Ovarian Cancer Symptom Clusters: Use of the NIH Symptom Science Model for Precision in Symptom Recognition and Management

Clin J Oncol Nurs. 2022 Sep 15;26(5):533-542. doi: 10.1188/22.CJON.533-542.

Abstract

Background: In the United States, ovarian cancer remains the deadliest gynecologic cancer because most women are diagnosed with advanced disease. Although early-stage ovarian tumors are considered asymptomatic, women experience symptoms throughout disease.

Objectives: This review identifies ovarian cancer symptom clusters and explores the applicability of the National Institutes of Health Symptom Science Model (NIH-SSM) for prompt symptom recognition and clinical intervention.

Methods: A focused CINAHL® and PubMed® database search was conducted for studies published from January 2000 to May 2022 using combinations of key terms.

Findings: The NIH-SSM can guide the delivery of precision-focused interventions that address racial disparities and foster equity in symptom- focused care. Enhanced understanding of symptom biology can support clinical oncology nurses in ambulatory and inpatient settings.

Keywords: ovarian cancer; quality of life; symptom clusters; symptom management.

Publication types

  • Review

MeSH terms

  • Carcinoma, Ovarian Epithelial
  • Female
  • Humans
  • Medical Oncology
  • National Institutes of Health (U.S.)
  • Ovarian Neoplasms* / diagnosis
  • Ovarian Neoplasms* / therapy
  • Syndrome
  • United States