related deaths did not change over time (p=0·52). All on-treatment death risk during the study period was 8·0% (95% CI 7·6-8·5). The most common grade 3-4 adverse events were haematological; grade 3-4 neutropenia occurred in 2336 (16·9%) of 13 847 patients, lymphopenia in 1230 (8·9%), anaemia in 894 (6·5%), and thrombocytopenia in 979 (7·1%). The overall response rate for all trials during the study period was 12·2% (95% CI 11·5-12·8; 1133 of 9325 patients) and complete response rate was 2·7% (2·4-3·0; 249 of 9325). Overall response increased from 9·6% (95% CI 8·7-10·6) in 2000-05 to 18·0% (15·7-20·5) in 2013-19, and complete response rates from 2·5% (2·0-3·0) to 4·3% (3·2-5·7). Overall response rates for combination therapy were substantially higher than for monotherapy (15·8% [15·0-16·8] vs 3·5% [2·8-4·2]). The overall response by class of agents differed across diseases. Anti-angiogenesis agents were associated with higher overall response rate for bladder, colon, kidney and ovarian cancer. DNA repair inhibitors were associated with higher overall response rate in ovarian and pancreatic cancer. The rates of overall response over time differed markedly by disease; there were notable improvements in bladder, breast, and kidney cancer and melanoma, but no change in the low response of pancreatic and colon cancer.

INTERPRETATION

During the past 20 years, the response rate in phase 1 trials nearly doubled without an increase in the treatment-related death rate. However, there is significant heterogeneity in overall response by various factors such as cancer type, investigational agent, and trial design. Therefore, informed decision making is crucial for patients before participating in phase 1 trials. This study provides updated encouraging outcomes of modern phase 1 trials in solid tumours.

FUNDING

National Cancer Institute.

Characteristics of Early Phase Clinical Trials for Rare Cancers: Insights From Interviews With Stakeholders

Background: Rare cancers occur with an incidence of no more than six cases per 100,000 people according to the definition used by the Surveillance of Rare Cancers in Europe project. For a variety of reasons (low prevalence, cytotoxicity), it is challenging to perform the necessary clinical studies to investigate the safety and efficacy of investigational medicines against such rare malignancies, reformulating even at the earliest stages of the drug development process. This article investigates the differences between phase I rare cancer trials performed in commercial (companies) and non-commercial settings (academic hospitals).

Materials and Methods: The differences were explored through the conduct of semi-structured interviews with three different stakeholder groups: representatives from academia (n = 7), representatives from companies (n = 4) and representatives from patient organizations (n = 4). All the interviews were transcribed verbatim and analyzed in NVivo using the framework method.

Results: According to the interviewees, the academic and commercial stakeholders collaborate in the majority of phase I rare cancer trials. In general, the commercial partner finances the trial, whereas academia is responsible for the execution of the study procedures. The average cost of undertaking these trials is difficult to estimate because it depends on what is specifically requested during the trial. The 3 + 3 study design remains the most widely used design and the use of expansion cohorts is controversial. With regard to the regulatory aspects of phase I rare cancer trials, it was expressed that a good regulatory framework facilitates the conduct of these studies, but that increased regulation and oversight also has drawbacks, e.g., differences in standards between different ethics committees, over interpretation of the rules, insufficient availability of qualified personnel and higher workloads. The patient organization representatives claimed that patients experience no differences in terms of accommodation, compensation and paperwork between the academic and commercial settings or the degree of follow-up. They also believed that the direct input of patients can bring added value to such studies not only with regard to the recruitment process and the feasibility of the study but also the legibility of the informed consent forms.

Conclusion: The growing need for first-in-man trials in rare malignancies needs to be highlighted, as difficult as they are to undertake and to co-develop, not only because rare cancer patients deserve an appropriate treatment, but also because these medicines represent the future of cancer therapy in the precision medicine era. Cooperation of commercial and academic sites are needed. Patient organizations need to be educated to take part in this process.

Optimal Sequential Predictive Probability Designs for Early-Phase Oncology Expansion Cohorts

PURPOSE

The customary approach to early-phase clinical trial design, where the focus is on identification of the maximum tolerated dose, is not always suitable for noncytotoxic or other targeted therapies. Many trials have continued to follow the 3 + 3 dose-escalation design, but with the addition of phase I dose-expansion cohorts to further characterize safety and assess efficacy. Dose-expansion cohorts are not always planned in advance nor rigorously designed. We introduce an approach to the design of phase I expansion cohorts on the basis of sequential predictive probability monitoring.

METHODS

Two optimization criteria are proposed that allow investigators to stop for futility to preserve limited resources while maintaining traditional control of type I and type II errors. We demonstrate the use of these designs through simulation, and we elucidate their implementation with a redesign of the phase I expansion cohort for atezolizumab in metastatic urothelial carcinoma.

