Home > Research > Publications & Outputs > Developing a nomogram for predicting intravesic...

Links

Text available via DOI:

View graph of relations

Developing a nomogram for predicting intravesical recurrence after radical nephroureterectomy: A retrospective cohort study of mainland Chinese patients

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published
  • S. Lai
  • X. Long
  • P. Wu
  • J. Liu
  • S. Seery
  • H. Hou
  • M. Liu
  • Y. Li
  • J. Wang
Close
<mark>Journal publication date</mark>31/07/2021
<mark>Journal</mark>Japanese Journal of Clinical Oncology
Issue number7
Volume51
Number of pages10
Pages (from-to)1132-1141
Publication StatusPublished
Early online date26/02/21
<mark>Original language</mark>English

Abstract

Objective: To evaluate the role of Ki-67 in predicting subsequent intravesical recurrence following radical nephroureterectomy and to develop a predictive nomogram for upper tract urothelial carcinoma patients. Methods: This retrospective analysis involved 489 upper tract urothelial carcinoma patients who underwent radical nephroureterectomy with bladder cuff excision. The data set was randomly split into a training cohort of 293 patients and a validation cohort of 196 patients. Immunohistochemical analysis was used to assess the immunoreactivity of the biomarker Ki-67 in the tumor tissues. A multivariable Cox regression model was utilized to identify independent intravesical recurrence predictors after radical nephroureterectomy before constructing a nomographic model. Predictive accuracy was quantified using time-dependent receiver operating characteristic curve. Decision curve analysis was performed to evaluate the clinical benefit of models. Results: With a median follow-up of 54 months, intravesical recurrence developed in 28.2% of this sample (n = 137). Tumor location, multifocality, pathological T stage, surgical approach, bladder cancer history and Ki-67 expression levels were independently associated with intravesical recurrence (all P <0.05). The full model, which intercalated Ki-67 with traditional clinicopathological parameters, outperformed both the basic model and Xylinas' model in terms of discriminative capacity (all P <0.05). Decision-making analysis suggests that the more comprehensive model can also improve patients' net benefit. Conclusions: This new model, which intercalates the Ki-67 biomarker with traditional clinicopathological factors, appears to be more sensitive than nomograms previously tested across mainland Chinese populations. The findings suggest that Ki-67 could be useful for determining risk-stratified surveillance protocols following radical nephroureterectomy and in generating an individualized strategy based around intravesical recurrence predictions.