New Paradigm in Dose-Finding Trials: Patient-Specific Dosing and Beyond Phase I

The Right Dose: Results of a Patient Advocate-Led Survey of Individuals With Metastatic Breast Cancer Regarding Treatment-Related Side Effects and Views About Dosage Assessment to Optimize Quality of Life

PURPOSE

Although patients with metastatic breast cancer (MBC) have been living longer with the advent of more effective treatments such as targeted therapy and immunotherapy, the disease remains incurable, and most patients will undergo therapy indefinitely. When beginning therapy, patients are typically prescribed dose often based upon the maximum tolerated dose identified in phase I clinical trials. However, patients' perspectives about tolerability and willingness to discuss individualized dosing of drugs upon initiation of a new regimen and throughout the course of treatment have not been comprehensively evaluated.

METHODS

Patient advocates and medical oncologists from the Patient-Centered Dosing Initiative (PCDI) developed a survey to ascertain the prevalence and severity of MBC patients' treatment-related side effects, the level of patient-physician communication, mitigation strategies, perception about the relative efficacy of higher versus lower doses, and willingness to discuss alternative dosing. The PCDI distributed the anonymous confidential online survey in August 2020 to individuals with self-reported MBC.

RESULTS

One thousand and two hundred twenty-one patients with MBC completed the survey. 86.1% (n = 1,051) reported experiencing at least one significant treatment-related side effect, and of these, 20.3% (n = 213) visited the emergency room/hospital and 43.2% (n = 454) missed at least one treatment. Nearly all patients with side effects (97.6%, n = 1,026) informed their doctor and 81.7% (n = 838) received assistance. Of the 556 patients given a dose reduction for side-effect mitigation, 82.6% (n = 459) reported relief. Notably, majority of patients (53.3%, n = 651) do not believe that higher dose is always more effective than lower dose, and 92.3% (n = 1,127) would be willing to discuss flexible dosing options with their physicians based upon personal characteristics to optimize quality of life.

CONCLUSION

Given that the majority of patients with MBC experienced at least one substantial treatment-related side effect and most patients given a dose reduction reported improvement, innovative dosage-related strategies are warranted to sustain and improve patients' well-being. Patient-physician discussions in which the patient's unique attributes and circumstances are assessed upon initiation of new treatment and throughout the course of therapy may facilitate the identification of the most favorable dose for each patient, and the majority of patients would be receptive to this approach.

A flexible dose-response modeling framework based on continuous toxicity outcomes in phase I cancer clinical trials

BACKGROUND

The past few decades have seen remarkable developments in dose-finding designs for phase I cancer clinical trials. While many of these designs rely on a binary toxicity response, there is an increasing focus on leveraging continuous toxicity responses. A continuous toxicity response pertains to a quantitative measure represented by real numbers. A higher value corresponds not only to an elevated likelihood of side effects for patients but also to an increased probability of treatment efficacy. This relationship between toxicity and dose is often nonlinear, necessitating flexibility in the quest to find an optimal dose.

METHODS

A flexible, fully Bayesian dose-finding design is proposed to capitalize on continuous toxicity information, operating under the assumption that the true shape of the dose-toxicity curve is nonlinear.

RESULTS

We conduct simulations of clinical trials across varying scenarios of non-linearity to evaluate the operational characteristics of the proposed design. Additionally, we apply the proposed design to a real-world problem to determine an optimal dose for a molecularly targeted agent.

CONCLUSIONS

Phase I cancer clinical trials, designed within a fully Bayesian framework with the utilization of continuous toxicity outcomes, offer an alternative approach to finding an optimal dose, providing unique benefits compared to trials designed based on binary toxicity outcomes.

A Phase I, Multicenter, Open-Label, First-in-Human Study of DS-6157a in Patients with Advanced Gastrointestinal Stromal Tumor

PURPOSE

To evaluate DS-6157a, an antibody-drug conjugate targeting G protein-coupled receptor 20 (GPR20), in gastrointestinal stromal tumors (GIST).

PATIENTS AND METHODS

In this phase I multicenter, open-label, multiple-dose study, patients with previously treated advanced GIST received intravenous DS-6157a on Day 1 of 21-day cycles, with a starting dose of 1.6 mg/kg. The primary objective evaluated the safety and tolerability of DS-6157a, while determining dose-limiting toxicity (DLT) and the MTD. Secondary objectives included plasma pharmacokinetics parameters, plasma antidrug antibodies (ADA), and efficacy.

