Evidence map›Paper›PMID 29769209›Full record

ArticleClinical cancer research : an official journal of the American Association for Cancer Research2018

Time-to-Event Bayesian Optimal Interval Design to Accelerate Phase I Trials.

Ying Yuan, Ruitao Lin, Daniel Li, Lei Nie, Katherine E Warren

2 registry-linked trialsOpen access · bronzeAbstract read
In one paragraph

Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 53 papers.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed
10.3field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT05603702 phase1active not recruitingnot on this mapstarted 2023, after this paper: background citation

STTEPP: Safety, Tolerability and Dose Limiting Toxicity of Lacosamide in Patients With Painful Chronic Pancreatitis

TypeinterventionalSponsorIndiana UniversityRan2023 to 2027Enrolled21ConditionsChronic Pain, Chronic Pain Syndrome, Chronic Pancreatitis, HyperalgesiaArmsLacosamide
NCT06192758 naactive not recruitingnot on this mapstarted 2024, after this paper: background citation

An Early Feasibility Study to Evaluate the Safety of the TheraSphere Prostate Cancer (PCa) Device in Patients With Clinically Localized Prostate Cancer

TypeinterventionalSponsorBoston Scientific CorporationRan2024 to 2032Enrolled36ConditionsProstate, CancerArmsTheraSphere PCa
3 · Its place in the literature

Who cites it

53 citing papers in PubMed, 125 citations in OpenAlex.

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  7. Practical Considerations for Using the TITE-BOIN Design to Handle Late-Onset Toxicity or Fast Accrual in Phase I Trials.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025
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  14. Tips for Accelerating BOIN Design.Therapeutic innovation & regulatory science · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 2 countries.

Ying YuanDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas. yyuan@mdanderson.org daniel.li@junotherapeutics.com.
Ruitao LinDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Daniel LiJuno Therapeutics, Seattle, Washington. yyuan@mdanderson.org daniel.li@junotherapeutics.com.
Lei NieCenter for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland.
Katherine E WarrenCenter for Cancer Research, National Cancer Institute, Bethesda, Maryland.
The University of Texas MD Anderson Cancer Center · USCenter for Drug Evaluation and Research · USInternational Therapeutics (United States) · USNational Cancer Institute · US

Funding

Targeting the PI3K Signaling Pathway in Endometrial CarcinomaP50CA098258 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI BODURKA, DIANE · 2003 to 2020
$32.0M
Early Clinical Trials for Children with CNS TumorsZIABC011447 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI WARREN, KATHERINE E · 2012 to 2019
$2.1M
NCI NIH HHS P50 CA098258
6 · The paper itself

Abstract

Late-onset toxicity is common for novel molecularly targeted agents and immunotherapy. It causes major logistic difficulty for existing adaptive phase I trial designs, which require the observance of toxicity early enough to apply dose-escalation rules for new patients. The same logistic difficulty arises when the accrual is rapid. We propose the time-to-event Bayesian optimal interval (TITE-BOIN) design to accelerate phase I trials by allowing for real-time dose assignment decisions for new patients while some enrolled patients' toxicity data are still pending. Similar to the rolling six design, the TITE-BOIN dose-escalation/deescalation rule can be tabulated before the trial begins, making it transparent and simple to implement, but is more flexible in choosing the target dose-limiting toxicity (DLT) rate and has higher accuracy to identify the MTD. Compared with the more complicated model-based time-to-event continuous reassessment method (TITE-CRM), the TITE-BOIN has comparable accuracy to identify the MTD but is simpler to implement with substantially better overdose control. As the TITE-CRM is more aggressive in dose escalation, it is less likely to underdose patients. When there are no pending data, the TITE-BOIN seamlessly reduces to the BOIN design. Numerical studies show that the TITE-BOIN design supports continuous accrual without sacrificing patient safety or the accuracy of identifying the MTD, and therefore has great potential to accelerate early-phase drug development.

Indexed as

Bayes TheoremClinical Trials, Phase I as TopicResearch DesignAlgorithmsAntineoplastic AgentsAntineoplastic Combined Chemotherapy ProtocolsComputer SimulationHumansModels, StatisticalNeoplasmsTime FactorsAntineoplastic Agents

Identifiers

PMID29769209
PMCPMC6191365
OpenAlexW2804829033

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.