Evidence map›Paper›PMID 35530285›Full record

ArticleAmerican journal of cancer research2022

A novel score system for predicting conversion to no evidence of Disease (C-NED) in initially unresectable colorectal cancer liver metastases.

Weihao Li, Jian Zhou, Tianqi Zhang, Yi Tai, Yanbo Xu, Yanfang Bai, Yu Jiang, Zhenhai Lu, Liren Li, Jinhua Huang and 4 more

Open access · greenAbstract read
In one paragraph

Article in American journal of cancer research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 53% 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 citations in OpenAlex.

  1. 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

14 authors at 1 institution in 1 country.

Weihao LiDepartment of Colorectal Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou 510060, Guangdong, P. R. China.
Jian ZhouDepartment of Radiology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou 510060, Guangdong, P. R. China.
Tianqi ZhangDepartment of Minimally Invasive Interventional Radiology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou 510060, Guangdong, P. R. China.
Yi TaiDepartment of Colorectal Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou 510060, Guangdong, P. R. China.
Yanbo XuDepartment of Colorectal Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou 510060, Guangdong, P. R. China.
Yanfang BaiDepartment of Anesthesiology & Operating Theatre, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou 510060, Guangdong, P. R. China.
Yu JiangDepartment of Radiology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou 510060, Guangdong, P. R. China.
Zhenhai LuDepartment of Colorectal Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou 510060, Guangdong, P. R. China.
Liren LiDepartment of Colorectal Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou 510060, Guangdong, P. R. China.
Jinhua HuangDepartment of Minimally Invasive Interventional Radiology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou 510060, Guangdong, P. R. China.
Zhizhong PanDepartment of Colorectal Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou 510060, Guangdong, P. R. China.
Xiaojun WuDepartment of Colorectal Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou 510060, Guangdong, P. R. China.
Jianhong PengDepartment of Colorectal Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou 510060, Guangdong, P. R. China.
Junzhong LinDepartment of Colorectal Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou 510060, Guangdong, P. R. China.
Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An estimated 70-80% of cases of colorectal cancer liver metastasis (CRLM) are defined as initially unresectable. "Converting" to no evidence of disease (NED) status may prolong survival. The current study aimed to develop a novel scoring system that predicts the conversion outcome for initially unresectable CRLM. A total of 215 consecutive CRLM patients who received first-line systemic therapy from December 2012 to January 2020 at Sun Yat-sen University Cancer Center were enrolled in the internal cohort. Forty CRLM patients from the database of the Chinese Colorectal Cancer Multidisciplinary Team Alliance were enrolled in the external cohort. A logistic regression model was applied to identify risk factors associated with the conversion outcome. The tumor-to-liver volume ratio (TLVR) was calculated as the total tumor volume divided by the total liver volume, and its cutoff value was 0.23. Three predictors of conversion failure were identified in the internal cohort and incorporated into the C-NED score: poor tumor differentiation (1 point), number of liver metastases > 8 (1 point) and TLVR ≥ 0.23 (1 point). The conversion rate was significantly negatively associated with the C-NED score (

Indexed as

Colorectal cancerconversion outcome predictionliver metastasesprognosisthree-dimensional reconstruction

Identifiers

PMID35530285
PMCPMC9077072
OpenAlexW4286829621

What OpenQuestion holds

Textmetadata
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.