RESULTS

A sequential predictive probability design outperforms Simon's two-stage designs and posterior probability monitoring with respect to both proposed optimization criteria. The Bayesian sequential predictive probability design yields increased power while significantly reducing the average sample size under the null hypothesis in the context of the case study, whereas the original study design yields too low type I error and power. The optimal efficiency design tended to have more desirable properties, subject to constraints on type I error and power, compared with the optimal accuracy design.

CONCLUSION

The optimal efficiency design allows investigators to preserve limited financial resources and to maintain ethical standards by halting potentially large dose-expansion cohorts early in the absence of promising efficacy results, while maintaining traditional control of type I and II error rates.

Stopping rules for phase I clinical trials with dose expansion cohorts

Many clinical trials incorporate stopping rules to terminate early if the clinical question under study can be answered with a high degree of confidence. While common in later-stage trials, these rules are rarely implemented in dose escalation studies, due in part to the relatively smaller sample size of these designs. However, even with a small sample size, this paper shows that easily implementable stopping rules can terminate dose-escalation early with minimal loss to the accuracy of maximum tolerated dose estimation. These stopping rules are developed when the goal is to identify one or two dose levels, as the maximum tolerated dose and co-maximum tolerated dose. In oncology, this latter goal is frequently considered when the study includes dose-expansion cohorts, which are used to further estimate and compare the safety and efficacy of one or two dose levels. As study protocols do not typically halt accrual between escalation and expansion, early termination is of clinical importance as it either allows for additional patients to be treated as part of the dose expansion cohort to obtain more precise estimates of the study endpoints or allows for an overall reduction in the total sample size.

Of some innovations in clinical trial design in hematology and oncology

The design of clinical trials, formalized in the immediate post-war period, has undergone major changes due to therapeutic innovations, particularly the arrival of targeted therapies in onco-hematology. The traditional phase I-II-III regimen is regularly questioned and multiple adaptations are proposed. This article proposes to expose some of these modifications and the issues they lead to.

Trends in patient-reported outcome use in early phase dose-finding oncology trials - an analysis of ClinicalTrials.gov

BACKGROUND

Patient-reported adverse events (AEs) may be a useful adjunct to clinician-assessed AEs for assessing tolerability in early phase, dose-finding oncology trials (DFOTs). We reviewed DFOTs on ClinicalTrials.gov to describe trends in patient-reported outcome (PRO) use.

METHODS

DFOTs commencing 01 January 2007 - 20 January 2020 with 'PROs' or 'quality of life' as an outcome were extracted and inclusion criteria confirmed. Study and PRO characteristics were extracted. Completed trials that reported PRO outcomes and published manuscripts on ClinicalTrials.gov were identified, and PRO reporting details were extracted.

RESULTS

5.3% (548/10 372) DFOTs included PROs as an outcome. 231 (42.2%) were eligible: adult (224, 97%), solid tumour (175, 75.8%), and seamless phase 1/2 (108, 46.8%). PRO endpoints were identified in more trials (2.3 increase/year, 95% CI: 1.6-2.9) from an increasing variety of countries (0.7/year) (95% CI: 0.4-0.9) over time. PROs were typically secondary endpoints (207, 89.6%). 15/77 (19.5%) completed trials reported results on the ClinicalTrials.gov results database, and of those eight included their PRO results. Eighteen trials had published manuscripts available on ClinicalTrials.gov. Three (16.7%) used PROs to confirm the maximum tolerated dose. No trials identified who completed the PROs or how PROs were collected.

CONCLUSIONS

PRO use in DFOT has increased but remains limited. Future work should explore the role of PROs in DFOT and determine what guidelines are needed to standardise PRO use.

Unified exact design with early stopping rules for single arm clinical trials with multiple endpoints

Adaptive designs are gaining popularity in early phase clinical trials because they enable investigators to change the course of a study in response to accumulating data. We propose a novel design to simultaneously monitor several endpoints. These include efficacy, futility, toxicity and other outcomes in early phase, single-arm studies. We construct a recursive relationship to compute the exact probabilities of stopping for any combination of endpoints without the need for simulation, given pre-specified decision rules. The proposed design is flexible in the number and timing of interim analyses. A R Shiny app with user-friendly web interface has been created to facilitate the implementation of the proposed design.

