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.

Baseline Tumor Size as Prognostic Index in Patients With Advanced Solid Tumors Receiving Experimental Targeted Agents

BACKGROUND

Baseline tumor size (BTS) has been associated with outcomes in patients with cancer treated with immunotherapy. However, the prognostic impact of BTS on patients receiving targeted therapies (TTs) remains undetermined.

METHODS

We reviewed data of patients with advanced solid tumors consecutively treated within early-phase clinical trials at our institution from 01/2014 to 04/2021. Treatments were categorized as immunotherapy-based or TT-based (biomarker-matched or not). BTS was calculated as the sum of RECIST1.1 baseline target lesions.

RESULTS

A total of 444 patients were eligible; the median BTS was 69 mm (IQR 40-100). OS was significantly longer for patients with BTS lower versus higher than the median (16.6 vs. 8.2 months, P < .001), including among those receiving immunotherapy (12 vs. 7.5 months, P = .005). Among patients receiving TT, lower BTS was associated with longer PFS (4.7 vs. 3.1 months, P = .002) and OS (20.5 vs. 9.9 months, P < .001) as compared to high BTS. However, such association was only significant among patients receiving biomarker-matched TT, with longer PFS (6.2 vs. 3.3 months, P < .001) and OS (21.2 vs. 6.7 months, P < .001) in the low-BTS subgroup, despite a similar ORR (28% vs. 22%, P = .57). BTS was not prognostic among patients receiving unmatched TT, with similar PFS (3.7 vs. 4.4 months, P = .30), OS (19.3 vs. 11.8 months, P = .20), and ORR (33% vs. 28%, P = .78) in the 2 BTS groups. Multivariate analysis confirmed that BTS was independently associated with PFS (P = .03) and OS (P < .001) but not with ORR (P = .11).

CONCLUSIONS

Higher BTS is associated with worse survival outcomes among patients receiving biomarker-matched, but not biomarker-unmatched TT.

Backfilling cohorts in phase I dose-escalation studies

BACKGROUND

The use of 'backfilling', assigning additional patients to doses deemed safe, in phase I dose-escalation studies has been used in practice to collect additional information on the safety profile, pharmacokinetics and activity of a drug. These additional patients help ensure that the maximum tolerated dose is reliably estimated and give additional information to determine the recommended phase II dose.

METHODS

In this article, we study the effect of employing backfilling in a phase I trial on the estimation of the maximum tolerated dose and the duration of the study. We consider the situation where only one cycle of follow-up is used for escalation as well as the case where there may be delayed onset toxicities.

RESULTS

We find that, over a range of scenarios, the use of backfilling gives an increase in the percentage of correct selections by up to 9%. On average, for a treatment with a cycle length of 6 weeks, each additional backfilling patient reduces the trial duration by half a week.

CONCLUSIONS

Backfilling in phase I dose-escalation studies can substantially increase the accuracy of estimation of the maximum tolerated dose, with a larger impact in the setting with a dose-limiting toxicity event assessment period of only one cycle. This increased accuracy and reduction in the trial duration are at the cost of increased sample size.

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.

Ethical Criteria for Improved Human Subject Protections in Phase I Healthy Volunteer Trials

Phase I healthy volunteer trials test the safety and tolerability of investigational pharmaceuticals. In them, participants are exposed to study-drug risks without the possibility of direct medical benefit and typically must spend days or weeks in a residential research facility. Monetary payments are used to incentivize enrollment and compensate participants for their time. Together, these features of phase I healthy volunteer trials create a research context that differs markedly from most other clinical research, including by enrolling disproportionate numbers of economically disadvantaged people of color as participants. Due to these unique trial features and participation patterns, traditional biomedical research oversight offers inadequate ethical and policy guidance for phase I healthy volunteer research. This article details five ethical criteria crafted to be responsive to the particularities of this type of research: translational science value, fair opportunity and burden sharing, fair compensation for service, experiential welfare, and enhanced voice and recourse.

