RESUMEN

In targeted therapies and immunotherapies, the occurrence of low-grade (e.g., grade 1-2) toxicities (LGT) is common, while dose-limiting toxicities (DLT) are relatively rare. As a result, conventional phase I trial designs, solely based on DLTs and disregarding milder toxicities, are problematic when evaluating these novel therapies. Methods: To address this issue, we propose a novel phase I design called a multiple-constraint keyboard (MC-Keyboard) that integrates multiple toxicity constraints, accounting for both DLT and LGT, for precise dose escalation and de-escalation, and identification of the maximum tolerated dose (MTD). As a model-assisted design, an important feature of MC-Keyboard is that its dose-escalation or de-escalation rule can be pretabulated and incorporated into the trial protocol before the initiation of the trial, greatly simplifying its implementation. Results: The simulation study showed that the MC-Keyboard had high accuracy in identifying the MTD and is safer than some existing designs. Conclusion: The MC-Keyboard provides a novel, simple, and safe approach to assessing safety and identifying the MTD for targeted therapies and immunotherapies.

RESUMEN

Dose-finding studies play a crucial role in drug development by identifying the optimal dose(s) for later studies while considering tolerability. This not only saves time and effort in proceeding with Phase III trials but also improves efficacy. In an era of precision medicine, it is not ideal to assume patient homogeneity in dose-finding studies as patients may respond differently to the drug. To address this, we propose a personalized dose-finding algorithm that assigns patients to individualized optimal biological doses. Our design follows a two-stage approach. Initially, patients are enrolled under broad eligibility criteria. Based on the Stage 1 data, we fit a regression model of toxicity and efficacy outcomes on dose and biomarkers to characterize treatment-sensitive patients. In the second stage, we restrict the trial population to sensitive patients, apply a personalized dose allocation algorithm, and choose the recommended dose at the end of the trial. Simulation study shows that the proposed design reliably enriches the trial population, minimizes the number of failures, and yields superior operating characteristics compared to several existing dose-finding designs in terms of both the percentage of correct selection and the number of patients treated at target dose(s).

RESUMEN

Dose optimization is a critical challenge in drug development. Historically, dose determination in oncology has followed a divergent path from other non-oncology therapeutic areas due to the unique characteristics and requirements in Oncology. However, with the emergence of new drug modalities and mechanisms of drugs in oncology, such as immune therapies, radiopharmaceuticals, targeted therapies, cytostatic agents, and others, the dose-response relationship for efficacy and toxicity could be vastly varied compared to the cytotoxic chemotherapies. The doses below the MTD may demonstrate similar efficacy to the MTD with an improved tolerability profile, resembling what is commonly observed in non-oncology treatments. Hence, alternate strategies for dose optimization are required for new modalities in oncology drug development. This paper delves into the historical evolution of dose finding methods from non-oncology to oncology, highlighting examples and summarizing the underlying drivers of change. Subsequently, a practical framework and guidance are provided to illustrate how dose optimization can be incorporated into various stages of the development program. We provide the following general recommendations: 1) The objective for phase I is to identify a dose range rather than a single MTD dose for subsequent development to better characterize the safety and tolerability profile within the dose range. 2) At least two doses separable by PK are recommended for dose optimization in phase II. 3) Ideally, dose optimization should be performed before launching the confirmatory study. Nevertheless, innovative designs such as seamless II/III design can be implemented for dose selection and may accelerate the drug development program.

