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Development and validation of a clinical and ultrasound features-based nomogram for preoperative differentiation of renal urothelial carcinoma and central renal cell carcinoma

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Abstract

Purpose

This study aimed to develop and validate an ultrasound (US)-based nomogram for the preoperative differentiation of renal urothelial carcinoma (rUC) from central renal cell carcinoma (c-RCC).

Methods

Clinical data and US images of 655 patients with 655 histologically confirmed malignant renal tumors (521 c-RCCs and 134 rUCs) were collected and divided into training (n = 455) and validation (n = 200) cohorts according to examination dates. Conventional US and contrast-enhanced US (CEUS) tumor features were analyzed to determine those that could discriminate rUC from c-RCC. Least absolute shrinkage and selection operator regression was applied to screen clinical and US features for the differentiation of rUC from c-RCC. Using multivariate logistic regression analysis, a diagnostic model of rUC was constructed and visualized as a nomogram. The diagnostic model’s performance was assessed in the training and validation cohorts by calculating the area under the receiver operating characteristic curve (AUC) and calibration plot. Decision curve analysis (DCA) was used to assess the clinical usefulness of the US-based nomogram.

Results

Seven features of both clinical features and ultrasound imaging were selected to build the diagnostic model. The nomogram achieved favorable discrimination in the training (AUC = 0.996, 95% CI: 0.993–0.999) and validation (AUC = 0.995, 95% CI: 0.974, 1.000) cohorts, and good calibration (Brier scores: 0.019 and 0.016, respectively). DCA demonstrated the clinical usefulness of the US-based nomogram.

Conclusion

A noninvasive clinical and US-based nomogram combining conventional US and CEUS features possesses good predictive value for differentiating rUC from c-RCC.

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Data availability

The data that support the findings of this study are available from the corresponding author, upon reasonable request.

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Funding

Natural Science Foundation (CN), 12174074, Bei-jian Huang, Shanghai Municipal Health Commission, R2021-007, Cuixian Li, 202240153, Cuixian Li.

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Author notes

  1. Cuixian Li, Beilei Lu and Qing Zhao contributed equally to this work.

Authors and Affiliations

  1. Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, 200032, China

    Cuixian Li, Beilei Lu, Qing Lu, Jingjing Wang, Pei Sun, Huixiong Xu & Beijian Huang

  2. Shanghai Institute of Medical Imaging, Fudan University, No. 180 of Fenglin Road, Shanghai, 200032, China

    Cuixian Li, Huixiong Xu & Beijian Huang

  3. Department of Interventional Radiology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China

    Qing Zhao

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  1. Cuixian Li
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  4. Qing Lu
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Contributions

LC: protocol/project development, data collection and management, and manuscript writing; LB: protocol/project development, data collection and management; ZQ: data analysis, manuscript writing/editing; LQ: manuscript editing; WJ: data collection and management; SP: and data collection and management; XH: conceptualization and supervision; HB: conceptualization, data collection, validation, supervision, and funding acquisition.

Corresponding author

Correspondence to Beijian Huang.

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Conflict of interest

The authors declared no potential conflicts of interest.

Ethical approval

The studies involving human participants were reviewed and approved by the institutional Ethics Review Board (Approval No.: B2021-290R, Approval Date: 2021.5.19).

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Written consent from the patients was waived for this retrospective study.

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Li, C., Lu, B., Zhao, Q. et al. Development and validation of a clinical and ultrasound features-based nomogram for preoperative differentiation of renal urothelial carcinoma and central renal cell carcinoma. World J Urol 42, 227 (2024). https://doi.org/10.1007/s00345-024-04935-0

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