The changing landscape of phase I trials in oncology

Time Toxicity Experienced by Early-Phase Cancer Clinical Trial Participants

PURPOSE

Early-phase clinical trials (EP-CTs) are designed to determine optimal dosing, tolerability, and preliminary activity of novel cancer therapeutics. Little is known about the time that patients spend interacting with the health care system (eg, time toxicity) while participating in these studies.

METHODS

We retrospectively reviewed the electronic health records of consecutive patients enrolled in EP-CTs from 2017 to 2019 to obtain baseline characteristics and number of health care-associated days, defined as all inpatient and outpatient visits while on trial. We used univariable and multivariable analyses to identify predictors of increased time toxicity, defined as the proportion of health care-associated days among total days on trial. For ease of interpretation, we created a dichotomous variable, with high time toxicity defined as ≥20% health care-associated days during time on trial and used regression models to evaluate relationships between time toxicity and clinical outcomes.

RESULTS

Among 408 EP-CT participants (mean age, 60.5 years [standard deviation, SD, 12.6]; 56.5% female; 88.2% White; 96.0% non-Hispanic), patients had an average of 22.5% health care-associated days while on trial (SD, 13.8%). Those with GI (B = 0.07; P = .002), head/neck (B = 0.09; P = .004), and breast (B = 0.06; P = .015) cancers and those with worse performance status (B = 0.04; P = .017) and those receiving targeted therapies (B = 0.04; P = .014) experienced higher time toxicity. High time toxicity was associated with decreased disease response rates (odds ratio, 0.07; P < .001), progression-free survival (hazard ratio [HR], 2.10; P < .001), and overall survival (HR, 2.16; P < .001).

CONCLUSION

In this cohort of EP-CT participants, patients spent more than one-fifth of days on trial with health care contact. We identified characteristics associated with higher time toxicity and found that high toxicity correlated with worse clinical outcomes. These data could help inform patient-clinician discussions about EP-CTs, guide future trial design, and identify at-risk patients.

Navigating the complexities of drug development for inflammatory bowel disease

Inflammatory bowel disease (IBD) - consisting of ulcerative colitis and Crohn's disease - is a complex, heterogeneous, immune-mediated inflammatory condition with a multifactorial aetiopathogenesis. Despite therapeutic advances in this arena, a ceiling effect has been reached with both single-agent monoclonal antibodies and advanced small molecules. Therefore, there is a need to identify novel targets, and the development of companion biomarkers to select responders is vital. In this Perspective, we examine how advances in machine learning and tissue engineering could be used at the preclinical stage where attrition rates are high. For novel agents reaching clinical trials, we explore factors decelerating progression, particularly the decline in IBD trial recruitment, and assess how innovative approaches such as reconfiguring trial designs, harmonizing end points and incorporating digital technologies into clinical trials can address this. Harnessing opportunities at each stage of the drug development process may allow for incremental gains towards more effective therapies.

A comparison of model-free phase I dose escalation designs for dual-agent combination therapies

It is increasingly common for therapies in oncology to be given in combination. In some cases, patients can benefit from the interaction between two drugs, although often at the risk of higher toxicity. A large number of designs to conduct phase I trials in this setting are available, where the objective is to select the maximum tolerated dose combination. Recently, a number of model-free (also called model-assisted) designs have provoked interest, providing several practical advantages over the more conventional approaches of rule-based or model-based designs. In this paper, we demonstrate a novel calibration procedure for model-free designs to determine their most desirable parameters. Under the calibration procedure, we compare the behaviour of model-free designs to model-based designs in a comprehensive simulation study, covering a number of clinically plausible scenarios. It is found that model-free designs are competitive with the model-based designs in terms of the proportion of correct selections of the maximum tolerated dose combination. However, there are a number of scenarios in which model-free designs offer a safer alternative. This is also illustrated in the application of the designs to a case study using data from a phase I oncology trial.

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.

A demand-offer critical analysis of current drug development. Phase I drugs versus TCGA sequencing data

BACKGROUND

Phase I clinical trials have become increasingly critical to regulatory approvals of novel agents. In phase I drug development, a global problem of unknown magnitude is the multiplicity of similar drugs being investigated against the same target, colloquially known as the 'me too' phenomenon.

METHODS

Ranging from December 2020 to December 2022 we annotated phase I clinical trials present on clinicaltrials.gov. Public databases were queried for annotation of investigational agents (IAs). Extensive literature research and data mining were performed to annotate agents not present in public databases. The Cancer Genome Atlas (TCGA) pan-cancer sequencing cohort was used to perform second-level analyses to evaluate tumour types with a higher number of IA matches.

RESULTS

A total of 1054 unique drug targets were identified. The most frequent IA classes were: cell products (1223), small-molecule inhibitors (1110), antibodies (733), and vaccines (346). Only a minority (8.9%) of phase I IAs were explored against a target without a competitive agent; 7% of agents shared targets with 2-3 other agents. Unfortunately, the majority (84%) shared targets with at least four other agents. Using data from the TCGA pan-cancer sequencing potentially underserved histologies were identified. Analysis of alteration-IA matches revealed potentially frequent and unexplored alterations in many tumour types.

CONCLUSIONS

The majority of IAs (86%) shared targets with at least three other agents. We argue that these duplicative efforts could be redirected toward unmet needs instead.

Identifying Early-Phase Clinical Trial Participants at Risk for Experiencing Worse Clinical Outcomes

PURPOSE

To identify early-phase clinical trial (EP-CT) participants at risk for experiencing worse clinical outcomes and describe receipt of supportive care services.

METHODS

A retrospective review of the electronic health records of consecutive patients enrolled in EP-CTs from 2017 to 2019 examined baseline characteristics, clinical outcomes, and receipt of supportive care services. The validated Royal Marsden Hospital (RMH) prognosis score was calculated using data at the time of EP-CT enrollment (scores range from 0 to 3; scores ≥ 2 indicate poor prognosis). Differences in patient characteristics, clinical outcomes, and receipt of supportive care services were compared on the basis of RMH scores.