RESUMEN

BACKGROUND: Tracheal intubation may cause significant hemodynamic responses. Many drugs have been shown to be effective in modifying these cardiovascular responses, including remifentanil, fentanyl, sufentanil, and alfentanil. However, the 90% effect-site concentration (EC90) of remifentanil required to control cardiovascular responses to tracheal intubation when combined with ciprofol remains unclear. The purpose of this study was to determine the EC90 of remifentanil inhibiting cardiovascular responses to tracheal intubation during anesthesia induction with ciprofol using biased-coin design up-and-down sequential method (BC-UDM). METHODS: This is a prospective sequential allocation dose-finding study. American Society of Anesthesiologists physical status (ASA) I-II elective surgical patients receiving target-controlled infusion (TCI) of remifentanil effect-site concentration (Ce), followed by ciprofol and rocuronium for anesthesia, were enrolled. The cardiovascular response to tracheal intubation was defined as positive when mean arterial pressure (MAP) or heart rate (HR) is 15% higher than the baseline value. Using the BC-UDM, the Ce of remifentanil was determined based on the cardiovascular response to tracheal intubation of the previous patient. The EC90 and 90% confidence intervals (90% CIs) were estimated by R-Foundation centered isotonic regression and the pooled adjacent violators algorithm with bootstrapping. DISCUSSION: The results of this study sought to demonstrate EC90 of remifentanil blunting sympathetic responses to tracheal intubation during anesthesia index (Ai)-guided ciprofol anesthesia using BCD-UDM. It may help to minimize the cardiovascular responses to tracheal intubation. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2300078275. Registered on December 3, 2023.

Asunto(s)

Frecuencia Cardíaca , Intubación Intratraqueal , Remifentanilo , Humanos , Remifentanilo/administración & dosificación , Intubación Intratraqueal/métodos , Estudios Prospectivos , Frecuencia Cardíaca/efectos de los fármacos , Masculino , Anestésicos Intravenosos/administración & dosificación , Femenino , Adulto , Relación Dosis-Respuesta a Droga , Persona de Mediana Edad , Presión Arterial/efectos de los fármacos , Hemodinámica/efectos de los fármacos , Rocuronio/administración & dosificación , Analgésicos Opioides/administración & dosificación

RESUMEN

OBJECTIVE: Transgender women who underwent gonadectomy have lower serum testosterone concentrations than cisgender women. There is uncertainty regarding the dosing and side effects of supplementation of testosterone in transgender women. This study aimed to assess the feasibility of dosing testosterone to the cisgender female physiological range in transgender women. In addition, we explored changes in cardiovascular parameters, virilizing side effects, and clinical symptoms. DESIGN: This is an open-label, single-arm feasibility study. Participants initially went through a dose-titration phase with 2-week intervals of 0.07-0.09-0.13 mL (277-318-403 µg bioavailable testosterone) testosterone 2% gel to establish a dose leading to serum testosterone concentrations between 1.5 and 2.5 nmol/L. This dose was then continued for 8 weeks. METHODS: Participants applied daily transdermal testosterone 2% gel (Tostran®) at the prescribed dosage. Testosterone was measured every 2-4 weeks. Laboratory analyses, side effects, and clinical symptoms were evaluated. RESULTS: In total, 12 participants were included. Most participants required a dose of 0.07 mL (277 µg bioavailable testosterone) or 0.09 mL (318 µg bioavailable testosterone) to reach serum testosterone concentrations of 1.5-2.5 nmol/L. Continuing this dose, testosterone concentrations remained stable throughout the study. Changes in clinical outcomes were in the desired direction, and side effects were mild. CONCLUSIONS: The use of testosterone supplementation in transgender women seems feasible and safe in the short term. Although dosing requires personalized titration, stable testosterone levels can be established. A blinded, placebo-controlled, randomized clinical trial is needed to study the clinical benefit.

Asunto(s)

Estudios de Factibilidad , Testosterona , Personas Transgénero , Humanos , Testosterona/administración & dosificación , Testosterona/sangre , Femenino , Adulto , Masculino , Persona de Mediana Edad , Adulto Joven , Relación Dosis-Respuesta a Droga , Administración Cutánea , Andrógenos/administración & dosificación , Andrógenos/sangre , Andrógenos/efectos adversos , Terapia de Reemplazo de Hormonas/métodos

