Evidence map›Paper›PMID 23496812›Full record

ArticleBMC cancer2013

Is the prediction of prognosis not improved by the seventh edition of the TNM classification for colorectal cancer? Analysis of the surveillance, epidemiology, and end results (SEER) database.

Peng Gao, Yong-xi Song, Zhen-ning Wang, Ying-ying Xu, Lin-lin Tong, Jing-xu Sun, Miao Yu, Hui-mian Xu

Abstract readComparative Study
In one paragraph

Article in BMC cancer, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing 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

36 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Observational
  8. The utility of surveillance CT scans in a cohort of survivors of colorectal cancer.Journal of cancer survivorship : research and practice · 2023
    Article
  9. Review
  10. Article
  11. Review
  12. Review
  13. Article
  14. Oncology research · 2021
    Article
  15. Article
  16. Article
  17. Review
  18. An Immunoscore System Based On CD3OncoTargets and therapy · 2019
    Article
  19. Article
  20. 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

8 authors.

Peng GaoDepartment of Surgical Oncology and General Surgery, the First Hospital of China Medical University, Shenyang City, PR China.
Yong-xi Song
Zhen-ning Wang
Ying-ying Xu
Lin-lin Tong
Jing-xu Sun
Miao Yu
Hui-mian Xu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWhether the 7th edition of American Joint Committee on Cancer (AJCC) TNM staging system (AJCC-7) is a successful revision remains debatable. We aimed to compare the predictive capacity of the AJCC-7 for colorectal cancer with the 6th edition of the AJCC TNM staging system (AJCC-6).

methodsThe National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) dataset consisting of 158,483 records was used in this study. We evaluated the predictive capacity of the two editions of the staging system using Harrell's C index and Bayesian Information Criterion (BIC).

resultsThere was a significant prognostic difference between patients at stage IIB and IIC (P < 0.001). Stage III patients with similar prognoses were adequately sub-grouped in the same stage according to AJCC-7. The Harrell's C index revealed a value of 0.7692 for AJCC-7, which was significantly better than 0.7663 for AJCC-6 (P < 0.001). BIC analysis provided consistent results (P < 0.001).

conclusionsThis study demonstrates that AJCC-7 is superior to the AJCC-6 staging system in predictive capacity.

Indexed as

AgedAged, 80 and overColorectal NeoplasmsFemaleHumansKaplan-Meier EstimateLymphatic MetastasisMaleMiddle AgedNeoplasm StagingPredictive Value of TestsPrognosisSEER Program

Identifiers

PMID23496812
PMCPMC3651725

What OpenQuestion holds

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Registered trials

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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.