Evidence map›Paper›PMID 26448046›Full record

ArticlePloS one2015

Statistical Use in Clinical Studies: Is There Evidence of a Methodological Shift?

Dali Yi, Dihui Ma, Gaoming Li, Liang Zhou, Qin Xiao, Yanqi Zhang, Xiaoyu Liu, Hongru Chen, Julia Christine Pettigrew, Dong Yi and 2 more

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Reporting of data analysis methods in psychiatric journals: Trends from 1996 to 2018.International journal of methods in psychiatric research · 2019
    Article
  6. Female-Authored Articles Are More Likely to Include Methods-Trained Authors.Mayo Clinic proceedings. Innovations, quality & outcomes · 2019
    Article
  7. Article
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.

Dali YiDepartment of Health Statistics, College of Preventive Medicine, Third Military Medical University, Chongqing, China.
Dihui MaDepartment of Health Statistics, College of Preventive Medicine, Third Military Medical University, Chongqing, China.
Gaoming LiDepartment of Health Statistics, College of Preventive Medicine, Third Military Medical University, Chongqing, China.
Liang ZhouDepartment of Health Statistics, College of Preventive Medicine, Third Military Medical University, Chongqing, China.
Qin XiaoDepartment of Health Statistics, College of Preventive Medicine, Third Military Medical University, Chongqing, China.
Yanqi ZhangDepartment of Health Statistics, College of Preventive Medicine, Third Military Medical University, Chongqing, China.
Xiaoyu LiuDepartment of Health Statistics, College of Preventive Medicine, Third Military Medical University, Chongqing, China.
Hongru ChenDepartment of Health Statistics, College of Preventive Medicine, Third Military Medical University, Chongqing, China.
Julia Christine PettigrewUniversity of Washington, School of Arts and Sciences, Department of Biological Sciences, Seattle, Washington, United States of America; University of Washington, School of Arts and Sciences, Department of Asian Language and Literature, Seattle, Washington, United States of America.
Dong YiDepartment of Health Statistics, College of Preventive Medicine, Third Military Medical University, Chongqing, China.
Ling LiuDepartment of Health Statistics, College of Preventive Medicine, Third Military Medical University, Chongqing, China.
Yazhou WuDepartment of Health Statistics, College of Preventive Medicine, Third Military Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSeveral studies indicate that the statistical education model and level in medical training fails to meet the demands of clinicians, especially when they want to understand published clinical research. We investigated how study designs and statistical methods in clinical studies have changed in the last twenty years, and we identified the current trends in study designs and statistical methods in clinical studies.

methodsWe reviewed 838 eligible clinical study articles that were published in 1990, 2000, and 2010 in four journals New England Journal of Medicine, Lancet, Journal of the American Medical Association and Nature Medicine. The study types, study designs, sample designs, data quality controls, statistical methods and statistical software were examined.

resultsSubstantial changes occurred in the past twenty years. The majority of the studies focused on drug trials (61.6%, n = 516). In 1990, 2000, and 2010, there was an incremental increase in RCT studies (74.4%, 82.8%, and 84.0%, respectively, p = 0.013). Over time, there was increased attention on the details of selecting a sample and controlling bias, and there was a higher frequency of utilizing complex statistical methods. In 2010, the most common statistical methods were confidence interval for superiority and non-inferiority comparison (41.6%), survival analysis (28.5%), correction analysis for covariates (18.8%) and Logistic regression (15.3%).

conclusionsThese findings indicate that statistical measures in clinical studies are continuously developing and that the credibility of clinical study results is increasing. These findings provide information for future changes in statistical training in medical education.

Indexed as

Models, StatisticalData Interpretation, StatisticalHumansRandomized Controlled Trials as TopicResearch DesignSoftware

Identifiers

PMID26448046
PMCPMC4598157

What OpenQuestion holds

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LicenceCC BY
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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.