Modern Challenges for Early-Phase Clinical Trial Design and Biomarker Discovery in Metastatic Non-Small-Cell Lung Cancer

Oncology research has changed extensively due to the possibility to categorize each cancer type into smaller subgroups based on histology and particularly on different genetic alterations due to their heterogeneity. The consequences of this heterogeneity are particularly evident in the management of metastatic non-small-cell lung cancer (NSCLC). This review will discuss the benefits and challenges of incorporating precision medicine into early- through late-phase metastatic NSCLC clinical trials, discussing examples of drug development programs in oncogene- and non-oncogene-addicted NSCLC. The experiences of clinical development of crizotinib, gefitinib and osimertinib are depicted showing that when a targeted drug is administrated in a study population not selected by any biomarker, trials could produce negative results. However, the early detection of biomarker-driven biology helps to obtain a greater benefit for a selected population and can reduce the required time for drug approval. Early clinical development programs involving nivolumab, pembrolizumab and avelumab, immune checkpoint inhibitors, taught us that, beyond safety and activity, the optimal selection of patients should be based on pre-specified biomarkers. Overall, the identification of predictive biomarkers is one of the greatest challenges of NSCLC research that should be optimized with solid methodological trial designs to maximize the clinical outcomes.

Randomised Phase 1 clinical trials in oncology

The aims of Phase 1 trials in oncology have broadened considerably from simply demonstrating that the agent/regimen of interest is well tolerated in a relatively heterogeneous patient population to addressing multiple objectives under the heading of early-phase trials and, if possible, obtaining reliable evidence regarding clinical activity to lead to drug approvals via the Accelerated Approval approach or Breakthrough Therapy designation in cases where the tumours are rare, prognosis is poor or where there might be an unmet therapeutic need. Constructing a Phase 1 design that can address multiple objectives within the context of a single trial is not simple. Randomisation can play an important role, but carrying out such randomisation according to the principles of equipoise is a significant challenge in the Phase 1 setting. If the emerging data are not sufficient to definitively address the aims early on, then a proper design can reduce biases, enhance interpretability, and maximise information so that the Phase 1 data can be more compelling. This article outlines objectives and design considerations that need to be adhered to in order to respect ethical and scientific principles required for research in human subjects in early phase clinical trials.

Moving Beyond 3+3: The Future of Clinical Trial Design

Misgivings have been raised about the operating characteristics of the canonical 3+3 dose-escalation phase I clinical trial design. Yet, the traditional 3+3 design is still the most commonly used. Although it has been implied that adhering to this design is due to a stubborn reluctance to adopt change despite other designs performing better in hypothetical computer-generated simulation models, the continued adherence to 3+3 dose-escalation phase I strategies is more likely because these designs perform the best in the real world, pinpointing the correct dose and important side effects with an acceptable degree of precision. Beyond statistical simulations, there are little data to refute the supposed shortcomings ascribed to the 3+3 method. Even so, to address the unique nuances of gene- and immune-targeted compounds, a variety of inventive phase 1 trial designs have been suggested. Strategies for developing these therapies have launched first-in-human studies devised to acquire a breadth of patient data that far exceed the size of a typical phase I design and blur the distinction between dose selection and efficacy evaluation. Recent phase I trials of promising cancer therapies assessed objective tumor response and durability at various doses and schedules as well as incorporated multiple expansion cohorts spanning a variety of histology or biomarker-defined tumor subtypes, sometimes resulting in U.S. Food and Drug Administration approval after phase I. This article reviews recent innovations in phase I design from the perspective of multiple stakeholders and provides recommendations for future trials.

Comparison of Duration of Response vs Conventional Response Rates and Progression-Free Survival as Efficacy End Points in Simulated Immuno-oncology Clinical Trials

IMPORTANCE

Phase 2 trials and early efficacy end points play a crucial role in informing decisions about whether to continue to phase 3 trials. Conventional end points, such as objective response rate (ORR) and progression-free survival (PFS), have demonstrated inconsistent associations with overall survival (OS) benefits in immune checkpoint inhibitor (ICI) trials. Restricted mean duration of response (DOR) is a rigorous metric that combines both response status and duration information. However, its utility in clinical development has not been comprehensively explored.

OBJECTIVE

To determine whether using restricted mean DOR in phase 2 trials can advance promising regimens to phase 3 trials sooner and eliminate unfavorable regimens earlier and with a higher degree of confidence compared with PFS and ORR.

DESIGN, SETTING, AND PARTICIPANTS

This simulated modeling study randomized phase 2 screening trials by resampling 1376 patients from 2 completed randomized phase 3 trials of ICIs. Data were analyzed from August 2019 to July 2020.

EXPOSURES

Use of ICIs.

MAIN OUTCOMES AND MEASURES

Restricted mean DOR, PFS, ORR, and OS were estimated and compared between groups. Three scenarios were considered: (1) significant differences in OS, PFS, and ORR; (2) significant differences in OS and noticeable differences in ORR but not PFS; and (3) no differences in OS, PFS, or ORR. For each setting, 5000 randomized phase 2 trials with different sample sizes were simulated, with additional censoring applied to mimic staggered accruals and ensure fair comparisons between different analysis methods. Probabilities of concluding positive phase 2 trials using PFS, ORR, and DOR were summarized and compared.

