Attributions of cancer 'alarm' symptoms in a community sample

PLoS One. 2014 Dec 2;9(12):e114028. doi: 10.1371/journal.pone.0114028. eCollection 2014.

Abstract

Background: Attribution of early cancer symptoms to a non-serious cause may lead to longer diagnostic intervals. We investigated attributions of potential cancer 'alarm' and non-alarm symptoms experienced in everyday life in a community sample of adults, without mention of a cancer context.

Methods: A questionnaire was mailed to 4858 adults (≥50 years old, no cancer diagnosis) through primary care, asking about symptom experiences in the past 3 months. The word cancer was not mentioned. Target 'alarm' symptoms, publicised by Cancer Research UK, were embedded in a longer symptom list. For each symptom experienced, respondents were asked for their attribution ('what do you think caused it'), concern about seriousness ('not at all' to 'extremely'), and help-seeking ('did you contact a doctor about it': Yes/No).

Results: The response rate was 35% (n = 1724). Over half the respondents (915/1724; 53%) had experienced an 'alarm' symptom, and 20 (2%) cited cancer as a possible cause. Cancer attributions were highest for 'unexplained lump'; 7% (6/87). Cancer attributions were lowest for 'unexplained weight loss' (0/47). A higher proportion (375/1638; 23%) were concerned their symptom might be 'serious', ranging from 12% (13/112) for change in a mole to 41% (100/247) for unexplained pain. Just over half had contacted their doctor about their symptom (59%), although this varied by symptom. Alarm symptoms were appraised as more serious than non-alarm symptoms, and were more likely to trigger help-seeking.

Conclusions: Consistent with retrospective reports from cancer patients, 'alarm' symptoms experienced in daily life were rarely attributed to cancer. These results have implications for understanding how people appraise and act on symptoms that could be early warning signs of cancer.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Diagnostic Self Evaluation
  • Female
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Neoplasms / diagnosis*
  • Neoplasms / pathology