RESUMEN

BACKGROUND: Determining the maximum tolerated dose (MTD) remains the primary objective for the majority of dose-finding oncology trials. Whilst MTD determination often relies upon clinicians to identify dose-limiting toxicities (DLTs) experienced by patients during the trial, research suggests that clinicians may underreport patient's adverse events. Therefore, contemporary practice may be exposed to recommending intolerable doses to patients for further investigation in subsequent trials. There is increasing interest in patients self-assessing their own symptoms using patient-reported outcomes (PROs) in dose-finding trials. DESIGN: We present Utility-PRO-Continual Reassessment Method (U-PRO-CRM), a novel trial design which simultaneously uses clinician-rated and patient-rated DLTs (Clinician-DLTs and Patient-DLTs, respectively) to make dose (de-)escalation decisions and to recommend an MTD. U-PRO-CRM contains the published PRO-CRM as a special case and provides greater flexibility to trade-off the rate of Patient-DLTs and Clinician-DLTs to find an optimal dose. We present simulation results for U-PRO-CRM. RESULTS: For specified trade-offs between Clinician-DLT and Patient-DLT rate, U-PRO-CRM outperforms the PRO-CRM design by identifying the true MTD more often. In the special case where U-PRO-CRM generalises to PRO-CRM, U-PRO-CRM performs as well as its published counterpart. U-PRO-CRM minimises the number of patients overdosed whilst maintaining a similar proportion of patients allocated to the true MTD. CONCLUSIONS: By using a utility-based dose selection approach, U-PRO-CRM offers the flexibility to define a trade-off between the risk of patient-rated and clinician-rated DLTs for an optimal dose. Patient-centric dose-finding strategies, which integrate PROs, are poised to assume an ever more pivotal role in significantly advancing our understanding of treatment tolerability. This bears significant implications in shaping the future landscape of early-phase trials.

Asunto(s)

Dosis Máxima Tolerada , Medición de Resultados Informados por el Paciente , Humanos , Proyectos de Investigación , Relación Dosis-Respuesta a Droga , Neoplasias/tratamiento farmacológico , Ensayos Clínicos como Asunto , Antineoplásicos/administración & dosificación , Antineoplásicos/uso terapéutico

RESUMEN

Background: Traditional dose selection for oncology registration trials typically employs a one- or two-step single maximum tolerated dose (MTD) approach. However, this approach may not be appropriate for molecularly targeted therapy, which tends to have toxicity profiles that are markedly different than cytotoxic agents. The US Food and Drug Administration launched Project Optimus to reform dose optimization in oncology drug development and has recently released a related guidance for industry. Methods: We propose a "three steps toward dose optimization" procedure, in response to these initiatives, and discuss the details in dose-optimization designs and analyses. The first step is dose escalation to identify the MTD or maximum administered dose with an efficient hybrid design, which can offer good overdose control and increases the likelihood of the recommended MTD being close to the true MTD. The second step is the selection of appropriate recommended doses for expansion (RDEs), based on all available data, including emerging safety, pharmacokinetics, pharmacodynamics, and other biomarker information. The third step is dose optimization, which uses data from a randomized fractional factorial design with multiple RDEs explored in multiple tumor cohorts during the expansion phase to ensure a feasible dose is selected for registration trials, and that the tumor type most sensitive to the investigative treatment is identified. Conclusion: We believe using this three-step approach can increase the likelihood of selecting an optimal dose for a registration trial that demonstrates a balanced safety profile while retaining much of the efficacy observed at the MTD.

RESUMEN

Dual-agent treatment has become more and more popular in clinical trials. We have developed an approach called rapid enrollment dual-agent design (REDD) for dose-finding in Phase I clinical trials. This approach aims to administer treatment to patients using a dose combination that is highly probable to be the target dose combination. Unlike other non-model-based designs, rapid enrollment designs (RED and REDD) do not require waiting for all patients to complete an assessment before the assignment of the next participant. Simulations showed that across several scenarios, the average performance of REDD is comparable to that of the Bayesian optimal interval (BOIN) design and the partial order continual reassessment method (POCRM). The simulation results of REDD for late-onset toxicity assessments demonstrated that assigning patients to a dose combination as they are being enrolled, without waiting for the most recent cohort of patients to complete their follow-up, does not significantly compromise the quality of the maximum tolerated dose (MTD) estimation. Instead, it saves a considerable amount of time in clinical trial enrollment. User-friendly online applications have also been created to further facilitate the adoption of rapid enrollment designs in Phase I trials. In summary, being similar to BOIN and POCRM in performance, REDD is an approach that is easily comprehensible, straightforward to implement and offers an advantage of enrolling patients without having to wait for all current patients to complete their follow-ups for toxicity.