RESULTS

The restricted mean DOR difference correctly estimated a positive OS benefit more frequently than did the ORR or PFS tests, across different sample sizes, significance levels, and censoring levels evaluated. When both OS and PFS differed, the ranges of true-positive or power rates were 79.2% to 98.7% for DOR, 56.3% to 93.2% for PFS, and 67.0% to 96.0% for ORR. When OS differed but PFS did not, the ranges of power rates were 24.0% to 76.0% for DOR, 3.0% to 19.0% for PFS, and 10.5% to 38.0% for ORR. When OS was similar, the false-positive rate of restricted mean DOR test was close to the chosen significance level.

CONCLUSIONS AND RELEVANCE

These findings suggest that restricted mean DOR in randomized phase 2 trials is potentially more sensitive and useful than PFS and ORR in estimating the subsequent phase 3 conclusions and, thus, may be considered to complementarily facilitate decision-making in future clinical development.

A modular framework for early-phase seamless oncology trials

BACKGROUND

As our understanding of the etiology and mechanisms of cancer becomes more sophisticated and the number of therapeutic options increases, phase I oncology trials today have multiple primary objectives. Many such designs are now "seamless," meaning that the trial estimates both the maximum tolerated dose and the efficacy at this dose level. Sponsors often proceed with further study only with this additional efficacy evidence. However, with this increasing complexity in trial design, it becomes challenging to articulate fundamental operating characteristics of these trials, such as (1) what is the probability that the design will identify an acceptable, that is., safe and efficacious, dose level? or (2) how many patients will be assigned to an acceptable dose level on average?

METHODS

In this manuscript, we propose a new modular framework for designing and evaluating seamless oncology trials. Each module is comprised of either a dose assignment step or a dose-response evaluation, and multiple such modules can be implemented sequentially. We develop modules from existing phase I/II designs as well as a novel module for evaluating dose-response using a Bayesian isotonic regression scheme.

RESULTS

We also demonstrate a freely available R package called seamlesssim to numerically estimate, by means of simulation, the operating characteristics of these modular trials.

CONCLUSIONS

Together, this design framework and its accompanying simulator allow the clinical trialist to compare multiple different candidate designs, more rigorously assess performance, better justify sample sizes, and ultimately select a higher quality design.

Pretreatment Blood Parameters Predict Efficacy from Immunotherapy Agents in Early Phase Clinical Trials

BACKGROUND

Peripheral blood parameters are correlated to immune-checkpoint inhibitor efficacy in solid tumors, such as melanoma and non-small cell lung cancer. Few data are currently available on the prognostic role of these immune-inflammatory biomarkers for other solid tumors and immunotherapy combinations.

MATERIAL AND METHODS

From August 2014 to May 2019, 153 patients with metastatic solid tumors were enrolled in phase I clinical trials testing immunotherapy both as single agents and as combinations. Primary endpoint was to evaluate the impact of baseline blood parameters on progression-free survival (PFS) and overall survival (OS).

RESULTS

The most common tumor types were gastrointestinal, breast, and gynecological cancers (22.9%, 22.2%, and 15.0%, respectively). Higher lactate dehydrogenase (LDH) and derived neutrophil-to-lymphocyte ratio (dNLR) were independently associated with reduced PFS (hazard ratio [HR], 1.97; 95% confidence interval [CI], 1.30-2.99; p = .001, and HR, 2.29; 95% CI, 1.39-3.77; p = .001, respectively) and reduced OS (HR, 2.04; 95% CI, 1.26-3.28; p = .004, and HR, 2.06; 95% CI, 1.12-3.79; p = .02, respectively). In the subgroup analysis, (single agent vs. combination), patients at "good" (dNLR <3 and LDH < upper limit of normal [ULN]) and "intermediate and poor" (dNLR >3 and/or LDH > ULN) risk had higher and lower PFS, respectively (p for interaction = .002). Conversely, patients receiving monotherapy presented statistically significant difference in OS according to the risk group, whereas this effect was not observed for those treated with combinations (p for interaction = .004).

CONCLUSION

Elevated LDH and dNLR are associated with poorer survival outcomes in patients treated with immunotherapy in phase I clinical trials, regardless of tumor type. These parameters represent an easy tool that might be considered as stratification factors in immunotherapy-based clinical trials.

IMPLICATIONS FOR PRACTICE

In this retrospective cohort study of 153 patients with metastatic solid tumors treated with immunotherapy in the context of phase I clinical trials, elevated baseline lactate dehydrogenase and derived neutrophil-to-lymphocyte ratio were associated with reduced survival regardless of tumor subtype. If prospectively validated, these parameters might represent low-cost and easy biomarkers that could help patient selection for early phase immunotherapy trials and be applied as a stratification factor in randomized studies testing immunotherapy agents.

