Evidence map›Paper›PMID 40474201›Full record

ArticleBMC surgery2025

Clinicopathological-based nomogram prediction and molecular characterization of postoperative recurrence in clinical T1 clear cell renal cell carcinoma.

Zhao Yang, Keruo Wang, Haowen Chang, Songyang Li, Hongli Zhang, Yilei Lu, Jiaming Zhang, Kangkang Liu, Yuanjie Niu, Zhiqun Shang

Abstract read
In one paragraph

Article in BMC surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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

10 authors.

Zhao Yang *Department of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China.
Keruo Wang *Department of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China.
Haowen Chang *Department of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China.
Songyang LiDepartment of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China.
Hongli ZhangDepartment of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China.
Yilei LuDepartment of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China.
Jiaming ZhangDepartment of Otorhinolaryngology, Head and Neck Surgery, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China.
Kangkang LiuDepartment of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China.
Yuanjie NiuDepartment of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China. niuyuanjie9317@163.com.
Zhiqun ShangDepartment of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China. zhiqun_shang@tmu.edu.cn.

Funding

the Foundation for The Talents by Tianjin Institute of Urology MYSRC202307the Natural Science Foundation of Tianjin 23JCQNJC01120
6 · The paper itself

Abstract

objectiveThis study aimed to develop and validate a nomogram for predicting recurrence-free survival (RFS) in clinical T1 (cT1) clear cell renal cell carcinoma (ccRCC) following nephrectomy. Additionally, it explored transcriptional profiles across distinct risk groups.

methodsData from 2,492 cT1 ccRCC patients who underwent nephrectomy at The Second Hospital of Tianjin Medical University were analyzed. Univariate and multivariate Cox proportional hazards regression analyses were conducted to identify independent predictors of RFS. A nomogram was constructed and validated using a training cohort (n = 1744) and an internal validation cohort (n = 748). Model performance was evaluated using the concordance index (C-index), calibration plots, receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and Kaplan-Meier survival curves. An external validation was performed using The Cancer Genome Atlas (TCGA) ccRCC dataset. Furthermore, Cox-Lasso regression analysis was applied to identify risk-associated genes in the high-risk group.

resultsAge, surgical margin status, Fuhrman grade, and pT3a upstage were identified as independent predictors. The areas under the ROC curve (AUC) for 3-year and 5-year RFS were 0.748 and 0.762 in the training cohort; 0.777 and 0.776 in the internal validation cohort; and 0.706 and 0.746 in the external validation cohort. Kaplan-Meier analysis showed significant differences in RFS between low- and high-risk groups across all cohorts (p < 0.0001, p < 0.0001, p = 0.0010, respectively). Nine genes, including MMP13, ITPKA, ATG9B, and CACNA1B, were identified as poor prognosis markers.

conclusionsWe developed and validated a robust nomogram for predicting RFS in cT1 ccRCC patients after nephrectomy, offering valuable insights for individualized patient management.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsNeoplasm Recurrence, LocalNephrectomyNomogramsAdultAgedFemaleHumansMaleMiddle AgedNeoplasm StagingRetrospective StudiesClear cell renal cell carcinomaCox-LassoNomogramRecurrenceRisk factor

Identifiers

PMID40474201
PMCPMC12139270

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LicenceCC BY-NC-ND
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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.