Phase I Trials of Molecularly Targeted Agents: Should We Pay More Attention to Late Toxicities?

Dose optimization for cancer treatments with considerations for late-onset toxicities

Given that novel anticancer therapies have different toxicity profiles and mechanisms of action, it is important to reconsider the current approaches for dose selection. In an effort to move away from considering the maximum tolerated dose as the optimal dose, the Food and Drug Administration Project Optimus points to the need of incorporating long-term toxicity evaluation, given that many of these novel agents lead to late-onset or cumulative toxicities and there are no guidelines on how to handle them. Numerous methods have been proposed to handle late-onset toxicities in dose-finding clinical trials. A summary and comparison of these methods are provided. Moreover, using PI3K inhibitors as a case study, we show how late-onset toxicity can be integrated into the dose-optimization strategy using current available approaches. We illustrate a re-design of this trial to compare the approach to those that only consider early toxicity outcomes and disregard late-onset toxicities. We also provide proposals going forward for dose optimization in early development of novel anticancer agents with considerations for late-onset toxicities.

Handling Incomplete or Late-Onset Toxicities in Early-Phase Dose-Finding Clinical Trials: Current Practice and Future Prospects

PURPOSE

The way late-onset toxicities are managed can affect trial outcomes and participant safety. Specifically, participants often might not have completed their entire follow-up period to observe any toxicities before new participants would be recruited. We conducted a methodological review of published early-phase dose-finding clinical trials that used designs accounting for partial and complete toxicity information, aiming to understand (1) how such designs were implemented and reported and (2) if sufficient information was provided to enable the replicability of trial results.

METHODS

Until March 26, 2023, we identified 141 trials using the rolling 6 design, the time-to-event continuous reassessment method (TITE-CRM), the TITE-CRM with cycle information, the TITE Bayesian optimal interval design, the TITE cumulative cohort design, and the rapid enrollment design. Clinical settings, design parameters, practical considerations, and dose-limiting toxicity (DLT) information were extracted from these published trials.

RESULTS

The TITE-CRM (61, 43.3%) and the rolling 6 design (76, 53.9%) were most frequently implemented in practice. Trials using the TITE-CRM had longer DLT assessment windows beyond the first cycle compared with the rolling 6 design (52.5% v 6.6%). Most trials implementing the TITE-CRM (91.8%, 56 of 61) failed to describe essential parameters in the protocols or the study result papers. Only five TITE-CRM trials (8.2%, 5 of 61) reported sufficient information to enable replication of the final analysis.

CONCLUSION

When compared with trials using the rolling 6 design, those implementing the TITE-CRM design exhibited notable deficiencies in reporting essential details necessary for reproducibility. Inadequate reporting quality of advanced model-based trial designs hinders their credibility. We provide recommendations that can improve transparency, reproducibility, and accurate interpretation of the results for such designs.

Statistical methods and data visualisation of patient-reported outcomes in early phase dose-finding oncology trials: a methodological review

Background

Traditionally, within dose-finding clinical trials, treatment toxicity and tolerability are assessed by clinicians. Research has shown that clinician reporting may have inadequate inter-rater reliability, poor correlation with patient reported outcomes, and under capture the true toxicity burden. The introduction of patient-reported outcomes (PROs), where the patient can assess their own symptomatic adverse events or quality of life, has potential to complement current practice to aid dose optimisation. There are no international recommendations offering guidance for the inclusion of PROs in dose-finding trial design and analysis. Our review aimed to identify and describe current statistical methods and data visualisation techniques employed to analyse and visualise PRO data in published early phase dose-finding oncology trials (DFOTs).

Methods

DFOTs published from June 2016-December 2022, which presented PRO analysis methods, were included in this methodological review. We extracted 35 eligible papers indexed in PubMed. Study characteristics extracted included: PRO objectives, PRO measures, statistical analysis and visualisation techniques, and whether the PRO was involved in interim and final dose selection decisions.

Findings

Most papers (30, 85.7%) did not include clear PRO objectives. 20 (57.1%) papers used inferential statistical techniques to analyse PROs, including survival analysis and mixed-effect models. One trial used PROs to classify a clinicians' assessed dose-limiting toxicities (DLTs). Three (8.6%) trials used PROs to confirm the tolerability of the recommended dose. 25 trial reports visually presented PRO data within a figure or table within their publication, of which 12 papers presented PRO score longitudinally.

Interpretation

This review highlighted that the statistical methods and reporting of PRO analysis in DFOTs are often poorly described and inconsistent. Many trials had PRO objectives which were not clearly described, making it challenging to evaluate the appropriateness of the statistical techniques used. Drawing conclusions based on DFOTs which are not powered for PROs may be misleading. With no guidance and standardisation of analysis methods for PROs in early phase DFOTs, it is challenging to compare study findings across trials. Therefore, there is a crucial need to establish international guidance to enhance statistical methods and graphical presentation for PRO analysis in the dose-finding setting.

Funding

EA has been supported to undertake this work as part of a PhD studentship from the Institute of Cancer Research within the MRC/NIHR Trials Methodology Research Partnership. AM is supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at the Royal Marsden NHS Foundation Trust, the Institute of Cancer Research and Imperial College.

Assessment of Patient-Reported Outcomes in Industry-Sponsored Phase I Oncology Studies: Considerations for Translating Theory Into Practice

An increasing interest in the identification of optimal dosage for oncology therapies has prompted key opinion leaders and regulators to encourage the integration of patient-reported outcome (PRO) assessments in phase I oncology clinical trials. Although the potential benefits of assessing PROs in early-phase studies have been acknowledged, the difficulties that arise from such a radical shift have been largely overlooked in the public discussion. In this commentary, the authors provide insight into the challenges that industry sponsors face in integrating PRO assessments into phase I oncology trials, with the ultimate goal of facilitating conversations that may help to resolve some of these issues.

Time-to-event calibration-free odds design: A robust efficient design for phase I trials with late-onset outcomes

Compared with most of the existing phase I designs, the recently proposed calibration-free odds (CFO) design has been demonstrated to be robust, model-free, and easy to use in practice. However, the original CFO design cannot handle late-onset toxicities, which have been commonly encountered in phase I oncology dose-finding trials with targeted agents or immunotherapies. To account for late-onset outcomes, we extend the CFO design to its time-to-event (TITE) version, which inherits the calibration-free and model-free properties. One salient feature of CFO-type designs is to adopt game theory by competing three doses at a time, including the current dose and the two neighboring doses, while interval-based designs only use the data at the current dose and is thus less efficient. We conduct comprehensive numerical studies for the TITE-CFO design under both fixed and randomly generated scenarios. TITE-CFO shows robust and efficient performances compared with interval-based and model-based counterparts. As a conclusion, the TITE-CFO design provides robust, efficient, and easy-to-use alternatives for phase I trials when the toxicity outcome is late-onset.

