Evidence map›Paper›PMID 39706537›Full record

ArticleJournal of clinical epidemiology2025

Trial sequential analysis involving same-year studies requires careful temporal ordering.

Xing Xing, Yipeng Wang, Lifeng Lin

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of clinical epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Xing XingDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Yipeng WangDepartment of Biostatistics, University of Florida, Gainesville, FL, USA.
Lifeng LinDepartment of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ, USA. Electronic address: lifenglin@arizona.edu.

Funding

Statistical Methods and Software for Multivariate Meta-analysisR01LM012982 · NLM · UNIVERSITY OF MINNESOTA · PI LIN, LIFENG, SIEGEL, LIANNE · 2019 to 2022
$1.3M
Advanced Methods and Software for Trial Sequential Analysis in Living Systematic ReviewsR21LM014533 · NLM · UNIVERSITY OF ARIZONA · PI LIN, LIFENG · 2024 to 2025
$364k
Joint modeling of continuous and binary data in meta-analysisR03MH128727 · NIMH · UNIVERSITY OF ARIZONA · PI LIN, LIFENG · 2022 to 2023
$146k
NIMH NIH HHS R03 MH128727NLM NIH HHS R01 LM012982NLM NIH HHS R21 LM014533
6 · The paper itself

Abstract

Trial sequential analysis (TSA) is an increasingly used tool in systematic reviews to monitor synthesized evidence. However, the current practice of TSAs often overlooks the order of same-year studies, which are typically ordered alphabetically based on the last names of the studies' authors by default in the widely used TSA software application. This practice is inappropriate and contrary to the TSA's definition. This issue is particularly concerning in systematic reviews on time-sensitive topics, such as COVID-19, where reviews include many studies within a short period. In this article, we use a case study to illustrate the impact of the order of same-year studies on TSA conclusions. It shows dramatically different patterns of evidence accumulation when same-year studies are ordered alphabetically vs in their actual temporal order. This article offers suggestions for authors to pay attention to study ordering in future TSAs.

Indexed as

Research DesignSystematic Reviews as TopicCOVID-19Data Interpretation, StatisticalHumansSARS-CoV-2Time FactorsCOVID-19Cumulative meta-analysisEvidence-based medicineMeta-analysisSystematic reviewTrial sequential analysis

Identifiers

PMID39706537
PMCPMC11928275

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.