Completeness of prostate cancer staging in the Danish Cancer Registry, 2004-2009

• Published in: Clinical epidemiology 2012, Vol.4 Suppl 2 (Suppl 2), p.17-23
• Main Authors: Nguyen-Nielsen, Mary, Frøslev, Trine, Friis, Søren, Borre, Michael, Harving, Niels, Søgaard, Mette
• Format: Article
• Language: English
• Subjects: Algorithms; Prostate cancer; Short Report
• ISSN: 1179-1349; 1179-1349
• DOI: 10.2147/CLEP.S32004

To investigate the completeness of TNM (Tumor-Node-Metastasis) staging for prostate cancer (PC) in the Danish Cancer Registry (DCR). We identified 20,184 men registered with first-time PC in the DCR between 2004 and 2009. These patients were linked to the Danish National Patient Register to obtain data on comorbidity according to the Charlson Comorbidity Index (CCI). We calculated the completeness and corresponding 95% confidence intervals (CI) of TNM staging overall and by the individual components. We also defined a clinically-based algorithm classifying PC into four stage categories: localized, regional, distant, and unknown. The overall completeness of TNM staging was 34.2% (95% CI: 0.34-0.35). TNM completeness improved gradually over time reaching 41.2% in 2009. TNM completeness decreased substantially with age from 75.0% among patients 0-39 years to 11.3% among patients 80 years or older. Similarly, completeness decreased with increasing comorbidity level from 37.6% among patients with low CCI to 20.3% among those with high CCI. When classifying T1 cancer as a complete registration regardless of missing N or M stage, the overall TNM completeness increased to 48.7% (95% CI: 0.48-0.49). According to the clinically-based staging algorithm, 70.5% of PC cases could be categorized into a definite clinical stage. One-third of PC patients had a complete registration of all TNM components in the DCR. Although TNM completeness improved over time, older age and high comorbidity were consistently associated with missing TNM staging. Research and monitoring based on cancer registries such as the DCR should account for missing TNM staging. Failing to do so could otherwise lead to biased results of stage-specific analyses.