RESULTS

A total of 34 patients enrolled. DS-6157a was well tolerated, with DLTs in 4 patients (11.8%) at doses of 6.4 mg/kg, 9.6 mg/kg, and 12.8 mg/kg; the MTD was determined to be 6.4 mg/kg. Treatment-emergent adverse events (TEAE) grade ≥3 occurred in 17 patients (50.0%), including decreased platelet count (23.5%), anemia (20.6%), decreased neutrophil count (14.7%), and decreased white blood cell count (11.8%). Four patients (11.8%) experienced serious adverse events related to DS-6157a. Six patients died with 5 due to disease progression and 1 due to DS-6157a-related TEAE. Tumor shrinkage was observed in 7 patients (20.6%), and 1 patient (2.9%) achieved a partial response. Plasma concentrations and exposure of intact DS-6157a, DXd, and total anti-GPR20 antibody all demonstrated a dose-dependent profile. No treatment-emergent ADAs were observed.

CONCLUSIONS

Targeting GPR20 with DS-6157a was tolerated in patients with advanced GIST with tumor shrinkage demonstrated in KIT/PDGFRA wild-type GIST. However, the study did not proceed further due to lower efficacy outcomes than anticipated.

Dose Optimization in Oncology Drug Development: The Emerging Role of Pharmacogenomics, Pharmacokinetics, and Pharmacodynamics

Drugs' safety and effectiveness are evaluated in randomized, dose-ranging trials in most therapeutic areas. However, this is only sometimes feasible in oncology, and dose-ranging studies are mainly limited to Phase 1 clinical trials. Moreover, although new treatment modalities (e.g., small molecule targeted therapies, biologics, and antibody-drug conjugates) present different characteristics compared to cytotoxic agents (e.g., target saturation limits, wider therapeutic index, fewer off-target side effects), in most cases, the design of Phase 1 studies and the dose selection is still based on the Maximum Tolerated Dose (MTD) approach used for the development of cytotoxic agents. Therefore, the dose was not optimized in some cases and was modified post-marketing (e.g., ceritinib, dasatinib, niraparib, ponatinib, cabazitaxel, and gemtuzumab-ozogamicin). The FDA recognized the drawbacks of this approach and, in 2021, launched Project Optimus, which provides the framework and guidance for dose optimization during the clinical development stages of anticancer agents. Since dose optimization is crucial in clinical development, especially of targeted therapies, it is necessary to identify the role of pharmacological tools such as pharmacogenomics, therapeutic drug monitoring, and pharmacodynamics, which could be integrated into all phases of drug development and support dose optimization, as well as the chances of positive clinical outcomes.

Patient-centered dosing: oncologists' perspectives about treatment-related side effects and individualized dosing for patients with metastatic breast cancer (MBC)

PURPOSE

Although metastatic breast cancer (MBC) is treatable, it is not curable and most patients remain on treatment indefinitely. While oncologists commonly prescribe the recommended starting dose (RSD) from the FDA-approved label, patient tolerance may differ from that seen in clinical trials. We report on a survey of medical oncologists' perspectives about treatment-related toxicity and willingness to discuss flexible dosing with patients.

METHODS

We disseminated a confidential survey via social media/email in Spring 2021. Eligible respondents needed to be US-based medical oncologists with experience treating patients with MBC.

RESULTS

Of 131 responses, 119 were eligible. Physicians estimated that 47% of their patients reported distressing treatment-related side effects; of these, 15% visited the Emergency Room/hospital and 37% missed treatment. 74% (n = 87) of doctors reported improvement of patient symptoms after dose reduction. 87% (n = 104) indicated that they had ever, if appropriate, initiated treatment at lower doses. Most (85%, n = 101) respondents did not believe that the RSD is always more effective than a lower dose and 97% (n = 115) were willing to discuss individualized dosing with patients.

