Evidence map›Paper›PMID 35178111›Full record

ArticleComputational and mathematical methods in medicine2022

Efficient Algorithms and Implementation of a Semiparametric Joint Model for Longitudinal and Competing Risk Data: With Applications to Massive Biobank Data.

Shanpeng Li, Ning Li, Hong Wang, Jin Zhou, Hua Zhou, Gang Li

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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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.

Shanpeng LiDepartment of Biostatistics, University of California at Los Angeles, Los Angeles, CA, USA.ORCID https://orcid.org/0000-0002-0724-4564
Ning LiDepartment of Medicine, University of California at Los Angeles, Los Angeles, CA, USA.
Hong WangSchool of Mathematics and Statistics, Central South University, Changsha, China.
Jin ZhouDepartment of Biostatistics, University of California at Los Angeles, Los Angeles, CA, USA.ORCID https://orcid.org/0000-0001-7983-0274
Hua ZhouDepartment of Biostatistics, University of California at Los Angeles, Los Angeles, CA, USA.ORCID https://orcid.org/0000-0003-1320-7118
Gang LiDepartment of Biostatistics, University of California at Los Angeles, Los Angeles, CA, USA.ORCID https://orcid.org/0000-0002-4753-9420

Funding

Women's CancersP30CA016042 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Samuel Wheeler French · 1985 to 2026
$134.5M
UCLA Clinical Translational Science InstituteUL1TR001881 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ARLEEN F. BROWN, ARASH NAEIM · 2016 to 2026
$118.1M
UCLA Clinical and Translational Science InstituteUL1TR000124 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DUBINETT, STEVEN M. · 2012 to 2015
$57.0M
UCLA SPORE in Brain CancerP50CA211015 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Yvonne Yu-Hsuan Chen · 2017 to 2026
$25.2M
UCLA Center for Excellence in Pancreatic DiseasesP01AT003960 · NCCIH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI GO, VAY LIANG W · 2007 to 2011
$5.6M
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
Develop T2D Patient-Centered Treatment Suggestion Rule using EMR dataK01DK106116 · NIDDK · UNIVERSITY OF ARIZONA · PI ZHOU, JIN · 2016 to 2019
$524k
A Role for Glycemic Variation in Optimizing Management of Diabetes and Vascular ComplicationsR21HL150374 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI REAVEN, PETER D, ZHOU, JIN · 2020 to 2021
$250k
NCATS NIH HHS UL1 TR000124NCATS NIH HHS UL1 TR001881NCCIH NIH HHS P01 AT003960NCI NIH HHS P30 CA016042NCI NIH HHS P50 CA211015NHGRI NIH HHS R01 HG006139NHLBI NIH HHS R21 HL150374NIDDK NIH HHS K01 DK106116NIGMS NIH HHS R35 GM141798
6 · The paper itself

Abstract

Semiparametric joint models of longitudinal and competing risk data are computationally costly, and their current implementations do not scale well to massive biobank data. This paper identifies and addresses some key computational barriers in a semiparametric joint model for longitudinal and competing risk survival data. By developing and implementing customized linear scan algorithms, we reduce the computational complexities from

Indexed as

AlgorithmsModels, StatisticalBiological Specimen BanksBronchodilator AgentsComputational BiologyComputer SimulationData Interpretation, StatisticalDisease ProgressionHumansLongitudinal StudiesPrimary Health CarePulmonary Disease, Chronic ObstructiveRisk AssessmentSmoking CessationSoftwareBronchodilator Agents

Identifiers

PMID35178111
PMCPMC8846996

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.