Evidence map›Paper›PMID 36428688›Full record

ArticleCancers2022

EMT-Related Genes Have No Prognostic Relevance in Metastatic Colorectal Cancer as Opposed to Stage II/III: Analysis of the Randomised, Phase III Trial FIRE-3 (AIO KRK 0306; FIRE-3).

Elise Pretzsch, Volker Heinemann, Sebastian Stintzing, Andreas Bender, Shuo Chen, Julian Walter Holch, Felix Oliver Hofmann, Haoyu Ren, Florian Bösch, Helmut Küchenhoff and 2 more

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact, top 78% 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it, 0 citations in OpenAlex.

  1. Pooled it
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

12 authors at 6 institutions in 1 country.

Elise PretzschDepartment of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, 80539 Munich, Germany.
Volker HeinemannGerman Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), 69120 Heidelberg, partner site 80336 Munich, Germany.
Sebastian StintzingDepartment of Hematology, Oncology, and Cancer Immunology (CCM), Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, 10117 Berlin, Germany.ORCID 0000-0002-3297-5801
Andreas BenderStatistical Consulting Unit, StaBLab, Department of Statistics, LMU Munich, 80539 Munich, Germany.ORCID 0000-0001-5628-8611
Shuo ChenMunich Center for Machine Learning, LMU Munich, 81377 Munich, Germany.
Julian Walter HolchDepartment of Hematology/Oncology and Comprehensive Cancer Center Munich, LMU University Hospital Munich, Ludwig-Maximilians-University Munich, 81377 Munich, Germany.
Felix Oliver HofmannDepartment of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, 80539 Munich, Germany.ORCID 0000-0002-6913-2429
Haoyu RenDepartment of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, 80539 Munich, Germany.
Florian BöschDepartment of General, Visceral, and Pediatric Surgery, University Medical Center Goettingen, 37075 Göttingen, Germany.
Helmut KüchenhoffStatistical Consulting Unit, StaBLab, Department of Statistics, LMU Munich, 80539 Munich, Germany.
Jens WernerDepartment of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, 80539 Munich, Germany.
Martin Konrad AngeleDepartment of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, 80539 Munich, Germany.
Ludwig-Maximilians-Universität München · DEGerman Cancer Research Center · DEStatistisches Bundesamt · DEHumboldt-Universität zu Berlin · DEMunich Center for Machine LearningUniversity of Göttingen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThere is no standard treatment after resection of colorectal liver metastases and the role of systemic therapy remains controversial. To avoid over- or undertreatment, proper risk stratification with regard to postoperative treatment strategy is highly needed. We recently demonstrated the prognostic relevance of EMT-related (epithelial-mesenchymal transition) genes in stage II/III CRC. As EMT is a major step in CRC progression, we now aimed to analyse the prognostic relevance of EMT-related genes in stage IV CRC using the study cohort of the FIRE-3 trial, an open-label multi-centre randomised controlled phase III trial of patients with metastatic CRC.

methodsOverall and progression free survival were considered as endpoints (

resultsThe baseline KM model showed the best performance (OS: 0.250, PFS: 0.251). None of the other models were able to outperform the KM when using clinical data only according to the IBS scores (OS: 0.253 (Cox), 0.256 (RSF), 0.284 (GBT); PFS: 0.254 (Cox), 0.256 (RSF), 0.276 (GBT)). When adding gene data, performance of GBT improved slightly (OS: 0.262 vs. 0.284; PFS: 0.268 vs. 0.276), however, none of the models performed better than the KM baseline.

conclusionOverall, the results suggest that the prognostic relevance of EMT-related genes may be stage-dependent and that EMT-related genes have no prognostic relevance in stage IV CRC.

Indexed as

colorectal cancerEMTEMT-related genesmetastasis

Identifiers

PMID36428688
PMCPMC9688410
OpenAlexW4309455543

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.