RESUMEN

BACKGROUND: Previous studies have shown that a 0.05 µg/kg/min of norepinephrine infusion in combination with an initial bolus reduces the incidence of spinal hypotension during cesarean delivery. The initial norepinephrine bolus influences the incidence of spinal hypotension during continuous norepinephrine infusion; however, the ideal initial bolus dose for 0.05 µg/kg/min of continuous infusion remains unknown. METHODS: This randomized, controlled, dose-finding study randomly allocated 120 parturients scheduled for elective cesarean delivery to receive initial bolus doses of 0, 0.05, 0.10, and 0.15 µg/kg of norepinephrine, followed by continuous infusion at a rate of 0.05 µg/kg/min. The primary outcome was the dose-response relationship of the initial norepinephrine bolus in preventing the incidence of spinal hypotension. Spinal hypotension was defined as systolic blood pressure (SBP) decreased to <80% of the baseline value or to an absolute value of <90 mmHg from intrathecal injection to delivery, and severe spinal hypotension was defined as SBP decreased to <60% of the baseline value. The secondary outcomes included the incidence of nausea and/or vomiting, hypertension, and bradycardia, as well as the Apgar scores and results of the umbilical arterial blood gas analysis. The effective dose (ED) 90 and ED95 were estimated using probit regression. RESULTS: The per-protocol analysis included 117 patients. The incidence of spinal hypotension varied significantly among the groups: Group 0 (51.7%), Group 0.05 (44.8%), Group 0.10 (23.3%), and Group 0.15 (6.9%). The ED90 and ED95 values were 0.150 µg/kg (95% confidence interval [CI], 0.114-0.241 µg/kg) and 0.187 µg/kg (95% CI, 0.141-0.313 µg/kg), respectively. However, the ED95 value fell outside the dose range examined in this study. The incidence of severe spinal hypotension differed significantly (P = 0.02) among Groups 0 (17.2%), 0.05 (10.3%), 0.10 (3.3%), and 0.15 (0.0%); however, the incidence of hypertension and bradycardia did not. The incidence of nausea and/or vomiting decreased with an increase in the initial bolus dose (P = 0.03). The fetal outcomes were comparable among the groups. CONCLUSIONS: An initial bolus of 0.150 µg/kg of norepinephrine may be the optimal dose for preventing spinal hypotension during cesarean delivery with a continuous infusion rate of 0.05 µg/kg/min, and does not significantly increase the incidence of hypertension but substantially reduces the risk of nausea and/or vomiting.

Asunto(s)

Presión Sanguínea , Cesárea , Relación Dosis-Respuesta a Droga , Hipotensión , Norepinefrina , Humanos , Femenino , Cesárea/efectos adversos , Embarazo , Hipotensión/prevención & control , Hipotensión/epidemiología , Hipotensión/etiología , Hipotensión/inducido químicamente , Adulto , Norepinefrina/administración & dosificación , Norepinefrina/efectos adversos , Infusiones Intravenosas , Presión Sanguínea/efectos de los fármacos , Vasoconstrictores/administración & dosificación , Vasoconstrictores/efectos adversos , Anestesia Obstétrica/efectos adversos , Anestesia Obstétrica/métodos , Anestesia Raquidea/efectos adversos , Anestesia Raquidea/métodos , Hipertensión/prevención & control , Hipertensión/epidemiología , Incidencia , Bradicardia/prevención & control , Bradicardia/epidemiología , Bradicardia/inducido químicamente , Puntaje de Apgar , Náusea y Vómito Posoperatorios/prevención & control , Náusea y Vómito Posoperatorios/epidemiología , Náusea y Vómito Posoperatorios/etiología

