Evidence map›Paper›PMID 39687883›Full record

ArticleFrontiers in oncology2024

Prognostic importance of an indicator related to systemic inflammation and insulin resistance in patients with gastrointestinal cancer: a prospective study.

Guo-Tian Ruan, Jin-Yu Shi, Hai-Lun Xie, He-Yang Zhang, Hong Zhao, Xiao-Yue Liu, Yi-Zhong Ge, Xiao-Wei Zhang, Ming Yang, Li-Chen Zhu and 1 more

Abstract read
In one paragraph

Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed, 1 synthesis or guideline 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

11 authors.

Guo-Tian RuanDepartment of Gastrointestinal Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Jin-Yu ShiDepartment of Gastrointestinal Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Hai-Lun XieDepartment of Gastrointestinal Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
He-Yang ZhangDepartment of Gastrointestinal Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Hong ZhaoDepartment of Gastrointestinal Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Xiao-Yue LiuDepartment of Gastrointestinal Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Yi-Zhong GeDepartment of Gastrointestinal Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Xiao-Wei ZhangDepartment of Gastrointestinal Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Ming YangDepartment of Gastrointestinal Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Li-Chen ZhuDepartment of Gastrointestinal Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Han-Ping ShiDepartment of Gastrointestinal Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Systemic inflammation (SI) and insulin resistance (IR) are correlated to the progression of gastrointestinal (GI) cancer. Therefore, this study aimed to analyze the potential clinical value of the C-reactive protein-triglyceride-glucose index (CTI) in relation to SI and IR in patients with GI cancer. Methods: This prospective cohort study included patients with GI cancer. Patient data were collected from Fujian Cancer Hospital as an external validation cohort. Prognostic AUC, time-dependent ROC curve, C-index, and calibration curve analyses were used to predict the efficacy and accuracy of CTI survival prediction. Multivariate survival analysis was performed to evaluate the potential prognostic value of the CTI. Multiple logistic regression was performed to evaluate the relationship between the CTI and 90-day and 180-day mortalities. Results: We divided 1520 patients with GI cancer (mean age, 60.39 ± 11.3 years; male sex, 67%) into a training cohort and internal validation cohort; the external validation cohort included 476 patients. Prognostic AUC, time-dependent ROC curve, C-index, and calibration curve analyses of all cohorts indicated that the CTI could reliably and accurately predict the short- and long-term survival outcomes of patients with GI cancer. Multivariate survival analysis showed that for each standard deviation increase in the CTI, the risk of death increased by 32%, 21%, and 40% in the training, internal validation, and external validation cohorts, respectively. A high CTI was correlated to worse survival in patients with GI cancer (training cohort, hazard ratio [HR]=1.67, 95% confidence interval [CI]=1.35-2.08; internal validation cohort, HR=1.51, 95% CI=1.07-2.14, and external validation cohort, HR=1.59, 95% CI=1.18-2.13). In different tumor subgroups, a high CTI predicted worse survival outcomes for upper GI cancer (HR=1.54, 95% CI=1.18-2.01) and lower GI cancer (HR=1.98, 95% CI=1.36-2.86). Multivariate logistic regression analysis showed that a high CTI was positively correlated with 90-day (odds ratio [OR]=3.25, 95% CI=1.75-6.23) and 180-day mortalities (OR=2.66, 95% CI=1.72-4.15). Conclusions: The CTI is related to SI and IR and can predict the short- and long-term prognosis of patients with GI cancer. Evaluation of the CTI could provide clinicians with an effective tool for predicting the prognosis of patients with GI cancer. Clinical trial registration: https://www.chictr.org.cn/showproj.html?proj=31813, identifier ChiCTR1800020329.

Indexed as

CTIgastrointestinal cancerinsulin resistanceoverall survivalsystemic inflammation

Identifiers

PMID39687883
PMCPMC11646804

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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.