A curve free Bayesian decision-theoretic design for phase Ia/Ib trials considering both safety and efficacy outcomes

A curve-free, Bayesian decision-theoretic two-stage design is proposed to select biological efficacious doses (BEDs) for phase Ia/Ib trials in which both toxicity and efficacy signals are observed. No parametric models are assumed to govern the dose-toxicity, dose-efficacy, and toxicity-efficacy relationships. We assume that the dose-toxicity curve is monotonic non-decreasing and the dose-efficacy curve is unimodal. In the phase Ia stage, a Bayesian model on the toxicity rates is used to locate the maximum tolerated dose. In the phase Ib stage, we model the dose-efficacy curve using a step function while continuing to monitor the toxicity rates. Furthermore, a measure of the goodness of fit of a candidate step function is proposed, and the interval of BEDs associated with the best fitting step function is recommended. At the end of phase Ib, if some doses are recommended as BEDs, a cohort of confirmation is recruited and assigned at these doses to improve the precision of estimates at these doses. Extensive simulation studies show that the proposed design has desirable operating characteristics across different shapes of the underlying true toxicity and efficacy curves.

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.

Lessons From the Development of the Immune Checkpoint Inhibitors in Oncology

Immunotherapies are becoming increasingly important in the treatment armamentarium of a variety of malignancies. Immune checkpoint inhibitors are the most representative drugs receiving regulatory approval over the past few years. In a recent study published in Clinical Cancer Research, we demonstrated that these agents are being developed faster than other prior anticancer therapies. All checkpoint inhibitors received priority review, being granted with at least one Food and Drug Administration expedited program. Hence, some of them are getting marketing approval after preliminary trials. The model continues to rely on phase I trials, designed with traditional models for dose definition, although a substantial number of patients are treated during the dose expansion cohorts. We demonstrated that efficacy and safety are reasonably predicted from the dose-finding portion of phase I trials with these agents, assuring a low treatment-related mortality for patients throughout the development process. In this article, we further discuss and summarize these findings and update some recent approval information for immune checkpoint inhibitors.

Prevalence of MDM2 amplification and coalterations in 523 advanced cancer patients in the MD Anderson phase 1 clinic

Background

TP53 is the most commonly mutated gene in cancer and codes for the best studied tumor suppressor, p53. MDM2 is involved in the negative regulation of p53 and itself serves as an oncogene, reported to be overexpressed in several cancer tumor types. In this retrospective study, we assessed the occurrence of MDM2 amplification among patients with various types of cancers and its association with clinical factors, other genetic aberrations, and response to targeted therapy in a phase I clinical trial setting.

Methods

Samples from patients with advanced solid tumors who had been referred to the MD Anderson phase I clinical trials program between January 2011 and January 2016 were collected and analyzed for MDM2 amplification using FoundationOne's genomic profiling assay. Patients whose tumors expressed MDM2 amplification were compared to those with tumors of the same histologic types without MDM2 amplification.

Results

We tested tumors from 523 patients, of which 23 (4.4%) had MDM2 amplification. The highest prevalence of MDM2 amplification was in sarcoma (57%), breast cancer (13%) and bladder cancer (9%). Six patients with liposarcoma were treated on phase I protocol with an MDM2 inhibitor. The most common molecular aberrations co-occurring with MDM2 amplification was CDK4 amplification (70%). TP53 mutation was also detected in 7 patients (30%).

Conclusion

MDM2 amplification was most commonly associated with liposarcoma. Concomitant alterations in additional genes such as CDK4 amplification and TP53 mutations, along with variable responses to targeted therapies including MDM2 inhibitors, suggest that further combinational studies are needed to target this population.

Older adults in phase I clinical trials: a comparative analysis of participation and clinical benefit rate among older adults versus middle age and AYA patients on phase I clinical trials with VEGF/VEGFR inhibitors

Background

Older adults aged 65 years and above remain underrepresented in cancer clinical trials. We hypothesized that older participation in early phase trials with VEGF/VEGFR (VEGF/R) inhibitors was lower than cancer prevalence in this group and lower than other age groups (middle age, adolescent/young adults [AYA]).

Results

Of 1489 patients, 278 were older adults (18%, median age 68.9y), 220 AYA (15%, median age 32.6 y), 991 middle age (67%, median age 53.8 y). Common malignancies included gastrointestinal (n = 438, 29%), gynecologic (n = 234, 16%), and thoracic/head/neck (n = 216, 15%). Median time to treatment failure did not vary significantly between the 3 age-based cohorts (3m in older adults, 3.5 m middle age, 3.3 m AYA). OR of achieving clinical benefit in older adults vs middle age (OR 1.10, p 0.19 [two-tailed], p 0.09 [one-tailed]) and AYA vs middle age (OR 0.85, p 0.31 [proportions z-test, two tailed], p 0.15 [one-tailed]) showed no significant differences.

