Unstaged cancer in a population-based registry: prevalence, predictors and patient prognosis

Cancer Epidemiol. 2013 Aug;37(4):498-504. doi: 10.1016/j.canep.2013.03.005. Epub 2013 Mar 31.

Abstract

Purpose: Information on cancer stage at diagnosis is critical for population studies investigating cancer care and outcomes. Few studies have examined the factors which impact (1) staging or (2) outcomes for patients who are registered as having unknown stage. This study investigated (1) the prevalence of unknown stage at diagnosis on the New Zealand Cancer Registry (NZCR); (2) explored factors which predict unknown stage; (3) described receipt of surgery and (4) survival outcomes for patients with unknown stage.

Methods: Patients diagnosed with the most prevalent 18 cancers between 2006 and 2008 (N=41,489) were identified from the NZCR, with additional data obtained from mortality and hospitalisation databases. Logistic and Cox regression were used to investigate predictors of unknown stage and patient outcomes.

Results: (1) Three distinct groups of cancers were found based on proportion of patients with unknown stage (low=up to 33% unknown stage; moderate=33-64%; high=65%+). (2) Increasing age was a significant predictor of unknown stage (adjusted odds ratios [ORs]: 1.18-1.24 per 5-year increase across groups). Patients with substantive comorbidity were more likely to have unknown stage but only for those cancers with a low (OR=2.65 [2.28-3.09]) or moderate (OR=1.17 [1.03-1.33]) proportion of patients with unknown stage. (3) Patients with unknown stage were significantly less likely to have received definitive surgery than those with local or regional disease across investigated cancers. (4) Patients with unknown stage had 28-day and 1-year survival which was intermediate between regional and distant disease.

Discussion: We found that stage completeness differs widely by cancer site. In many cases, the proportion of unknown stage on a population-based register can be explained by patient, service and/or cancer related factors.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors
  • Aged
  • Aged, 80 and over
  • Female
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Neoplasm Staging
  • Neoplasms / epidemiology*
  • Neoplasms / pathology
  • Neoplasms / surgery
  • New Zealand / epidemiology
  • Outcome Assessment, Health Care*
  • Prevalence
  • Prognosis
  • Proportional Hazards Models
  • Registries
  • Survival Rate
  • Time Factors