Purpose: The renewal and iteration of chemotherapy drugs have resulted in more frequent long-term remissions for patients with multiple myeloma (MM). MM has transformed into a chronic illness for many patients, but the cancer-related fatigue (CRF) of many MM convalescent patients experience is frequently overlooked. We investigated whether the accompanying treatment of family members would affect MM patients' CRF and explore their serum metabolomics, so as to provide clinicians with new ideas for identifying and treating CRF of MM patients.
Methods: This was a single-center study, and a total of 30 MM patients were included in the study. Patients were divided into two groups based on whether they have close family members accompanying them through the whole hospitalization treatment. These patients received regular chemotherapy by hematology specialists, and long-term follow-up was done by general practitioners. Patients' CRF assessment for several factors used the Chinese version of the Brief Fatigue Inventory (BFI-C). Face-to-face questionnaires were administered at a time jointly determined by the patient and the investigator. All questionnaires were conducted by a general practitioner. The LC-MS-based metabolomics analysis determined whether the patients' serum metabolites were related to their fatigue severity. A correlation analysis investigated the relationship between serum metabolites and clinical laboratory indicators.
Results: The fatigue severity of MM patients whose family members participated in the treatment process (group A) was significantly lower than patients whose family members did not participate in the treatment process (group B). There was a statistically significant difference (fatigue severity composite score: t = - 2.729, p = 0.011; fatigue interference composite score: t = - 3.595, p = 0.001). There were no differences between the two groups of patients' gender, age, regarding clinical staging, tumor burden, blood routine, biochemical, or coagulation indexes. There were 11 metabolites, including guanidine acetic acid (GAA), 1-(Methylthio)-1-hexanethiol, isoeucyl-asparagine, L-agaritine, tryptophyl-tyrosine, and betaine, which significantly distinguished the two groups of MM patients. GAA had the strongest correlation with patient fatigue, and the difference was statistically significant (fatigue severity composite score: r = 0.505, p = 0.0044; fatigue interference composite score: r = 0.576, p = 0.0009). The results showed that GAA negatively correlated with albumin (r = - 0.4151, p = 0.0226) and GGT (r = - 0.3766, p = 0.0402). Meanwhile, GAA positively correlated with PT (r = 0.385, p = 0.0473), and the difference was statistically significant.
Conclusion: The study is the first to report that family presence throughout the whole hospitalization may alleviate CRF in MM patients. Moreover, the study evaluated serum metabolites linked to CRF in MM patients and found that CRF has a significant positive correlation with GAA. GAA may be a more sensitive biomarker than liver enzymes, PT, and serum albumin in predicting patient fatigue. While our sample may not represent all MM patients, it proposes a new entry point to help clinicians better identify and treat CRF in MM patients.
Keywords: Cancer-related fatigue; Guanidinoacetic acid; Metabolomics; Multiple myeloma; Oncology.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.