Conclusions

Older adults accounted for <20% of participants on phase I clinical trials with VEGF/R inhibitors but those who participated were just as likely to achieve a clinical benefit as AYA and middle age patients. These findings merit further exploration into patient selection for early phase trials.

Methods

We identified and separated patients treated on VEGF/R-inhibitor-based phase I trials from 12/1/2004–07/31/2013 into 3 age-based cohorts, AYA (15–39y), middle age (40–64 y), older adults (65 y+). We analyzed clinical/treatment characteristics and response outcomes, calculating the odds ratios (OR) of clinical benefit (defined as SD ≥ 6months, PR, CR) for older adults and AYAs versus middle age participants.

Clinical genomic profiling to identify actionable alterations for investigational therapies in patients with diverse sarcomas

Background

There are currently no United States Food and Drug Administration approved molecularly matched therapies for sarcomas except gastrointestinal stromal tumors. Complicating this is the extreme diversity, heterogeneity, and rarity of these neoplasms. Few therapeutic options exist for relapsed and refractory sarcomas. In clinical practice many oncologists refer patients for genomic profiling hoping for guidance on treatment options after standard therapy. However, a systematic analysis of actionable mutations has yet to be completed. We analyzed genomic profiling results in patients referred to MD Anderson Cancer Center with advanced sarcomas to elucidate the frequency of potentially actionable genomic alterations in this population.

Methods

We reviewed charts of patients with advanced sarcoma who were referred to investigational cancer therapeutics department and had CLIA certified comprehensive genomic profiling (CGP) of 236 or 315 cancer genes in at least 50ng of DNA. Actionable alterations were defined as those identifying anti-cancer drugs on the market, in registered clinical trials, or in the Drug-Gene Interaction Database.

Results

Among the 102 patients analyzed median age was 45.5 years (range 8-76), M: F ratio 48:54. The most common subtypes seen in our study were leiomyosarcoma (18.6%), dedifferentiated liposarcoma (11%), osteosarcoma (11%), well-differentiated liposarcoma (7%), carcinosarcoma (6%), and rhabdomyosarcoma (6%). Ninety-five out of 102 patients (93%) had at least one genomic alteration identified with a mean of six mutations per patient. Of the 95 biopsy samples with identifiable genomic alterations, the most commonly affected genes were TP53 (31.4%), CDK4 (23.5%), MDM2 (21.6%), RB1 (18.6%), and CDKN2A/B (13.7%). Notable co-segregating amplifications included MDM2-CDK4 and FRS2-FGF. Sixteen percent of patients received targeted therapy based on CGP of which 50% had at least stable disease.

Conclusions

Incorporating CGP into sarcoma management may allow for more precise diagnosis and sub-classification of this diverse and rare disease, as well as personalized matching of patients to targeted therapies such as those available in basket clinical trials.

An adaptive dose-finding design based on both safety and immunologic responses in cancer clinical trials

Dose-finding in cancer clinical trials has been dominated by algorithmic designs on the principle that the highest tolerable dose is also the most effective dose. This assumption no longer applies to the biologic treatments that are characterized by different toxicity and/or efficacy profiles to the extent that the best therapeutic dose might be well below any dose that produces serious toxicity. As such, we propose a two-stage design with focus on immunotherapy trials, incorporating both safety and efficacy information. The 1^st stage establishes the safety profile of each dose, with escalation decisions based on likelihood principles. Continuous immunologic outcomes are used to evaluate the relative efficacy of the doses. The 2^nd stage employs an adaptive randomization to assign patients to doses showing higher efficacy. Safety is being continuously monitored throughout stage 2, where some doses may be 'closed' due to unacceptable toxicity. The proposed design is compared to the modified toxicity probability interval (mTPI) design using percent dose allocation and estimation of outcomes under different scenarios. We show that by using an efficacy-driven adaptive randomization with safety constraints, the allocation distribution is skewed towards more efficacious doses, and thus limit the number of patients exposed to toxic or non-therapeutic doses.