CONCLUSION

Treatment-related side effects are prevalent among patients with MBC, resulting in missed treatments and acute care visits. To help patients tolerate treatment, oncologists may decrease initial and/or subsequent doses. The majority of oncologists reject the premise that a higher dose is always superior and are willing to discuss individualized dosing with patients. Given potential improvements regarding quality of life and clinical care, dose modifications should be part of routine shared decision-making between patients and oncologists.

Multidimensional Phase I Dose Ranging Trials for Stroke Recovery Interventions: Key Challenges and How to Address Them

Despite an increase in the amount of published stroke recovery research, interventions have failed to markedly affect the trajectory of recovery poststroke. We argue that early-phase research to systematically investigate dose is an important contributor to advance the science underpinning stroke recovery. In this article, we aim to (a) define the problem of insufficient use of a systematic approach to early-phase, multidimensional dose articulation research and (b) propose a solution that applies this approach to design a multidimensional phase I trial to identify the maximum tolerated dose (MTD). We put forward a design template as a decision support tool to increase knowledge of how to develop a phase I dose-ranging trial for nonpharmaceutical stroke recovery interventions. This solution has the potential to advance the development of efficacious stroke recovery interventions, which include activity-based rehabilitation interventions.

Inferences About Drug Safety in Phase III Trials in Oncology: Examples From Advanced Prostate Cancer

BACKGROUND

Safety is a central consideration when choosing between multiple medications with similar efficacy. We aimed to evaluate whether adverse event (AE) profiles of 3 such drugs in advanced prostate cancer could be distinguished based on published literature.

METHODS

We assessed consistency in AE reporting, AE risk in placebo arms, and methodology used for risk estimates and quantification of statistical uncertainty in randomized placebo-controlled phase III trials of apalutamide, enzalutamide, and darolutamide in advanced prostate cancer.

RESULTS

Seven included clinical trials enrolled a total of 9215 participants (range = 1051-1715 per trial) across 3 prostate cancer disease states. Within disease states, baseline patient characteristics appeared similar between trials. Of 54 distinct AE types in total, only 3 (fatigue, hypertension, and seizure) were reported by all 7 trials. Absolute risks of AEs in the placebo arms differed systematically and more than twofold between trials, which was associated with visit frequency and resulted in different degrees of uncertainty in AE profiles between trials. No trial used inferential methodology to quantify statistical uncertainty in AE risks, but 6 of 7 trials drew overall conclusions. Two trials concluded that there was no elevated AE risk because of the intervention, including the trial of darolutamide, which had the greatest statistical uncertainty.

CONCLUSIONS

Rigorous comparison of drug safety was precluded by heterogeneity in AE reporting, variation in AE risks in the placebo arms, and lack of inferential statistical methodology, underscoring considerable opportunities to improve how AE data are collected, analyzed, and interpreted in oncology trials.

Flexible, rule-based dose escalation: The cohort-sequence design

Phase I oncology trials seek to acquire preliminary information on the safety of novel treatments. In current practice, most such trials employ rule-based designs that determine whether to escalate the dose using data from the current dose only. The most popular of these, the 3 + 3, is simple and familiar but inflexible and inefficient. We propose a rule-based design that addresses these deficiencies. Our method, which we denote the cohort-sequence design, is defined by a sequence of J increasing cohort sizes n = ( n 1 , … , n J ) and corresponding critical values b = ( b 1 , … , b J ) . The idea is to begin with a small cohort size n 1 and escalate through the planned doses, increasing the cohort size when we encounter toxicities. By selection of J and a safety threshold tuning parameter θ, one can create a design that will efficiently identify a target toxicity rate, potentially including a built-in dose-expansion cohort. We compared our designs to the 3 + 3 under a range of toxicity scenarios, observing that our approach generally rapidly identifies an MTD without enrolling patients unnecessarily at low doses where both toxicity and response rates are likely to be low. We have implemented the design in the R package cohortsequence.