RESULTS

Among 350 patients (median age = 63.2 years [range, 23.0-84.3 years], 57.1% female, 98.0% metastatic cancer), 31.7% had an RMH score indicating a poor prognosis. Those with poor prognosis RMH scores had worse overall survival (hazard ratio [HR], 2.00; P < .001), shorter time on trial (HR, 1.53; P < .001), and lower likelihood of completing the dose-limiting toxicity period (odds ratio, 0.42; P = .006) versus those with good prognosis scores. Patients with poor prognosis scores had greater risk of emergency room visits (HR, 1.66; P = .037) and hospitalizations (HR, 1.69; P = .016) while on trial, and earlier hospice enrollment (HR, 2.22; P = .006). Patients with poor prognosis scores were significantly more likely to receive palliative care consultation (46.8% v 27.6%; P < .001), but not other supportive care services.

CONCLUSION

This study found that RMH prognosis score could identify patients at risk for decreased survival, shorter time on trial, and greater use of health care services. The findings underscore the need to develop supportive care interventions targeting EP-CT participants' distinct needs.

What is the impact of targeted therapies given within phase I trials on the cognitive function of patients with advanced cancer: a mixed-methods exploratory study conducted in an early clinical trials unit

INTRODUCTION

Novel therapies such as small protein molecule inhibitors and immunotherapies are tested in early phase trials before moving to later phase trials and ultimately standard practice. A key aim of these clinical trials is to define a toxicity profile, however, the emphasis is often on safety with measurements of organ toxicity. Other subjective side effects can be under-reported because they are not measured formally within the trial protocols. The concern from clinical practice is that cognitive toxicity is poorly studied and may be under-reported in this context. This could lead to toxicity profiles of new treatments not being fully described and patients with unmet need in terms of acknowledgement and support of symptoms. This protocol outlines a framework of an exploratory study with feasibility aspects to investigate the impact and experience of cognitive changes for patients on phase I trials.

METHODS AND ANALYSIS

This is a mixed-methods study, combining quantitative and qualitative approaches. The sample is 30 patients with advanced cancer who are participating in phase I trials of novel therapies in the early clinical trials unit of a specialist cancer centre. A test battery of validated cognitive assessments will be taken alongside patient reported outcome measures at three time points from baseline, day eight and day 28 post start of treatment. At day 28, a semi-structured interview will be conducted and the narrative thematically analysed. Results will be integrated to offer a comprehensive description of cognitive function in this patient group.

ETHICS AND DISSEMINATION

The study has received full HRA and ethical approval. It is the first study to introduce formal cognitive assessments in a cancer phase I trial context. The study has the potential to highlight previously unreported side effects and more importantly unmet need in terms of care for patients who are participating in the trials.

Integration of healthy volunteers in early phase clinical trials with immuno-oncological compounds

Aim

Traditionally, early phase clinical trials in oncology have been performed in patients based on safety risk-benefit assessment. Therapeutic transition to immuno-oncology may open new opportunities for studies in healthy volunteers, which are conducted faster and are less susceptible to confounders. Aim of this study was to investigate to what extent this approach is utilized and whether pharmacodynamic endpoints are evaluated in these early phase trials. We conducted a comprehensive review of clinical trials with healthy volunteers using immunotherapies potentially relevant for oncology.

Methods

Literature searches according to PRISMA guidelines and after registration in PROSPERO were conducted in PubMed, Embase, Web of Science and Cochrane databases with the cut-off date 20 October 2020, using search terms of relevant targets in immuno-oncology. Articles describing clinical trials with immunotherapeutics in healthy volunteers with a mechanism relevant for oncology were included. “Immunotherapeutic” was defined as compounds exhibiting effects through immunological targets. Data including study design and endpoints were extracted, with specific attention to pharmacodynamic endpoints and safety.

Results

In total, we found 38 relevant immunotherapeutic compounds tested in HVs, with 86% of studies investigating safety, 82% investigating the pharmacokinetics (PK) and 57% including at least one pharmacodynamic (PD) endpoint. Most of the observed adverse events (AEs) were Grade 1 and 2, consisting mostly of gastrointestinal, cutaneous and flu-like symptoms. Severe AEs were leukopenia, asthenia, syncope, headache, flu-like reaction and liver enzymes increase. PD endpoints investigated comprised of cytokines, immune and inflammatory biomarkers, cell counts, phenotyping circulating immune cells and ex vivo challenge assays.

Discussion

Healthy volunteer studies with immuno-oncology compounds have been performed, although not to a large extent. The integration of healthy volunteers in well-designed proof-of-mechanism oriented drug development programs has advantages and could be pursued more in the future, since integrative clinical trial protocols may facilitate early dose selection and prevent cancer patients to be exposed to non-therapeutic dosing regimens.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=210861, identifier CRD42020210861

Eventual success rate and predictors of success for oncology drugs tested in phase I trials

Previous estimates of the likelihood of a drug tested in phase I trials obtaining FDA clearance are out of date. In the intervening years, newer pharmaceuticals have been developed, resulting in new delivery systems and lines of therapies. We sought to explore and update these estimates by comprehensively searching drugs tested in phase I trials and to determine the factors associated with later receiving FDA approval. In a cross-sectional analysis, we searched for anti-tumor drugs tested in phase I trials and published in scientific journals or presented at hematology/oncology conferences. For each drug, we searched PubMed for phase II and phase III studies testing the drug for the same indication tested in phase I studies. We found 51 drug approvals; 4 were withdrawn. The probability of a drug tested in 2015 being approved by 2021 was 6.2%. Drugs tested as monotherapy were more likely to receive approval than drugs tested in combination, and monoclonal antibodies were more likely to receive approval than drugs of other mechanisms. In adjusted models, response rates higher than 40% in phase I studies, demonstrating an improvement in overall survival (OS) in phase III studies, and drugs tested as monotherapy were associated with receiving FDA approval. When looking at all drugs tested during a single year, most drugs were not approved, and among those that are approved, almost 8% are withdrawn. Response rates higher than 40%, testing a drug as monotherapy, and demonstrating an improvement in OS were associated with receiving FDA approval. This article is protected by copyright. All rights reserved.

