Evidence map›Paper›PMID 29204700›Full record

ArticleCancer immunology, immunotherapy : CII2018

The Immunoscore system predicts prognosis after liver metastasectomy in colorectal cancer liver metastases.

Yun Wang, Hao-Cheng Lin, Ma-Yan Huang, Qiong Shao, Zhi-Qiang Wang, Feng-Hua Wang, Yun-Fei Yuan, Bin-Kui Li, De-Shen Wang, Pei-Rong Ding and 10 more

Abstract read
In one paragraph

Article in Cancer immunology, immunotherapy : CII, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 2 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

51 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

20 authors.

Yun WangState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China.
Hao-Cheng LinState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China.
Ma-Yan HuangState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China.
Qiong ShaoState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China.
Zhi-Qiang WangState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China.
Feng-Hua WangState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China.
Yun-Fei YuanState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China.
Bin-Kui LiState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China.
De-Shen WangState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China.
Pei-Rong DingState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China.
Gong ChenState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China.
Xiao-Jun WuState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China.
Zhen-Hai LuState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China.
Li-Ren LiState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China.
Zhi-Zhong PanState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China.
Peng SunState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China.
Shu-Mei YanState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China.
De-Sen WanState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China.
Rui-Hua XuState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China. xurh@sysucc.org.cn.
Yu-Hong LiState Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, 651# Dongfeng Road East, Guangzhou, 510060, People's Republic of China. liyh@sysucc.org.cn.ORCID 0000-0002-5710-9096

Funding

Science and Technology Planning Project of Guangdong Province, China 201508020247
6 · The paper itself

Abstract

backgroundThe Immunoscore was initially established to evaluate the prognosis of stage I/II/III colorectal cancer patients. However, the feasibility of the Immunoscore for the prognosis of colorectal cancer liver metastases (CRCLM) has not been reported.

methodsLiver metastases in 249 CRCLM patients were retrospectively analyzed. The Immunoscore was assessed according to the counts and densities of CD3+ and CD8+ T cells in the central- and peritumoral areas by immunohistochemistry. The prognostic role of the Immunoscore for relapse-free survival (RFS) and overall survival (OS) was analyzed with Kaplan-Meier curves and Cox multivariate models, and confirmed via an internal validation. Receiver operating characteristic (ROC) curves were plotted to compare the prognostic values of the Immunoscore and the clinical risk score (CRS) system.

resultsCRCLM patients with high Immunoscores (> 2) had significantly longer RFS [median RFS (95% confidence interval; 95% CI) 21.4 (7.8-35.1) vs. 8.7 (6.8-10.5) months, P < 0.001] and OS [median OS (95% CI): not reached vs. 28.7 (23.2-34.2) months, P < 0.001] than those with low Immunoscores (≤ 2). After stratification by CRS, the Immunoscore retained a statistically significant prognostic value for OS. The areas under the ROC curves (AUROCs) of the Immunoscore and the CRS system for RFS were 0.711 [95% CI 0.642-0.781] and 0.675[95% CI 0.601-0.749] (P = 0.492), whereas the AUROC of the Immunoscore system for OS was larger than that of the CRS system [0.759 (95% CI 0.699-0.818) vs. 0.660 (95% CI 0.592-0.727); P = 0.029].

conclusionsThe Immunoscore of liver metastases can be applied to predict the prognosis of CRCLM patients following liver resection.

Indexed as

AgedCD3 ComplexCD8-Positive T-LymphocytesColorectal NeoplasmsDisease-Free SurvivalFemaleHepatectomyHumansLiverLiver NeoplasmsLymphocytes, Tumor-InfiltratingMaleMetastasectomyNeoplasm Recurrence, LocalPrognosisProportional Hazards ModelsCD3 ComplexColorectal cancer liver metastasesImmunoscorePrognosisTumor-infiltrating lymphocyte

Identifiers

PMID29204700
PMCPMC11028131

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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.