Innovation in Oncology Drug Development

Significant progress has been made in our understanding of the molecular lesions responsible for tumor cells to exhibit uncontrolled growth while circumventing normal mechanisms of apoptosis and their ability to migrate and invade normal tissues while evading recognition and destruction by the immune system. This understanding has enabled the development of therapies specifically targeted to these lesions coupled to innovative treatment regimens to most effectively use these new targeted therapies with precision in selected subpopulations of patients. Innovation at the scientific and clinical levels has been appropriately embraced and supported at the FDA, resulting in regulatory innovation to facilitate and adapt to the Precision Medicine environment.

Phase I trials as valid therapeutic options for patients with cancer

For many years, oncology phase I trials have been referred to as 'toxicity trials' and have been believed to have low clinical utility other than that of establishing the adverse event profile of novel therapeutic agents. The traditional distinction of clinical trials into three phases has been challenged in the past few years by the introduction of targeted therapies and immunotherapies into the routine management of patients with cancer. This transformation has especially affected early phase trials, leading to the current situation in which response rates are increasingly reported from phase I trials. In this Perspectives, we highlight key elements of phase I trials and discuss how each one of them contributes to a new paradigm whereby preliminary measurements of the clinical benefit from a novel treatment can be obtained in current phase I trials, which can therefore be considered to have a therapeutic intent.

New designs in early clinical drug development

The availability of an unprecedented massive amount of data has provided a magnificent window of opportunity for the development of new drugs. There are currently more drugs in development targeting cancer than any other disease. While this has brought us new waves of drugs, the counterpart is that with these new molecules we have different mechanisms of action, drug kinetics and dynamics, response types and toxicity profiles, which impair classical early clinical trial designs from being effective and efficient. What we once treated as a 'one-size-fits-all' homogeneous disease, has now been uncovered to be a rather heterogeneous condition with multiple targetable mutations. As this generates endless scenarios, it will be impossible to design single 'me-too' trials for every different disease, target, biomarker and agent. To overcome this, we must focus on improving early phase studies, undoubtedly the most critical step from bench to bedside. Goals include decreasing clinical development times, lowering research and development costs and optimizing decisions in advancing through the several phases with a higher degree of certainty in exchange for less failed attempts. We need more informative and, really, transformative early phase designs that seek to obtain the typical late phase objectives in a time continuum and to allow for more robust and efficient go/no-go decisions. With this in mind, different classes of drugs seem to fit with different designs, which present solutions to the different challenges that they pose after finding the maximum tolerated dose/optimum biological dose. This article reviews these concepts and designs and how they can adapt to this new reality in early phase investigation.

Clinical Development and Initial Approval of Novel Immune Checkpoint Inhibitors in Oncology: Insights From a Global Regulatory Perspective

Immune checkpoint inhibitors (ICI) have demonstrated meaningful patterns of clinical efficacy across various cancers. During their development, novel regulatory strategies and clinical design approaches were explored. This metrics-based narrative review examines submission strategies and clinical evidence expectations of the US, European, and Japanese drug agencies, as well as their impact on approval and overall development times. Also discussed is the role of emerging clinical science and biomarker evaluation to get the first six ICI initially approved.

Design considerations for early-phase clinical trials of immune-oncology agents

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.

Statistical justification of expansion cohorts in phase 1 cancer trials

BACKGROUND

Phase I cancer trials increasingly incorporate dose-expansion cohorts (DECs), reflecting a growing demand to acquire more information about investigational drugs. Protocols commonly fail to provide a sample-size justification or analysis plan for the DEC. In this study, we develop a statistical framework for the design of DECs.

METHODS

We assume the maximum tolerated dose (MTD) for the investigational drug has been identified in the dose-escalation stage of the trial. We use the 80% lower confidence bound and the 90% upper confidence bound for the response and toxicity rates, respectively, as decision thresholds for the dose-expansion stage. We calculate the operating characteristics with reference to prespecified minimum effective response rates and maximum safe DLT rates.

RESULTS

We apply our framework to specify a system of DEC plans. The design comprises three components: 1) the number of subjects enrolled at the MTD, 2) the minimum number of responses necessary to indicate provisional drug efficacy, and 3) the maximum number of dose-limiting toxicities (DLTs) permitted to indicate drug safety. We demonstrate our method in an application to a cancer immunotherapy trial.

CONCLUSIONS

Our simple and practical tool enables creation of DEC designs that appropriately address the safety and efficacy objectives of the trial.

Impact of Availability of Companion Diagnostics on the Clinical Development of Anticancer Drugs

BACKGROUND

Companion diagnostics permit the selection of patients likely to respond to targeted anticancer drugs; however, it is unclear if the drug development process differs between drugs developed with or without companion diagnostics. Identification of differences in study design could help future clinical development.

