Evidence map›Paper›PMID 30563540›Full record

ArticleJournal of translational medicine2018

Preoperative systemic immune-inflammation index predicts prognosis of patients with oral squamous cell carcinoma after curative resection.

Pengfei Diao, Yaping Wu, Jin Li, Wei Zhang, Rong Huang, Chen Zhou, Yanling Wang, Jie Cheng

Abstract read
In one paragraph

Article in Journal of translational medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 5 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.

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3 · Its place in the literature

Who cites it

43 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  11. Platelet Lymphocyte Ratio as a Prognosticator in Oral Cancer Patients.Journal of maxillofacial and oral surgery · 2025
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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.

Pengfei DiaoJiangsu Key Laboratory of Oral Disease, Nanjing Medical University, 136 Hanzhong Road, Nanjing, 210029, Jiangsu, China.
Yaping WuJiangsu Key Laboratory of Oral Disease, Nanjing Medical University, 136 Hanzhong Road, Nanjing, 210029, Jiangsu, China.
Jin LiJiangsu Key Laboratory of Oral Disease, Nanjing Medical University, 136 Hanzhong Road, Nanjing, 210029, Jiangsu, China.
Wei ZhangDepartment of Oral and Maxillofacial Surgery, Affiliated Stomatological Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
Rong HuangJiangsu Key Laboratory of Oral Disease, Nanjing Medical University, 136 Hanzhong Road, Nanjing, 210029, Jiangsu, China.
Chen ZhouDepartment of Oral and Maxillofacial Surgery, Affiliated Hospital of Jiangnan University, Wuxi, 214000, Jiangsu, China.
Yanling WangJiangsu Key Laboratory of Oral Disease, Nanjing Medical University, 136 Hanzhong Road, Nanjing, 210029, Jiangsu, China.
Jie ChengJiangsu Key Laboratory of Oral Disease, Nanjing Medical University, 136 Hanzhong Road, Nanjing, 210029, Jiangsu, China. jiecheng_njmu@163.com.ORCID 0000-0001-9068-4271

Funding

A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions 2014-37National Natural Science Foundation of China 81572669National Natural Science Foundation of China 81602378National Natural Science Foundation of China 81602386Natural Science Foundation of Jiangsu Province BK20151561Natural Science Foundation of Jiangsu Province BK20161024Natural Science Foundation of Jiangsu Province BK20161564Natural Scientific Research Project for College in Jiangsu Province 16KJB320002Postgraduate Research & Practice Innovation Program of Jiangsu Province KYCX18_1510Project from Nanjing Municipal Committee of Science and Technology 201803044
6 · The paper itself

Abstract

backgroundDeregulated inflammation and immune deficit both intricately associate with cancer initiation and progression, which have been increasingly exploited as prognostic biomarkers and therapeutic targets. Recently, systemic immune-inflammation index (SII) based on peripheral neutrophil, lymphocyte and platelet counts serves as a novel and powerful cancer biomarker with prognostic significance in multiple types of malignancies. Here, we sought to evaluate the prognostic value of preoperative SII in patients with primary oral squamous cell carcinoma (OSCC) after curative resection.

methodsTwo independent cohorts with a total number of 309 patients with OSCC from two tertiary referral hospitals were included and defined as training (Nanjing, 138) and validation (Wuxi, 171) cohort, respectively. Preoperative SII in both cohorts was calculated and its optimal cutoff value was initially determined by X-tile software in the training cohort and then verified in the validation cohort.

resultsOur data indicated that high SII (≥ 484.5) was significantly associated with larger tumor size (P < 0.05, Chi square test), reduced overall and disease-free survival (Kaplan-Meir, P < 0.05, Log-rank test). Univariate and multivariate analyses further revealed that SII was an independent prognostic predictor for patient survival. Moreover, the area under receiver operating characteristic curve of SII for survival was significantly greater or comparable to other well-established prognostic parameters, indicative of its satisfactory prediction accuracy and specificity.

conclusionsOur findings reveal that high preoperative SII associates with poor outcome and serves as a non-invasive, low-cost and powerful prognostic predictor for patients with OSCC. This inflammation/immune-related biomarker holds translational potentials to supplement currently prognostic regime to better stratification of patients and treatment planning.

Indexed as

Preoperative CareBlood PlateletsCarcinoma, Squamous CellCohort StudiesFemaleHumansInflammationLymphocytesMaleMiddle AgedMouth NeoplasmsMultivariate AnalysisNeutrophilsPrognosisOral squamous cell carcinomaPrognostic biomarkerSystemic immune-inflammation index

Identifiers

PMID30563540
PMCPMC6299596

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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.