Evidence map›Paper›PMID 29740620›Full record

ArticleContemporary clinical trials communications2017

Systematic comparison of the statistical operating characteristics of various Phase I oncology designs.

Revathi Ananthakrishnan, Stephanie Green, Mark Chang, Gheorghe Doros, Joseph Massaro, Michael LaValley

Abstract read
In one paragraph

Article in Contemporary clinical trials communications, 2017. 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. First-in-Human Study of [Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2025
    Trial
  2. Article
  3. Article
  4. Phase I CAR-T Clinical Trials Review.Anticancer research · 2022
    Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. The Impact of Early-Phase Trial Design in the Drug Development Process.Clinical cancer research : an official journal of the American Association for Cancer Research · 2019
    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.

Revathi AnanthakrishnanDepartment of Biostatistics, Boston University, 801 Massachusetts Avenue 3rd Floor, Boston, MA 02118, USA.
Stephanie GreenPfizer Oncology, 445 Eastern Point Road, Groton, CT 06340, USA.
Mark ChangDepartment of Biostatistics, Boston University, 801 Massachusetts Avenue 3rd Floor, Boston, MA 02118, USA.
Gheorghe DorosDepartment of Biostatistics, Boston University, 801 Massachusetts Avenue 3rd Floor, Boston, MA 02118, USA.
Joseph MassaroDepartment of Biostatistics, Boston University, 801 Massachusetts Avenue 3rd Floor, Boston, MA 02118, USA.
Michael LaValleyDepartment of Biostatistics, Boston University, 801 Massachusetts Avenue 3rd Floor, Boston, MA 02118, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dose finding Phase I oncology designs can be broadly categorized as rule based, such as the 3 + 3 and the accelerated titration designs, or model based, such as the CRM and Eff-Tox designs. This paper systematically reviews and compares through simulations several statistical operating characteristics, including the accuracy of maximum tolerated dose (MTD) selection, the percentage of patients assigned to the MTD, over-dosing, under-dosing, and the trial dose-limiting toxicity (DLT) rate, of eleven rule-based and model-based Phase I oncology designs that target or pre-specify a DLT rate of ∼0.2, for three sets of true DLT probabilities. These DLT probabilities are generated at common dosages from specific linear, logistic, and log-logistic dose-toxicity curves. We find that all the designs examined select the MTD much more accurately when there is a clear separation between the true DLT rate at the MTD and the rates at the dose level immediately above and below it, such as for the DLT rates generated using the chosen logistic dose-toxicity curve; the separations in these true DLT rates depend, in turn, not only on the functional form of the dose-toxicity curve but also on the investigated dose levels and the parameter set-up. The model based mTPI, TEQR, BOIN, CRM and EWOC designs perform well and assign the greatest percentages of patients to the MTD, and also have a reasonably high probability of picking the true MTD across the three dose-toxicity curves examined. Among the rule-based designs studied, the 5 + 5 a design picks the MTD as accurately as the model based designs for the true DLT rates generated using the chosen log-logistic and linear dose-toxicity curves, but requires enrolling a higher number of patients than the other designs. We also find that it is critical to pick a design that is aligned with the true DLT rate of interest. Further, we note that Phase I trials are very small in general and hence may not provide accurate estimates of the MTD. Thus our work provides a map for planning Phase I oncology trials or developing new ones.

Indexed as

Accuracy of MTD selectionBOIN design, Bayesian optimal interval designCRM, continual reassessment methodDLT, dose limiting toxicityDose findingEWOC design, escalation with overdose control designModel-based designsMTD, maximum tolerated dosemTPI design, modified toxicity probability interval designOncologyPhase 1 designsRule-based designsTEQR design, toxicity equivalence range design

Identifiers

PMID29740620
PMCPMC5936704

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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.