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Cited by 26Statistical Methods in Clinical TrialsMeta-analysis and systematic reviewsStatistical Methods in Epidemiology

Trends in study design and the statistical methods employed in a leading general medicine journal

Gosho, M., Sato, Y., Nagashima, K., Takahashi, S.·2018·Journal of Clinical Pharmacy and Therapeutics
DOI 10.1111/jcpt.12605
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Abstract

WHAT IS KNOWN AND OBJECTIVE: Study design and statistical methods have become core components of medical research, and the methodology has become more multifaceted and complicated over time. The study of the comprehensive details and current trends of study design and statistical methods is required to support the future implementation of well-planned clinical studies providing information about evidence-based medicine. Our purpose was to illustrate study design and statistical methods employed in recent medical literature. METHODS: This was an extension study of Sato et al. (N Engl J Med 2017; 376: 1086-1087), which reviewed 238 articles published in 2015 in the New England Journal of Medicine (NEJM) and briefly summarized the statistical methods employed in NEJM. Using the same database, we performed a new investigation of the detailed trends in study design and individual statistical methods that were not reported in the Sato study. RESULTS AND DISCUSSION: Due to the CONSORT statement, prespecification and justification of sample size are obligatory in planning intervention studies. Although standard survival methods (eg Kaplan-Meier estimator and Cox regression model) were most frequently applied, the Gray test and Fine-Gray proportional hazard model for considering competing risks were sometimes used for a more valid statistical inference. With respect to handling missing data, model-based methods, which are valid for missing-at-random data, were more frequently used than single imputation methods. These methods are not recommended as a primary analysis, but they have been applied in many clinical trials. Group sequential design with interim analyses was one of the standard designs, and novel design, such as adaptive dose selection and sample size re-estimation, was sometimes employed in NEJM. WHAT IS NEW AND CONCLUSION: Model-based approaches for handling missing data should replace single imputation methods for primary analysis in the light of the information found in some publications. Use of adaptive design with interim analyses is increasing after the presentation of the FDA guidance for adaptive design.

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  • In RCTs, many statistical analyses are based on logistic and Cox regression models, which use the multiplicative scale.

    “In RCTs, many statistical analyses are based on logistic and Cox regression models (ie binary outcomes are often analysed) which utilize the multiplicative scale.11”

    From Understanding of interaction (subgroup) analysis in clinical trials (2019) · cites this paper as [11]

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Authors
Gosho, M., Sato, Y., Nagashima, K., & Takahashi, S.
Affiliations
  • University of Tsukuba (JP)
  • Chiba University (JP)
  • Chiba University Hospital (JP)
Corresponding author
Gosho, M.
ORCID
Venue
Journal of Clinical Pharmacy and Therapeutics
Publisher
Wiley
Published
2017-07-27
Volume
43
Issue
1
Pages
36-44
ISSN
0269-4727 (ISSN-L)
DOI
10.1111/jcpt.12605
OpenAlex
W2742162420
Cited by
26
References
28
Citations by year
2025: 3 · 2023: 1 · 2022: 2 · 2021: 1 · 2020: 13 · 2019: 3 · 2018: 2 · 2017: 1
FWCI
3.61
Type
journal article
Language
en
Open access
closed
Licence
Locations
  • Journal of Clinical Pharmacy and Therapeutics (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Keywords
statistical methods in clinical trials, New England Journal of Medicine, CONSORT, sample size justification, competing risks, missing data handling, model-based approach, single imputation, group sequential designs, interim analysis, sample size re-estimation, adaptive trial design, Kaplan-Meier estimator, Cox proportional hazards model
MeSH terms
Data Interpretation, Statistical, Humans, Publications, Research Design, Models, Statistical, Evidence-Based Medicine, Biomedical Research

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