Evidence map›Paper›PMID 32226510›Full record

ReviewJournal of Cancer2020

Statistics and pitfalls of trend analysis in cancer research: a review focused on statistical packages.

Jie Xu, Yong Lin, Mu Yang, Lanjing Zhang

Open access · goldAbstract readReview
In one paragraph

Review in Journal of Cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
2.3field-weighted citation impact, top 10% of its field
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

22 citing papers in PubMed, 38 citations in OpenAlex.

  1. Article
  2. Article
  3. Trends and spatial distribution of pediatric second-dose COVID-19 vaccination coverage: a temporal analysis, Brazil, 2022-2023.Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil · 2026
    Article
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  12. High-throughput proteomics: a methodological mini-review.Laboratory investigation; a journal of technical methods and pathology · 2022
    Review
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  14. 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

4 authors at 3 institutions in 2 countries.

Jie XuDepartment of Infectious Disease, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yong LinRutgers Cancer Institute of New Jersey, New Brunswick, New Jersey.
Mu YangDepartment of Pathology, Shanghai First Hospital, Shangai Jiao Tong University, Shanghai, China.
Lanjing ZhangRutgers Cancer Institute of New Jersey, New Brunswick, New Jersey.
University Medical Center of Princeton · USRutgers Cancer Institute of New JerseyShanghai Jiao Tong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Trend analysis is the analysis using statistical models to estimate and predict potential trends over time, space or any independent continuous-variable. It has been widely used in epidemiology and public health, but much less so in clinical oncology and basic cancer research. Methodological imitations of the chosen statistical package also appear to result in biased or less rigorous interrogation of cancer-related data. We thus review the basic statistics of trend analysis, commonly used commands of statistical packages and the common pitfalls of conducting trend analysis. Four free and 3 commercial statistical-packages were discussed in depth, including Joinpoint, Epi info, R package, Python, SAS, Stata and SPSS. We hope that this review could serve as a practical yet concise guide for using statistical packages for trend analysis in translational and clinical oncology, and help improve the scientific rigor of trend analyses in these fields. The guide, however, may also be applied to other research fields.

Indexed as

cancerjoinpoint regressionlinear spline regression.nonlinear trendsoftwarestatistical analysis

Identifiers

PMID32226510
PMCPMC7086268
OpenAlexW3012631907

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.