Evidence map›Paper›PMID 37275462›Full record

ArticleStatistics in biopharmaceutical research2022

Accuracy and Safety of Novel Designs for Phase I Drug-Combination Oncology Trials.

Rong Liu, Ying Yuan, Suman Sen, Xin Yang, Qi Jiang, Xiaoyun Nicole Li, Chengxing Cindy Lu, Mithat Göneng, Hong Tian, Heng Zhou and 2 more

Abstract read
In one paragraph

Article in Statistics in biopharmaceutical research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
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

12 authors.

Rong LiuBristol-Myers Squibb, Berkeley Heights, NJ 07922.
Ying YuanThe University of Texas MD Anderson Cancer Center, Houston, TX 77030.
Suman SenNovartis, East Hanover, NJ 07936.
Xin YangNovartis, East Hanover, NJ 07936.
Qi JiangSeattle Genetics, Bothell, WA 98021.
Xiaoyun Nicole LiMerck & Co., Inc., Kenilworth, NJ 07033.
Chengxing Cindy LuAstraZeneca, Gaithersburg, MD 20878.
Mithat GönengMemorial Sloan Kettering Cancer Center, New York, NY 10022.
Hong TianBeiGene, Ridgefield Park, NJ 07660.
Heng ZhouMerck & Co., Inc., Kenilworth, NJ 07033.
Ruitao LinThe University of Texas MD Anderson Cancer Center, Houston, TX 77030.
Olga MarchenkoBayer, Whippany, NJ 07981.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
Bayesian Methods for Complex Precision Biotherapy Trials in OncologyR01CA261978 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LIN, RUITAO, THALL, PETER F · 2021 to 2024
$1.4M
NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA261978
6 · The paper itself

Abstract

Despite numerous innovative designs having been published for phase I drug-combination dose finding trials, their use in real applications is rather limited. As a working group under the American Statistical Association Biopharmaceutical Section, our goal is to identify the unique challenges associated with drug combination, share industry's experiences with combination trials, and investigate the pros and cons of the existing designs. Toward this goal, we review seven existing designs and distinguish them based on the criterion of whether their primary objectives are to find a single maximum tolerated dose (MTD) or the MTD contour (i.e., multiple MTDs). Numerical studies, based on either industry-specified fixed scenarios or randomly generated scenarios, are performed to assess their relative accuracy, safety, and ease of implementation. We show that the algorithm-based 3+3 design has poor performance and often fails to find the MTD. The performance of model-based combination trial designs is mixed: some demonstrate high accuracy of finding the MTD but poor safety, while others are safe but with compromised identification accuracy. In comparison, the model-assisted designs, such as BOIN and waterfall designs, have competitive and balanced performance in the accuracy of MTD identification and patient safety, and are also simple to implement, thus offering an attractive approach to designing phase I drug-combination trials. By taking into consideration the design's operating characteristics, ease of implementation and regulation, the need for advanced infrastructures, as well as the risk of regulatory acceptance, our paper offers practical guidance on the selection of a suitable dose-finding approach for designing future combination trials.

Indexed as

Clinical trialDose findingDrug combinationMaximum tolerated doseToxicity

Identifiers

PMID37275462
PMCPMC10237505

What OpenQuestion holds

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Registered trials

None linked

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.