Symptom Interval and Patient Delay Affect Survival Outcomes in Adolescent Cancer Patients

Yonsei Med J. 2016 May;57(3):572-9. doi: 10.3349/ymj.2016.57.3.572.

Abstract

Purpose: Unique features of adolescent cancer patients include cancer types, developmental stages, and psychosocial issues. In this study, we evaluated the relationship between diagnostic delay and survival to improve adolescent cancer care.

Materials and methods: A total of 592 patients aged 0-18 years with eight common cancers were grouped according to age (adolescents, ≥10 years; children, <10 years). We retrospectively reviewed their symptom intervals (SIs, between first symptom/sign of disease and diagnosis), patient delay (PD, between first symptom/sign of disease and first contact with a physician), patient delay proportion (PDP), and overall survival (OS).

Results: Mean SI was significantly longer in adolescents than in children (66.4 days vs. 28.4 days; p<0.001), and OS rates were higher in patients with longer SIs (p=0.001). In children with long SIs, OS did not differ according to PDP (p=0.753). In adolescents with long SIs, OS was worse when PDP was ≥0.6 (67.2%) than <0.6 (95.5%, p=0.007). In a multivariate analysis, adolescents in the long SI/PDP ≥0.6 group tended to have a higher hazard ratio (HR, 6.483; p=0.069) than those in the long SI/PDP <0.6 group (HR=1, reference).

Conclusion: Adolescents with a long SI/PDP ≥0.6 had lower survival rates than those with a short SI/all PDP or a long SI/PDP <0.6. They should be encouraged to seek prompt medical assistance by a physician or oncologist to lessen PDs.

Keywords: Adolescent cancer patients; patient delay; symptom interval.

Publication types

  • Evaluation Study

MeSH terms

  • Adolescent
  • Child
  • Delayed Diagnosis*
  • Female
  • Humans
  • Male
  • Multivariate Analysis
  • Neoplasms / classification
  • Neoplasms / diagnosis*
  • Neoplasms / mortality*
  • Neoplasms / psychology
  • Patient Acceptance of Health Care / statistics & numerical data*
  • Retrospective Studies
  • Survival Analysis
  • Survival Rate
  • Time Factors