Outcomes and endpoints in clinical trials supporting the marketing authorisation of treatments in paediatric acute lymphoblastic leukaemia

The improvement in acute lymphoblastic leukaemia (ALL) treatment has led research efforts to focus on the unmet medical needs of an increasingly smaller patient cohort with resistant leukaemia and to develop more-targeted agents. Survival and response rates remain the most-prevalent endpoints in paediatric ALL research, but other intermediate clinical endpoints and molecular biomarkers for efficacy and mid- and long-term safety endpoints are also being investigated. The success of current ALL treatment appears to be driving new paradigms to optimise clinical drug development, while at the same time, regulatory tools in place are supporting meaningful drug development in the area.

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.

Trends of Phase I Clinical Trials of New Drugs in Mainland China Over the Past 10 Years (2011–2020)

Background: In recent years, the number of clinical trials initiated in China has increased rapidly. The aim of this study was to overview the changing landscape of phase I clinical trials in mainland China from 2011 to 2020.

Methods: We analyzed phase I clinical trials registered on 3 websites including the Chinese Clinical Trial Registry, ClinicalTrials.gov, and the China National Medical Products Administration Center for Drug Evaluation platform.

Findings: A total of 2,842 phase I clinical trials were posted from January 1, 2011, to December 31, 2020. The overall number of clinical trials for innovative drugs was 1,497, accounting for half of all the phase I clinical trials (53%). Among these 1,486 innovative drug clinical trials, 924 were newly tested drugs with an average annual growth rate of 59%. Biological drug research increased significantly from 22.6% during 2011–2015 to 33.3% during 2016–2020. These principal investigators (PIs) of these clinical trials were mainly from Beijing (n = 871), followed by Shanghai (n = 496) and Jiangsu (n = 281). As for the therapeutic area of phase I clinical trials, cancer took up the most percentage of all the clinical trials (35%), followed by infectious disease (9%), nervous system disease (9%), etc. Most phase I clinical trials are conducted on healthy volunteers (n = 1,642, 57.8%), some cancer drugs are conducted in patients with cancer (n = 846, 29.8%), and only a few clinical trials were conducted in the elderly (n = 7). Among these clinical trials of the newly tested innovative drugs, the first in human (FIH) clinical trials accounted for 82% (744), and the First in Chinese (FIC) clinical trials only took up 18% (167). Only a small number of drugs could be made the transition to phase II (n = 207, 22%). In addition, despite the number of newly tested drugs during 2011–2015 (n = 163) was much less than that in 2016–2020 (n = 761), the percentage of drugs that could enter into phase II clinical trials in 2011–2015 (34%) was higher than that in 2016–2020 (20%).

Conclusion: In the past 10 years, the development of phase I clinical trials has achieved great progress in mainland China due to the novel design and drug innovation policy. Nevertheless, future efforts are needed to make for improving the phase transition success rate of innovative drugs.

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.

Healthy volunteers in first-in-human oncology drug development for small molecules

This review provides tools to consider the inclusion of healthy volunteers (HVs) in first-in-human (FIH) oncology clinical trials with small molecules, including targeted and immunomodulatory agents, a strategy that was not envisioned with classic chemotherapy. To enable an FIH oncology trial in HVs compared to cancer patients (CPs), a robust nonclinical package must be generated, which includes toxicokinetic and pharmacokinetic studies, as well as more extensive safety pharmacology, toxicology and genotoxicity studies. This strategy could provide an early clinical characterization of the pharmacokinetic parameters and clinical safety profile in the absence of comorbidities and concomitant medication. It also avoids the ethical issue of administrating subtherapeutic doses to CPs, and could potentially help to accelerate the timelines of clinical drug development for patient care. That being said, stakeholders involved in these studies need to proceed with caution, fully understand the regulatory guidance and thoroughly evaluate the benefits and risks. This paper serves to address the regulatory guidance and other considerations needed when using healthy volunteers in early oncology trials.

Recruitment, outcomes, and toxicity trends in phase I oncology trials: Six-year experience in a large institution

Background

With the rapid influx of novel anti‐cancer agents, phase I clinical trials in oncology are evolving. Historically, response rates on early phase trials have been modest with the clinical benefit and ethics of enrolment debated. However, there is a paucity of real‐world data in this setting.

Aim

To better understand the changing landscape of phase I oncology trials, we performed a retrospective review at our institution to examine patient and trial characteristics, screening outcomes, and treatment outcomes.

Methods and results

We analyzed all consecutive adult patients with advanced solid organ malignancies who were screened across phase I trials from January 2013 to December 2018 at a single institution. During this period, 242 patients were assessed for 28 different trials. Median age was 64 years (range 30–89) with an equal sex distribution. Among 257 screening visits, the overall screen failure rate was 18%, resulting in 212 patients being enrolled onto a study. Twenty‐six trials (93%) involved immunotherapeutic agents or molecular targeted agents either alone or in combination, with only two trials of cytotoxic agents (7%). Twenty‐two (13.4%) of the 209 treated patients experienced a total of 33 grade 3 or higher treatment‐related adverse events. There was one treatment‐related death (0.5%). Of 190 response‐evaluable patients, 7 (4%) had a complete response, 34 (18%) a partial response, and 59 (31%) experienced stable disease for a disease control rate of 53%. The median overall survival for our cohort was 8.0 (95% CI: 6.8–9.2) months.

