Evidence map›Paper›PMID 39905567›Full record

ArticleEuropean journal of medical research2025

The value of inflammation-related indicators in chemotherapy efficacy and disease-free survival of triple-negative breast cancer.

Jie Zhu, Jiale Cheng, Yuyuan Ma, Ying Wang, Zhonghua Zou, Wenjie Wang, Haihua Shi, You Meng

Abstract read
In one paragraph

Article in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 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

8 authors.

Jie Zhu *Department of Oncology, Changzhou Traditional Chinese Medicine Hospital, Changzhou, 213004, China.
Jiale Cheng *Department of Thyroid and Breast Surgery, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, 215001, China.
Yuyuan Ma *Department of Thyroid and Breast Surgery, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, 215001, China.
Ying WangDepartment of Oncology, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, 215001, China.
Zhonghua ZouDepartment of Radio-Oncology, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, 215001, China.
Wenjie WangDepartment of General Surgery, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, 215001, China. suda_wangwenjie@163.com.
Haihua ShiDepartment of Thyroid and Breast Surgery, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, 215001, China. doctorhaihua0309@163.com.
You MengDepartment of Radio-Oncology, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, 215001, China. ymeng2025@njmu.edu.cn.

Funding

Clinical Oncology Research Foundation of Beijing CSCO Y-Young2021-0087the Science and Technology Project Foundation of Suzhou SKJY2021126
6 · The paper itself

Abstract

backgroundSystemic inflammation is closely correlated with the progression of cancer. Inflammation-related indicators has been recognized as outcome predictors in triple-negative breast cancer (TNBC). Our study aimed to investigate the predictive value of several inflammation-related indicators in TNBC patients underwent chemotherapy (NAC).

methods100 TNBC patients were enrolled in the study. Levels of interleukin-6 (IL-6) were detected by enzyme-linked immunosorbent assays (ELISAs). Platelet-to-lymphocyte ratio (PLR) and immune inflammatory index (SII) were obtained from blood routine. Levels of Ki-67 expression were detected by immunohistochemistry (IHC). Mentioned indicators were divided into two groups based on their median values. The correlation between these indicators and NAC efficacy was analyzed using t tests. Prognostic risk scores were calculated by univariate Cox regression analysis and Lasso-penalized Cox regression. The patients were divided into low- and high-risk groups based on the median risk score. Survival curves were obtained by Kaplan-Meier method. Models for univariate and multivariate Cox regression analyses were performed to determine the independent risk factors. A nomogram was used for the prediction of 1-, 2-, and 3-year disease-free survival (DFS). Accuracy of the prognostic model was validated by receiver operating characteristic curve (ROC).

resultsIL-6, PLR, SII, and Ki-67 levels were associated with neoadjuvant efficacy. IL-6, PLR, SII, Ki-67, and lymphocyte count were associated with DFS. The risk score for each TNBC patient was obtained using LASSO regression analysis to construct a prognostic model. In the prognostic model, patients in the high-risk score group showed worse DFS than those in the low-risk group. Risk score and tumor size were independently correlated with outcomes in multivariate Cox regression analysis. A nomogram was constructed using IL-6, PLR, SII, Ki-67, and Miller-Payne (MP) scores. Calibration curves demonstrated good consistency between the actual and predictive values of the nomogram.

conclusionA prognostic model was established by combining four prognosis-related indicators in TNBC patients who underwent NAC.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsInflammationTriple Negative Breast NeoplasmsAdultAgedBiomarkers, TumorDisease-Free SurvivalFemaleHumansInterleukin-6Ki-67 AntigenMiddle AgedNomogramsPrognosisROC CurveBiomarkers, TumorIL6 protein, humanInterleukin-6Ki-67 AntigenInflammation-related indicatorsNomogramPrognostic modelTriple-negative breast cancer

Identifiers

PMID39905567
PMCPMC11792380

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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.