Evidence map›Paper›PMID 38842727›Full record

ArticleAbdominal radiology (New York)2024

Development of a CT-assessed adiposity nomogram for predicting outcome in localized ccRCC.

Xiaoxia Li, Shaoting Zhang, Xiaolan Huang, Dengqiang Lin, Jianjun Zhou

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Article in Abdominal radiology (New York), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Xiaoxia Li *Department of Radiology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, 361015, China.
Shaoting Zhang *Department of Radiology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, 250117, China.
Xiaolan Huang *Department of Radiology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, 361015, China.
Dengqiang Lin *Department of Urology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, 361015, China. 153365650@qq.com.
Jianjun Zhou *Department of Radiology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, 361015, China. zhoujianjunzs@126.com.

Funding

the Scientific Research Project of Fujian for Youth 2020QNB061the Scientific Research Project of Fujian for Youth 2020QNB062
6 · The paper itself

Abstract

purposeThis study aimed to develop and validate a computed tomography-based nomogram assessing visceral and subcutaneous adiposity for predicting outcomes in localized clear cell renal cell carcinoma (ccRCC).

methodsA cohort of 364 patients with pathologically confirmed ccRCC participated in this retrospective study, with 254 patients assigned to the training set and 110 to the validation set (a 7:3 distribution ratio). The adipose score (AS) was generated using the least absolute shrinkage and selection operator Cox regression. Subsequently, a nomogram was constructed by integrating the clinical independent predictor with the AS to predict disease-free survival (DFS) in localized ccRCC after surgery. The performance of the nomogram was compared with the University of California, Los Angeles, Integrated Staging System (UISS), and the Stage, Size, Grade, and Necrosis (SSIGN) score.

resultsIn both the training and validation cohorts, the nomogram exhibited superior discrimination compared to SSIGN and UISS (C-index: 0.897 vs. 0.781 vs. 0.776 in the training cohort, and 0.752 vs. 0.596 vs. 0.686 in the validation cohort; 5 year AUC: 0.907 vs. 0.805 vs. 0.820 in the training cohort, and 0.832 vs. 0.577 vs. 0.726 in the validation cohort). Decision curve analysis (DCA) revealed a superior net benefit across a wider range of threshold probabilities for predicting 5 year DFS compared to UISS and SSIGN scores.

conclusionsThe developed prognostic nomogram demonstrated high accuracy and overall superior performance compared to existing prognostic models.

Indexed as

AdiposityCarcinoma, Renal CellKidney NeoplasmsNomogramsTomography, X-Ray ComputedAdultAgedFemaleHumansMaleMiddle AgedNeoplasm StagingPredictive Value of TestsRetrospective StudiesComputed tomographyPrognosisRenal cell carcinomaSubcutaneous adiposityVisceral adiposity

Identifiers

PMID38842727

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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.