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Development and external validation of a novel nomogram to predict intravesical recurrence after radical nephroureterectomy: a multicenter study

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Abstract

Objective

This study aimed to establish and validate nomograms to predict the probability of intravesical recurrence (IVR) after radical nephroureterectomy (RNU) for upper urinary tract epithelial carcinoma (UTUC).

Methods

Clinical data of 528 patients with UTUC after RNU were collected from two medical centers between 2009 and 2020. We used the least absolute shrinkage and selection operator (LASSO) regression to select variables for multivariable Cox regression analysis in the training cohort and included independent risk factors into nomogram models predicting IVR-free survival (IVRFS). Another center was applied as the external cohort to validate the predictive accuracy and discriminative ability of the nomogram by performing area under the receiver operating curve (AUC), consistency index (C-index), and calibration curve.

Results

History of bladder cancer, tumor size, preoperative urine cytology, postoperative instillation, Ki-67, and platelet-to-lymphocyte ratio (PLR) were identified as independent risk factors for IVR. The prognosis model including these predictors demonstrated excellent discriminatory performance in both the training cohort (C-index, 0.814) and external validation cohort (C-index, 0.748). The calibration plots of the nomogram revealed good consistency in both cohorts. Finally, patients could be classified into two risk groups based on scores obtained from the nomogram, with significant differences in IVRFS.

Conclusion

Our study provided a reliable nomogram for predicting the probability of IVR in patients with UTUC after RNU. Risk stratification based on this model may assist urologists make optimal clinical decisions on the management of UTUC.

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Data availability statement

All the data were presented in the manuscript. No additional data are available.

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Acknowledgements

We gratefully acknowledge Ruihuan Shen and Ziqi Pan for their professional statistical help.

Funding

No funding was received.

Author information

Author notes

  1. Zhenkai Luo and Binbin Jiao contributed to the work equally and should be regarded as co-first authors.

Authors and Affiliations

  1. Graduate School of Peking Union Medical College and Chinese Academy of Medical Sciences, No. 9 Dongdan Santiao, Dongcheng District, Beijing, 100730, China

    Zhenkai Luo

  2. Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Nanli, Panjiayuan, Chaoyang District, Beijing, 100021, China

    Zhenkai Luo

  3. Department of Urology, Beijing Chao-Yang Hospital, Capital Medical University, Gongren Tiyuchang Nanlu, Chaoyang District, Beijing, 100020, China

    Binbin Jiao, Weifeng He & Yuxuan Bo

  4. Department of Urology, The First Affiliated Hospital of Nanjing Medical University, No. 300. Guangzhou Road, Nanjing, 210029, China

    Tao Huang

  5. Department of Head and Neck Surgery, Fudan University Shanghai Cancer Center, 270 Dong an Road, Xuhui District, Shanghai, 200032, China

    Hang Zhao

  6. Department of Oncology, Shanghai Medical College, Fudan University, 270 Dong an Road, Xuhui District, Shanghai, 200032, China

    Hang Zhao

  7. Department of Urology, China-Japan Friendship Hospital, Yinghuadong Road, Chaoyang District, Beijing, 100029, China

    Zhenshan Ding & Guan Zhang

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  1. Zhenkai Luo
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Contributions

Study design: ZD, GZ. Data collection: TH, HZ, BJ. Data analysis and interpretation: WH, YB, ZL. Manuscript writing: ZL, BJ.

Corresponding authors

Correspondence to Zhenshan Ding or Guan Zhang.

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Conflict of interest

The authors declare that this study has received no financial support and there was no conflict of interest.

Statement of ethics

The studies involving human participants were reviewed and approved by the China–Japan Friendship Hospital and Beijing Chaoyang Hospital. The patients/participants provided their written informed consent to participate in this study.

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432_2023_5016_MOESM1_ESM.tif

Figure S1. LASSO coefficient profiles of all variables predicting IVR (A). 10-fold cross-validation for tuning parameter selection in the least LASSO model related to IVR (B) (TIF 4243 KB)

Supplementary file2 (DOCX 20 KB)

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Luo, Z., Jiao, B., Huang, T. et al. Development and external validation of a novel nomogram to predict intravesical recurrence after radical nephroureterectomy: a multicenter study. J Cancer Res Clin Oncol 149, 11223–11231 (2023). https://doi.org/10.1007/s00432-023-05016-2

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  • DOI: https://doi.org/10.1007/s00432-023-05016-2

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