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Symptom clusters experienced by breast cancer patients at various treatment stages: A systematic review

乳腺癌 医学 焦虑 易怒 疾病 星团(航天器) 生活质量(医疗保健) 担心 萧条(经济学) 癌症 悲伤 干预(咨询) 临床心理学 精神科 内科学 愤怒 护理部 计算机科学 经济 宏观经济学 程序设计语言
作者
Winnie K.W. So,Bernard M. H. Law,Marques Shek Nam Ng,Xiaole He,Dorothy N.S. Chan,Carmen W.H. Chan,Alexandra McCarthy
出处
期刊:Cancer Medicine [Wiley]
卷期号:10 (8): 2531-2565 被引量:122
标识
DOI:10.1002/cam4.3794
摘要

Abstract Breast cancer patients often experience symptoms that adversely affect their quality of life. It is understood that many of these symptoms tend to cluster together: while they might have different manifestations and occur during different phases of the disease trajectory, the symptoms often have a common aetiology that is a potential target for intervention. Understanding the symptom clusters associated with breast cancer might usefully inform the development of effective care plans for affected patients. The aim of this paper is to provide an updated systematic review of the known symptom clusters among breast cancer patients during and/or after cancer treatment. A search was conducted using five databases for studies reporting symptom clusters among breast cancer patients. The search yielded 32 studies for inclusion. The findings suggest that fatigue‐sleep disturbance and psychological symptom cluster (including anxiety, depression, nervousness, irritability, sadness, worry) are the most commonly‐reported symptom clusters among breast cancer patients. Further, the composition of symptom clusters tends to change across various stages of cancer treatment. While this review identified some commonalities, the different methodologies used to identify symptom clusters resulted in inconsistencies in symptom cluster identification. It would be useful if future studies could separately examine the symptom clusters that occur in breast cancer patients undergoing a particular treatment type, and use standardised instruments across studies to assess symptoms. The review concludes that further studies could usefully determine the biological pathways associated with various symptom clusters, which would inform the development of effective and efficient symptom management strategies.
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