RESUMEN

We consider a dose-optimization design for a first-in-human oncology trial that aims to identify a suitable dose for late-phase drug development. The proposed approach, called the Pharmacometrics-Enabled DOse OPtimization (PEDOOP) design, incorporates observed patient-level pharmacokinetics (PK) measurements and latent pharmacodynamics (PD) information for trial decision-making and dose optimization. PEDOOP consists of two seamless phases. In phase I, patient-level time-course drug concentrations, derived PD effects, and the toxicity outcomes from patients are integrated into a statistical model to estimate the dose-toxicity response. A simple dose-finding design guides dose escalation in phase I. At the end of the phase I dose finding, a graduation rule is used to assess the safety and efficacy of all the doses and select those with promising efficacy and acceptable safety for a randomized comparison against a control arm in phase II. In phase II, patients are randomized to the selected doses based on a fixed or adaptive randomization ratio. At the end of phase II, an optimal biological dose (OBD) is selected for late-phase development. We conduct simulation studies to assess the PEDOOP design in comparison to an existing seamless design that also combines phases I and II in a single trial.

RESUMEN

Therapeutic advances in oncology in the 21st century have contributed to significant declines in cancer mortality. Notably, targeted therapies comprised the largest proportion of oncology drugs approved by the United States (US) Food and Drug Administration (FDA) over the past 25 years and have become the standard of care for the treatment of many cancers. However, despite the metamorphosis of the therapeutic landscape, some aspects of cancer drug development have remained essentially unchanged. In particular, the dose-finding methodology originally developed for cytotoxic chemotherapy drugs continues to be implemented, even though this approach no longer represents the most appropriate strategy for modern cancer therapies. In recognition of the need to reconsider assumptions, adapt the dose selection process for newer drugs, and design alternative strategies, the FDA has undertaken several initiatives in recent years to address these concerns. These actions include the launch of Project Optimus in 2021 and the issuance of draft guidance for industry on dose optimization of oncology drugs in 2023. Amid this evolving regulatory environment, the present manuscript reviews case studies for six different targeted cancer therapies, highlighting how dose-finding challenges have been managed to date by oncologists, sponsors, and regulators.

RESUMEN

BACKGROUND: In light of the FDA's Project Optimus initiative, there is fresh interest in leveraging Patient-reported Outcome (PRO) data to enhance the assessment of tolerability for investigational therapies within early phase dose-finding oncology trials. Typically, dose escalation in most trial designs is solely reliant on clinician assessed adverse events. Research has shown a disparity between patients and clinicians when assessing whether an investigational therapy is tolerable, leading to the recommendation of potentially intolerable doses for further investigation in subsequent trials. It is also increasingly recognized that patient and public involvement and engagement (PPIE) plays a pivotal role in enriching trial design and conduct. However, to our knowledge, no PPIE has explored the optimal integration of PROs in the development of advanced statistical trial designs within early phase dose-finding oncology trials. METHODS: A virtual PPIE session was held with nine participants on 18th October 2023 to discuss the incorporation of PROs within a dose-finding trial design. This cross disciplinary session was developed and led by a team of statisticians, clinical specialists, qualitative experts, and trial methodologists. Following the session, in-depth perspectives were provided by two patient advocates who actively engaged in the PPIE session. We discuss the importance of PPIE in shaping advanced dose-finding trial designs, share insights from patients on integrating PROs to inform treatment tolerability, and present a template for meaningful patient involvement in trial design development. RESULTS: Participants generally supported the introduction of PROs within dose-finding trials but showed some apprehensiveness as to how PROs may reduce the size of the recommended dose (and potentially efficacious effect). Some participants shared that they may be reluctant to record the real severity of their symptoms via PROs if it would mean that they would have to discontinue treatment. They discussed that PROs could be used to assess tolerability rather than toxicity of a dose. CONCLUSIONS: Amplifying patient voice in the development of patient-centric dose-finding trial designs is now essential. This paper offers an exemplary illustration of how trialists and methodologists can effectively incorporate patient voice in the future development of advanced dose-finding trial designs.

