Evidence map›Paper›PMID 35277188›Full record

ArticleWorld journal of surgical oncology2022

A novel inflammation-related prognostic biomarker for predicting the disease-free survival of patients with colorectal cancer.

Xiaoling Cai, Fa Chen, Lisheng Liang, Weizhong Jiang, Xing Liu, Dong Wang, Yunli Wu, Jinyan Chen, Guoxian Guan, Xian-E Peng

Abstract read
In one paragraph

Article in World journal of surgical oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Safety and efficacy of encorafenib-cetuximab combination inESMO real world data and digital oncology · 2024
    Article
  6. Article
  7. Article
  8. Article
  9. 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

10 authors.

Xiaoling Cai *Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, The School of Public Health, Fujian Medical University, Fuzhou, China.
Fa Chen *Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, The School of Public Health, Fujian Medical University, Fuzhou, China.
Lisheng Liang *Department of Nursing, Fujian Medical University Union Hospital, Fuzhou, China.
Weizhong JiangDepartment of Colorectal Surgery, Fujian Medical University Union Hospital, Fuzhou, China.
Xing LiuDepartment of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Dong WangDepartment of General Surgery, Fujian Medical University Union Hospital, Fuzhou, China.
Yunli WuKey Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China.
Jinyan ChenInstitute for Immunology, Fujian Academy of Medical Sciences, Fuzhou, Fujian, China.
Guoxian GuanDepartment of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China. gxguan1108@163.com.
Xian-E PengDepartment of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, The School of Public Health, Fujian Medical University, Fuzhou, China. peng123456@fjmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo develop and evaluate the prognostic value of a comprehensive inflammatory biomarker for postoperative colorectal cancer (CRC) patients.

methodsA total of 646 CRC patients were recruited between August 2017 and December 2019 from Fujian Medical University Union Hospital, with follow-up data up to 2021. The least absolute shrinkage and selection operator method (LASSO) was used to select inflammation indicators in order to construct a comprehensive biomarker (named NSAP). The Cox regression model was utilized to analyze the association between the NSAP and the disease-free survival (DFS) of CRC. Predictive performance and clinical utility of prognostic models were evaluated by area under the curve (AUC) and decision curve analyses (DCAs).

resultsDuring a median follow-up of 23 months, 95 clinical outcomes were observed, with a 1-year survival rate is 89.47%. A comprehensive inflammatory biomarker (NSAP) was established based on four blood indicators (including neutrophil-to-lymphocyte ratio (NLR), neutrophil×monocyte-to-lymphocyte ratio (SIRI), albumin-to-globulin ratio (AGR), and platelet-to-lymphocytes ratio (PLR)). Patients with a lower NSAP had significantly associated with better DFS of CRC (HR=0.53, 95%CI 0.32-0.89). Moreover, compared to a previously established model, the traditional TNM staging system or/and tumor markers, the nomogram based on NSAP displayed more excellent predictive ability (0.752 vs 0.597, 0.711 and 0.735, P < 0.05). DCAs also demonstrated that the established nomogram had better utility for decision making.

conclusionsOur study suggests that NSAP may be a useful comprehensive prognostic biomarker for predicting the DFS of CRC patients. The nomogram based on NSAP can be considered a valuable tool to estimate the prognosis of patients with CRC.

Indexed as

Colorectal NeoplasmsBiomarkers, TumorDisease-Free SurvivalHumansInflammationPlatelet CountPrognosisBiomarkers, TumorColorectal cancerDecision curve analysisDisease-free survivalInflammatory biomarkersPrognosis

Identifiers

PMID35277188
PMCPMC8917685

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.