Oncology phase I trial design and conduct: time for a change - MDICT Guidelines 2022

In 2021, the Food and Drug Administration Oncology Center of Excellence announced Project Optimus focusing on dose optimization for oncology drugs. The Methodology for the Development of Innovative Cancer Therapies (MDICT) Taskforce met to review and discuss the optimization of dosage for oncology trials and to develop a practical guide for oncology phase I trials. Defining a single recommended phase II dose based on toxicity may define doses that are neither the most effective nor the best tolerated. MDICT recommendations address the need for robust non-clinical data which are needed to inform trial design, as well as an expert team including statisticians and pharmacologists. The protocol must be flexible and adaptive, with clear definition of all endpoints. Health authorities should be consulted early and regularly. Strategies such as randomization, intrapatient dose escalation, and real-world eligibility criteria are encouraged whereas serial tumor sampling is discouraged in the absence of a strong rationale and appropriately validated assay. Endpoints should include consideration of all longitudinal toxicity. The phase I dose escalation trial should define the recommended dose range for later testing in randomized phase II trials, rather than a single recommended phase II dose, and consider scenarios where different populations may require different dosages. The adoption of these recommendations will improve dosage selection in early clinical trials of new anticancer treatments and ultimately, outcomes for patients.

Dose finding studies for therapies with late-onset toxicities: A comparison study of designs

An objective of phase I dose-finding trials is to find the maximum tolerated dose; the dose with a particular risk of toxicity. Frequently, this risk is assessed across the first cycle of therapy. However, in oncology, a course of treatment frequently consists of multiple cycles of therapy. In many cases, the overall risk of toxicity for a given treatment is not fully encapsulated by observations from the first cycle, and hence it is advantageous to include toxicity outcomes from later cycles in phase I trials. Extending the follow up period in a trial naturally extends the total length of the trial which is undesirable. We present a comparison of eight methods that incorporate late onset toxicities while not extensively extending the trial length. We conduct simulation studies over a number of scenarios and in two settings; the first setting with minimal stopping rules and the second setting with a full set of standard stopping rules expected in such a dose finding study. We find that the model-based approaches in general outperform the model-assisted approaches, with an interval censored approach and a modified version of the time-to-event continual reassessment method giving the most promising overall performance in terms of correct selections and trial length. Further recommendations are made for the implementation of such methods.

Surv-CRM-12: A Bayesian phase I/II survival CRM for right-censored toxicity endpoints with competing disease progression

The growing interest in new classes of anti-cancer agents, such as molecularly-targeted therapies and immunotherapies with modes of action different from those of cytotoxic chemotherapies, has changed the dose-finding paradigm. In this setting, the observation of late-onset toxicity endpoints may be precluded by treatment and trial discontinuation due to disease progression, defining a competing event to toxicity. Trial designs where dose-finding is modeled in the framework of a survival competing risks model appear particularly well-suited. We aim to provide a phase I/II dose-finding design that allows dose-limiting toxicity (DLT) outcomes to be delayed or unobserved due to competing progression within the possibly long observation window. The proposed design named the Survival-continual reassessment method-12, uses survival models for right-censored DLT and progression endpoints. In this competing risks framework, cause-specific hazards for DLT and progression-free of DLT were considered, with model parameters estimated using Bayesian inference. It aims to identify the optimal dose (OD), by minimizing the cumulative incidence of disease progression, given an acceptable toxicity threshold. In a simulation study, design operating characteristics were evaluated and compared to the TITE-BOIN-ET design and a nonparametric benchmark approach. The performance of the proposed method was consistent with the complexity of scenarios as assessed by the nonparametric benchmark. We found that the proposed design presents satisfying operating characteristics in selecting the OD and safety.

Implementation of telemedicine in cancer clinical trials: Connectpatienttodoctor study

Background

Telemedicine is currently being adopted for the management of patients in routine care. However, its use remains limited in the context of clinical trials.

Objective

This study aimed to demonstrate the feasibility of telemonitoring and patient-reported outcomes collection in the context of clinical trials.

Methods

The patients who were included in an interventional oncology clinical trial were eligible. The patients were registered with a digital tool to respond to a patient-reported outcomes questionnaire (ePRO) based on CTCAE (The Common Terminology Criteria for Adverse Events, National Cancer Institute), version 5.0, personalized to their pathology and treatment. An algorithm evaluated the health status of the patient based on the reported adverse events, with a classification in 4 different states (correct, compromise, state to be monitored, or critical state). The main objective was to evaluate the feasibility of remote monitoring via a connected platform of patients included in a clinical trial.

Results

From July 1, 2020, to March 31, 2021, 39 patients were included. The median age was 71 years (range 41-94); 74% (n=29) were male, and 59% (n=23) had metastatic disease. Out of the 969 ePRO questionnaires completed over the course of the study, 77.0% (n=746) were classified as “correct,” 10.9% (n=106) as “compromised,” and 12.1% (n=117) as “to be monitored” or “critical.” The median response time was 7 days (IQR 7-15.5), and 76% (25/33) of the patients were compliant. Out of the 35 patients who answered a satisfaction questionnaire, 95% (n=33) were satisfied or very satisfied with the tool, and 85% (n=30) were satisfied with their relationship with the health care team. There were 5 unscheduled hospitalizations during the study period.

Conclusions

Remote monitoring in clinical trials is feasible, with a high level of patient participation and satisfaction. It benefits patients, but it also ensures the high quality of the trial through the early management of adverse events and better knowledge of the tolerance profile of experimental treatments. This e-technology will likely be deployed more widely in our clinical trials.

TITE-gBOIN: Time-to-event Bayesian optimal interval design to accelerate dose-finding accounting for toxicity grades

The new therapeutic agents, such as molecular targeted agents and immuno-oncology therapies, appear more likely to induce multiple toxicities at different grades than dose-limiting toxicities defined in traditional dose-finding trials. In addition, it is often challenging to make adaptive decisions on dose escalation and de-escalation on time because of the fast accrual rate and/or the late-onset toxicity outcomes, causing the potential suspension of the enrollment and the delay of the trials. To address these issues, we propose a time-to-event Bayesian optimal interval design to accelerate the dose-finding process utilizing toxicity grades based on both cumulative and pending toxicity outcomes. The proposed design, named "TITE-gBOIN" design, is a nonparametric and model-assisted design and has the virtues of robustness, simplicity and straightforward to implement in actual oncology dose-finding trials. A simulation study shows that the TITE-gBOIN design has a higher probability of selecting the MTDs correctly and allocating more patients to the MTDs across various realistic settings while reducing the trial duration significantly, therefore can accelerate early-stage dose-finding trials.