PATIENTS AND METHODS

Anticancer drugs approved for use in solid tumors between 28 September 2000 and 4 January 2014 were identified using a search of the US FDA website. Phase III trials supporting registration were extracted from the drug label. Each published study was reviewed to obtain information about the phase I and II trials used for the development of the respective drug.

RESULTS

We identified 35 drugs and 59 phase III randomized trials supporting regulatory approval. Fifty-three phase I trials and 47 phase II trials were cited in the studies and were used to support the design of these phase III trials. The approval of drugs using a companion diagnostic has increased over time (p for trend 0.01). Expansion cohorts were more frequently observed with drugs developed with a companion diagnostic (62 vs. 20%; p = 0.005). No differences between drugs developed with or without a companion diagnostic were observed for the design of phase I and II studies.

CONCLUSIONS

The approval of drugs developed with a companion diagnostic has increased over time. The availability of a companion diagnostic was associated with more frequent use of phase I expansion cohorts comprising patients selected by the companion diagnostic.

Evolving paradigms for new agent development in pediatric oncology

PURPOSE OF REVIEW

To discuss considerations of new paradigms for clinical drug development in pediatric oncology that incorporate our expanding knowledge and complexity of molecular alterations associated with cancer; advances in cancer immunology and cellular therapy; the increasing number of new anticancer drugs, therapeutic approaches, and potential combinations; and recent initiatives by regulatory agencies to improve access to safe and effective therapies.

RECENT FINDINGS

Cancer in children and adolescents is a rare event with significant long-term impact on individuals and society. Using multimodality therapy, stratified by patient and disease characteristics, the cure rate for childhood cancer exceeds 80%. Cancer genomics has transformed anticancer drug development. Understanding the genetic basis of pediatric cancers and the use of genomics for risk stratification has changed the focus of drug development from cytotoxic drugs to targeted therapeutic approaches. Advances in cancer immunology, immune checkpoint blockade, and cellular therapy offer novel approaches to harness T cells to treat cancer. To improve the outcome for children and adolescents with cancer and accelerate drug development, understanding drug and target interactions in preclinical models of pediatric cancer should be coupled with efficient clinical trial designs that incorporate biomarker selection, assessment of toxicity and drug exposure, and improved measures of response.

SUMMARY

Clinical trials for children and adolescents with cancer evaluate cytotoxic drugs, molecularly target drugs, immunotherapy as well as combination therapies. The framework for oncology clinical trials will continually adapt to improve efficiency of trials and evaluate new therapeutic approaches.

Drug development and clinical trial design in pancreatico-biliary malignancies

Pancreatico-biliary (P-B) tumors arise from the pancreas, bile duct, and ampulla of Vater. Despite their close anatomical location, they have different etiology and biology. However, they uniformly share a poor prognosis, with no major improvements observed in overall survival over decades, even in the face of progress in diagnostic imaging and surgical techniques, and advances in systemic and loco-regional radiation therapies. To date, cytotoxic treatment has been associated with modest benefits in the advanced disease setting, and survival for patients with stage IV disease has not exceeded a year. Therefore, there is a pressing need to identify better treatments which may impact more significantly. Frequently, encouraging signals of potential efficacy for novel agents in early phase clinical trials have been followed by disappointing failures in larger phase III trials, raising the valid question of how drug development can be optimized for patients with pancreatic adenocarcinoma and biliary tract malignancies. In this article we summarize the current therapeutic options for these patients and their limitations. The biological context of these cancers is reviewed, highlighting features that may make them resistant to standard chemotherapeutics and could be potential therapeutic targets. We discuss the role of early phase clinical trials, defined as phase I and non-randomised phase II trials, within the clinical context and current therapeutic landscape of P-B tumors and postulate how translational studies and trial design may enable better realization of emerging targets together with a proposed model for future patient management. A detailed summary of current phase I clinical trials in P-B tumors is provided.

Early Phase Clinical Trial Designs - State of Play and Adapting for the Future

The process of anti-cancer drug development is complex, with high attrition rates. Factors that may optimise this process include well-constructed and relevant pre-clinical testing and use of biomarkers for patient selection. However, the design of early phase clinical trials will probably play a vital role in both the robust clinical investigation of new targeted therapies and in streamlining drug development. In this overview, we assess current concepts in phase I clinical trials, highlighting issues and opportunities to improve their meaningfulness. The particular challenge of how to design combination trials is addressed, with focus on the potential of new adaptive and model-based designs.

