Stage II breast cancer: Differences between four coping patterns in side effects during adjuvant chemotherapy

Exploring the differential experience of breast cancer treatment-related symptoms: a cluster analytic approach

“…Taken together, the study findings corroborate published literature using cluster analysis in chronic pain patients [19][20][21][22][23] and cancer patients [11,12,[14][15][16] and support our hypothesis that distinct patient subgroups can be identified based on differential treatment-related symptom experience in a homogeneous sample of breast cancer patients. In addition, the differences in QOL support our hypothesis that the clusters would be associated with differential treatment-related impact on QOL [13][14][15][16].…”

“…The identification of patient subgroups that experience differential symptom burden and deleterious QOL outcomes is most beneficial if the findings can guide treatment/ management of disease-or treatment-related symptoms through interventions tailored to individuals in each group. This indeed has been the goal of cluster analyses in chronic pain patients [19,22,23] and cancer patients [12][13][14][15][16].…”

“…Rather than using factor or cluster analysis to group "similar" or "related" symptoms (factors) [5][6][7]9,10,17,35], the current study utilized cluster analysis to identify patient subgroups (distinct, mutually exclusive subgroups) that were defined by a similar symptom experience [12][13][14][15]19,22,23]. Given that symptom cluster research is still in its infancy in oncology [17], it is likely that both approaches may contribute unique insights to symptom burden analysis and possibly inform development of more effective symptom intervention approaches.…”

“…In addition, studies have shown that the number or intensity of symptoms reported by patients is correlated with their perception of quality of life (QOL) [3][4][5][6][7][8]. Thus, previous research has focused on identifying distinct subgroups of patients [11][12][13][14][15][16] who report similar outcomes, and more recently, on clusters of related or similar symptoms (symptom clusters) [3][4][5][6][7][8][9][10]17].…”

“…More recently, several studies have used cluster analysis with cancer patients to identify subgroups of patients who differ in coping [11][12][13]15], quality of life [14,15], and symptoms [15] using published psychometric instruments. A study by Hack and Degner [13] identified three patient subgroups among stage I and stage II breast cancer patients using the Coping Responses Inventory, but did not generate subgroups based on symptoms or examine whether the patient subgroups differed on QOL outcomes.…”