Evidence map›Paper›PMID 26909861›Full record

ArticleOncotarget2016

Prospective evaluation of 64 serum autoantibodies as biomarkers for early detection of colorectal cancer in a true screening setting.

Hongda Chen, Simone Werner, Julia Butt, Inka Zörnig, Phillip Knebel, Angelika Michel, Stefan B Eichmüller, Dirk Jäger, Tim Waterboer, Michael Pawlita and 1 more

Abstract read
In one paragraph

Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 3 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

18 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Trial
  6. Article
  7. Article
  8. Review
  9. Auto-antibodies to p53 and the Subsequent Development of Colorectal Cancer in a U.S. Prospective Cohort Consortium.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020
    Article
  10. Article
  11. Article
  12. Multi-panel assay of serum autoantibodies in colorectal cancer.International journal of clinical oncology · 2018
    Article
  13. Article
  14. Epigenetic Biomarkers in Colorectal Cancer.Molecular diagnosis & therapy · 2017
    Review
  15. Article
  16. Article
  17. Article
  18. Review
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

11 authors.

Hongda ChenDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Simone WernerDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Julia ButtDivision of Molecular Diagnostics of Oncogenic Infections, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Inka ZörnigDepartment of Medical Oncology, National Center for Tumor Diseases (NCT), Internal Medicine VI, University of Heidelberg, Heidelberg, Germany.
Phillip KnebelDepartment of General, Visceral and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany.
Angelika MichelDivision of Molecular Diagnostics of Oncogenic Infections, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Stefan B EichmüllerGMP & T cell Therapy Unit, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Dirk JägerDepartment of Medical Oncology, National Center for Tumor Diseases (NCT), Internal Medicine VI, University of Heidelberg, Heidelberg, Germany.
Tim WaterboerDivision of Molecular Diagnostics of Oncogenic Infections, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Michael PawlitaDivision of Molecular Diagnostics of Oncogenic Infections, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Hermann BrennerDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Novel blood-based screening tests are strongly desirable for early detection of colorectal cancer (CRC). We aimed to identify and evaluate autoantibodies against tumor-associated antigens as biomarkers for early detection of CRC. 380 clinically identified CRC patients and samples of participants with selected findings from a cohort of screening colonoscopy participants in 2005-2013 (N=6826) were included in this analysis. Sixty-four serum autoantibody markers were measured by multiplex bead-based serological assays. A two-step approach with selection of biomarkers in a training set, and validation of findings in a validation set, the latter exclusively including participants from the screening setting, was applied. Anti-MAGEA4 exhibited the highest sensitivity for detecting early stage CRC and advanced adenoma. Multi-marker combinations substantially increased sensitivity at the price of a moderate loss of specificity. Anti-TP53, anti-IMPDH2, anti-MDM2 and anti-MAGEA4 were consistently included in the best-performing 4-, 5-, and 6-marker combinations. This four-marker panel yielded a sensitivity of 26% (95% CI, 13-45%) for early stage CRC at a specificity of 90% (95% CI, 83-94%) in the validation set. Notably, it also detected 20% (95% CI, 13-29%) of advanced adenomas. Taken together, the identified biomarkers could contribute to the development of a useful multi-marker blood-based test for CRC early detection.

Indexed as

AdenomaAgedAntigens, NeoplasmAutoantibodiesBiomarkers, TumorColorectal NeoplasmsEarly Detection of CancerFemaleHumansMaleMass ScreeningMiddle AgedNeoplasm ProteinsProspective StudiesReproducibility of ResultsSensitivity and SpecificityAntigens, NeoplasmAutoantibodiesBiomarkers, TumorMAGEA4 protein, humanNeoplasm Proteinsautoantibodycolorectal cancerdiagnosisscreening settingtumor-associated antigens

Identifiers

PMID26909861
PMCPMC4941325

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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.