Evidence map›Paper›PMID 33647505›Full record

ArticleJournal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer2021

Statistical Models in Clinical Studies.

Shigeyuki Matsui, Jennifer Le-Rademacher, Sumithra J Mandrekar

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

3 authors.

Shigeyuki MatsuiDepartment of Biostatistics, Nagoya University Graduate School of Medicine, Nagoya, Japan; Department of Data Science, The Institute of Statistical Mathematics, Tokyo, Japan. Electronic address: smatsui@med.nagoya-u.ac.jp.
Jennifer Le-RademacherDepartment of Health Sciences, Research, Mayo Clinic, Rochester, Minnesota.
Sumithra J MandrekarDepartment of Health Sciences, Research, Mayo Clinic, Rochester, Minnesota.

Funding

Women's Cancer ProgramP30CA015083 · NCI · MAYO CLINIC ROCHESTER · PI AKHILESH PANDEY · 1985 to 2026
$151.3M
Statistics CoreU10CA180882 · NCI · MAYO CLINIC ROCHESTER · PI Sumithra Jay Mandrekar · 2014 to 2026
$115.0M
NCI NIH HHS P30 CA015083NCI NIH HHS U10 CA180882
6 · The paper itself

Abstract

Although statistical models serve as the foundation of data analysis in clinical studies, their interpretation requires sufficient understanding of the underlying statistical framework. Statistical modeling is inherently a difficult task because of the general lack of information of the nature of observable data. In this article, we aim to provide some guidance when using regression models to aid clinical researchers to better interpret results from their statistical models and to encourage investigators to collaborate with a statistician to ensure that their studies are designed and analyzed appropriately.

Indexed as

Lung NeoplasmsHumansModels, StatisticalClassification and predictionEffect AssessmentMultivariable modelsRegression modelsStatistical modelsUnivariable models

Identifiers

PMID33647505
PMCPMC8085106

What OpenQuestion holds

Textmetadata
LicenceTDM
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.