Dose-escalation strategies which use subgroup information

Dose-escalation trials commonly assume a homogeneous trial population to identify a single recommended dose of the experimental treatment for use in future trials. Wrongly assuming a homogeneous population can lead to a diluted treatment effect. Equally, exclusion of a subgroup that could in fact benefit from the treatment can cause a beneficial treatment effect to be missed. Accounting for a potential subgroup effect (ie, difference in reaction to the treatment between subgroups) in dose-escalation can increase the chance of finding the treatment to be efficacious in a larger patient population. A standard Bayesian model-based method of dose-escalation is extended to account for a subgroup effect by including covariates for subgroup membership in the dose-toxicity model. A stratified design performs well but uses available data inefficiently and makes no inferences concerning presence of a subgroup effect. A hypothesis test could potentially rectify this problem but the small sample sizes result in a low-powered test. As an alternative, the use of spike and slab priors for variable selection is proposed. This method continually assesses the presence of a subgroup effect, enabling efficient use of the available trial data throughout escalation and in identifying the recommended dose(s). A simulation study, based on real trial data, was conducted and this design was found to be both promising and feasible.

Current challenges in clinical development of "targeted therapies": the case of acute myeloid leukemia

A fundamental difficulty in testing "targeted therapies" in acute myeloid leukemia (AML) is the limitations of preclinical models in capturing inter- and intrapatient genomic heterogeneity. Clinical trials typically focus on single agents despite the routine emergence of resistant subclones and experience in blast-phase chronic myeloid leukemia and acute promyelocytic leukemia arguing against this strategy. Inclusion of only relapsed-refractory, or unfit newly diagnosed, patients risks falsely negative results. There is uncertainty as to whether eligibility should require demonstration of the putative target and regarding therapeutic end points. Although use of in vivo preclinical models employing primary leukemic cells is first choice, newer preclinical models including "organoids" and combinations of pharmacologic and genetic approaches may better align models with human AML. We advocate earlier inclusion of combinations ± chemotherapy and of newly diagnosed patients into clinical trials. When a drug plausibly targets a pathway uniquely related to a specific genetic aberration, eligibility should begin with this subset, including patients with other malignancies, with subsequent extension to other patients. In other cases, a more open-minded approach to initial eligibility would facilitate quicker identification of responsive subsets. Complete remission without minimal residual disease seems a particularly useful short-term end point. Genotypic and phenotypic studies should be prespecified and performed routinely to distinguish responders from nonresponders.

The Integrated Web Portal for Escalation with Overdose Control (EWOC)

In this paper, we present the design and implementation of a novel web portal for the cancer phase I clinical trial design method Escalation with Overdose Control (EWOC). The web portal has two major components: a web-based dose finding calculator; and a standalone and downloadable dose finding software which can be installed on Windows operating systems. The web-based dose finding calculator uses industry standards and is a database-driven and distributed computing platform for designing and conducting dose finding in cancer phase I clinical trials utilizing EWOC methodology. The web portal is developed using open source software: PHP, JQuery, R and OpenBUGS. It supports any standard browsers with internet connection. The web portal can be accessed at: http://biostatistics.csmc.edu.

Translating cellular therapies from bench to bedside for amyotrophic lateral sclerosis

The last decade has witnessed an increasing number of biologic (e.g., cell- or viral vector-based) therapeutics supported by preclinical efficacy data for the treatment of afflictions to the CNS. While some international investigators have undertaken preliminary clinical safety studies, published literature indicate varying degrees of rigor with respect to study design and technical approach. To our knowledge, ours is the first group to have systematically generated preclinical validation data for a delivery approach and translated this into a Phase I trial attempting to covalidate the safety of a direct, targeted delivery approach, as well as a cell-based therapeutic. This article discusses the rationale for cell-based therapy in amyotrophic lateral sclerosis and several of the unique considerations encountered during this process.

Effectiveness of adaptive designs for phase II cancer trials

BACKGROUND

Evaluation of new therapies for cancer has suffered a paradigm shift in the last years. The use of innovative and more efficient designs is a priority for the scientific community; nevertheless, the use of this kind of design is not yet wide spread.

PURPOSE

In this paper will examine the effectiveness of adaptive designs compared with traditional designs in phase II clinical trials.

METHODS

We reviewed a group of abstracts records between 1980 and 2008 and extracted data regarding statistical design, year of publication, kind of evaluated product, localization, sample size and results of the trials.

RESULTS

Nine hundred and eighty-nine clinical trials were identified and from them 333 traditional designs and 19 adaptive designs were included in the review. Two hundred statistical papers were located and 16 were included in the review. The most frequent designs were Standard up and down designs, continual reassessment methods and its variation and designs with Bayesian approaches. More than 80% of the studies evaluated different schemes of chemotherapy. Adaptive designs evaluated only drugs and not any kind of treatment combination and the most often localizations evaluated in both designs were lung, haematology malignancies, and colon cancers.

