Evidence map›Paper›PMID 38926690›Full record

ArticleBMC surgery2024

Development and validation of a nomogram to predict recurrence for clinical T1/2 clear cell renal cell carcinoma patients after nephrectomy.

Keruo Wang, Baoyin Guo, Yuanjie Niu, Gang Li

Abstract readValidation Study
In one paragraph

Article in BMC surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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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

2 citing papers in PubMed.

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4 · The record

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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

4 authors.

Keruo Wang *Department of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University Tianjin, Tianjin, 300211, China.
Baoyin Guo *Department of Urology, Tianjin Baodi Hospital, Baodi Clinical College of Tianjin Medical University, Tianjin, 301800, China.
Yuanjie NiuDepartment of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University Tianjin, Tianjin, 300211, China.
Gang LiDepartment of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University Tianjin, Tianjin, 300211, China. 797980@sina.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo develop and validate a nomogram for predicting recurrence-free survival (RFS) for clinical T1/2 (cT1/2) clear cell renal cell carcinoma (ccRCC) patients after nephrectomy.

methodsClinicopathological and survival data from 1289 cT1/2 ccRCC patients treated at the Second Hospital of Tianjin Medical University between 2017 and 2020 were included. Cox regression analysis was used to identify independent risk factors in 902 and 387 ccRCC patients in the training and validation cohorts, respectively, and construct the nomogram. The performance of the nomogram was assessed through calibration plots, time-dependent receiver operating characteristic (ROC) curves, C-index (concordance-index), and decision curve analysis (DCA). Kaplan-Meier curves were used to evaluate the probability of RFS in patients with different recurrence risks.

resultsAge, tumor size, surgical approach, Fuhrman grade, and pT3a upstage were identified as independent predictors of RFS. The area under the curve (AUC) for the 3-year and 5-year RFS ROC curves were 0.791 and 0.835 in the training cohort, and 0.860 and 0.880 in the validation cohort. The DCA and calibration plots demonstrated the optimal application and excellent accuracy of the nomogram for predicting 3-year and 5-year RFS. Kaplan-Meier curves revealed significant differences in RFS among the three risk groups in both the training and validation cohorts. Clinically, the developed nomogram provides a more precise tool for risk stratification, enabling tailored postoperative management and surveillance strategies, ultimately aiming to improve patient outcomes.

conclusionsWe developed a nomogram for predicting RFS in cT1/2 ccRCC patients after nephrectomy with high accuracy. The clinical implementation of this nomogram can significantly enhance clinical decision-making, leading to improved patient outcomes and optimized resource utilization in the management of ccRCC.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsNeoplasm Recurrence, LocalNephrectomyNomogramsAdultAgedFemaleHumansMaleMiddle AgedNeoplasm StagingRetrospective StudiesRisk FactorsROC CurveClear cell renal cell carcinomaNephrectomyNomogramRecurrence-free survivalValidation

Identifiers

PMID38926690
PMCPMC11201317

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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.