BOIN: a novel Bayesian design platform to accelerate early phase brain tumor clinical trials

Despite decades of extensive research, the progress in developing effective treatments for primary brain tumors lags behind that of other cancers, largely due to the unique challenges of brain tumors (eg, the blood-brain barrier and high heterogeneity) that limit the delivery and efficacy of many therapeutic agents. One way to address this issue is to employ novel trial designs to better optimize the treatment regimen (eg, dose and schedule) in early phase trials to improve the success rate of subsequent phase III trials. The objective of this article is to introduce Bayesian optimal interval (BOIN) designs as a novel platform to design various types of early phase brain tumor trials, including single-agent and combination regimen trials, trials with late-onset toxicities, and trials aiming to find the optimal biological dose (OBD) based on both toxicity and efficacy. Unlike many novel Bayesian adaptive designs, which are difficult to understand and complicated to implement by clinical investigators, the BOIN designs are self-explanatory and user friendly, yet yield more robust and powerful operating characteristics than conventional designs. We illustrate the BOIN designs using a phase I clinical trial of brain tumor and provide software (freely available at www.trialdesign.org) to facilitate the application of the BOIN design.

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.

Seamless phase I/II design for novel anticancer agents with competing disease progression

Molecularly targeted agents and immunotherapies have prolonged administration and complicated toxicity and efficacy profiles requiring longer toxicity observation windows and the inclusion of efficacy information to identify the optimal dose. Methods have been proposed to either jointly model toxicity and efficacy, or for prolonged observation windows. However, it is inappropriate to address these issues individually in the setting of dose-finding because longer toxicity windows increase the risk of patients experiencing disease progression and discontinuing the trial, with progression defining a competing event to toxicity, and progression-free survival being a commonly used efficacy endpoint. No method has been proposed to address this issue in a competing risk framework. We propose a seamless phase I/II design, namely the competing risks continual reassessment method (CR-CRM). Given an observation window, the objective is to recommend doses that minimize the progression probability, among a set of tolerable doses in terms of toxicity risk. In toxicity-centered stage of the design, doses are assigned based on toxicity alone, and in optimization stage of the design, doses are assigned integrating both toxicity and progression information. Design operating characteristics were examined in a simulation study compared with benchmark performances, including sensitivity to time-varying hazards and correlated events. The method performs well in selecting doses with acceptable toxicity risk and minimum progression risk across a wide range of scenarios.

A simulation study of approaches for handling disease progression in dose-finding clinical trials

In traditional dose-finding studies, dose-limiting toxicity (DLT) is determined within a fixed time observation window where DLT is often defined as a binary outcome. In the setting of oncology dose-finding trials, often patients in advanced stage of diseases are enrolled. Therefore, disease progression may occur within the DLT observation window leading to treatment discontinuation and rendering the patient unevaluable for DLT assessment. As a result, additional patients have to be enrolled, increasing the sample size. We propose and compare several practical approaches for handling disease progression which occurs within the DLT observation window, while in the framework of the time-to-event continual reassessment method (TITE-CRM) which allows using partial observations. The approaches differ on the way they define an evaluable patient and in the way incomplete observations are included. The practical approaches, which we call strategies A, B and C, are illustrated and contrasted in the context of a single simulated trial, and compared via simulations under various scenarios of dose-progression relationship, in the setting of advanced soft-tissue sarcoma.

Time-to-event model-assisted designs for dose-finding trials with delayed toxicity

Two useful strategies to speed up drug development are to increase the patient accrual rate and use novel adaptive designs. Unfortunately, these two strategies often conflict when the evaluation of the outcome cannot keep pace with the patient accrual rate and thus the interim data cannot be observed in time to make adaptive decisions. A similar logistic difficulty arises when the outcome is late-onset. Based on a novel formulation and approximation of the likelihood of the observed data, we propose a general methodology for model-assisted designs to handle toxicity data that are pending due to fast accrual or late-onset toxicity and facilitate seamless decision making in phase I dose-finding trials. The proposed time-to-event model-assisted designs consider each dose separately and the dose-escalation/de-escalation rules can be tabulated before the trial begins, which greatly simplifies trial conduct in practice compared to that under existing methods. We show that the proposed designs have desirable finite and large-sample properties and yield performance that is comparable to that of more complicated model-based designs. We provide user-friendly software for implementing the designs.

Fractional design: An alternative paradigm for late-onset toxicities in oncology dose-finding studies

Late-onset (LO) toxicities often arise in the new era of phase I oncology dose-finding trials with targeted agents or immunotherapies. The current LO toxicities modelling is often formulated in a weighted likelihood framework, where the time-to-event continual reassessment method (TITE-CRM) is commonly used. The TITE-CRM uses the patient exposure time as a weight for the censored observation, while there is large uncertainty on which weight function to be used. As an alternative, the fractional scheme formulates an efficient and robust paradigm to address LO toxicity issues in dose finding. We review the fractional continual reassessment method (fCRM) and compare its operating characteristics with those of the TITE-CRM as well as other competitive designs via extensive simulation studies based on both the fixed and randomly generated scenarios. The fCRM is shown to possess desirable operating characteristics in identifying the maximum tolerated dose (MTD) and deliver competitive performances in comparison with other designs. It provides an alternative efficient and robust paradigm for interpreting and addressing LO toxicities in the new era of phase I dose-finding trials in precision oncology. A real trial example is used to illustrate the practical use of the fCRM design.

A Review of the Mechanisms and Clinical Implications of Precision Cancer Therapy-Related Toxicity: A Primer for the Radiologist

OBJECTIVE. The purpose of this review is to elucidate the mechanisms, types, and clinical significance of molecular targeted therapy (MTT) and immune checkpoint inhibitors (ICIs) and their related toxicity, emphasizing the radiologic manifestations. CONCLUSION. The related toxicities of MTT and ICIs can have acute, recurrent, chronic, and delayed presentations. These toxicities may serve as markers of response and survival. By understanding the clinical significance of drug toxicities, radiologists can play an important role in personalized cancer therapy.

