Evidence map›Paper›PMID 40893409›Full record

ArticleJournal of data science, statistics, and visualisation2024

An Efficient Way to Find Optimal Crossover Designs Using CVX for Precision Medicine.

Yin Li, Weng Kee Wong, Hua Zhou, Keumhee Chough Carriere

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of data science, statistics, and visualisation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Yin LiOntario Medical Association.
Weng Kee WongUniversity of California-Los Angeles.
Hua ZhouUniversity of California-Los Angeles.
Keumhee Chough CarriereUniversity of Alberta.

Funding

Genomics, GPUs, and Next Generation Computational StatisticsR01HG006139 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SOBEL, ERIC · 2011 to 2023
$5.1M
Modeling, Inference, and Optimization for Genomic and Biomedical Big DataR35GM141798 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LANGE, KENNETH L · 2021 to 2025
$2.7M
Transforming Precision Medicine: Dynamic Learning and Prediction of Disease Progression in Massive, Diverse, and Multimodal CohortsR01DK142026 · NIDDK · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI GANG LI, Hua Zhou · 2025 to 2026
$1.1M
NHGRI NIH HHS R01 HG006139NIDDK NIH HHS R01 DK142026NIGMS NIH HHS R35 GM141798
6 · The paper itself

Abstract

Crossover designs play an increasingly important role in precision medicine. We formulate the optimal crossover design problem as a convex optimization problem and demonstrate that the convex optimization package CVX is effective for searching a broad class of optimal crossover designs, including cases where analytical optimal crossover designs are unavailable. We also use CVX to search for N-of-1 trials frequently used in precision medicine and dual-objective optimal crossover designs to estimate treatment effects and carryover treatment effects with unequal interest. We provide CVX codes and as illustrations, use them to find optimal crossover designs under the A-optimality criterion.

Indexed as

convex optimizationdual-objective optimal designinformation matrixN-of-1 trialprecision medicinerepeated measures design

Identifiers

PMID40893409
PMCPMC12395556

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.