Early phase clinical trials of anticancer agents in children and adolescents - an ITCC perspective

In the past decade, the landscape of drug development in oncology has evolved dramatically; however, this paradigm shift remains to be adopted in early phase clinical trial designs for studies of molecularly targeted agents and immunotherapeutic agents in paediatric malignancies. In drug development, prioritization of drugs on the basis of knowledge of tumour biology, molecular 'drivers' of disease and a drug's mechanism of action, and therapeutic unmet needs are key elements; these aspects are relevant to early phase paediatric trials, in which molecular profiling is strongly encouraged. Herein, we describe the strategy of the Innovative Therapies for Children with Cancer (ITCC) Consortium, which advocates for the adoption of trial designs that enable uninterrupted patient recruitment, the extrapolation from studies in adults when possible, and the inclusion of expansion cohorts. If a drug has neither serious dose-related toxicities nor a narrow therapeutic index, then studies should generally be started at the adult recommended phase II dose corrected for body surface area, and act as dose-confirmation studies. The use of adaptive trial designs will enable drugs with promising activity to progress rapidly to randomized studies and, therefore, will substantially accelerate drug development for children and adolescents with cancer.

Statistical controversies in clinical research: building the bridge to phase II-efficacy estimation in dose-expansion cohorts

BACKGROUND

Regulatory agencies and others have expressed concern about the uncritical use of dose expansion cohorts (DECs) in phase I oncology trials. Nonetheless, by several metrics-prevalence, size, and number-their popularity is increasing. Although early efficacy estimation in defined populations is a common primary endpoint of DECs, the types of designs best equipped to identify efficacy signals have not been established.

METHODS

We conducted a simulation study of six phase I design templates with multiple DECs: three dose-assignment/adjustment mechanisms multiplied by two analytic approaches for estimating efficacy after the trial is complete. We also investigated the effect of sample size and interim futility analysis on trial performance. Identifying populations in which the treatment is efficacious (true positives) and weeding out inefficacious treatment/populations (true negatives) are competing goals in these trials. Thus, we estimated true and false positive rates for each design.

RESULTS

Adaptively updating the MTD during the DEC improved true positive rates by 8-43% compared with fixing the dose during the DEC phase while maintaining false positive rates. Inclusion of an interim futility analysis decreased the number of patients treated under inefficacious DECs without hurting performance.

CONCLUSION

A substantial gain in efficiency is obtainable using a design template that statistically models toxicity and efficacy against dose level during expansion. Design choices for dose expansion should be motivated by and based upon expected performance. Similar to the common practice in single-arm phase II trials, cohort sample sizes should be justified with respect to their primary aim and include interim analyses to allow for early stopping.

Use of Expansion Cohorts in Phase I Trials and Probability of Success in Phase II for 381 Anticancer Drugs

Purpose: Evaluate the association between the use of phase I expansion cohorts (ECs) and drug performance in phase II as well as time to approval by the FDA.Experimental Design: We performed a systematic search of MEDLINE for single-agent dose-finding adult oncology phase I trials published in 2006 to 2011 and subsequent phase II trials. Successful phase II trials were those that met their primary endpoints. Dates of approval were obtained from the Drugs@FDA website in April 2014. A logistic regression model was used to determine the associations between variables and success in phase II.Results: We identified 533 phase I trials evaluating 381 drugs; 112 drugs had at least one phase I trial with an expansion cohort. Phase I trials with expansion cohorts of two to 20 patients were associated with a higher rate of successful phase II trials than those with no expansion cohort [48% vs. 27%; OR, 2.1; 95% confidence interval (CI), 1.1-4.0; P = 0.037]. Phase II success rates were the same for expansion cohort with two to 20 and more than 20 patients (48% vs. 52%). Other positive associations were disease-specific trials (OR, 1.7; 95% CI, 1.0-2.9; P = 0.037), industry sponsorship (OR, 2.9; 95% CI, 1.5-5.7; P = 0.0024), and response rate of 6% to 20% (OR, 2.89; 95% CI, 1.6-5.2; P = 0.0007). Drugs tested in phase I trials with expansion cohorts had a higher rate of 5-year approval (19% vs. 5%; HR, 4.4; 95% CI, 2.2-8.8; P < 0.001).Conclusions: The use of expansion cohorts in phase I trials was associated with success of subsequent phase II trials. However, confounders may play a role in this association. Clin Cancer Res; 23(15); 4020-6. ©2017 AACR.

The European Organization for Research and Treatment of Cancer perspective on designing clinical trials with immune therapeutics

Cancer immunotherapy has had a major impact on the established paradigms of drug development and clinical trial research. The innovative mechanism of action of these compounds has resulted in new patterns of response and safety profiles, which pose challenges for the classical trial methodology. In this review we report on the search for the maximum tolerated dose, the recommended phase II dose and the appropriate target population in phase I trials. We provide some statistical considerations on the choice of endpoints for phase II and III trials and the limitations of frequently used trial designs in the presence of a delayed treatment effect, which may be induced by the immune modulating effect of the checkpoint inhibitors. We summarize the currently available data on the safety profile of these new compounds, which can guide protocol safety recommendations. Finally, we report on the current evidence of biomarker development.

