Evidence map›Paper›PMID 36969019›Full record

ArticleFrontiers in oncology2023

Prognostic nomograms integrating preoperative serum lipid derivative and systemic inflammatory marker of patients with non-metastatic colorectal cancer undergoing curative resection.

Dimei Huang, Shaochu Zheng, Fang Huang, Jingyu Chen, Yuexiang Zhang, Yusha Chen, Bixun Li

Open access · goldFull text read
In one paragraph

Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 20% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

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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

7 authors at 3 institutions in 1 country.

Dimei HuangDepartment of General Internal Medicine, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, China.
Shaochu ZhengDepartment of Haematology/Oncology and Paediatric Oncology, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, China.
Fang HuangDepartment of General Internal Medicine, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, China.
Jingyu ChenDepartment of General Internal Medicine, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, China.
Yuexiang ZhangDepartment of Oncology, Affiliated Changzhi People's Hospital of Changzhi Medical College, Changzhi, China.
Yusha ChenDepartment of Oncology, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China.
Bixun LiDepartment of General Internal Medicine, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, China.
Tumor Hospital of Guangxi Medical University · CNAffiliated Hospital of Youjiang Medical University for Nationalities · CNChangzhi Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Lipid metabolism and cancer-related inflammation are closely related to the progression and prognosis of colorectal cancer (CRC). Therefore, this study aims to establish novel nomograms based on the combined detection of preoperative blood lipids and systemic inflammatory indicators to predict the overall survival (OS) and cancer-specific survival (CCS) of CRC patients. Methods: A total of 523 patients with stage I-III CRC in our institute were collected from 2014 to 2018. The independent predictors for OS and CCS were determined by forward stepwise Cox regression for the establishment of prognostic models. The superiorities of different models were compared by concordance index (C-index), Akaike information criterion (AIC) and integrated discrimination improvement analysis. The performance of the nomograms based on the optimal models was measured by the plotting time-dependent receiver operating characteristic curves, calibration curves, and decision curves, and compared with the tumor-node-metastasis (TNM) staging system. The cohort was categorized into low-risk, medium-risk and high-risk groups according to the risk points of the nomogram, and analyzed using Kaplan-Meier curves and log-rank test. Results: Preoperative TG/HDL-C ratio (THR) ≥ 1.93 and prognostic nutritional index (PNI) ≥ 42.55 were independently associated with favorable outcomes in CRC patients. Six (pT stage, pN stage, histological subtype, perineural invasion, THR and PNI) and seven (pT stage, pN stage, histological subtype, perineural invasion, gross appearance, THR and PNI) variables were chosen to develop the optimal models and construct nomograms for the prediction of OS and CCS. The models had lower AIC and larger C-indexes than other models lacking either or both of THR and PNI, and improved those integrated discrimination ability significantly. The nomograms showed better discrimination ability, calibration ability and clinical effectiveness than TNM system in predicting OS and CCS, and these results were reproducible in the validation cohort. The three risk stratifications based on the nomograms presented significant discrepancies in prognosis. Conclusion: Preoperative THR and PNI have distinct prognostic value in stage I-III CRC patients. The nomograms incorporated the two indexes provide an intuitive and reliable approach for predicting the prognosis and optimizing individualized therapy of non-metastatic CRC patients, which may be a complement to the TNM staging system.

Indexed as

colorectal cancernomogramprognosisserum lipidsystemic inflammation index

Identifiers

PMID36969019
PMCPMC10034181
OpenAlexW4323667012

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LicenceCC BY
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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.