Isoquercetin as an Adjunct Therapy in Patients With Kidney Cancer Receiving First-Line Sunitinib (QUASAR): Results of a Phase I Trial

Sunitinib is the most commonly prescribed drug for advanced renal cell carcinoma in the first-line setting and has been associated with multiple adverse events related to its on–and off–target effects, including hand and foot syndrome and fatigue. It was hypothesized that sunitinib-induced fatigue may be related to off target inhibition of the AMPK enzyme, which results in impairment of energy-producing processes at a systemic level. Quercetin is a naturally occurring flavonol with established AMPK-stimulating activity. While clinical use of quercetin is limited by its poor bio-availability, quercetin-3-O-β-d-glucopyranoside, that is isoquercetin, has an improved pharmacokinetic profile. On the grounds of the in vitro stimulatory activity with respect to AMPk, we hypothesized that oral isoquercetin could improve fatigue in kidney cancer patients receiving sunitinib. Given the lack of data on the safety of isoquercetin given concomitantly with sunitinib, we conducted a phase I trial to assess the safety of GMP manufactured isoquercetin given at two dose levels (450 and 900 mg a day). In the 12-patient study cohort included in this study, isoquercetin was administered concomitantly with 50 mg sunitinib for a median 81 days (IQR, 75.5, 86.5). None of the 12 patients required isoquercetin suspension or isoquercetin dose reduction because of adverse events. No abnormalities in ECG, heart or lower limbs doppler ultrasound were detected. A statistically significant improvement was reported for the FACIT fatigue score (6.8 points; 95% CI: 2.8–10.8; p = 0.002) and for the FACIT Adverse Events score (18.9 points; 95% CI: 9.1–28.8; p < 0.001) after isoquercetin consumption vs. baseline. In this phase I trial, isoquercetin was remarkably safe, with a preliminary signal of activity in terms of improvement of sunitinib adverse events.

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.

Toxicity-dependent feasibility bounds for the escalation with overdose control approach in phase I cancer trials

Phase I trials of anti-cancer therapies aim to identify a maximum tolerated dose (MTD), defined as the dose that causes unacceptable toxicity in a target proportion of patients. Both rule-based and model-based methods have been proposed for MTD recommendation. The escalation with overdose control (EWOC) approach is a model-based design where the dose assigned to the next patient is one that, given all available data, has a posterior probability of exceeding the MTD equal to a pre-specified value known as the feasibility bound. The aim is to conservatively dose-escalate and approach the MTD, avoiding severe overdosing early on in a trial. The EWOC approach has been applied in practice with the feasibility bound either fixed or varying throughout a trial, yet some of the methods may recommend incoherent dose-escalation, that is, an increase in dose after observing severe toxicity at the current dose. We present examples where varying feasibility bounds have been used in practice, and propose a toxicity-dependent feasibility bound approach that guarantees coherent dose-escalation and incorporates the desirable features of other EWOC approaches. We show via detailed simulation studies that the toxicity-dependent feasibility bound approach provides improved MTD recommendation properties to the original EWOC approach for both discrete and continuous doses across most dose-toxicity scenarios, with comparable performance to other approaches without recommending incoherent dose escalation. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Response Assessment in Paediatric Phase I Trials According to RECIST Guidelines: Survival Outcomes, Patterns of Progression and Relevance of Changes in Tumour Measurements

INTRODUCTION

RECIST guidelines constitute the reference for radiological response assessment in most paediatric trials of anticancer agents. However, these criteria have not been validated in children. We evaluated the outcomes and patterns of progression of children/adolescents enrolled in phase I trials in two paediatric drug development units.

METHODS

Patients aged ≤21 assessed with RECIST (v1.0 or v1.1) were eligible. Clinico-radiological data were analysed using Mann-Whitney U and log-rank tests to correlate response categories and sum of longest diameters (SLD) with time-to-event variables and overall survival (OS).

RESULTS

Sixty-one patients (71 enrolments) were evaluated; median age: 12.7 years (range, 3.1-20.9). Overall, 7% achieved complete/partial response (n = 5) and 31% disease stabilisation (n = 22). Median (95% CI) OS (in months) was 29.1 (27.6-30.6) with complete/partial response, 8.9 (2.0-15.8) with stable disease and 2.8 (2.3-3.3) with disease progression (P < 0.001); 32.6% patients with measurable disease presented exclusive progression of existing non-target lesions and/or new lesions. The change in SLD at best response showed a linear correlation with duration of response (r = -0.605; P = 0.004) and time on trial (r = -0.61; P = 0.003), but the change in SLD at progression did not correlate with time to progression (r = -0.219; P = 0.206).

