Evidence map›Paper›PMID 31799471›Full record

ArticleContemporary clinical trials communications2019

2D (2 Dimensional) TEQR design for Determining the optimal Dose for safety and efficacy.

Revathi Ananthakrishnan, Stephanie Green, Daniel Li, Michael LaValley

Erratum issuedAbstract read
In one paragraph

Article in Contemporary clinical trials communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Chimeric antigen receptor T-cell therapies: Optimising the dose.British journal of clinical pharmacology · 2020
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Revathi AnanthakrishnanCelgene, 300 Connell Drive, Berkeley Heights, NJ, 07922, USA.
Stephanie GreenNew London, CT, 06320, USA.
Daniel LiJuno Therapeutics, A Celgene Company, Seattle, WA, 98109, USA.
Michael LaValleyBoston University, School of Public Health, Boston, MA, 02118, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Designs, such as the Eff-Tox, OBD (optimal biological dose), STEIN (simple efficacy toxicity interval), and TEPI (toxicity efficacy probability interval) designs, have been proposed to determine the optimal dose of a new oncology drug using both efficacy and toxicity. The goal of these designs is to select the optimal drug dose for further phase trials more accurately than dose finding designs that only consider toxicity, such as the 3 + 3, TEQR (toxicity equivalence range), mTPI (modified toxicity probability interval), and EWOC (escalation with overdose control) designs. We propose a new frequentist design for optimal dose selection, the 2D TEQR design, that is easier to understand and simpler to implement than the TEPI, Eff-Tox, STEIN and OBD designs, as it is based on the empirical or observed toxicity and efficacy rates and does not require specialized computations. We compare the performance of this new design with those of the TEPI, STEIN, Eff-Tox and OBD Isotonic designs. Although for the same sample size and cohort size, the frequentist 2D TEQR design is less accurate than the Bayesian TEPI design and also the STEIN design in selecting the optimal dose, the accuracy of optimal dose selection of the 2D TEQR design can be increased, in many cases, with a moderate increase in cohort size. The 2D TEQR design is as accurate as or more accurate than the Eff-Tox design in optimal dose selection, and better than the OBD Isotonic design, unless there is a clear peak in the true response rates, in which case the OBD Isotonic design performs better than the other designs.

Indexed as

2D TEQR designEarly phase oncology designOBD isotonic and eff-tox designsOptimal dose for safety and efficacy

Identifiers

PMID31799471
PMCPMC6881644

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