Cumulative Toxicity in Targeted Therapies: What to Expect at the Recommended Phase II Dose

BACKGROUND

In the era of molecularly targeted agents (MTAs), it is recommended to account for toxicity over several cycles to identify the recommended phase II dose (RP2D). We investigated the relationship between the risk of toxicity at cycle 1 and the cumulative incidence of toxicity over subsequent cycles in trials of single MTAs.

METHODS

On individual patient data from 26 phase I clinical trials of single MTAs provided by the National Cancer Institute, we estimated the probability of first-severe toxicity per treatment cycle as well as the cumulative incidence at, below, and above the maximum tolerated dose (MTD). Toxicity was further subclassified into nonhematologic and hematologic. A prediction table was developed to estimate the cumulative incidence up to six cycles based on the toxicity rate observed in the first cycle.

RESULTS

Overall, 942 patients were included. For patients treated at the MTD, the probability of first-severe toxicity decreased from 24.8% (95% prediction interval [PI] = 20.3% to 32.9%) to 2.2% (95% PI = 0.1% to 7.7%) from cycle 1 to 6, whereas the cumulative incidence of toxicity reached 51.7% (95% PI = 40.5% to 66.3%) after six cycles. Toxicity rates ranging from 20.0% to 30.0% in the first cycle were associated with 46.8% (95% PI = 39.5% to 54.2%) and 65.8% (95% PI = 57.7% to 73.1%) cumulative incidence after six cycles.

CONCLUSION

This study examined the risk of severe toxicity over time of single MTAs. The cumulative incidence of toxicity at the MTD was higher than the usually accepted toxicity targets, challenging the definition of the RP2D of MTAs. The prediction table may help calibrate the target rate at the RP2D.

Design and Conduct of Early Clinical Studies of Immunotherapy: Recommendations from the Task Force on Methodology for the Development of Innovative Cancer Therapies 2019 (MDICT)

PURPOSE

To review key aspects of the design and conduct of early clinical trials (ECT) of immunotherapy agents.

EXPERIMENTAL DESIGN

The Methodology for the Development of Innovative Cancer Therapies Task Force 2019 included experts from academia, nonprofit organizations, industry, and regulatory agencies. The review focus was on methodology for ECTs testing immune-oncology therapies (IO) used in combination with other IO or chemotherapy.

RESULTS

Although early successes have been seen, the landscape continues to be very dynamic, and there are ongoing concerns regarding the capacity to test all new drugs and combinations in clinical trials.

CONCLUSIONS

Optimization of drug development methodology is required, taking into account early, late, and lower grade intolerable toxicities, novel response patterns, as well as pharmacodynamic data.

Methodological Development of Combination Drug and Radiotherapy in Basic and Clinical Research

Newer technical improvements in radiation oncology have been rapidly implemented in recent decades, allowing an improved therapeutic ratio. The development of strategies using local and systemic treatments concurrently, mainly targeted therapies, has however plateaued. Targeted molecular compounds and immunotherapy are increasingly being incorporated as the new standard of care for a wide array of cancers. A better understanding of possible prior methodology issues is therefore required and should be integrated into upcoming early clinical trials including individualized radiotherapy-drug combinations. The outcome of clinical trials is influenced by the validity of the preclinical proofs of concept, the impact on normal tissue, the robustness of biomarkers and the quality of the delivery of radiation. Herein, key methodological aspects are discussed with the aim of optimizing the design and implementation of future precision drug-radiotherapy trials.

Proportional odds assumption for modeling longitudinal ordinal multiple toxicity outcomes in dose finding studies of targeted agents: A pooled analysis of 54 studies

BACKGROUND

Data generated by phase I trials is richer than the classical binary DLT measured at the first cycle used as primary endpoints. Several works developed designs for more informative endpoints, e.g. ordinal toxicity grades and/or longitudinal data which relied however on strong assumptions, in particular the proportional odds (PO) assumption.

METHODS

We evaluated this PO assumption for the dose and cycle on a large database of individual patient data from 54 phase I clinical trials of molecularly targeted agents. The PO model is a specific case of the continuation ratio logit model (CRLM) with null parameters. We compared the PO and CRLM models using the widely applicable information criterion (WAIC). We considered a longitudinal multivariate ordinal toxicity outcome (cutaneous, digestive, hematological, general disorders, and other toxicities).

RESULTS

WAIC suggested that the CRLM model (WAIC = 30911.58) outperformed the PO model (WAIC = 31432.10). Deviance from PO assumption for dose was observed for digestive and general disorder toxicities. There was moderate cycle effect with slight deviance from PO assumption for the other type of toxicity.

CONCLUSIONS

Designs based on PO for dose should be a useful tool for drug with low expected digestive or general disorder toxicity dose-related incidence.

TITE-BOIN-ET: Time-to-event Bayesian optimal interval design to accelerate dose-finding based on both efficacy and toxicity outcomes

One of the primary purposes of an oncology dose-finding trial is to identify an optimal dose (OD) that is both tolerable and has an indication of therapeutic benefit for subjects in subsequent clinical trials. In addition, it is quite important to accelerate early stage trials to shorten the entire period of drug development. However, it is often challenging to make adaptive decisions of dose escalation and de-escalation in a timely manner because of the fast accrual rate, the difference of outcome evaluation periods for efficacy and toxicity and the late-onset outcomes. To solve these issues, we propose the time-to-event Bayesian optimal interval design to accelerate dose-finding based on cumulative and pending data of both efficacy and toxicity. The new design, named "TITE-BOIN-ET" design, is nonparametric and a model-assisted design. Thus, it is robust, much simpler, and easier to implement in actual oncology dose-finding trials compared with the model-based approaches. These characteristics are quite useful from a practical point of view. A simulation study shows that the TITE-BOIN-ET design has advantages compared with the model-based approaches in both the percentage of correct OD selection and the average number of patients allocated to the ODs across a variety of realistic settings. In addition, the TITE-BOIN-ET design significantly shortens the trial duration compared with the designs without sequential enrollment and therefore has the potential to accelerate early stage dose-finding trials.