Conclusion

The profile of phase I trials at our institution are consistent with the changing early drug development landscape. Response rates and overall survival in our cohort are superior to historically reported rates and comparable to contemporaneous studies. Severe treatment‐related toxicity was relatively uncommon, and treatment‐related mortality was rare.

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.

Targeted Treatment of Head and Neck (Pre)Cancer: Preclinical Target Identification and Development of Novel Therapeutic Applications

Head and neck squamous cell carcinomas (HNSCC) develop in the mucosal lining of the upper-aerodigestive tract. In carcinogen-induced HNSCC, tumors emerge from premalignant mucosal changes characterized by tumor-associated genetic alterations, also coined as 'fields' that are occasionally visible as leukoplakia or erythroplakia lesions but are mostly invisible. Consequently, HNSCC is generally diagnosed de novo at more advanced stages in about 70% of new diagnosis. Despite intense multimodality treatment protocols, the overall 5-years survival rate is 50-60% for patients with advanced stage of disease and seems to have reached a plateau. Of notable concern is the lack of further improvement in prognosis despite advances in treatment. This can be attributed to the late clinical presentation, failure of advanced HNSCC to respond to treatment, the deficit of effective targeted therapies to eradicate tumors and precancerous changes, and the lack of suitable markers for screening and personalized therapy. The molecular landscape of head and neck cancer has been elucidated in great detail, but the absence of oncogenic mutations hampers the identification of druggable targets for therapy to improve outcome of HNSCC. Currently, functional genomic approaches are being explored to identify potential therapeutic targets. Identification and validation of essential genes for both HNSCC and oral premalignancies, accompanied with biomarkers for therapy response, are being investigated. Attentive diagnosis and targeted therapy of the preceding oral premalignant (preHNSCC) changes may prevent the development of tumors. As classic oncogene addiction through activating mutations is not a realistic concept for treatment of HNSCC, synthetic lethality and collateral lethality need to be exploited, next to immune therapies. In recent studies it was shown that cell cycle regulation and DNA damage response pathways become significantly altered in HNSCC causing replication stress, which is an avenue that deserves further exploitation as an HNSCC vulnerability for treatment. The focus of this review is to summarize the current literature on the preclinical identification of potential druggable targets for therapy of (pre)HNSCC, emerging from the variety of gene knockdown and knockout strategies, and the testing of targeted inhibitors. We will conclude with a future perspective on targeted therapy of HNSCC and premalignant changes.

National Maintenance Cost for Precision Diagnostics Under the Verifying Accurate Leading-Edge In Vitro Clinical Test Development (VALID) Act of 2020

PURPOSE

The proposed legislation Verifying Accurate and Leading-edge In vitro clinical test Development (VALID) clarifies the US Food and Drug Administration's authority to regulate laboratory-developed tests. Many stakeholders have pointed out that the lack of direct US Food and Drug Administration oversight has led to erroneous results that have serious patient consequences-in particular for patients with cancer. Technology Certification is a key provision proposed in VALID to navigate the balance between safety, patient access, and innovation; however, the maintenance cost of the proposed framework after implementation is unclear.

METHODS

On the basis of 2019 retrospective data from a laboratory-developed test-based cancer diagnostics laboratory, we expressed laboratory complexity by the number and complexity of assays and in vitro diagnostic technologies. We estimated the national health care cost increase by modeling three stringencies of complying with the Act. We performed sensitivity analysis of our regulatory stringency model taking into account number of patients tested, materials, submission cost, and labor using extra cost per patient as the output.

RESULTS

We estimate the national health care cost increase to range from $33M US dollars (USD) to $1,110M USD or $0.21 USD to $0.70 USD per employed person in the United States. Sensitivity analysis demonstrates that regulatory stringency is the primary driver of extra cost per patient. Cancer testing does not reflect all areas of in vitro diagnostics affected by VALID; nonetheless, concrete cost models are paramount in informing the ongoing legislative negotiations.

CONCLUSION

Our findings show the critical importance of clarity in the legislative language to ensure balance between VALID's goals of assuring high-quality test performance and the burden to laboratories and overall health care cost.

ANALYSIS OF "LEARN-AS-YOU-GO" (LAGO) STUDIES

In Learn-As-you-GO (LAGO) adaptive studies, the intervention is a complex multicomponent package, and is adapted in stages during the study based on past outcome data. This design formalizes standard practice in public health intervention studies. An effective intervention package is sought, while minimizing intervention package cost. In LAGO study data, the interventions in later stages depend upon the outcomes in the previous stages, violating standard statistical theory. We develop an estimator for the intervention effects, and prove consistency and asymptotic normality using a novel coupling argument, ensuring the validity of the test for the hypothesis of no overall intervention effect. We develop a confidence set for the optimal intervention package and confidence bands for the success probabilities under alternative package compositions. We illustrate our methods in the BetterBirth Study, which aimed to improve maternal and neonatal outcomes among 157,689 births in Uttar Pradesh, India through a multicomponent intervention package.

Cancer Clinical Trials: What Every Radiologist Wants to Know but Is Afraid to Ask

OBJECTIVE. The purpose of this article is to provide radiologists with a guide to the fundamental principles of oncology clinical trials. The review summarizes the evolution and structure of modern clinical trials with an emphasis on the relevance of clinical trials in the field of oncologic imaging. CONCLUSION. Understanding the structure and clinical relevance of modern clinical trials is beneficial for radiologists in the field of oncologic imaging.

Change-point joint model for identification of plateau of activity in early phase trials

This article presents a phase I/II trial design for targeted therapies and immunotherapies, with the objective of identifying the optimal dose (OD). We employ a joint modeling technique for discrete time-to-event toxicity data and repeated and continuous biomarker measurements. For the biomarker measurements, we implement a change point linear mixed effects skeleton model. This model can accommodate both plateauing and nonplateauing dose-activity relationships. For each new cohort of patients, we estimate the maximum tolerated dose (MTD) taking toxicity as a cumulative endpoint, over six treatment cycles. Then, we select the OD using two different criteria. The OD is a dose that is equally active to the MTD or a dose located on the beginning of the plateau of the dose-activity relationship. Joint modeling allows us to take into account informative censoring due to toxicities or lack of activity and we also consider consent withdrawal and intermittent missing responses. Model estimation relies on likelihood inference.

