Evidence map›Paper›PMID 39856710›Full record

ArticleBMC oral health2025

Predictive value of preoperative pan-immune-inflammation value index in the prognosis of oral cancer patients undergoing radical resection.

Weihai Huang, Yulan Lin, Enling Xu, Yanmei Ji, Jing Wang, Fengqiong Liu, Fa Chen, Yu Qiu, Bin Shi, Lisong Lin and 1 more

Abstract read
In one paragraph

Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
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.

Weihai HuangDepartment of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, Fujian, China.
Yulan LinDepartment of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, Fujian, China.
Enling XuDepartment of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, Fujian, China.
Yanmei JiDepartment of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, Fujian, China.
Jing WangLaboratory Center, School of Public Health, The Major Subject of Environment and Health of Fujian Key Universities, Fujian Medical University, Fuzhou, China.
Fengqiong LiuDepartment of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, Fujian, China.
Fa ChenDepartment of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, Fujian, China.
Yu QiuDepartment of Oral and Maxillofacial Surgery, Stomatology Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Bin ShiDepartment of Oral and Maxillofacial Surgery, Stomatology Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Lisong LinDepartment of Oral and Maxillofacial Surgery, Stomatology Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Baochang HeDepartment of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, Fujian, China. prof_hbc@163.com.

Funding

Fujian Natural Science Foundation Program 2022J01235, and 2022J01239Mutual Expert Research Project of the First Affiliated Hospital of Fujian Medical University YJRCHP- 2023HBC
6 · The paper itself

Abstract

backgroundTo evaluate the prognostic role of the preoperative pan-immune-inflammation value (PIV) index in patients with oral squamous cell carcinoma (OSCC) after undergoing radical resection and to develop a prognostic prediction model for these patients.

methodsA large cohort study was conducted between January 2015 and March 2022. Univariate and multivariate Cox regression was used to assess the prognostic value of PIV, and propensity score matching (PSM) analysis was used to adjust for potential confounders. Randomized survival forest (RSF) was used to assess the relative importance of preoperative PIV in prognostic prediction. Finally, a Nomogram model was plotted to predict the prognosis of oral cancer patients.

resultsA total of 779 patients were enrolled and followed up (mean follow-up time 34.14 ± 24.39). High PIV was significantly associated with worse survival in OSCC patients (hazard ratio [HR] = 1.62, 95% confidence interval [CI]: 1.15-2.29, P = 0.006). The same trend was observed in PSM (HR = 1.55,95% CI: 1.03-2.23, P = 0.035). RSF showed that PIV ranked third in the importance ranking of all prognostic factors. The calibration curves indicated that the Nomogram model was superior in predicting the prognostic 1-, 3-, and 5-year survival of oral cancer patients.

conclusionsPIV is an independent predictor of prognosis in patients with oral squamous cell carcinoma, and a column-line graphical model based on PIV can effectively predict prognosis.

Indexed as

Carcinoma, Squamous CellInflammationMouth NeoplasmsAdultAgedFemaleHumansMaleMiddle AgedNomogramsPredictive Value of TestsPrognosisPropensity ScoreNomogramOral squamous cell carcinomaPIVPrognosis

Identifiers

PMID39856710
PMCPMC11761202

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.