Pragmatic dose-escalation methods incorporating relative dose intensity assessment for molecularly targeted agents in phase I trials

The recommended phase 2 doses of molecularly targeted agents, determined by using an ordinal dose-finding method that only uses toxicity data at first cycle, may not be optimal. Some researchers have proposed the use of relative dose intensity that can account for late-onset, cumulative, and low-grade toxicities to determine the recommended phase 2 dose (RP2D). In this study, we proposed two dose escalation methods based on the observed relative dose intensities (RDIs) between the pre-specified intervals (cycles) for toxicity evaluation used in combination with DLT evaluation in the first cycle. First, we propose the modified 3 + 3 design that incorporates longitudinal RDI assessment. Second, we propose the sequential assessment method for longitudinal RDI (SARDI) to achieve faster dose escalation compared to that of the modified 3 + 3 design. Simulation studies demonstrated that the SARDI was, in many cases, superior to the ordinal and modified 3 + 3 designs in respect to the selection rate of true RP2D and study period. The two proposed methods could also in some cases decrease the average number of patients enrolled in the trial compared to that of the ordinary 3 + 3 design. Incorporation of the RDI assessment into the 3 + 3 design is not difficult and does not require the use of complex statistical techniques. Therefore, we believe that investigators who routinely use the 3 + 3 design in practice can easily use our proposed methods.

Improved survival among patients enrolled in oncology phase 1 trials in recent decades

PURPOSE

This study aimed to compare the survival of patients enrolled in phase 1 trials in recent decades.

METHODS

The medical records of consecutive patients with advanced cancer who participated in single-agent oncology phase 1 trials from 1995 to 2015 at a single institution were retrospectively investigated.

RESULTS

A total of 267 (34.1%) patients participated in 1995-2004 and 516 (65.9%) participated in 2005-2015. The median follow-up period was 25.4 months (range 1.3-166.9). The response rate did not differ significantly between the two periods (3.9% vs. 6.2%, p = 0.17). The median survival times were 9.5 (95% confidence interval 8.4-11.2) months in 1995-2004 and 11.8 (95% confidence interval 10.9-13.3) months in 2005-2015 (p = 0.0009). The enrolment period was an independent prognostic factor of overall survival according to multivariate analysis (hazard ratio: 0.85, 95% confidence interval 0.72-0.99, p = 0.042).

CONCLUSIONS

In our single-centre, retrospective analysis, the trends in patients characteristic were consistent with those of Western countries, and the overall survival of cancer patients enrolled in oncology phase 1 trials tended to improve in recent decades, suggesting that patient selection, the population that benefits from investigational agents and treatment after phase 1 trials have improved.

Model-Assisted Designs for Early-Phase Clinical Trials: Simplicity Meets Superiority

Drug development enterprise is struggling because of prohibitively high costs and slow progress. There is urgent need for adoption of novel adaptive designs to improve the efficiency and success of clinical trials. A major barrier is that many conventional designs are inadequate for modern drug development, yet most novel adaptive designs are difficult to understand, require complicated statistical modeling, demand complex computation, and need expensive infrastructure for implementation. The objective of this article is to introduce and review a class of novel adaptive designs, known as model-assisted designs, to remove this barrier and increase the use of novel adaptive designs. Model-assisted designs enjoy superior performance comparable to more complicated, model-based adaptive designs, but their decision rule can be pretabulated and included in the protocol-thus implemented as simply as the conventional designs. We review state-of-the-art model-assisted designs for phase I clinical trials for single-agent, drug-combination and late-onset toxicity scenarios. We also briefly introduce model-assisted designs for phase II trials to handle binary, coprimary endpoints and delayed response. Freely available user-friendly software and trial examples (trialdesign.org) facilitate the adoption of model-assisted designs.

Combining epigenetic drugs with other therapies for solid tumours - past lessons and future promise

Epigenetic dysregulation has long been recognized as a key factor contributing to tumorigenesis and tumour maintenance that can influence all of the recognized hallmarks of cancer. Despite regulatory approvals for the treatment of certain haematological malignancies, the efficacy of the first generation of epigenetic drugs (epi-drugs) in patients with solid tumours has been disappointing; however, successes have now been achieved in selected solid tumour subtypes, thanks to the development of novel compounds and a better understanding of cancer biology that have enabled precision medicine approaches. Several lines of evidence support that, beyond their potential as monotherapies, epigenetic drugs could have important roles in synergy with other anticancer therapies or in reversing acquired therapy resistance. Herein, we review the mechanisms by which epi-drugs can modulate the sensitivity of cancer cells to other forms of anticancer therapy, including chemotherapy, radiation therapy, hormone therapy, molecularly targeted therapy and immunotherapy. We provide a critical appraisal of the preclinical rationale, completed clinical studies and ongoing clinical trials relating to combination therapies incorporating epi-drugs. Finally, we propose and discuss rational clinical trial designs and drug development strategies, considering key factors including patient selection, tumour biomarker evaluation, drug scheduling and response assessment and study end points, with the aim of optimizing the development of such combinations.

Identification of high-risk drugs related to chemotherapy-induced peripheral neuropathy in Cancer Therapy Evaluation Program-sponsored phase I trials

BACKGROUND

Chemotherapy-induced peripheral neuropathy (CIPN) is a significant and debilitating side effect. However, there have been no studies of the relative risk of CIPN with known causative agents. We examined the risk of CIPN in patients taking such agents as a part of the National Cancer Institute (NCI) Cancer Therapy Evaluation Program-sponsored phase I trials.

METHODS

CIPN events in each patient were graded according to the Clinical Terminology of Common Adverse Effects and compared among several high-risk chemotherapeutic agent groups, adjusting for possible confounding factors. Patients receiving tubulin-targeted agents were analysed separately for specific background factors associated with CIPN.

RESULTS

In 135 phase I clinical trials, 259 of 3614 patients were identified as developing CIPN during chemotherapy. Tubulin-targeting agents and proteasome inhibitors were identified as high-risk agents (hazard ratio 9.04 and 5.01, respectively) for CIPN, whereas platinum-complex agents and thalidomide analogues imparted lower risk (hazard ratio 1.52 and 1.11, respectively). Age, sex and medical history of diabetes were not significantly related to CIPN. CIPN developed over time as the number of chemotherapy cycles increased. Among patients with CIPN, treatment with tubulin-targeting agents resulted in a significantly higher rate of chemotherapy schedule modification compared with treatments with other chemotherapeutic agents.

CONCLUSIONS

Tubulin-targeting agents and proteasome inhibitors were associated with a greatly increased risk of CIPN compared with other agents. CIPN tended to develop in later chemotherapy cycles. These findings will help to minimise the risk of CIPN by encouraging increased surveillance and earlier dose adjustment of high-risk agents in phase I trials.

Health-related quality of life as an endpoint in oncology phase I trials: a systematic review

Background

Phase I trials aim to identify the recommended dose for further development. Health-related quality of life (HRQoL) could be a complement to the usual National Cancer Institute Common Terminology Criteria for Adverse Events (NCI-CTCAE) scale to detect adverse events and define the doses. The objective of this study is to review the phase I in oncology which used HRQoL as endpoint.

