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. 2013 Apr 16;108(7):1534-40.
doi: 10.1038/bjc.2013.106. Epub 2013 Mar 12.

Competing mortality in patients diagnosed with bladder cancer: evidence of undertreatment in the elderly and female patients

A P Noon  1 , P C Albertsen, F Thomas, D J Rosario, J W F Catto
Affiliations

Competing mortality in patients diagnosed with bladder cancer: evidence of undertreatment in the elderly and female patients

A P Noon et al. Br J Cancer. .

Abstract

Background: Bladder cancer (BC) predominantly affects the elderly and is often the cause of death among patients with muscle-invasive disease. Clinicians lack quantitative estimates of competing mortality risks when considering treatments for BC. Our aim was to determine the bladder cancer-specific mortality (CSM) rate and other-cause mortality (OCM) rate for patients with newly diagnosed BC.

Methods: Patients (n=3281) identified from a population-based cancer registry diagnosed between 1994 and 2009. Median follow-up was 48.15 months (IQ range 18.1-98.7). Competing risk analysis was performed within patient groups and outcomes compared using Gray's test.

Results: At 5 years after diagnosis, 1246 (40%) patients were dead: 617 (19%) from BC and 629 (19%) from other causes. The 5-year BC mortality rate varied between 1 and 59%, and OCM rate between 6 and 90%, depending primarily on the tumour type and patient age. Cancer-specific mortality was highest in the oldest patient groups. Few elderly patients received radical treatment for invasive cancer (52% vs 12% for patients <60 vs >80 years, respectively). Female patients with high-risk non-muscle-invasive BC had worse CSM than equivalent males (Gray's P<0.01).

Conclusion: Bladder CSM is highest among the elderly. Female patients with high-risk tumours are more likely to die of their disease compared with male patients. Clinicians should consider offering more aggressive treatment interventions among older patients.

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Figures

Figure 1
Figure 1
All-cause mortality (top) and disease-specific mortality (bottom) are plotted using the Kaplan–Meier method. The number remaining at risk is shown below the time intervals.
Figure 2
Figure 2
The 5-year competing mortality data models for patients stratified by primary tumour (columns) and age at diagnosis (rows). Black shaded area=estimated CSM (eCSM) and grey shaded area=estimated OCM (eOCM) – plotted as 1 minus the sum of CSM and OCM.
Figure 3
Figure 3
Estimated cumulative incidence curves for OCM and CSM as competing events for male and female patients with (A) low-risk tumours (n=1027 males vs n=413 females), (B) high-risk tumours (n=743 males vs n=212 females) and (C) MIBC (n=598 males vs n=288 females).
See this image and copyright information in PMC

Comment in

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