Effect of routine follow-up after treatment for laryngeal cancer on life expectancy and mortality: results of a Markov model analysis

Cancer. 2007 Jan 15;109(2):239-47. doi: 10.1002/cncr.22401.

Abstract

Background: Routine follow-up is offered to all patients with laryngeal cancer who are treated with curative intent. Although time and resources are devoted to surveillance, the effect of asymptomatic recurrence detection is not well understood. For this study, the authors evaluated the effect that routine follow-up may have on life expectancy and disease-specific mortality rate for patients with laryngeal cancer.

Methods: Using a Markov model, a cohort simulation was performed on 4 hypothetical age groups of patients with laryngeal cancer. Three different follow-up strategies were compared-the current schedule, no follow-up, and the perfect follow-up-in which all recurrences were detected asymptomatically. Sensitivity analyses were performed to study the impact of variations in the transition rates on life expectancy.

Results: Compared with no follow-up, the current schedule showed a gain in life expectancy with a range from 0.3 years to 1.5 years that decreased with advancing age. Abolishing the current follow-up schedule raised the disease-specific mortality rate; the increase ranged from 2.8% to 5.9%. Variations of +/-25% in the transition rates produced only a modest effect on life expectancy.

Conclusions: A small reduction in life expectancy was observed when follow-up was withheld from the majority of patients. Disease-specific mortality rates rose when no follow-up was provided. These rates probably were overestimated. A simplified version of the current follow-up protocol may be implemented.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Female
  • Follow-Up Studies
  • Humans
  • Laryngeal Neoplasms / mortality*
  • Laryngeal Neoplasms / therapy
  • Life Expectancy
  • Male
  • Markov Chains*
  • Middle Aged
  • Models, Biological
  • Survival Analysis
  • Survival Rate
  • Time Factors