CONCLUSIONS

Response assessment according to RECIST correlated with OS in children/adolescents treated on phase I trials. The reduction in SLD at best response correlated with more prolonged responses. Tumour size did not constitute an optimal method to assess disease progression in one third of patients with measurable disease. Further refinement of current response assessment guidelines will enable the development of paediatric-specific radiological criteria.

Adaptive dose modification for phase I clinical trials

Most phase I dose-finding methods in oncology aim to find the maximum-tolerated dose from a set of prespecified doses. However, in practice, because of a lack of understanding of the true dose-toxicity relationship, it is likely that none of these prespecified doses are equal or reasonably close to the true maximum-tolerated dose. To handle this issue, we propose an adaptive dose modification (ADM) method that can be coupled with any existing dose-finding method to adaptively modify the dose, when it is needed, during the course of dose finding. To reflect clinical practice, we divide the toxicity probability into three regions: underdosing, acceptable, and overdosing regions. We adaptively add a new dose whenever the observed data suggest that none of the investigational doses are likely to be located in the acceptable region. The new dose is estimated via a nonparametric dose-toxicity model based on local polynomial regression. The simulation study shows that ADM substantially outperforms the similar existing method. We applied ADM to a phase I cancer trial. Copyright © 2016 John Wiley & Sons, Ltd.

Modelling semi-attributable toxicity in dual-agent phase I trials with non-concurrent drug administration

In oncology, combinations of drugs are often used to improve treatment efficacy and/or reduce harmful side effects. Dual‐agent phase I clinical trials assess drug safety and aim to discover a maximum tolerated dose combination via dose‐escalation; cohorts of patients are given set doses of both drugs and monitored to see if toxic reactions occur. Dose‐escalation decisions for subsequent cohorts are based on the number and severity of observed toxic reactions, and an escalation rule. In a combination trial, drugs may be administered concurrently or non‐concurrently over a treatment cycle. For two drugs given non‐concurrently with overlapping toxicities, toxicities occurring after administration of the first drug yet before administration of the second may be attributed directly to the first drug, whereas toxicities occurring after both drugs have been given some present ambiguity; toxicities may be attributable to the first drug only, the second drug only or the synergistic combination of both. We call this mixture of attributable and non‐attributable toxicity semi‐attributable toxicity. Most published methods assume drugs are given concurrently, which may not be reflective of trials with non‐concurrent drug administration. We incorporate semi‐attributable toxicity into Bayesian modelling for dual‐agent phase I trials with non‐concurrent drug administration and compare the operating characteristics to an approach where this detail is not considered. Simulations based on a trial for non‐concurrent administration of intravesical Cabazitaxel and Cisplatin in early‐stage bladder cancer patients are presented for several scenarios and show that including semi‐attributable toxicity data reduces the number of patients given overly toxic combinations. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Escalation with Overdose Control is More Efficient and Safer than Accelerated Titration for Dose Finding

The standard 3 + 3 or "modified Fibonacci" up-and-down (MF-UD) method of dose escalation is by far the most used design in dose-finding cancer trials. However, MF-UD has always shown inferior performance when compared with its competitors regarding number of patients treated at optimal doses. A consequence of using less effective designs is that more patients are treated with doses outside the therapeutic window. In June 2012, the U S Food and Drug Administration (FDA) rejected the proposal to use Escalation with Overdose Control (EWOC), an established dose-finding method which has been extensively used in FDA-approved first in human trials and imposed a variation of the MF-UD, known as accelerated titration (AT) design. This event motivated us to perform an extensive simulation study comparing the operating characteristics of AT and EWOC. We show that the AT design has poor operating characteristics relative to three versions of EWOC under several practical scenarios. From the clinical investigator's perspective, lower bias and mean square error make EWOC designs preferable than AT designs without compromising safety. From a patient's perspective, uniformly higher proportion of patients receiving doses within an optimal range of the true MTD makes EWOC designs preferable than AT designs.