Methods

A search in PubMed database identified phase I trials in oncology with HRQoL as endpoint, published between January 2012 to May 2016. Hematological and pediatric phase I were excluded.

Results

A total of 1333 phase I were identified and 15 trials were identified with HRQoL as endpoint (1.1%). The European Organisation for Treatment of Cancer Quality of Life Questionnaire C30 (EORTC QLQ-C30) was the most frequently used instrument: 5 studies (33.3%). The targeted dimensions of HRQoL and the minimal clinically important difference were prespecified in 1 study (6.7%) and 2 studies (13.3%), respectively. Twelve studies (80%) described the statistical approach to analyze HRQoL data. Eight studies used the mean change from baseline (60%) to analyse longitudinal HRQoL data, two the mean score at certain times (13.3%), one the linear mixed model for repeated measures (6.7%), one the time to HRQoL score deterioration (6.7%), one percentage of patient-reported symptoms (6.7%). None of the studies used HRQoL to determine the recommended doses.

Conclusion

Few phase I studies used HRQoL as endpoint and among studies with HRQoL as endpoint, the methodology of HRQoL measurement and statistical analysis was heterogeneous. HRQoL.

endpoint not used for assessing the recommended phase II doses.

An adaptive design for the identification of the optimal dose using joint modeling of continuous repeated biomarker measurements and time-to-toxicity in phase I/II clinical trials in oncology

We present a new adaptive dose-finding method, based on a joint modeling of longitudinal continuous biomarker activity measurements and time to first dose limiting toxicity, with a shared random effect. Estimation relies on likelihood that does not require approximation, an important property in the context of small sample sizes, typical of phase I/II trials. We address the important case of missing at random data that stem from unacceptable toxicity, lack of activity and rapid deterioration of phase I patients. The objective is to determine the lowest dose within a range of highly active doses, under the constraint of not exceeding the maximum tolerated dose. The maximum tolerated dose is associated to some cumulative risk of dose limiting toxicity over a predefined number of treatment cycles. Operating characteristics are explored via simulations in various scenarios.

An information theoretic phase I-II design for molecularly targeted agents that does not require an assumption of monotonicity

For many years phase I and phase II clinical trials have been conducted separately, but there has been a recent shift to combine these phases. Although a variety of phase I-II model-based designs for cytotoxic agents have been proposed in the literature, methods for molecularly targeted agents (TAs) are just starting to develop. The main challenge of the TA setting is the unknown dose-efficacy relationship that can have either an increasing, plateau or umbrella shape. To capture these, approaches with more parameters are needed or, alternatively, more orderings are required to account for the uncertainty in the dose-efficacy relationship. As a result, designs for more complex clinical trials, e.g. trials looking at schedules of a combination treatment involving TAs, have not been extensively studied yet. We propose a novel regimen finding design which is based on a derived efficacy-toxicity trade-off function. Because of its special properties, an accurate regimen selection can be achieved without any parametric or monotonicity assumptions. We illustrate how this design can be applied in the context of a complex combination-schedule clinical trial. We discuss practical and ethical issues such as coherence, delayed and missing efficacy responses, safety and futility constraints.

Delayed adverse events in phase I trials of molecularly targeted and cytotoxic agents

BACKGROUND

Grade 3 and 4 adverse events (AEs) during cycle 1 are traditionally used for dose escalation decisions in Phase I oncology trials. With molecularly targeted agents (MTAs), assessment of lower grade AEs and those in later cycles is considered increasingly relevant.

METHODS

We conducted a retrospective analysis of AEs in patients enrolled onto relevant phase I trials of MTAs and cytotoxic combinations (CCs) at our UK centre between 2006 and 2016. All AEs in the first six cycles deemed at least 'possibly related' were recorded.

RESULTS

A total of 912 AEs were identified in 127 patients across 15 trials. Mean AE totals for CCs or MTAs respectively was 4.7 versus 3.0 in cycle 1, 3.8 versus 2.8 in cycles 2-6. Patients on CCs had higher mean AEs in six cycles compared to those on MTAs (8.5 vs. 5.7, p = 0.0005). For patients experiencing grade 3 AEs, 58% (CCs) and 60% (MTAs) occurred for the first time after cycle 1.

CONCLUSION

Overall AE incidence was lower in MTAs than CCs across six cycles. For MTAs, more frequent incidence of first grade 3/4 AEs after cycle 1 supports incorporation of delayed AEs into recommendations for Phase 2 dosing.

The Current Understanding of the Endocrine Effects From Immune Checkpoint Inhibitors and Recommendations for Management

Clinical trials in the past decade have established the antitumor effects of immune checkpoint inhibition as a revolutionary treatment for cancer. Namely, blocking antibodies to cytotoxic T-lymphocyte antigen 4 and programmed death 1 or its ligand have reached routine clinical use. Manipulation of the immune system is not without side effects, and autoimmune toxicities often known as immune-related adverse events (IRAEs) are observed. Endocrine IRAEs, such as hypophysitis, thyroid dysfunction, and insulin-dependent diabetes mellitus, can present with unique profiles that are not seen with the use of traditional chemotherapeutics. In this Review, we discuss the current hypotheses regarding the mechanism of these endocrinopathies and their clinical presentations. Further, we suggest guidelines and algorithms for patient management and future clinical trials to optimize the detection and treatment of immune checkpoint–related endocrinopathies.

Report of the 14th International Conference on Malignant Lymphoma (ICML) Closed Workshop on Future Design of Clinical Trials in Lymphomas

The 14th ICML held in Lugano in June 2017 was preceded by a closed workshop (organized in collaboration with the American Association for Cancer Research and the European School of Oncology) where experts in preclinical and clinical research in lymphomas met to discuss the current drug development landscape focusing on critical open questions that need to be addressed in the future to permit a more efficient drug development paradigm in lymphoma. Topics discussed included both preclinical models that can be used to test new drugs and drug combinations, as well as the optimal design of clinical trials and the endpoints that should be used to facilitate accelerated progress. This report represents a summary of the workshop. Clin Cancer Res; 24(13); 2993-8. ©2018 AACR.

