Early phase clinical trials to identify optimal dosing and safety.
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ABSTRACT:
SUBMITTER: Cook N
PROVIDER: S-EPMC4329110 | biostudies-other | 2015 May
REPOSITORIES: biostudies-other
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Project description:Simon's optimal two-stage design has been widely used in early phase clinical trials for Oncology and AIDS studies with binary endpoints. With this approach, the second-stage sample size is fixed when the trial passes the first stage with sufficient activity. Adaptive designs, such as those due to Banerjee and Tsiatis (2006) and Englert and Kieser (2013), are flexible in the sense that the second-stage sample size depends on the response from the first stage, and these designs are often seen to reduce the expected sample size under the null hypothesis as compared with Simon's approach. An unappealing trait of the existing designs is that they are not associated with a second-stage sample size, which is a non-increasing function of the first-stage response rate. In this paper, an efficient intelligent process, the branch-and-bound algorithm, is used in extensively searching for the optimal adaptive design with the smallest expected sample size under the null, while the type I and II error rates are maintained and the aforementioned monotonicity characteristic is respected. The proposed optimal design is observed to have smaller expected sample sizes compared to Simon's optimal design, and the maximum total sample size of the proposed adaptive design is very close to that from Simon's method. The proposed optimal adaptive two-stage design is recommended for use in practice to improve the flexibility and efficiency of early phase therapeutic development.
| S-EPMC4777673 | biostudies-literature
Project description:In the early phase development of molecularly targeted agents (MTAs), a commonly encountered situation is that the MTA is expected to be more effective for a certain biomarker subgroup, say marker-positive patients, but there is no adequate evidence to show that the MTA does not work for the other subgroup, that is, marker-negative patients. After establishing that marker-positive patients benefit from the treatment, it is often of great clinical interest to determine whether the treatment benefit extends to marker-negative patients. The authors propose optimal sequential enrichment (OSE) designs to address this practical issue in the context of phase II clinical trials. The OSE designs evaluate the treatment effect first in marker-positive patients and then in marker-negative patients if needed. The designs are optimal in the sense that they minimize the expected sample size or the maximum sample size under the null hypothesis that the MTA is futile. An efficient, accurate optimization algorithm is proposed to find the optimal design parameters. One important advantage of the OSE design is that the go/no-go interim decision rules are specified prior to the trial conduct, which makes the design particularly easy to use in practice. A simulation study shows that the OSE designs perform well and are ethically more desirable than the commonly used marker-stratified design. The OSE design is applied to an endometrial carcinoma trial. Copyright © 2016 John Wiley & Sons, Ltd.
| S-EPMC5138118 | biostudies-literature
Project description:ObjectiveAdaptive designs can enable highly sophisticated and efficient early phase trials, but the clinical inference from these trials is surrounded by complexity, and currently there is a paucity but steadily increasing amount of use of these designs in all fields of medicine. We aim to review early phase trials in RA to discover those that have used adaptive designs and benchmark trial characteristics.MethodsFrom an OVID search for journal articles reporting the results of early phase trials in rheumatology, 35 studies were found, with 9 subsequently excluded; 11 were added from manual searches and 19 from searching the references. Study characteristics were extracted from the 56 papers (describing 62 trials), including the number of arms, number of patients, the primary outcome and when it was measured.ResultOne early phase trial using an adaptive design was found. The benchmark early phase trial in RA is a phase II double-blinded randomized trial, with four arms (one control and three intervention), each with 34 patients, and ACR20 measured at 16 weeks as the primary outcome.ConclusionThe one adaptive design reviewed here, and a simulation study found in the search, both indicate that adaptive designs can be applied to early phase trials in RA. We have described the benchmark, which the efficiency of early phase trials using an adaptive design needs to exceed. These efficient designs could drive down numbers required, time for data collection and thus cost. Changes have been suggested, but more needs to be done.
