Objective
To predict the risk of cancer-specific mortality (CSM) or other-cause mortality (OCM)
for T1 kidney cancer patients, aiming at identifying those who would benefit from
surgery over observation.
Patients and Methods
Overall, 11,192 T1 kidney cancer patients treated with surgery or observation in the
Surveillance, Epidemiology, and End Results-Medicare database were assessed. A competing
risk regression (CRR) model was fitted to predict CSM and OCM after surgery or observation.
Covariates consisted of age, gender, race, Charlson comorbidity index (CCI), history
of acute kidney injury or chronic kidney disease, tumor size, and year of diagnosis.
Results
At a median follow-up of 64 months, the 5-year rates of CSM and OCM were 6.7% and
24%, respectively. At CRR predicting CSM, surgery (hazard ratio [HR] 0.46; P < .0001) and year of diagnosis (HR 0.96; P < .0001) were associated with lower CSM risk. Conversely, age (HR 1.05; P < .0001), CCI (HR 1.07; P < .0001), and tumor size (HR 1.03; P < .0001) were associated with higher CSM risk. At CRR predicting OCM, surgery (HR
0.66; P < .0001), female gender (HR 0.83; P < .0001), Other race (HR 0.82; P < .0001), and year of diagnosis (HR 0.95; P < .0001) were associated with lower OCM risk. Conversely, age (HR 1.06; P < .0001), African American race (HR 1.16; P < .01), CCI (HR 1.17; P < .0001), and acute kidney injury or chronic kidney disease (HR 1.35; P < .0001) were associated with higher OCM risk.
Conclusion
The benefit of surgery over observation was more pronounced in younger and healthier
patients with larger tumors. The proposed model can aid in clinical decision-making,
providing crucial information on CSM and OCM risk after either treatment modality.
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Article info
Publication history
Published online: November 21, 2016
Accepted:
August 2,
2016
Received:
May 9,
2016
Footnotes
Alessandro Larcher and Vincent Trudeau contributed equally to this work.
Financial Disclosure: The authors declare that they have no relevant financial interests.
Identification
Copyright
© 2016 Elsevier Inc. All rights reserved.
