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

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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… Click to show full 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: oncology; symptom; cancer symptom; ovarian cancer; symptom clusters; cancer

Journal Title: Clinical journal of oncology nursing
Year Published: 2022

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