First-in-Human Phase I Study of Iadademstat (ORY-1001): A First-in-Class Lysine-Specific Histone Demethylase 1A Inhibitor, in Relapsed or Refractory Acute Myeloid Leukemia

PURPOSE

Iadademstat is a novel, highly potent, and selective inhibitor of LSD1 (KDM1A), with preclinical in vitro and in vivo antileukemic activity. This study aimed to determine safety and tolerability of iadademstat as monotherapy in patients with relapsed/refractory acute myeloid leukemia (R/R AML).

METHODS

This phase I, nonrandomized, open-label, dose-escalation (DE), and extension-cohort (EC) trial included patients with R/R AML and evaluated the safety, pharmacokinetics (PK), pharmacodynamics (PD), and preliminary antileukemic activity of this orally bioavailable first-in-class lysine-specific demethylase 1 inhibitor.

RESULTS

Twenty-seven patients were treated with iadademstat on days 1 to 5 (5-220 µg/m2/d) of each week in 28-day cycles in a DE phase that resulted in a recommended dose of 140 µg/m2/d of iadademstat as a single agent. This dose was chosen to treat all patients (n = 14) in an EC enriched with patients with MLL/KMT2A-rearranged AML. Most adverse events (AEs) were as expected in R/R AML and included myelosuppression and nonhematologic AEs, such as infections, asthenia, mucositis, and diarrhea. PK data demonstrated a dose-dependent increase in plasma exposure, and PD data confirmed a potent time- and exposure-dependent induction of differentiation biomarkers. Reductions in blood and bone marrow blast percentages were observed, together with induction of blast cell differentiation, in particular, in patients with MLL translocations. One complete remission with incomplete count recovery was observed in the DE arm.

CONCLUSION

Iadademstat exhibits a good safety profile together with signs of clinical and biologic activity as a single agent in patients with R/R AML. A phase II trial of iadademstat in combination with azacitidine is ongoing (EudraCT No.: 2018-000482-36).

Clinical outcomes of breast cancer patients treated in phase I clinical trials at University of Colorado Cancer Center

Patients with metastatic breast cancer (MBC) refractory to standard of care therapies have a poor prognosis. The purpose of this study was to assess patient characteristics and clinical outcomes for patients with MBC treated on phase I clinical trials. We performed a retrospective review of all patients with MBC who were enrolled in phase I clinical trials at the University of Colorado Cancer Center from January 2012 to June 2018. A total of 208 patients were identified. Patients had a mean age of 57 years and received on average 2.1 (range 0-10) prior lines of chemotherapy. The majority of patients had hormone receptor-positive/HER2-negative breast cancer (58.6%) and 30.3% had triple-negative breast cancer. The median progression free survival (PFS) was 2.8 months (95% CI, 2.3-3.9) and median overall survival (OS) was 11.5 months (95% CI, 9.6-13.2). Independent factors associated with longer PFS in multivariable analysis were treatment in a breast cancer-selective trial or cohort (p = 0.016), age >50 years (p = 0.002), and ≤2 prior lines of chemotherapy in the metastatic setting (p = 0.025). Phase I clinical trials remain a valuable option for select patients with MBC and enrollment should be encouraged when available.

How to improve clinical research in a department of radiation oncology

INTRODUCTION

Radiation therapy is a core modality for cancer treatment. Around 40% of cancer cures include the use of radiotherapy, either as a single strategy or combined with other treatments. In the past decade, substantial technical advances and novel insights into radiobiological properties have considerably improved patients' outcomes. This study overviewed the landscape of clinical research at our radiotherapy department.

METHODS

We surveyed our institutional database of clinical trials to collect information for completed or ongoing radiation therapy clinical trials, from 2005 to December 2017 at the Lucien Neuwirth cancer institute.

RESULTS

A total of 31 clinical trials were undertaken during the study period, of which 4 studies (12.9%) were industry-sponsored and 3 studies (9.7%) were launched by our radiotherapy unit. The vast majority of clinical trials (83.9%) were dedicated to unique organ localization, especially urological cancer (prostate or bladder) (42%). We also observed a shift towards more phase II trials during the study period as well as a special focus on elderly population. Over the last decade, the number of included patients increased by a 5.3 fold input, with 135 inclusions before 2011 and 720 inclusions after 2011.

DISCUSSION

This study provided an observational and comprehensive analysis of radiotherapy research. From a monocentric point-of-view, these results reflected the on-going progress of worldwide radiotherapy research. Based on a 13-years' experience, this study aimed at highlighting essential cues to ensure efficient and perennial research.

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.

Reprioritizing Risk and Benefit: The Future of Study Design in Early-Phase Cancer Research

The scientific purpose of phase I trials is to determine the maximum tolerated dose and/or optimal biological dose of experimental agents. Yet most participants in phase I oncology trials enroll hoping for direct medical benefit. The most common phase I trial designs use low starting doses and escalate cautiously in a "risk-escalation" model focused on minimizing risk for each participant. This approach ensures that a proportion of subjects will likely not receive any benefit, even if the intervention proves to be successful at appropriate doses. In this article, we propose that trial designs should employ dosing strategies that increase chances of providing benefit if the investigational agent should prove to be successful while limiting risk to reasonable levels. We then describe how adaptive trial designs can facilitate refined dose optimization based on both therapeutic benefit and toxicity, which can simultaneously decrease the risk of harm while increasing the chances of benefit.