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The aim of dose-finding oncology trials is to make sure a treatment is safe, understand its side effects, and recommend the right dose (or doses) for future clinical trials. Traditionally, a patient's tolerance to treatment is assessed by doctors who evaluate toxicities (side-effects) using established grading guidelines. Research has shown that doctors might not identify all the side effects that patients actually experience during a trial.There is growing interest in the introduction of patient-reported outcomes (PROs) within dose-finding trials. PROs are reports of a patient's health and well-being experiences which come directly from the patient themselves, usually assessed using a questionnaire.In a dose-finding trial, we start with a low dose of a drug and increase it until too many patients have severe side effects. The highest safe dose is then investigated in a later phase trial.   We are suggesting a new way to do these trials. We want to look at both what doctors see as severe side effects and what patients say. This enables us to recommend a dose that balances both perspectives. We would also like to ask patients what level of risk they are comfortable with regarding severe side effects.In this paper, we highlight the importance of involving patients in creating advanced dose-finding trial designs, particularly with PROs to help decide whether a dose is tolerable for patients. We also share findings of a patient and public involvement and engagement session and provide a guide for meaningful patient involvement in developing trial designs.

RESUMEN

Chimeric antigen receptor (CAR) T-cell therapy is a human gene therapy product where T cells from a patient are genetically modified to enable them to recognize desired target antigen(s) more effectively. In recent years, promising antitumor activity has been seen with autologous CAR T cells. Since 2017, six CAR T-cell therapies for the treatment of hematological malignancies have been approved by the Food and Drug Administration (FDA). Despite the rapid progress of CAR T-cell therapies, considerable statistical challenges still exist for this category of products across all phases of clinical development that need to be addressed. These include (but not limited to) dose finding strategy, implementation of the estimand framework, use of real-world data in contextualizing single-arm CAR T trials, analysis of safety data and long-term follow-up studies. This paper is the first step in summarizing and addressing these statistical hurdles based on the development of the six approved CAR T-cell products.

Asunto(s)

Inmunoterapia Adoptiva , Receptores Quiméricos de Antígenos , Humanos , Inmunoterapia Adoptiva/métodos , Inmunoterapia Adoptiva/efectos adversos , Neoplasias Hematológicas/terapia , Linfocitos T/inmunología , Linfocitos T/trasplante , Estados Unidos , United States Food and Drug Administration

RESUMEN

Background and Aim: Sevoflurane, a preferred anaesthetic for children, exhibits a dose-dependent reduction in intraocular pressure (IOP). However, consensus is lacking regarding optimal end-tidal sevoflurane concentration for safe IOP measurement. This study aimed to identify the concentration at which IOP measurement could be attempted without inducing movements in paediatric patients after inhalational induction. Methods: Two paediatric groups (1-12 months and 12-36 months) with glaucoma undergoing examination under anaesthesia were recruited. After induction with 8% sevoflurane and 100% oxygen, the first child had an end-tidal sevoflurane concentration maintained at 2% for 4 min, followed by IOP measurement. Success was defined as 'no movement', and subsequent concentrations (adjusted in 0.2% steps) were determined using the Dixon and Massey method based on the previous patient's responses. Results: The study included 75 children. The effective concentration of sevoflurane causing 'no movement' during IOP measurement in 50% of the study population for successful IOP measurement was 1.98% (95% confidence interval [CI] 1.63, 2.17, P = 0.017) for 1-12 months group and 0.55% (95% CI 0.39, 0.66, P = 0.002) for 12-36 months group. Probit regression analysis yielded effective concentration of sevoflurane causing 'no movement' during IOP measurement in 95% of the study population values of 2.47% (95% CI 2.24, 4.58, P = 0.017) for 1-12 months group and 0.94% (95% CI 0.78, 1.57, P = 0.002) for 12-36 months group. Conclusion: In paediatric patients, a higher end-tidal sevoflurane concentration of 2% is needed for IOP measurement in 1-12 months age group compared to 0.5% required in 12-36 months age group, achieving success in 50% of the study population.