Time-to-Event Bayesian Optimal Interval Design to Accelerate Phase I Trials

Late-onset toxicity is common for novel molecularly targeted agents and immunotherapy. It causes major logistic difficulty for existing adaptive phase I trial designs, which require the observance of toxicity early enough to apply dose-escalation rules for new patients. The same logistic difficulty arises when the accrual is rapid. We propose the time-to-event Bayesian optimal interval (TITE-BOIN) design to accelerate phase I trials by allowing for real-time dose assignment decisions for new patients while some enrolled patients' toxicity data are still pending. Similar to the rolling six design, the TITE-BOIN dose-escalation/deescalation rule can be tabulated before the trial begins, making it transparent and simple to implement, but is more flexible in choosing the target dose-limiting toxicity (DLT) rate and has higher accuracy to identify the MTD. Compared with the more complicated model-based time-to-event continuous reassessment method (TITE-CRM), the TITE-BOIN has comparable accuracy to identify the MTD but is simpler to implement with substantially better overdose control. As the TITE-CRM is more aggressive in dose escalation, it is less likely to underdose patients. When there are no pending data, the TITE-BOIN seamlessly reduces to the BOIN design. Numerical studies show that the TITE-BOIN design supports continuous accrual without sacrificing patient safety or the accuracy of identifying the MTD, and therefore has great potential to accelerate early-phase drug development. Clin Cancer Res; 24(20); 4921-30. ©2018 AACR.

A Phase I Study of Irinotecan, Capecitabine (Xeloda), and Oxaliplatin in Patients With Advanced Colorectal Cancer

BACKGROUND

The objective of the present phase I study was to define the dose-limiting toxicities (DLTs) and maximum tolerated dose (MTD) of irinotecan, capecitabine, and oxaliplatin given in combination (IXO regimen) to patients with previously untreated, unresectable advanced or metastatic colorectal cancer (CRC).

PATIENTS AND METHODS

Patients received oxaliplatin followed by irinotecan as intravenous infusions on day 1, with oral capecitabine taken twice daily (BID) on days 2 to 15 of a 3-week cycle. The dose ranges were explored as follows: oxaliplatin, 75 to 120 mg/m²; irinotecan, 160 to 230 mg/m²; capecitabine, 750 to 1000 mg/m² BID. Dose escalation was performed individually for each drug at each dose level according to the type and severity of toxicity encountered in the previous cohort.

RESULTS

A total of 39 patients were enrolled at 7 dose levels and the MTD. The recommended doses for phase II evaluation were oxaliplatin 100 mg/m², irinotecan 160 mg/m², and capecitabine 950 mg/m² BID. Diarrhea and febrile neutropenia were DLTs. Of the 39 enrolled patients, 26 (67%) had confirmed objective responses. The median progression-free survival was 11 months, and the median overall survival was 25 months. The survival rate at 5 years was 23%.

CONCLUSION

The IXO regimen has a manageable toxicity profile with promising antitumor activity as first-line treatment of advanced and metastatic CRC.

Potential utility of a longitudinal relative dose intensity of molecularly targeted agents in phase 1 dose-finding trials

Phase 1 trials of molecularly targeted agents (MTA) often do not use toxicity data beyond the first cycle of treatment to determine a recommended phase 2 dose (RP2D). We investigated the potential utility of longitudinal relative dose intensity (RDI) that may be a better new way of determining a more accurate RP2D as a lower dose that is presumably more tolerable over the long term without compromising efficacy. All consecutive patients who were initially treated using a single MTA at the conventional RP2D or at one level lower dose (OLLD) of that RP2D in 9 phase 1 trials sponsored by the National Cancer Institute were included. The associations between longitudinal RDI, time to first progression, and response rate were analyzed. The RDI of the conventional RP2D group were maintained a rate of ≥70% throughout 10 cycles, and were higher than those of the OLLD group, although in both groups the RDI gradually decreased with additional treatment cycles. The RP2D group was similar to the OLLD group with respect to time to first progression and response rate. In both groups, however, the decreasing RDI over time was significantly associated with shorter time to first disease progression; therefore, the longitudinal RDI, which takes into account lower grade toxicity occurrences, may be useful in determining a more desirable dose to use in phase 2 and 3 studies.

Estimating global treatment toxicity burden from adverse-event data

BACKGROUND

A summary measure that reflects the global toxicity burden of a treatment is essential for comparing therapies. Current toxicity summaries are ad hoc and do not distinguish among the severities and types of toxicities. Here a clinically feasible method for estimating the toxicity burden, based on a prospective evaluation of the toxicity profile of a randomized clinical trial of 746 prostate cancer patients conducted by SWOG, is proposed.

METHODS

For 308 patients who experienced severe toxicities, 2 physicians randomly selected from 14 physicians evaluated each toxicity profile and assigned a visual analogue scale score (0-10) based on their impression of the global burden of toxicities. With mixed-effects models, severity scores and a 10-point toxicity burden score (TBS) were derived from 27 predictors accounting for severe (grade 3) and life-threatening (grade 4) toxicities for each organ class of the Common Terminology Criteria for Adverse Events.

RESULTS

For most organ classes, grade 3 toxicities had a TBS of 4.14 (95% confidence interval [CI], 3.65-4.63), but infections, cardiovascular events, and pulmonary events had a higher TBS with differences of 0.87 (95% CI, 0.53-1.21), 0.88 (95% CI, 0.51-1.25), and 0.73 (95% CI, 0.22-1.24), respectively. Moreover, most grade 4 events had a higher TBS than grade 3 events, except for hemorrhaging, pain, metabolic events, and musculoskeletal events. The intrarater and interrater correlations were 0.91 and 0.59, respectively.

CONCLUSIONS

The burden of toxicity grades differs with toxicity types. A TBS provides a toxicity burden summary that incorporates physicians' perspectives and differentiates between severe and life-threatening toxicities and organ classes. Cancer 2018;124:858-64. © 2017 American Cancer Society.

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.

Revisiting the definition of dose-limiting toxicities in paediatric oncology phase I clinical trials: An analysis from the Innovative Therapies for Children with Cancer Consortium

BACKGROUND

Dose-escalation trials aim to identify the maximum tolerated dose and, importantly, the recommended phase II dose (RP2D) and rely on the occurrence of dose-limiting toxicities (DLTs) during the first treatment cycle. Molecularly targeted agents (MTAs) often follow continuous and prolonged administrations, displaying a distinct toxicity profile compared to conventional chemotherapeutics, and classical DLT criteria might not be appropriate to evaluate MTAs' toxicity. We investigated this issue in children.

METHODS

The Innovative Therapies for Children with Cancer Consortium (ITCC) phase I trials of novel anticancer agents between 2004 and 2015 were analysed. Data from investigational product, trial design, items defining DLT/RP2D were extracted. A survey on dose-escalation process, DLTs and RP2D definition was conducted among the ITCC clinical trials committee members.