Infection risk with PI3K-AKT-mTOR pathway inhibitors and immune checkpoint inhibitors in patients with advanced solid tumours in phase I clinical trials

Background

Patients undergoing chemotherapy are known to be at risk for infection from myelosuppression by cytotoxic agents (CTAs) or immunosuppressive effects from mTOR inhibitors. The infection risk of newly developed anticancer agents has not been fully evaluated. It remains unknown how T-cell activation induced by immune checkpoint inhibitors (ICIs) relates to infection.

Methods

We retrospectively examined infection risk in patients with cancer treated with investigational agents in a phase I study. The investigational agents were classified into four groups: CTA, phosphatidylinositol 3 kinase/Akt/mammalian target of rapamycin inhibitor (PAM), molecular targeted agent (MTA) and ICI. All infection-related adverse events (AEs) during treatment were recorded. We compared the CTA, PAM and ICI with MTA, because MTA are already considered low risk and were used in the largest number of patients.

Results

A total of 641 patients were enrolled: 35 CTAs (5.5%), 61 PAMs (9.5%), 445 MTAs (69.4%) and 100 ICIs (15.6%). Among all patients, 132 (20.6%) experienced infection-related AEs and 46 (7.2%) developed 50 ≥grade 3 infection-related AEs. In any infection-related AEs, the ORs compared with MTAs were 2.19 (95% CI 1.03 to 4.66) for CTAs, 3.55 (95% CI 2.02 to 6.24) for PAMs and 1.05 (95% CI 0.60 to 1.85) for ICIs, respectively. In time to the first infection-related AE analysis, the risks for any infection-related AE from CTAs and PAMs were higher than those from MTAs (HR 1.84 (95% CI 0.82 to 4.11); p=0.05 and 3.96 (95% CI 2.18 to 7.22); p<0.001). The risk from ICIs was not significantly different from that of MTAs (HR 0.71 (95% CI 0.46 to 1.10); p=0.19).

Conclusion

Our results validate that PAMs and CTAs carry a higher infection risk in patients with advanced solid tumours compared with MTAs. We suggest that the infection risk of ICIs is a similar infection risk to MTAs.

Estimated costs of pivotal trials for U.S. Food and Drug Administration-approved cancer drugs, 2015-2017

BACKGROUND

Pivotal clinical trials provide critical evidence to regulators regarding a product's suitability for marketing approval. The objectives of this study are (1) to characterize select features of trials for oncology products approved by the U.S. Food and Drug Administration between 2015 and 2017; and (2) to quantify the costs of these trials and how such costs varied based on trial characteristics.

METHODS

We identified novel oncology therapeutic drugs, and their respective pivotal trials, approved between 2015 and 2017 using annual summary reports from the Food and Drug Administration. Cost estimates for each pivotal trial were calculated using IQVIA's CostPro, a clinical trial cost estimating tool based on executed contracts between pharmaceutical manufacturers and contract research organizations. Measures of drug and trial characteristics included trial design, end point, patient enrollment, and regulatory pathway. We also performed sensitivity analyses that varied assumptions regarding how efficiently each trial was conducted.

RESULTS

A total of 39 pivotal clinical trials provided the basis for Food and Drug Administration approval of 30 new oncology drugs from 2015 to 2017. Among these trials, primary end points were objective response rate in 20 (51.3%), progression-free survival in 13 (33.3%), and overall survival in 6 (15.4%). Twenty trials (51.3%) were single-arm studies. The median estimated cost of oncology pivotal trials was $31.7 million (interquartile range = $17.0-$60.4 million). Trials with objective response rate as primary end point had a median estimate of $17.7 million (interquartile range = $11.9-$27.1 million), compared with trials examining progression-free survival ($42.3 million, interquartile range = $34.6-$101.2 million) or overall survival ($79.4 million, interquartile range = $56.9-$97.7 million) (p < 0.001). Estimated costs for single-arm trials ($17.7 million, interquartile range = $11.9-$23.7 million) were less than for trials with a placebo-controlled ($56.7 million, interquartile range = $40.9-$103.9 million) or active control arm ($67.6 million, IQR = $35.5-$93.5 million) (p < 0.001).

CONCLUSIONS

Relative to the estimated costs of drug development, the costs of these oncology pivotal trials were modest, with trials that produced more valuable scientific information costing more than their counterparts.

Prediction of Drug Approval After Phase I Clinical Trials in Oncology: RESOLVED2

PURPOSE

Drug development in oncology currently is facing a conjunction of an increasing number of antineoplastic agents (ANAs) candidate for phase I clinical trials (P1CTs) and an important attrition rate for final approval. We aimed to develop a machine learning algorithm (RESOLVED2) to predict drug development outcome, which could support early go/no-go decisions after P1CTs by better selection of drugs suitable for further development.

METHODS

PubMed abstracts of P1CTs reporting on ANAs were used together with pharmacologic data from the DrugBank5.0 database to model time to US Food and Drug Administration (FDA) approval (FDA approval-free survival) since the first P1CT publication. The RESOLVED2 model was trained with machine learning methods. Its performance was evaluated on an independent test set with weighted concordance index (IPCW).

RESULTS

We identified 462 ANAs from PubMed that matched with DrugBank5.0 (P1CT publication dates 1972 to 2017). Among 1,411 variables, 28 were used by RESOLVED2 to model the FDA approval-free survival, with an IPCW of 0.89 on the independent test set. RESOLVED2 outperformed a model that was based on efficacy/toxicity (IPCW, 0.69). In the test set at 6 years of follow-up, 73% (95% CI, 49% to 86%) of drugs predicted to be approved were approved, whereas 92% (95% CI, 87% to 98%) of drugs predicted to be nonapproved were still not approved (log-rank P < .001). A predicted approved drug was 16 times more likely to be approved than a predicted nonapproved drug (hazard ratio, 16.4; 95% CI, 8.40 to 32.2).

CONCLUSION

As soon as P1CT completion, RESOLVED2 can predict accurately the time to FDA approval. We provide the proof of concept that drug development outcome can be predicted by machine learning strategies.