Clinical characteristics and outcomes of pediatric oncology patients with aggressive biology enrolled in phase I clinical trials designed for adults: the university of Texas MD anderson cancer center experience

Background

Children (patients ≤ 18 years of age) are not usually included on pharmaceutical industry sponsored Phase I trials.

Methods

We reviewed the medical records of 40 patients ≤ 18 years treated in ≥ 1 phase I trial at MD Anderson.

Results

The median OS was 8.5 months (95% CI, 5.5-13.2 months). In the multivariate analysis, age ≥15 only predicted increased OS (P = 0.0065), and >3 prior therapies (P = 0.053) predicted decreased OS. The median PFS was 2.8 months (95% CI, 2.3-4.1 months). In the multivariate analysis, independent factors that predicted increased PFS were age ≥15 years (P < 0.001) and prior radiation therapy (P = 0.049); performance status >1 (P < 0.001) and >3 prior therapies (P = 0.002) predicted decreased PFS. RMH score ≥ 2 and MDACC score ≥ 3 were associated with decreased median OS (P = 0.029 and P = 0.031 respectively).

Conclusions

It is feasible to conduct phase I studies in pediatric patients based on adult protocols. In the era of targeted therapy more trials should allow pediatric patients earlier in the drug development especially if deemed safe in adults in early phase trials.

Translational Relevance

Most pharmaceutical industry sponsored trials exclude patients less than 18 years in phase I clinical trials. Even in the era of targeted therapy pediatric patients usually have to wait for most phases of trials to be completed in adults before being allowed to enroll in clinical trials of new therapies, even in the advanced metastatic and relapsed setting. Some investigator initiated phase 1 trials of combinations of US FDA approved agents allow patients less than 18 years. We report the preliminary analyses of the outcomes of pediatric patients enrolled in phase I studies initially designed for adults, but allowing for enrollment of patients under 18.

Exploring Ethnic Differences in Toxicity in Early-Phase Clinical Trials for Oncology Drugs

During oncology drug development, it is important that ethnic differences are evaluated to determine the optimal dose and administration schedule in a new region based on the clinical data from other regions. The objective of this study was to explore the possibility of detecting ethnic differences in toxicity during early-phase clinical trials. Data were reviewed from phase I clinical trials for new drug applications conducted in Japan and Western countries. The maximum tolerated doses (MTDs), recommended phase II doses (RP2Ds), and approved doses in Japan were compared with those in Western countries. There were 4 of 28 drugs eligible for analysis that showed differences in MTDs or RP2Ds between Japanese and Western patients. Differences in MTDs or RP2Ds in 2 phase I trials were associated with ethnic differences in toxicity. It may be worthwhile to evaluate ethnic differences in toxicity during early-phase clinical trials for oncology drugs.

Phase I design for completely or partially ordered treatment schedules

The majority of methods for the design of phase I trials in oncology are based upon a single course of therapy, yet in actual practice, it may be the case that there is more than one treatment schedule for any given dose. Therefore, the probability of observing a dose-limiting toxicity may depend upon both the total amount of the dose given, as well as the frequency with which it is administered. The objective of the study then becomes to find an acceptable combination of both dose and schedule. Past literature on designing these trials has entailed the assumption that toxicity increases monotonically with both dose and schedule. In this article, we relax this assumption for schedules and present a dose-schedule finding design that can be generalized to situations in which we know the ordering between all schedules and those in which we do not. We present simulation results that compare our method with other suggested dose-schedule finding methodology.

Specifications of a continual reassessment method design for phase I trials of combined drugs

In studies of combinations of agents in phase I oncology trials, the dose-toxicity relationship may not be monotone for all combinations, in which case the toxicity probabilities follow a partial order. The continual reassessment method for partial orders (PO-CRM) is a design for phase I trials of combinations that leans upon identifying possible complete orders associated with the partial order. This article addresses some practical design considerations not previously undertaken when describing the PO-CRM. We describe an approach in choosing a proper subset of possible orderings, formulated according to the known toxicity relationships within a matrix of combination therapies. Other design issues, such as working model selection and stopping rules, are also discussed. We demonstrate the practical ability of PO-CRM as a phase I design for combinations through its use in a recent trial designed at the University of Virginia Cancer Center.