| S-EPMC6649924 | biostudies-literature
Project description:Pivotal trials of COVID-19 vaccines did not include cancer patients, with questions remaining about their safety and efficacy in this population. Patients enrolled in early-phase clinical trials receive novel treatments with unknown efficacy and safety profiles. Studies on the safety of COVID-19 vaccines in these patients are urgently required. This is a retrospective, real-world, cohort study of patients receiving anticancer treatments and COVID-19 vaccines between 1 February and 25 June 2021 at the Division of New Drugs Development for Innovative Therapies of the European Institute of Oncology. One hundred thirteen patients were enrolled, 40 in early-phase clinical trials, and 20 under novel immunotherapy agents. Nearly three-quarters of the patients experienced at least one adverse event (AE) after the first dose (1D) (74.3%) and second dose (2D) (72.6%). Most of the AEs were local (67.3% 1D and 61.9% after 2D), while 31.8% (1D) and 38.1% (2D) of the patients had systemic AEs. No AEs above grade 2 were observed. Therefore, COVID-19 vaccines appear to be safe in patients enrolled in early-phase clinical trials, including patients receiving novel immunotherapy compounds. All cancer patients should be prioritized for COVID-19 vaccination, regardless of ongoing treatments or enrollment in early-phase trials.
| S-EPMC8616209 | biostudies-literature
Project description:BackgroundClassical phase 1 dose-finding designs based on a single toxicity endpoint to assess the maximum tolerated dose were initially developed in the context of cytotoxic drugs. With the emergence of molecular targeted agents and immunotherapies, the concept of optimal biological dose (OBD) was subsequently introduced to account for efficacy in addition to toxicity. The objective was therefore to provide an overview of published phase 1 cancer clinical trials relying on the concept of OBD.MethodsWe performed a systematic review through a computerized search of the MEDLINE database to identify early phase cancer clinical trials that relied on OBD. Relevant publications were selected based on a two-step process by two independent readers. Relevant information (phase, type of therapeutic agents, objectives, endpoints and dose-finding design) were collected.ResultsWe retrieved 37 articles. OBD was clearly mentioned as a trial objective (primary or secondary) for 22 articles and was traditionally defined as the smallest dose maximizing an efficacy criterion such as biological target: biological response, immune cells count for immunotherapies, or biological cell count for targeted therapies. Most trials considered a binary toxicity endpoint defined in terms of the proportion of patients who experienced a dose-limiting toxicity. Only two articles relied on an adaptive dose escalation design.ConclusionsIn practice, OBD should be a primary objective for the assessment of the recommended phase 2 dose (RP2D) for a targeted therapy or immunotherapy phase I cancer trial. Dose escalation designs have to be adapted accordingly to account for both efficacy and toxicity.
| S-EPMC7805102 | biostudies-literature
Project description:There has been constant development of novel statistical methods in the design of early-phase clinical trials since the introduction of model-based designs, yet the traditional or modified 3+3 algorithmic design remains the most widely used approach in dose-finding studies. Research has shown the limitations of this traditional design compared with more innovative approaches yet the use of these model-based designs remains infrequent. This can be attributed to several causes including a poor understanding from clinicians and reviewers into how the designs work, and how best to evaluate the appropriateness of a proposed design. These barriers are likely to be enhanced in the coming years as the recent paradigm of drug development involves a shift to more complex dose-finding problems. This article reviews relevant information that should be included in clinical trial protocols to aid in the acceptance and approval of novel methods. We provide practical guidance for implementing these efficient designs with the aim of augmenting a broader transition from algorithmic to adaptive model-guided designs. In addition we highlight issues to consider in the actual implementation of a trial once approval is obtained. Copyright © 2016 John Wiley & Sons, Ltd.
| S-EPMC5003756 | biostudies-literature
Project description:PurposeTo develop a statistical approach that compares patient selection strategies across clinical trials and apply this approach to acute ischemic stroke clinical trials to identify the optimal inclusion criteria.MethodsWe developed a statistical approach that compares the number needed to treat to achieve one success (NNT) along with the number needed to screen to achieve one success (NNS) and assesses if there are significant differences in inclusion criteria, treatment course, and clinical outcome among patients that may have been included/excluded in the trials. We applied this approach to the study population from four recent positive acute stroke clinical trials: MR CLEAN, EXTEND-IA, ESCAPE, and SWIFT PRIME, applying published trial criteria to an independent registry of 612 acute stroke patients, since we did not have access to the complete trial data.ResultsAlthough reported NNT were similar for EXTEND-IA, SWIFT PRIME and ESCAPE, and somewhat higher for MR CLEAN, NNS varied across the trials from 21 for EXTEND-IA, 27 for MR CLEAN, to 46 for ESCAPE and 64 for SWIFT PRIME, reflecting less and more stringent inclusion criteria, respectively. Although there were significant differences in imaging biomarkers and other clinical characteristics among patients that may have been included/excluded in the trials, these differences did not translate to significant differences in treatment course or clinical outcomes.ConclusionsOur study proposes a robust statistical approach that can be applied to a larger pooled trial dataset, if made available, to objectively compare across clinical trials and inform inclusion criteria of future trials. Pooled analysis of the acute stroke trial data is needed to determine which imaging biomarker inclusion criteria are critical and which may be relaxed. If this procedure were applied across the pooled trial data, it could decrease costs and refine the design of future trials to be the most efficacious for the greatest number of patients.