Cancer-Related Internet Use and Online Social Networking Among Patients in an Early-Phase Clinical Trials Clinic at a Comprehensive Cancer Center

PURPOSE

We examined patterns, correlates, and the impact of cancer-related Internet use among patients with advanced cancer in a phase I clinical trials clinic for molecularly targeted oncologic agents.

METHODS

An anonymous questionnaire on Internet use for cancer-related purposes that incorporated input from phase I clinical trial oncologists and patients was self-administered by patients age ≥ 18 years in a phase I clinic. Multivariable modeling was used. Data were analyzed for the overall sample and by generation, which was defined by year of birth.

RESULTS

Of 291 patients (52% women, 82% non-Hispanic white, 50% age ≤ 60 years), 62% were cancer-related Internet users (CIUs). Cancer-related Internet use was associated with an income of ≥ $60,000 (odds ratio, 2.42; P = .004). CIUs used the Internet to learn about their cancer (85%), treatment adverse effects (65%), clinical trials (52%), new alternative treatments (42%), and symptom management (41%). CIUs most frequently used the hospital Web site (70%) to learn about clinical trials, followed by ClinicalTrials.gov (42%) and search engines (41%). The emotional impact of Internet-derived cancer information on CIUs varied-56% felt empowered, 34% anxious, 29% relieved, and 17% confused. Cancer-related Internet information made 51% of patients from the Millennial (born after 1990) and Generation X/Y (born 1965 to 1990) CIU populations anxious compared with < 29% of CIUs from older generations (born 1964 and before). Most CIUs desired more online information about new experimental drugs (91%) and US Food and Drug Administration-approved drugs for cancer (72%).

CONCLUSION

As most phase I patients use the Internet for cancer-related purposes, the Internet overall and hospital Web sites should provide more extensive, pertinent, and helpful information on clinical trials and cancer treatment to phase I patients.

Drug-adapted cancer cell lines as preclinical models of acquired resistance

Acquired resistance formation limits the efficacy of anti-cancer therapies. Acquired and intrinsic resistance differ conceptually. Acquired resistance is the consequence of directed evolution, whereas intrinsic resistance depends on the (stochastic) presence of pre-existing resistance mechanisms. Preclinical model systems are needed to study acquired drug resistance because they enable: (1) in depth functional studies; (2) the investigation of non-standard treatments for a certain disease condition (which is necessary to identify small groups of responders); and (3) the comparison of multiple therapies in the same system. Hence, they complement data derived from clinical trials and clinical specimens, including liquid biopsies. Many groups have successfully used drug-adapted cancer cell lines to identify and elucidate clinically relevant resistance mechanisms to targeted and cytotoxic anti-cancer drugs. Hence, we argue that drug-adapted cancer cell lines represent a preclinical model system in their own right that is complementary to other preclinical model systems and clinical data.

First-in-Human, Healthy Volunteers Integrated Protocol of ETC-206, an Oral Mnk 1/2 Kinase Inhibitor Oncology Drug

In the last decade, drug development has tackled substantial challenges to improve efficiency and facilitate access to innovative medicines. Integrated clinical protocols and the investigation of targeted oncology drugs in healthy volunteers (HVs) have emerged as modalities with an increase in scope and complexity of early clinical studies and first‐in‐human (FIH) studies in particular. However, limited work has been done to explore the impact of these two modalities, alone or in combination, on the scientific value and on the implementation of such articulated studies. We conducted an FIH study in HVs with an oncology targeted drug, an Mnk 1/2 small molecule inhibitor. In this article, we describe results, advantages, and limitations of an integrated clinical protocol with an oncology drug. We further discuss and indicate points to consider when designing and conducting similar scientifically and operationally demanding FIH studies.

On the relative efficiency of model-assisted designs: a conditional approach

In phase I dose-finding trials, model-assisted designs are a novel class of designs that combine the simplicity of algorithm-based methods with the superior performance of model-based methods. Examples of model-assisted designs include the modified toxicity probability (mTPI), Bayesian optimal interval (BOIN) and keyboard designs. To achieve simplicity, these model-assisted methods model only "local" data observed at the current dose, typically using a binomial model, to guide dose assignments. This potentially causes efficiency loss, however, by ignoring the data observed in other doses. To investigate this issue, we propose a conditional approach that utilizes the data from both current and adjacent (i.e., next higher or lower) doses to make the dose-assignment decisions. Specifically, we propose the conditional optimal interval (COIN) design, as the conditional approach extension of the BOIN design. We investigate the theoretical properties of the COIN design and conduct extensive numerical studies to examine its performance in comparison with existing model-assisted designs. We also present the conditional approach to the keyboard design. We observe that the conditional approach improves patient allocation, but yields similar maximum-tolerated dose (MTD) identification accuracy as the model-assisted designs, suggesting only minor efficiency loss using local data under the model-assisted designs.

Cancer-Related Internet Use and Its Association With Patient Decision Making and Trust in Physicians Among Patients in an Early Drug Development Clinic: A Questionnaire-Based Cross-Sectional Observational Study

Background

The role of cancer-related internet use on the patient-physician relationship has not been adequately explored among patients who are cancer-related internet users (CIUs) in early-phase clinical trial clinics.

Objective

We examined the association between cancer-related internet use and the patient-physician relationship and decision making among CIUs in an early drug development clinic.

Methods

Of 291 Phase I clinic patients who completed a questionnaire on internet use, 179 were CIUs. Generations were defined by the year of patient’s birth: “millennials” (after 1990) and “Generation X/Y” (1965-1990) grouped as “Millennials or Generation X/Y”; “Baby Boomers” (1946-1964); and “Greatest or Silent Generation” (1945 and earlier). Statistical analyses included the Wilcoxon matched-pairs signed-rank test and the Mann-Whitney U test.

