Evidence map›Paper›PMID 37301716›Full record

ArticleEuropean journal of cancer (Oxford, England : 1990)2023

Early phase clinical trials in oncology: Realising the potential of seamless designs.

Thomas Jaki, Abigail Burdon, Xijin Chen, Pavel Mozgunov, Haiyan Zheng, Richard Baird

Abstract read
In one paragraph

Article in European journal of cancer (Oxford, England : 1990), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Estimands for Early-Phase Dose Optimization Trials in Oncology.Biometrical journal. Biometrische Zeitschrift · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Article
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

6 authors.

Thomas JakiMRC Biostatistics Unit, University of Cambridge, UK; University of Regensburg, Germany. Electronic address: thomas.jaki@mrc-bsu.cam.ac.uk.
Abigail BurdonMRC Biostatistics Unit, University of Cambridge, UK.
Xijin ChenMRC Biostatistics Unit, University of Cambridge, UK.
Pavel MozgunovMRC Biostatistics Unit, University of Cambridge, UK.
Haiyan ZhengMRC Biostatistics Unit, University of Cambridge, UK.
Richard BairdDepartment of Oncology, University of Cambridge, UK.

Funding

Cancer Research UK RCCPDF\100008Medical Research Council MC_UU_00002/14
6 · The paper itself

Abstract

backgroundThe pharmaceutical industry's productivity has been declining over the last two decades and high attrition rates and reduced regulatory approvals are being seen. The development of oncology drugs is particularly challenging with low rates of approval for novel treatments when compared with other therapeutic areas. Reliably establishing the potential of novel treatment and the corresponding optimal dosage is a key component to ensure efficient overall development. A growing interest lies in terminating developments of poor treatments quickly while enabling accelerated development for highly promising interventions.

methodsOne approach to reliably establish the optimal dosage and the potential of a novel treatment and thereby improve efficiency in the drug development pathway is the use of novel statistical designs that make efficient use of the data collected.

resultsIn this paper, we discuss different (seamless) strategies for early oncology development and illustrate their strengths and weaknesses through real trial examples. We provide some directions for good practices in early oncology development, discuss frequently seen missed opportunities for improved efficiency and some future opportunities that have yet to fully develop their potential in early oncology treatment development. DISCUSSION: Modern methods for dose-finding have the potential to shorten and improve dose-finding and only small changes to current approaches are required to realise this potential.

Indexed as

Medical OncologyNeoplasmsDrug DevelopmentHumansResearch DesignDose-determinationEfficient trialsModel-based designs

Identifiers

PMID37301716
PMCPMC7614750

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Registered trials

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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.