Evidence map›Paper›PMID 29881307›Full record

ArticleCancer management and research2018

Tumor-infiltrating lymphocyte as a prognostic biomarker in stage IV colorectal cancer should take into account the metastatic status and operation modality.

Qian-Kun Xie, Wen-Zhuo He, Wan-Ming Hu, Lin Yang, Chang Jiang, Peng-Fei Kong, Yuan-Zhong Yang, Qiong Yang, Hui-Zhong Zhang, Bei Zhang and 1 more

Abstract read
In one paragraph

Article in Cancer management and research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Review
  6. Review
  7. CD8Clinical & translational immunology · 2020
    Article
  8. Article
  9. Current status of immunotherapy in metastatic colorectal cancer.International journal of colorectal disease · 2019
    Review
  10. TFrontiers in oncology · 2019
    Review
  11. 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

11 authors.

Qian-Kun Xie *VIP Region, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Wen-Zhuo He *VIP Region, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Wan-Ming HuDepartment of Pathology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, SunYat-sen University Cancer Center, Guangzhou, China.
Lin YangVIP Region, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Chang JiangVIP Region, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Peng-Fei KongVIP Region, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Yuan-Zhong YangDepartment of Pathology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, SunYat-sen University Cancer Center, Guangzhou, China.
Qiong YangVIP Region, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Hui-Zhong ZhangDepartment of Pathology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, SunYat-sen University Cancer Center, Guangzhou, China.
Bei ZhangVIP Region, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Liang-Ping XiaVIP Region, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough tumor-infiltrating lymphocytes (TILs) have been understood for years as a favorable prognostic factor for colorectal cancers (CRCs) after complete surgical resection, its prognostic role in metastatic CRC (mCRC) remains poorly defined, and it is largely unknown how this prognostic benefit relates to the metastatic status and operation modality. MATERIALS AND

methodsAfter reviewing 2215 consecutive cases of surgically resected CRC, 332 patients newly diagnosed with stage IV CRC and treated at the Sun Yat-Sen University Cancer Center between 2009 and 2014 were included. H&E-stained (HES) slides from surgical specimens were evaluated for the extent of TILs. The primary end point was overall survival (OS). Cox proportional hazards regression was conducted to determine the prognostic significance of TILs. All statistical tests were 2-sided.

resultsHES slides from primary tumor samples were evaluable for 302 of the 332 included cases. Among the 302 patients, 105 patients (34.8%) were classified as high TIL, the remaining 197 (65.2%) were defined as low TIL. In the univariate analysis, TILs were significantly associated with better OS (

conclusionOur findings indicate that the level of TILs can be used to predict the outcome for patients with mCRC; however, the operation modality and the metastatic status of patients should also be taken into account.

Indexed as

colorectal cancermetastatic statusstage IVsurvivaltumor-infiltrating lymphocytes

Identifiers

PMID29881307
PMCPMC5985807

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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.