RESUMEN

Traditional approaches in dose-finding trials, such as the continual reassessment method, focus on identifying the maximum tolerated dose. In contemporary early-phase dose-finding trials, especially in oncology with targeted agents or immunotherapy, a more relevant aim is to identify the lowest dose level that maximises efficacy whilst remaining tolerable. Backfilling, defined as the practice of assigning patients to dose levels lower than the current highest tolerated dose, has been proposed to gather additional pharmacokinetic, pharmacodynamic and biomarker data to recommend the most appropriate dose to carry forward for subsequent studies. The first formal framework [5] for backfilling proposed randomising backfill patients with equal probability among those doses below the dose level where the study is currently at. Here, we propose to use Bayesian response-adaptive randomisation to backfill patients. This patient-oriented approach to backfilling aims to allocate more patients to dose levels in the backfill set with higher expected efficacy based on emerging data. The backfill set constitutes of the doses below the dose the dose-finding algorithm is at. At study completion, collective patient data inform the dose-response curve, suggesting an optimal dose level balancing toxicity and efficacy. Our simulation study across diverse clinical trial settings demonstrates that a backfilling strategy using Bayesian response-adaptive randomisation can result in a patient-oriented patient assignment procedure which simultaneously enhances the likelihood of correctly identifying the most appropriate dose level. This contribution offers a methodological framework and practical implementation for patient-oriented backfilling, encompassing design and analysis considerations in early-phase trials.

Asunto(s)

Teorema de Bayes , Relación Dosis-Respuesta a Droga , Dosis Máxima Tolerada , Humanos , Proyectos de Investigación , Ensayos Clínicos Controlados Aleatorios como Asunto/métodos , Neoplasias/tratamiento farmacológico , Antineoplásicos/administración & dosificación , Antineoplásicos/farmacocinética

RESUMEN

The calibration-free odds (CFO) design has been demonstrated to be robust, model-free, and practically useful but faces challenges when dealing with late-onset toxicity. The emergence of the time-to-event (TITE) method and fractional method leads to the development of TITE-CFO and fractional CFO (fCFO) designs to accumulate delayed toxicity. Nevertheless, existing CFO-type designs have untapped potential because they primarily consider dose information from the current position and its two neighboring positions. To incorporate information from all doses, we propose the accumulative CFO (aCFO) design by utilizing data at all dose levels similar to a tug-of-war game where players distant from the center also contribute their strength. This approach enhances full information utilization while still preserving the model-free and calibration-free characteristics. Extensive simulation studies demonstrate performance improvement over the original CFO design, emphasizing the advantages of incorporating information from a broader range of dose levels. Furthermore, we propose to incorporate late-onset outcomes into the TITE-aCFO and f-aCFO designs, with f-aCFO displaying superior performance over existing methods in both fixed and random simulation scenarios. In conclusion, the aCFO and f-aCFO designs can be considered robust, efficient, and user-friendly approaches for conducting phase I trials without or with late-onsite toxicity.

Asunto(s)

Ensayos Clínicos Fase I como Asunto , Simulación por Computador , Humanos , Ensayos Clínicos Fase I como Asunto/métodos , Proyectos de Investigación , Relación Dosis-Respuesta a Droga , Calibración , Efectos Colaterales y Reacciones Adversas Relacionados con Medicamentos , Modelos Estadísticos , Factores de Tiempo

RESUMEN

This paper proposes a trial design for locating group-specific doses when groups are partially or completely ordered by dose sensitivity. Previous trial designs for partially ordered groups are model-based, whereas the proposed method is model-assisted, providing clinicians with a design that is simpler. The proposed method performs similarly to model-based methods, providing simplicity without losing accuracy. Additionally, to the best of our knowledge, the proposed method is the first paper on dose-finding for partially ordered groups with convergence results. To generalize the proposed method, a framework is introduced that allows partial orders to be transferred to a grid format with a known ordering across rows but an unknown ordering within rows.

