Evidence map›Paper›PMID 35079223›Full record

ArticleJournal of inflammation research2022

A Novel Inflammatory-Nutritional Prognostic Scoring System for Patients with Early-Stage Breast Cancer.

Xin Hua, Fangfang Duan, Wenyu Zhai, Chenge Song, Chang Jiang, Li Wang, Jiajia Huang, Huanxin Lin, Zhongyu Yuan

Abstract read
In one paragraph

Article in Journal of inflammation research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

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3 · Its place in the literature

Who cites it

24 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

9 authors.

Xin Hua *Department of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People's Republic of China.ORCID 0000-0002-2045-1293
Fangfang Duan *Department of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People's Republic of China.ORCID 0000-0002-7887-5232
Wenyu Zhai *Department of Thoracic Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People's Republic of China.
Chenge SongDepartment of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People's Republic of China.
Chang JiangDepartment of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People's Republic of China.
Li WangDepartment of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People's Republic of China.
Jiajia HuangDepartment of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People's Republic of China.
Huanxin LinDepartment of Radiotherapy, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People's Republic of China.
Zhongyu YuanDepartment of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeWe attempted to explore the prognostic value of baseline inflammatory and nutritional biomarkers at diagnosis in patients with early-stage breast cancer and develop a novel scoring system, the inflammatory-nutritional prognostic score (INPS). PATIENTS AND

methodsWe collected clinicopathological and baseline laboratory data of 1259 patients with early-stage breast cancer between December 2010 and November 2012 from Sun Yat-sen University Cancer Center. Eligible patients were randomly divided into training and validation cohorts (n = 883 and 376, respectively) in a 7:3 ratio. We selected the most valuable biomarkers to develop INPS by the least absolute shrinkage and selection operator (LASSO) Cox regression model. A prognostic nomogram incorporating INPS and other independent clinicopathological factors was developed based on the stepwise multivariate Cox regression method. Then, we used the concordance index (C-index), calibration plot, and time-dependent receiver operating characteristic (ROC) analysis to evaluate the prognostic performance and predictive accuracy of the predictive nomogram.

resultsFour inflammatory-nutritional biomarkers, including neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), prognostic nutritional index (PNI), and albumin-alkaline phosphatase ratio (AAPR), were selected using the LASSO Cox analysis to construct INPS, which remained an independent prognostic indicator per the multivariate Cox regression analysis. Patients were stratified into low- and high-INPS groups based on the cutoff INPS determined by the maximally selected rank statistics. The prognostic model for overall survival consisting of INPS and other independent clinicopathological indicators showed excellent discrimination with C-indexes of 0.825 (95% confidence interval [CI]: 0.786-0.864) and 0.740 (95% CI: 0.657-0.822) in the training and validation cohorts, respectively. The time-dependent ROC curves showed a higher predictive accuracy of our prognostic nomogram than that of traditional tumor-node-metastasis staging.

conclusionBaseline INPS is an independent indicator of OS in patients with early-stage breast cancer. The INPS-based prognostic nomogram could be used as a practical tool for individualized prognostic predictions.

Indexed as

early-stage breast cancerinflammatory-nutritional biomarkerLASSO Cox analysisoverall survivalprognostic nomograms

Identifiers

PMID35079223
PMCPMC8776566

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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.