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Abstract A100: Seamless phase I/II clinical trials in oncology: retrospective analysis of the last 7 years

2018· article· en· W2886557345 on OpenAlexaff
Pedro Barata, Brian P. Hobbs, Brian I. Rini, Channing J. Paller, Daniel P. Normolle, Elizabeth Garrett‐Mayer, Eric H. Rubin, Gary L. Rosner, Gregory R. Pond, Jane Perlmutter, Lesley Seymour, Lillian L. Siu, Nolan A. Wages, Percy Ivy, Tatiana M. Prowell, Timothy A. Yap, David S. Hong

Bibliographic record

VenueMolecular Cancer Therapeutics · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsPrincess Margaret Cancer CentreQueen's UniversityMcMaster University
Fundersnot available
KeywordsMedicineClinical trialInternal medicinePhases of clinical researchClinical OncologyPopulationOncologyFood and drug administrationCancerDrug developmentSample size determinationDrugPharmacology

Abstract

fetched live from OpenAlex

Abstract Introduction: Drug development has evolved from the conventional sequence of three-phase clinical trial process to a seamless approach of adding cohorts to first-in-human trials to investigate both safety and efficacy in various cancers. In this retrospective study, we evaluated the prevalence of large early-phase studies in adult cancer patients; described the clinical characteristics, design, and statistical plan of these studies; and identified which investigational drugs using this seamless strategy were included in the accelerated approval program by the Food and Drug Administration (FDA). Methods: All abstracts presented at the American Society of Clinical Oncology (ASCO) annual meetings from 2010 to 2017 were reviewed. Clinical studies conducted in the pediatric population as well as abstracts reporting trials in progress were excluded. Seamless clinical trials were defined as any phase I/II studies with a sample size of 100 or more patients. The Center for Drug Evaluation and Research (CDER) drug approvals report was used to access the list of drugs included in the accelerated approval program by FDA. Results: We identified a total of 1786 early-phase trials enrolling more than 57,500 patients with malignant neoplasms. More frequently these studies included patients with advanced solid tumors (87%) and targeted therapy and immunotherapy agents were investigated in 64% and 15% of the cases, respectively. Of the 1786 trials, 51 were identified as seamless phase I/II with a sample size of 100 or more patients, representing only 3% of the total number of trials (n=1786) but 15% of the total number of patients (n=57,559). These seamless trials had a median number of 3 (1-13) expansion cohorts and a higher fraction (65%) were presented in the last 3 years (2014-2017), compared with 35% of the studies with results presented between 2010-2013. Fifty active investigational new drugs (67% targeted therapy, 18% immunotherapy, 10% antibody-drug conjugate, 2.0% chemotherapy, 3.9% other) were studied as single agents (53%) or in combination with other therapies (47%). Of the 51 identified large seamless phase I/II trials, only 29 (57%) studies had published results. Further, of these 29 studies, a planned statistical analysis for the calculation of the expansion cohorts’ sample-size was not available in 69% of the cases. The overall rate of significant (grade 3-4) adverse events was 49% (range, 0-100%), and at least one toxic death was reported in 5 of these studies. The pooled response rate (CR+PR) per study was 20% (range, 0.9-77). Considering the group of drugs studied in the 51-seamless phase I/II trials identified here, the FDA granted accelerated approval to 8 drugs and 1 other agent was given priority review. Conclusions: Approximately two-thirds of the studies identified were presented after the year 2014, suggesting an increased use of the seamless approach. While the high rate of accelerated approvals granted by the FDA endorses the observed preliminary clinical benefit of these drugs, the absence of a prespecified statistical plan is a weakness of most of the published studies. Citation Format: Pedro Barata, Brian Hobbs, Brian Rini, Channing Paller, Dan Normolle, Elizabeth Garrett-Mayer, Eric Rubin, Gary Rosner, Greg Pond, Jane Perlmutter, Lesley Seymour, Lillian Siu, Nolan Wages, Percy Ivy, Tatiana Prowell, Timothy Yap, David Hong. Seamless phase I/II clinical trials in oncology: retrospective analysis of the last 7 years [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2017 Oct 26-30; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2018;17(1 Suppl):Abstract nr A100.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.038
metaresearch head score (Gemma)0.109
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.109
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0090.012
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.068
GPT teacher head0.431
Teacher spread0.363 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2018
Admission routes1
Has abstractyes

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