RESUMEN

The U.S. Food and Drug Administration (FDA) has launched Project Optimus to shift dose selection from the maximum tolerated dose (MTD) to the dose that produces the optimal risk-benefit tradeoff. One approach highlighted in the FDA's guidance involves conducting a randomized phase II trial following the completion of a phase I trial, where multiple doses (typically including the MTD and one or two doses lower than the MTD) are compared to identify the optimal dose that maximizes the benefit-risk tradeoff. This article focuses on the design of such a multiple-dose randomized trial, specifically the determination of the sample size. We generalized the standard definitions of type I error and power to accommodate the unique characteristics of dose optimization and derived a decision rule along with an algorithm to determine the optimal sample size. The resulting design is referred to as MERIT (Multiple-dosE RandomIzed Trial design for dose optimization based on toxicity and efficacy). Simulation studies demonstrate that MERIT has desirable operating characteristics, and a sample size between 20 and 40 per dosage arm often offers reasonable power and type I errors to ensure patient safety and benefit. To facilitate the implementation of the MERIT design, we provide software, available at https://www.trialdesign.org.

Asunto(s)

Algoritmos , Ensayos Clínicos Fase II como Asunto , Simulación por Computador , Dosis Máxima Tolerada , Ensayos Clínicos Controlados Aleatorios como Asunto , Proyectos de Investigación , Tamaño de la Muestra , Humanos , Ensayos Clínicos Fase II como Asunto/métodos , Relación Dosis-Respuesta a Droga , Estados Unidos , United States Food and Drug Administration

RESUMEN

In recent years, both model-based and model-assisted designs have emerged to efficiently determine the optimal biological dose (OBD) in phase I/II trials for immunotherapy and targeted cellular agents. Model-based designs necessitate repeated model fitting and computationally intensive posterior sampling for each dose-assignment decision, limiting their practical application in real trials. On the other hand, model-assisted designs employ simple statistical models and facilitate the precalculation of a decision table for use throughout the trial, eliminating the need for repeated model fitting. Due to their simplicity and transparency, model-assisted designs are often preferred in phase I/II trials. In this paper, we systematically evaluate and compare the operating characteristics of several recent model-assisted phase I/II designs, including TEPI, PRINTE, Joint i3+3, BOIN-ET, STEIN, uTPI, and BOIN12, in addition to the well-known model-based EffTox design, using comprehensive numerical simulations. To ensure an unbiased comparison, we generated 10,000 dosing scenarios using a random scenario generation algorithm for each predetermined OBD location. We thoroughly assess various performance metrics, such as the selection percentages, average patient allocation to OBD, and overdose percentages across the eight designs. Based on these assessments, we offer design recommendations tailored to different objectives, sample sizes, and starting dose locations.

Asunto(s)

Biometría , Ensayos Clínicos Fase I como Asunto , Ensayos Clínicos Fase II como Asunto , Modelos Estadísticos , Humanos , Ensayos Clínicos Fase I como Asunto/métodos , Ensayos Clínicos Fase II como Asunto/métodos , Biometría/métodos , Proyectos de Investigación

RESUMEN

Bayesian logistic regression model (BLRM) is widely used to guide dose escalation decisions in phase 1 oncology trials. An important feature of BLRM design is the appealing safety performance due to its escalation with overdose control (EWOC). However, some recent literature indicates that BLRM with EWOC may have a relatively low probability to find the maximum tolerated dose (MTD) compared to some other dose escalation designs. This work discusses this design problem and proposes a practical solution to improve the performance of BLRM design. Specifically, we suggest increasing the EWOC cutoff from routine value 0.25 to a value between 0.3 and 0.4, which will increase the chance of finding the correct MTD with minimal compromise to overdosing risk. Our comparative simulation studies indicate that BLRM with an increased EWOC cutoff has comparable operating characteristics on the correct MTD selection and over-toxicity control as other dose escalation designs (BOIN, mTPI, keyboard, etc.). Moreover, we compare the methodology and operating characteristics of BLRM designs with various decision rules that allow more flexible overdosing control. A case study of dose escalation in a recent phase 1 oncology trial is provided to show how BLRM with optimal EWOC cutoff operates well in practice.