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Project description:Purpose The purpose of this study was to evaluate the safety and tolerability profile of drugs used for treating common eye disorders when applied to normal healthy volunteers (NHVs) as explored in phase 1 trials. Subjects and Methods A total of 166 NHVs were identified in six phase 1 trials, examined in a retrospective analysis. The primary endpoints were visual comfort (by ocular comfort index, OCI) and safety (laboratory evaluations, vital signs (VS), visual acuity (VA), intraocular pressure (IOP), lissamine green and fluorescein staining, conjunctival hyperemia, chemosis, and adverse events’ incidence (AE)). Results Compared to baseline, 75.9%, 40.4% and 73.7% of NHV (for lubricant, hypotensive and antibiotic treatments, respectively) improved their OCI score by their final visit. Laboratory evaluations and VS were within normal ranges in 88% of NHV. Similar results were found for VA, corneal and conjunctival staining, and chemosis. IOP decreased significantly in the hypotensive agents’ group, trace to mild hyperemia was reported in 32.1%, 27.1%, and 6.8%, respectively. Additionally, lubricant and hypotensive investigational drugs (ID) had a lower risk of incidence of AE than approved drugs (OR 0.856, 95% CI [0.365, 1.999] and 0.636, 95% CI [0.096, 4.197], respectively). Meanwhile, on antibiotic drugs, the risk for ID-related AE was higher (OR 1.313, 95% CI [0.309, 5.583]). Conclusion Phase 1 trials are important in order to ensure the safety and tolerability of ophthalmic medications. This study demonstrates that NHVs do not face a significant risk of harm in these studies, since 98% of the reported AE were mild, and all AE were resolved by the end of the study in which they appeared. Trial Registration This is a retrospective study of six previously conducted clinical trials, registered on clinicaltrials.gov with the following registration IDs: NCT04081610, NCT03524157, NCT03520348, NCT03966365, NCT03965052 and, NCT03519516.
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Project description:The clinical development of cancer drugs is rapidly moving from empirical "one drug fits all" or development-by-tumor-type approaches towards more personalized treatment models. A deeper understanding of cancer and the immune system, novel technologies, and powerful analytics have fueled an increase in precision oncology approaches integrating the molecular profiles of the tumor with the clinical profile of the patient. While this approach has been successful for targeted therapies, the complex mode of action of immunotherapies will likely require integration of clinical profiling with more comprehensive profiling of the tumor, of the tumor microenvironment, and of the immune system of the patient. Integration of precision oncology into clinical research for immunotherapies is viewed as a means to better select patients in the early clinical phase of drug development to (1) maximize the benefit-to-risk ratio for the patient, (2) generate early proof of concept and proof of relevance for the investigational drug, and (3) inform on how to best combine or sequence the therapeutic with other drugs. Here we discuss the upsides and challenges of incorporating precision immuno-oncology into early-phase clinical trials.
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Project description:When designing phase II clinical trials, it is important to construct interim monitoring rules that achieve a balance between reliable early stopping for futility or safety and maintaining a high true positive probability (TPP), which is the probability of not stopping if the new treatment is truly safe and effective. We define and compare several methods for specifying early stopping boundaries as functions of interim sample size, rather than as fixed cut-offs, using Bayesian posterior probabilities as decision criteria. We consider boundaries with constant, linear, or exponential shapes. For design optimization criteria, we use the TPP and mean number of patients enrolled in the trial. Simulations to evaluate and compare the designs' operating characteristics under a range of scenarios show that, while there is no uniformly optimal boundary, an appropriately calibrated exponential shape maintains high TPP while limiting the number of patients assigned to a treatment with an inferior response rate or an excessive toxicity rate.
| S-EPMC9149588 | biostudies-literature