RESULTS

Thirteen phase I trials with 15 dose-escalation cohorts were analysed. They explored 11 MTAs and 2 novel cytotoxics; 12 evaluated DLT during cycle 1. Definition of DLT was heterogeneous: Grade III-IV haematologic toxicities that were transient or asymptomatic and grade III-IV non-haematological toxicities manageable with adequate supportive care were often excluded, whereas some included dose intensity or grade II toxicities into DLT. None of the studies considered delayed toxicity into the RP2D definition.

CONCLUSION

DLTs should be homogeneously defined across trials, limiting the number of exceptions due to specific toxicities. Dose escalation should still be based on safety data from cycle 1, but delayed and overall toxicities, pharmacokinetic parameters and pharmacodynamic data should be considered to refine the final RP2D. The evaluation of long-term toxicity in the developing child cannot be adequately addressed in early trials.

Repeated measures dose-finding design with time-trend detection in the presence of correlated toxicity data

BACKGROUND

Phase I trials are designed to determine the safety, tolerability, and recommended phase 2 dose of therapeutic agents for subsequent testing. The dose-finding paradigm has thus traditionally focused on identifying the maximum tolerable dose of an agent or combination therapy under the assumption that there is a non-decreasing relationship between dose-toxicity and dose-efficacy. The dose is typically determined based on the probability of severe toxicity observed during the first treatment cycle. A novel endpoint, the total toxicity profile, was previously developed to account for the multiple toxicity types and grades experienced in the first cycle. More recently, this was extended to a repeated measures design based on the total toxicity profile to account for longitudinal toxicities over multiple treatment cycles in the absence of within-patient correlation.

METHODS

In this work, we propose to extend the design in the presence of within-patient correlation. Furthermore, we provide a framework to detect a toxicity time trend (toxicity increasing, decreasing, or stable) over multiple treatment cycles. We utilize a linear mixed model in the Bayesian framework, with the addition of Bayesian risk functions for decision-making in dose assignment.

RESULTS

The performance of this design was evaluated using simulation studies and real data from a phase I trial. We demonstrated that using available toxicity data from all cycles of treatment improves the accuracy of maximum tolerated dose identification and allows for the detection of a time trend. The performance is consistent regardless of the strength of the within-patient correlation. In addition, the use of a quasi-continuous total toxicity profile score significantly increased the power to detect time trends compared to when binary data only were used.

CONCLUSION

The increased interest in molecularly targeted agents and immunotherapies in oncology necessitates innovative phase I study designs. Our proposed framework provides a tool to tackle some of the challenges presented by these novel agents, specifically through the ability to understand patterns of toxicity over time, which is important in the cases of cumulative or late toxicities.

Imatinib-induced ophthalmological side-effects in GIST patients are associated with the variations of EGFR, SLC22A1, SLC22A5 and ABCB1

Imatinib-induced ophthalmological side-effects, including conjunctiva hemorrhage and periorbital oedema, although very common and still remain relatively little understood. The present study investigated the effects of genetic polymorphisms of drug targets and membrane transporters on these side effects. We found that the minor allele of EGFR rs10258429 and SLC22A1 rs683369 were significant risk determinants of conjunctival hemorrhage with OR of 7.061 (95%CI=1.791-27.837, P=0.005 for EGFR rs10258429 CT+TT vs CC), and 4.809 (95%CI=1.267-18.431, P=0.021 for SLC22A1 rs683369 GG+CG vs CC). The minor allele of SLC22A5 rs274558 and ABCB1 rs2235040 were protective factors to periorbital oedema with OR of 0.313 (95%CI=0.149-0.656, P=0.002 for SLC22A5 rs274558 AA+AG vs GG), and 0.253 (95%CI=0.079-0.805, P=0.020 for ABCB1 rs2235040 CT vs CC). These results indicated that variants in EGFR, SLC22A1, SLC22A5 and ABCB1 influenced the incidence of Imatinib-induced ophthalmological toxicities, and polymorphism analyses in associated genes might be beneficial to optimize Imatinib treatment.

Do all patients in the phase I oncology trials need to be hospitalized? Domestic but outstanding issues for globalization of drug development in Japan

INTRODUCTION

Most trials investigating new drugs around the world, including phase I trials, are conducted in outpatient clinics. However, in Japan, regulatory authority requirements and traditional domestic guidelines often require hospitalization of phase I study participants.

PATIENTS AND METHODS

Patients participating in single-agent phase I clinical trials at National Cancer Center Hospital between December 1996 and August 2014 were monitored. Toxicity requiring hospitalization is defined as toxicity that needs intensive treatment. Study designs were classified into three types: first-in-human (FIH) study, dose-escalation study (conventional dose-escalation study to determine maximum tolerated dose (MTD) in Japanese patients), and dose-finding study (to assess safety and pharmacokinetic profiles up to the MTD previously determined in the West).

RESULTS

A total of 945 patients who participated in a variety of single-agent phase I clinical trials between December 1996 and August 2014 were included in this study. Patients participated in one of three study types: dose-escalation (n = 582, 62%), first-in-human (n = 129, 14%), or dose-finding (n = 234, 25%). A total of 76 study drugs were evaluated as part of this pool of phase I studies. Subdivided by mechanism of action, 20 (26%) were cytotoxic, 50 (66%) were molecularly targeted, and 6 (8%) were immune checkpoint inhibitor. Thirty-six patients (3.8%) had severe toxicities requiring hospitalization during the first cycle. The overall number of toxicities requiring hospitalization and/or grade 4 toxicities during any cycle was 5.0%.

CONCLUSIONS

The frequency of severe toxicity that needs to be hospitalized was unexpectedly low. The data did not demonstrate the need for hospitalization in the phase I trials, suggesting that phase I trials in Japan could be conducted in outpatient settings.

Using Delayed Toxicities to Re-evaluate Tolerability in Phase 2 Trials: A Case Example using Bortezomib

In advanced stage patients enrolled in dose-finding trials, it is difficult to assess delayed toxicities because frequently patients discontinue after one or two cycles of treatment. Patients enrolled in phase 2 trials are typically followed longer to assess efficacy. Thus, their data may be useful for evaluating long-term tolerability. We illustrate this using as example two phase 2 bortezomib trials (total N = 172) conducted by SWOG. While treatment-related severe toxicity rates based on cycle 1 were acceptable (23% and 31%), they were notably higher over extended administration (37% and 70%). This additional information should be considered when designing subsequent trials.