Evaluation of Tumor Size Response Metrics to Predict Survival in Oncology Clinical Trials

Bruno, René; Mercier, François; Claret, Laurent

doi:10.1038/clpt.2014.4

Cited by 60 publications

(102 citation statements)

References 54 publications

(67 reference statements)

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“…It is important, however, to ensure that there is a good understanding of the relationship between the target and the biomarker. The use of tumor size can be an important effect marker especially when continuous tumor size reduction is used as a continuous variable rather than a categorical variable as in the RECIST categories (11,12). The proposed approach could target a wide range of doses (5-fold or greater) that includes a minimal effective dose and an MTD.…”

Section: New Approachesmentioning

confidence: 99%

Rendering the 3 + 3 Design to Rest: More Efficient Approaches to Oncology Dose-Finding Trials in the Era of Targeted Therapy

Nie¹,

Rubin²,

Mehrotra³

et al. 2016

Clinical Cancer Research

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Selection of the maximum tolerated dose (MTD) as the recommended dose for registration trials based on a doseescalation trial using variations of an MTD/3 þ 3 design often occurs in the development of oncology products. The MTD/3 þ 3 approach is not optimal and may result in recommended doses that are unacceptably toxic for many patients and in dose reduction/interruptions that might have an impact on effectiveness. Instead of the MTD/3 þ 3 approach, the authors recommend an integrated approach. In this approach, typically an adaptive/Bayesian model provides a general framework to incorporate and make decisions for dose escalation based on nonclinical data, such as animal efficacy and toxicity data; clinical data, including pharmacokinetics/pharmacodynamics data; and dose/exposure-response data for efficacy and safety. To improve dose-ranging trials, model-based estimation, rather than hypothesis testing, should be used to maximize and integrate the information gathered across trials and doses. This approach may improve identification of optimal recommended doses, which can then be confirmed in registration trials.

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Section: New Approachesmentioning

confidence: 99%

Rendering the 3 + 3 Design to Rest: More Efficient Approaches to Oncology Dose-Finding Trials in the Era of Targeted Therapy

Nie¹,

Rubin²,

Mehrotra³

et al. 2016

Clinical Cancer Research

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“…For many mAbs, target engagement has been an important dosedriving marker. The use of tumor size can be an important effect marker for making decisions early in development, especially (and with more statistical power) when continuous tumor size reduction is used directly without discretization into the RECIST categories (40,41). Sometimes toxicity, such as neutropenia, can also be a useful effect marker.…”

Section: Discussionmentioning

confidence: 99%

Optimal Dosing for Targeted Therapies in Oncology: Drug Development Cases Leading by Example

Sachs

Mayawala

Gadamsetty

et al. 2016

Clinical Cancer Research

120

104

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One of the key objectives of oncology first-in-human trials has often been to establish the maximum tolerated dose (MTD). However, targeted therapies might not exhibit doselimiting toxicities (DLT) at doses significantly higher than sufficiently active doses, and there is frequently a limited ability to objectively quantify adverse events. Thus, while MTD-based determination of recommended phase II dose may have yielded appropriate dosing for some cytotoxics, targeted therapeutics (including monoclonal antibodies and/or immunotherapies) sometimes need alternative or complementary strategies to help identify dose ranges for a randomized dose-ranging study. One complementary strategy is to define a biologically efficacious dose (BED) using an "effect marker." An effect marker could be a target engagement, pharmacodynamic, or disease progression marker (change in tumor size for solid tumors or bone marrow blast count for some hematologic tumors). Although the concept of BED has been discussed extensively, we review specific examples in which the approach influenced oncology clinical development. Data extracted from the literature and the examples support improving dose selection strategies to benefit patients, providers, and the biopharmaceutical industry. Although the examples illustrate key contributions of effect markers in dose selection, no one-size-fits-all approach to dosing can be justified. Higher-than-optimal dosing can increase toxicity in later trials (and in clinical use), which can have a negative impact on efficacy (via lower adherence or direct sequelae of toxicities). Proper dose selection in oncology should follow a multifactorial decision process leading to a randomized, dose-ranging study instead of a single phase II dose.

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“…Recently, the limitation of ER analysis based on one dose level and a potential “false positive” ER relationship due to confounding factors for biologics have been acknowledged. Various approaches have been explored to address the confounding factors in ER analysis, such as incorporating case–control comparison, time‐varying CL, and TGI 23, 34, 43, 44, 45…”

Section: Future Opportunitiesmentioning

confidence: 99%

Challenges and Opportunities in Dose Finding in Oncology and Immuno‐oncology

Jin

Hyman

et al. 2018

Clinical Translational Sci

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Evaluation of Tumor Size Response Metrics to Predict Survival in Oncology Clinical Trials

Cited by 60 publications

References 54 publications

Rendering the 3 + 3 Design to Rest: More Efficient Approaches to Oncology Dose-Finding Trials in the Era of Targeted Therapy

Rendering the 3 + 3 Design to Rest: More Efficient Approaches to Oncology Dose-Finding Trials in the Era of Targeted Therapy

Optimal Dosing for Targeted Therapies in Oncology: Drug Development Cases Leading by Example

Challenges and Opportunities in Dose Finding in Oncology and Immuno‐oncology

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