Results

CIUs were 52% (94/179) female, 44% (78/179) were older than 60 years, and 60% (108/179) had household incomes exceeding US $60,000. The sources of information on cancer and clinical trials included physicians (171/179, 96%), the internet (159/179, 89%), and other clinical trial personnel (121/179, 68%). For the overall sample and each generation, the median values for trust in referring and Phase I clinical trial physicians among early drug development clinic CIUs were 5 on a 0-5 scale, with 5 indicating “complete trust.” CIUs’ trust in their referring (5) and phase 1 (5) physicians was higher than CIUs’ trust in Web-based cancer-related information (3; P<.001 for both). CIUs who reported visiting the National Cancer Institute (NCI) website, NCI.org, to learn about cancer reported higher levels of trust in Web-based cancer-related information than CIUs who did not use the NCI website (P=.02). Approximately half of CIUs discussed internet information with their doctor. Only 14% (23/165) of CIUs had asked their physician to recommend cancer-related websites, and 24% (35/144) of CIUs reported at least occasional conflict between their physician’s advice and Web-based information.

Conclusions

Despite the plethora of websites related to cancer and cancer clinical trials, patients in early-phase clinical trial settings trust their physicians more than Web-based information. Cancer-related organizations should provide regularly updated links to trustworthy websites with cancer and clinical trial information for patients and providers and educate providers on reliable cancer websites so that they can better direct their patients to appropriate internet content.

Interactive calculator for operating characteristics of phase I cancer clinical trials using standard 3+3 designs

Among various Phase I clinical trial designs, rule-based standard 3 + 3 designs are the most widely utilized for their simplicity and robustness. It is necessary to define crucial operating characteristics of a Phase I clinical trial before it starts. Based on the assumed probability of dose limiting toxicity (DLT) at each tested dose level, Lin and Shih elaborated formulas to calculate the five key operating characteristics of Phase I clinical trials using the two subtypes of standard 3 + 3 designs (with vs without dose de-escalation): probability of each dose level being chosen as the maximum tolerated dose (MTD); expected number of patients treated at each dose level; expected number of patients experiencing DLT at each dose level; target toxicity level (TTL) (expected probability of DLT at MTD); expected total number of patients experiencing DLT. Understanding these formulas requires advanced statistical knowledge and the formulas are too complicated to be used directly. To facilitate their application, we have developed stand-alone interactive software for convenient calculation of these key operating characteristics. The calculated results are presented in tables and plots that can be saved and easily edited for further use. Some examples of calculation using the software are presented and discussed.

Phase I Study of the Combination of Bendamustine, Rituximab, and Pixantrone in Patients With Relapsed/Refractory B-cell Non-Hodgkin Lymphoma

BACKGROUND

For patients with aggressive lymphomas who relapse after initial therapy, a durable response is rarely achieved with standard salvage therapies. Significant efforts have focused on the development of novel treatments with reduced toxicity. We conducted a phase I prospective single arm clinical trial of the novel combination of BuRP (bendamustine, rituximab, and pixantrone) in patients with relapsed/refractory (R/R) aggressive B-cell non-Hodgkin lymphoma (NHL).

PATIENTS AND METHODS

Eligible patients included adults with biopsy-proven R/R B-cell NHL who met the criteria for treatment. Patients received bendamustine 120 mg/m², rituximab 375 mg/m², and pixantrone, per cohort dose, on day 1 for up to 6 cycles. Dose escalation used a 3 + 3 design, from a starting dose level of pixantrone 55 mg/m² to 115 mg/^m at dose level 3.

RESULTS

Twenty-two patients were enrolled onto the study with a median follow-up of 7.9 months. The maximum tolerated dose was not reached, but the highest dose level of pixantrone of 115 mg/m² was well-tolerated. The most common grade 3/4 adverse events were neutropenia (27%) and thrombocytopenia (23%). The mean change in left ventricular ejection fraction was 2.5% (standard deviation, 5.51%; 95% confidence interval, 0.0%-4.9%). The overall response rate for the entire cohort was 37.5% (95% confidence interval, 15%-65%), but at the highest pixantrone dose, the overall response rate was 63%, with a complete response rate of 25%.

CONCLUSION

The BuRP regimen was found to be safe in patients with R/R B-cell NHL. The favorable toxicity profile plus the encouraging response rates seen suggest that continued investigation of the highest dose level is warranted.

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.

Global trends in the distribution of cancer types among patients in oncology phase I trials, 1991-2015

Background Systematic analyses regarding cancer types of patients enrolled in oncology phase I trials are scarce. The global distribution, time-dependent change, and regional differences were evaluated. Methods A systematic search of the PubMed database, in which all single-agent phase I trials permitting the enrollment of all-comer patients with any type of solid tumor published between January 1991 and December 2015 were specified, was performed. Trials expected to enroll specific patient populations were excluded according to predefined criteria. Results Eight hundred and sixty-six eligible trials, which had enrolled 29,112 advanced solid tumor patients, were identified. Colorectal (n = 7510; 25.8%) and lung cancer (n = 3212; 11.0%) were the most prevalent solid tumors, followed by sarcoma (n = 1756; 6.0%), breast cancer (n = 1623; 5.6%), and renal cancer (n = 1589; 5.5%). The proportion of patients with either colorectal or lung cancer tended to decrease over time. The proportion of trials, in which patients with either of these two cancers accounted for ≥50.0% of the total number of patients in each trial, also decreased: 33 of 67 trials (31/67) (46.3%) in 1991-1995, 58/142 (40.8%) in 1996-2000, 59/223 (26.5%) in 2001-2005, 38/189 (20.1%) in 2006-2010, and 41/245 (16.7%) in 2011-2015. Instead, the proportion of patients with various types of cancer increased, leading to diversification of enrolled patients. Conclusions The distribution of cancer types among patients in phase I trials has changed. The comprehensive review of the distribution of solid tumor types could contribute to flexible trial designs and optimal patient recruitment.

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.