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. 2020 Apr;125(4):561-567.
doi: 10.1111/bju.15001. Epub 2020 Feb 8.

Chest computed tomography for staging renal tumours: validation and simplification of a risk prediction model from a large contemporary retrospective cohort

James Voss  1 , Tamsin Drake  1   2 , Hannah Matthews  1 , James Jenkins  2 , Stanley Tang  1 , Joshua Doherty  1 , Keith Chan  1 , Harriet Dawe  1 , Tittu Thomas  1 , Samantha Kearley  2 , James Manners  1 , Charles Carter  1 , Salah Al-Buheissi  2 , Tobias Klatte  1   3
Affiliations

Chest computed tomography for staging renal tumours: validation and simplification of a risk prediction model from a large contemporary retrospective cohort

James Voss et al. BJU Int. 2020 Apr.

Abstract

Objectives: To externally validate a nomogram recently proposed by Larcher et al. (BJU Int. 2017; 120: 490) and to develop a simplified model with comparable accuracy to guide on the need for staging chest computed tomography (CT) for patients with new renal masses.

Patients and methods: We analysed the data of 1082 consecutive patients with unilateral enhancing renal masses referred to urology multidisciplinary team meetings at two centres between 2011 and 2017. All patients underwent a staging chest CT at diagnosis. We fitted multivariable logistic regression models and tested the Larcher model performance using area under the receiver-operating curve (AUC), calibration and decision curve analysis.

Results: Forty-two patients (3.9%) had a positive chest CT. The Larcher nomogram had an AUC of 83.8% (95% confidence interval [CI] 77.1-90.6), but was only moderately well calibrated (calibration-in-the-large = -0.61, slope = 0.82). Specifically, the nomogram overestimated the risk of positive chest CT, and the magnitude of miscalibration increased with increasing predicted risks. Using a stepwise backward approach, a new model was developed including tumour size, nodal stage and systemic symptoms. Compared with the Larcher model, the new model had a similar AUC (82.7% [95% CI 75.5-90.0]), but improved calibration and clinical net benefit. The predicted risk of positive chest CT was <1% in the low-risk group and 1.9-79.9% in the high-risk group.

Conclusion: The Larcher nomogram is an accurate prediction tool that was moderately well calibrated with our dataset. However, our simplified model has similar accuracy and uses more objective variables available from referral, so may be easier to incorporate into clinical practice. The low-risk group from our model (tumour size ≤4 cm and no systemic symptoms) had a risk of positive chest CT <1%, suggesting these patients may forego chest CT.

Keywords: cancer staging; chest computed tomography; kidney cancer; pulmonary metastases; risk stratification.

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