Integrating the escalation and dose expansion studies into a unified Phase I clinical trial

We focus on Phase I dose finding studies as they are currently undertaken. The design and analysis of these trials have changed over the last years and, in particular, it is now rare for a Phase I study to not include one or more dose-expansion cohorts (DEC). It is common to see DEC involving several hundred patients, building on an initial dose escalation study that may have no >20 to 30 patients. There has been recent focus by researchers on the design of DEC and the analysis of DEC data. It is reasonable to explicitly account for the uncertainty in the estimation of the MTD, the dose upon which the whole of the DEC is currently based. In this paper, we focus on the dose escalation phase prior to the DEC, with the purpose of adapting it to the needs of DEC. Specifically, before beginning the DEC phase, we need to identify those dose levels that will be taken into the DEC. We define a useful concept for this purpose, the co-MTD, and the results support that the estimated MTD and co-MTD contain the true MTD with high probability. We also provide stopping rules for when the data support that the dose escalation can end and the dose expansion can begin. Simulated trials support the use of the proposed approach and provide additional information on how this approach compares with current practice.

Dose expansion cohorts in Phase I trials

A rapidly increasing number of Phase I dose-finding studies, and in particular those based on the standard 3+3 design, are being prolonged with the inclusion of dose expansion cohorts (DEC) in order to better characterize the toxicity profiles of experimental agents and to study disease-specific cohorts. These trials consist of two phases: the usual dose escalation phase that aims to establish the maximum tolerated dose (MTD), and the dose expansion phase that accrues additional patients, often with different eligibility criteria, and where additional information is collected. Current protocols do not always specify whether and how the MTD will be updated in light of the new data accumulated from the DEC. In this paper, we propose methods that allow monitoring of safety in the DEC by re-evaluating the MTD in light of additional information. Our working assumption is that, regardless of the design being used for dose escalation, during the DEC we are experimenting in the neighborhood of a target dose with an acceptable rate of toxicity. We refine our initial estimate of the MTD by continuing experimentation in the immediate vicinity of the initial estimate of the MTD. The auxiliary information provided in such an evaluation can include toxicity, pharmacokinetic, efficacy or other endpoints. We consider approaches specifically focused on the aims of DEC that examine efficacy alone or simultaneously with safety and compare the proposed tests via simulations.

Thirty years of phase I radiochemotherapy trials: Latest development

Radiochemotherapy is undergoing a complete expansion. Currently, possibilities of treatment combination are skyrocketting, with different anticancer and targeted molecules, different radiotherapy techniques, and dose escalation with each therapy. The development of a modern phase I radiochemotherapy trial becomes more and more complex and should be fully investigated. In the literature, there are no exhaustive reviews describing the necessity of their characteristics. The present article explores historical and current phase I clinical trials involving a combination of radiation therapy and anticancer therapies. Selected trials were identified by searching in PubMed databases. A total of 228 studies were identified in the last three decades, and a portrait of their characteristics is presented. As expected, most frequently studied malignancies were head and neck cancers, followed by non-small cell lung cancer and brain cancer. Toxicity is reported in more than 90% of the studies. Most studies were published since 2010, at the area of targeted therapies, but mainly concerned classical chemotherapies (cisplatin and 5-fluorouracil). The present review highlights some limits. Indeed, methodology seems not optimised and could be based on more accurate methods of dose-escalation. The present portrait of phase I radiochemotherapy trials suggests that radiochemotherapy notion must be reinvented and trials should be adapted to its complexity. Step by step method does not sound like an option anymore. Let us build the future of radiochemotherapy on past evidences.

Sequential monitoring of Phase I dose expansion cohorts

A relatively recent development in the design of Phase I dose-finding studies is the inclusion of expansion cohort(s), that is, the inclusion of several more patients at a level considered to be the maximum tolerated dose established at the conclusion of the 'pure' Phase I part. Little attention has been given to the additional statistical analysis, including design considerations, that we might wish to consider for this more involved design. For instance, how can we best make use of new information that may confirm or may tend to contradict the estimate of the maximum tolerated dose based on the dose escalation phase. Those patients included during the dose expansion phase may possess different eligibility criteria. During the expansion phase, we will also wish to have an eye on any evidence of efficacy, an aspect that clearly distinguishes such studies from the classical Phase I study. Here, we present a methodology that enables us to continue the monitoring of safety in the dose expansion cohort while simultaneously trying to assess efficacy and, in particular, which disease types may be the most promising to take forward for further study. The most elementary problem is where we only wish to take account of further toxicity information obtained during the dose expansion cohort, and where the initial design was model based or the standard 3+3. More complex set-ups also involve efficacy and the presence of subgroups. Copyright © 2016 John Wiley & Sons, Ltd.