Symptom lead times in lung and colorectal cancers: what are the benefits of symptom-based approaches to early diagnosis?

Br J Cancer. 2015 Jan 20;112(2):271-7. doi: 10.1038/bjc.2014.597. Epub 2014 Dec 2.

Abstract

Background: Individuals with undiagnosed lung and colorectal cancers present with non-specific symptoms in primary care more often than matched controls. Increased access to diagnostic services for patients with symptoms generates more early-stage diagnoses, but the mechanisms for this are only partially understood.

Methods: We re-analysed a UK-based case-control study to estimate the Symptom Lead Time (SLT) distribution for a range of potential symptom criteria for investigation. Symptom Lead Time is the time between symptoms caused by cancer and eventual diagnosis, and is analogous to Lead Time in a screening programme. We also estimated the proportion of symptoms in lung and colorectal cancer cases that are actually caused by the cancer.

Results: Mean Symptom Lead Times were between 4.1 and 6.0 months, with medians between 2.0 and 3.2 months. Symptom Lead Time did not depend on stage at diagnosis, nor which criteria for investigation are adopted. Depending on the criteria, an estimated 27-48% of symptoms in individuals with as yet undiagnosed lung cancer, and 12-32% with undiagnosed colorectal cancer are not caused by the cancer.

Conclusions: In most cancer cases detected by a symptom-based programme, the symptoms are caused by cancer. These cases have a short lead time and benefit relatively little. However, in a significant minority of cases cancer detection is serendipitous. This group experiences the benefits of a standard screening programme, a substantial mean lead time and a higher probability of early-stage diagnosis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Case-Control Studies
  • Colorectal Neoplasms / diagnosis*
  • Colorectal Neoplasms / epidemiology
  • Early Detection of Cancer
  • Humans
  • Incidence
  • Lung Neoplasms / diagnosis*
  • Lung Neoplasms / epidemiology
  • Primary Health Care
  • Sensitivity and Specificity