CONCLUSIONS

Adaptive designs are more efficient from the statistical point of view but they are not yet widely used because of complex and computationally intensive methods needed, substantial effort for planning the trials and lack of regulatory guidance.

Phase I oncology studies: evidence that in the era of targeted therapies patients on lower doses do not fare worse

PURPOSE

To safely assess new drugs, cancer patients in initial cohorts of phase I oncology studies receive low drug doses. Doses are successively increased until the maximum tolerated dose (MTD) is determined. Because traditional chemotherapy is often more effective near the MTD, ethical concerns have been raised about administration of low drug doses to phase I patients. However, a substantial portion of oncology trials now investigate targeted agents, which may have different dose-response relationships than cytotoxic chemotherapies.

EXPERIMENTAL DESIGN

Twenty-four consecutive trials treating 683 patients between October 1, 2004, and June 30, 2008, at MD Anderson Cancer Center were analyzed. Patients were assigned to a low-dose (<or=25% MTD), medium-dose (25-75% MTD), or high-dose (>or=75% MTD) group, and groups were compared for response rate, time-to-treatment failure, progression-free survival, overall survival, and toxicity. To remove negatively biasing data from the high-dose group, in a second analysis, patients treated above the MTD were excluded (high-dose group, 75-100% MTD). Of the 683 patients, 97.7% received targeted agents.

RESULTS

Even when excluding patients above the MTD, there was an early trend favoring the low- versus high-dose group in time-to-treatment failure, with 32.9% versus 25.2% of patients on therapy at 3 months (P = 0.08). In addition, the low-dose group fared at least as well as the other groups in all other outcomes, including response rate, progression-free survival, overall survival, and toxicity.

CONCLUSIONS

These data may help alleviate concerns that patients who receive low drug doses on contemporary phase I oncology trials fare worse and suggest targeted agents may have different dose-response relationships than cytotoxic chemotherapies.

A phase I pharmacokinetic and pharmacodynamic study of CKD-732, an antiangiogenic agent, in patients with refractory solid cancer

We conducted a phase I trial of the antiangiogenic agent 6-O-(4-dimethylaminoethoxy) cinnamoyl fumagillol hemioxalate (CKD-732). Our aims were to determine the maximum tolerated dose (MTD), pharmacokinetics (PK), and safety profiles as well as identify the biologically active dose (BAD) from ex vivo pharmacodynamics (PD) and biomarkers of CKD-732. Using a dose escalation schedule, 19 patients with refractory solid tumors were enrolled at dose levels of CKD-732 ranging from 1 to 15 mg/m(2) given twice weekly for 2 weeks followed by a 1-week rest. No treatment-related deaths occurred in this study. Confusion and insomnia were dose-limiting toxicities (DLTs), and MTD was 15 mg/m(2). The area under the concentration-time curve (AUC) and maximum concentration (Cmax) increased dose dependently with increasing doses. The BAD was 5 mg/m(2) according to ex vivo PD. A decrement in soluble vascular endothelial growth factor receptor-3 (sVEGF-3) level was correlated with a reduction in tumor size (r = 0.54, P = 0.045). The results from this study showed an MTD of 15 mg/m(2) and a BAD of 5 mg/m(2).

Dose escalation methods in phase I cancer clinical trials

Phase I clinical trials are an essential step in the development of anticancer drugs. The main goal of these studies is to establish the recommended dose and/or schedule of new drugs or drug combinations for phase II trials. The guiding principle for dose escalation in phase I trials is to avoid exposing too many patients to subtherapeutic doses while preserving safety and maintaining rapid accrual. Here we review dose escalation methods for phase I trials, including the rule-based and model-based dose escalation methods that have been developed to evaluate new anticancer agents. Toxicity has traditionally been the primary endpoint for phase I trials involving cytotoxic agents. However, with the emergence of molecularly targeted anticancer agents, potential alternative endpoints to delineate optimal biological activity, such as plasma drug concentration and target inhibition in tumor or surrogate tissues, have been proposed along with new trial designs. We also describe specific methods for drug combinations as well as methods that use a time-to-event endpoint or both toxicity and efficacy as endpoints. Finally, we present the advantages and drawbacks of the various dose escalation methods and discuss specific applications of the methods in developmental oncotherapeutics.

