A bootstrapping method to optimize go/no‐go decisions from single‐arm, signal‐finding studies in oncology
Abstract Phase Ib trials are common in oncology development but often are not powered for statistical significance. Go/no‐go decisions are largely driven by observed trends in response data. We applied a bootstrapping method to systematically compare tumor dynamic end points to historical control da...
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| Format: | Article |
| Language: | English |
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Wiley
2024-08-01
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| Series: | CPT: Pharmacometrics & Systems Pharmacology |
| Online Access: | https://doi.org/10.1002/psp4.13161 |
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| author | Raunak Dutta Aparna Mohan Jacqueline Buros‐Novik Gregory Goldmacher Omobolaji O. Akala Brian Topp |
| author_facet | Raunak Dutta Aparna Mohan Jacqueline Buros‐Novik Gregory Goldmacher Omobolaji O. Akala Brian Topp |
| author_sort | Raunak Dutta |
| collection | DOAJ |
| description | Abstract Phase Ib trials are common in oncology development but often are not powered for statistical significance. Go/no‐go decisions are largely driven by observed trends in response data. We applied a bootstrapping method to systematically compare tumor dynamic end points to historical control data to identify drugs with clinically meaningful efficacy. A proprietary mathematical model calibrated to phase Ib anti–PD‐1 therapy trial data (KEYNOTE‐001) was used to simulate thousands of phase Ib trials (n = 30) with a combination of anti–PD‐1 therapy and four novel agents with varying efficacy. A redacted bootstrapping method compared these results to a simulated phase III control arm (N = 511) while adjusting for differences in trial duration and cohort size to determine the probability that the novel agent provides clinically meaningful efficacy. Receiver operating characteristic (ROC) analysis showed strong ability to separate drugs with modest (area under ROC [AUROC] = 83%), moderate (AUROC = 96%), and considerable efficacy (AUROC = 99%) from placebo in early‐phase trials (n = 30). The method was shown to effectively move drugs with a range of efficacy through an in silico pipeline with an overall success rate of 93% and false‐positive rate of 7.5% from phase I to phase III. This model allows for effective comparisons of tumor dynamics from early clinical trials with more mature historical control data and provides a framework to predict drug efficacy in early‐phase trials. We suggest this method should be employed to improve decision making in early oncology trials. |
| format | Article |
| id | doaj-art-7906cbcfdc6248e39282ae02750e4a99 |
| institution | DOAJ |
| issn | 2163-8306 |
| language | English |
| publishDate | 2024-08-01 |
| publisher | Wiley |
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| series | CPT: Pharmacometrics & Systems Pharmacology |
| spelling | doaj-art-7906cbcfdc6248e39282ae02750e4a992025-08-20T02:44:29ZengWileyCPT: Pharmacometrics & Systems Pharmacology2163-83062024-08-011381317132610.1002/psp4.13161A bootstrapping method to optimize go/no‐go decisions from single‐arm, signal‐finding studies in oncologyRaunak Dutta0Aparna Mohan1Jacqueline Buros‐Novik2Gregory Goldmacher3Omobolaji O. Akala4Brian Topp5Modeling and Simulation Vantage Research Chennai IndiaModeling and Simulation Vantage Research Chennai IndiaModeling and Simulation, Generable New York New York USAGlobal Clinical Trial Operations Merck & Co., Inc. Rahway New Jersey USAOncology Early Development Merck & Co., Inc. Rahway New Jersey USAOncology Early Development Merck & Co., Inc. Rahway New Jersey USAAbstract Phase Ib trials are common in oncology development but often are not powered for statistical significance. Go/no‐go decisions are largely driven by observed trends in response data. We applied a bootstrapping method to systematically compare tumor dynamic end points to historical control data to identify drugs with clinically meaningful efficacy. A proprietary mathematical model calibrated to phase Ib anti–PD‐1 therapy trial data (KEYNOTE‐001) was used to simulate thousands of phase Ib trials (n = 30) with a combination of anti–PD‐1 therapy and four novel agents with varying efficacy. A redacted bootstrapping method compared these results to a simulated phase III control arm (N = 511) while adjusting for differences in trial duration and cohort size to determine the probability that the novel agent provides clinically meaningful efficacy. Receiver operating characteristic (ROC) analysis showed strong ability to separate drugs with modest (area under ROC [AUROC] = 83%), moderate (AUROC = 96%), and considerable efficacy (AUROC = 99%) from placebo in early‐phase trials (n = 30). The method was shown to effectively move drugs with a range of efficacy through an in silico pipeline with an overall success rate of 93% and false‐positive rate of 7.5% from phase I to phase III. This model allows for effective comparisons of tumor dynamics from early clinical trials with more mature historical control data and provides a framework to predict drug efficacy in early‐phase trials. We suggest this method should be employed to improve decision making in early oncology trials.https://doi.org/10.1002/psp4.13161 |
| spellingShingle | Raunak Dutta Aparna Mohan Jacqueline Buros‐Novik Gregory Goldmacher Omobolaji O. Akala Brian Topp A bootstrapping method to optimize go/no‐go decisions from single‐arm, signal‐finding studies in oncology CPT: Pharmacometrics & Systems Pharmacology |
| title | A bootstrapping method to optimize go/no‐go decisions from single‐arm, signal‐finding studies in oncology |
| title_full | A bootstrapping method to optimize go/no‐go decisions from single‐arm, signal‐finding studies in oncology |
| title_fullStr | A bootstrapping method to optimize go/no‐go decisions from single‐arm, signal‐finding studies in oncology |
| title_full_unstemmed | A bootstrapping method to optimize go/no‐go decisions from single‐arm, signal‐finding studies in oncology |
| title_short | A bootstrapping method to optimize go/no‐go decisions from single‐arm, signal‐finding studies in oncology |
| title_sort | bootstrapping method to optimize go no go decisions from single arm signal finding studies in oncology |
| url | https://doi.org/10.1002/psp4.13161 |
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