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Depression Is Core Symptom Shown in All CRF Networks Among Patients With Breast Cancer

Key Takeaways

  • Network analyses reveal interconnectivity of cancer symptoms, focusing on cancer-related fatigue (CRF) and its dimensions in breast cancer patients.
  • Depression emerged as a central symptom across networks, significantly associated with most CRF dimensions except mental fatigue.
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The findings show robust connections between symptoms, with variations in depression scores directly or indirectly influence fatigue and other symptoms.

Women wearing pink ribbons for breast cancer awareness -- Image credit: Vasyl | stock.adobe.com

Image credit: Vasyl | stock.adobe.com

In oncology, understanding how cancer symptoms cluster through network analyses is a new approach to understanding interconnectivity and influential relationships among patient-reported symptoms. Study authors of research published in Cancer Medicine assessed cancer-related fatigue (CRF), its 5 dimensions, and the relationships between them and all other symptoms. Additionally, the authors hypothesized that the relationships between the CRF dimension and other symptoms will be different between the 5 networks.

The study is a secondary analysis of data from 2 longitudinal interventional studies, a randomized controlled trial (NCT03144154) and a preference-based trial (NCT04873661), in which patients had to complete several questionnaires prior to and after the trials’ interventions. For the randomized trial, patients were randomly assigned to a hypnosis-based intervention group, whereas for the preference-based trial, participants explored 3 different interventions (hypnosis, mindful self-compassion meditation, and auto-induced cognitive trance).

For the study, women with breast cancer aged 18 years and older who participated in 1 of the 2 trials were included. Between the 2 trials, a total of 159 women with breast cancer were enrolled. Patients were given several questionnaires that surveyed them on the following: general information, including sociodemographic and medical data; symptoms from psychoneurological symptom clusters, such as fatigue, pain, insomnia, anxiety and depression, and cognitive function; and other symptoms, which included mental adjustments to cancer and cognitive emotion regulation.

The included women had a mean age of 51.8 years with a mean time since diagnosis of 13.3 months. Most women in the sample had several modalities of treatments, the majority of which included surgeries, radiation therapies, and hormonal therapies. The 5 CRF dimensions included the following: general fatigue, physical fatigue, mental fatigue, reduced activity, and reduced motivation.

The authors observed that depression was significantly associated with all 5 dimensions except for mental fatigue. Additionally, general fatigue was also shown to be significantly positively associated to pain and sleep difficulties, and negatively connected to non-adaptive emotion regulation. Physical fatigue was also connected with pain but not with mental adjustment to cancer, and mental fatigue was significantly positively correlated to sleep difficulties and negatively with cognitive function and quality of life. Further, in all 5 networks, summary negative adjustment was positively associated with depression, anxiety, and nonadaptive regulation, whereas summary positive adjustment was strongly associated with cognitive emotion adaptive regulation.

According to the authors, depression had the highest strength in each network—except for mental fatigue—as well as the highest closeness and betweenness. The centrality of each symptom was similar in the 5 networks, and depression was the most core symptom; however, the centrality of each dimension of fatigue differs because some (eg, physical and mental) have larger strength than others in their respective network. Additionally, pain showed the smallest strength, closeness, and betweenness in each network.

Additionally, the authors note that there are potential limitations to the study. According to the authors, the studies were not originally intended to assess symptom clusters through network analyses, therefore, there may have been biases in the selection of participants that may limit the generalizability of the results. Additionally, the sample size was relatively small and covariates were not controlled in the present analyses. The study was also retrospective in nature, which could have influenced the ability to infer causality relationships between different symptoms. Further, the use of the Hospital and Anxiety and Depression scale may have been a potential bias, according to the authors.

REFERENCE

Baussard L, Ernst M, Diep A, et al. Network Analyses Applied to the Dimensions of Cancer-Related Fatigue in Women With Breast Cancer. Cancer Med, 2024;13:e70268. doi:10.1002/cam4.70268
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