Translation of Innovative Designs Into Phase I Trials

Purpose

Phase I clinical trials of new anticancer therapies determine suitable doses for further testing. Optimization of their design is vital in that they enroll cancer patients whose well-being is distinctly at risk. This study examines the effectiveness of knowledge transfer about more effective statistical designs to clinical practice.

Methods

We examined abstract records of cancer phase I trials from the Science Citation Index database between 1991 and 2006 and classified them into clinical (dose-finding trials) and statistical trials (methodologic studies of dose-escalation designs). We then mapped these two sets by tracking which trials adopted new statistical designs.

Results

One thousand two hundred thirty-five clinical and 90 statistical studies were identified. Only 1.6% of the phase I cancer trials (20 of 1,235 trials) followed a design proposed in one of the statistical studies. These 20 clinical studies showed extensive lags between publication of the statistical paper and its translation into a clinical paper. These 20 clinical trials followed Bayesian adaptive designs. The remainder used variations of the standard up-and-down method.

Conclusion

A consequence of using less effective designs is that more patients are treated with doses outside the therapeutic window. Simulation studies have shown that up-and-down designs treated only 35% of patients at optimal dose levels versus 55% for Bayesian adaptive designs. This implies needless loss of treatment efficacy and, possibly, lives. We suggest that regulatory agencies (eg, US Food and Drug Administration) should proactively encourage the adoption of statistical designs that would allow more patients to be treated at near-optimal doses while controlling for excessive toxicity.

Chemoinformatic analysis of NCI preclinical tumor data: evaluating compound efficacy from mouse xenograft data, NCI-60 screening data, and compound descriptors

We provide a chemoinformatic examination of the NCI public human tumor xenograft data to explore relationships between small molecules, treatment modality, efficacy, and toxicity. Efficacy endpoints of tumor weight reduction (TW) and survival time increase (ST) compared to tumor bearing control mice were augmented by a toxicity measure, defined as the survival advantage of treated versus control animals (TX). These endpoints were used to define two independent therapeutic indices (TIs) as the ratio of efficacy (TW or ST) to toxicity (TX). Linear models predictive of xenograft endpoints were successfully constructed (0.67 < r(2) < or = 0.74)(observed_versus_predicted) using a model comprised of variables in treatment modality, chemoinformatic descriptors, and in vitro cell growth inhibition in the NCI 60-cell assay. Cross-validation analysis based on randomly chosen training subsets found these predictive correlations to be robust. Model-based sensitivity analysis found chemistry and growth inhibition to provide the best, and treatment modality the worst, indicators of xenograft endpoint. The poor predictive power derived from treatment alone appears to be of less importance to xenograft outcome for compounds having strongly similar chemical and biological features. ROC-based model validation found a 70% positive predictive value for distinguishing FDA approved oncology agents from available xenograft tested compounds. Additional chemoinformatic applications are provided that relate xenograft outcome to biological pathways and putative mechanism of compound action. These results find a strong relationship between xenograft efficacy and pathways comprised of genes having highly correlated mRNA expressions. Our analysis demonstrates that chemoinformatic studies utilizing a combination of xenograft data and in vitro preclinical testing offer an effective means to identify compound classes with superior efficacy and reduced toxicity.

Review: new biological insights in early clinical studies

First in human phase I trials are an unaviodable gateway to the development of new anticancer therapies. The discovery of target therapies have significantly changed the process of clinical drug development.This short review will focus on the main features including knowledge of biological aspects, methodology and adequacy of design and of performance of early clinical studies.

How participants in cancer trials are chosen: ethics and conflicting interests

The development of new drugs for cancer is extremely complex and expensive, and poses ethical problems. In this article we will review issues in clinical trials for cancer drugs that will cast new light on the doctor-patient relationship and their interaction with industry, the health service, academic and administrative organizations. We show that the Declaration of Helsinki cannot be applied to cancer trials as it is currently written, that patients do not and perhaps cannot give fully informed consent to participate, and that the results of clinical trials do not translate into daily practice in a way that patients might expect.