| Sumario: | To explore the cancer-related fatigue (CRF) trajectories and their predictors of gastric cancer patients undergoing 6-cycle chemotherapy, and to identify subgroup characteristics of patients with different CRF trajectories. A prospective longitudinal study was conducted between November 2020 and December 2021, involving 189 first-time chemotherapy gastric cancer patients at a tertiary general hospital in Chengdu, Sichuan Province, China. Data were collected 7 times within 6 chemotherapy cycles (before the first cycle(T0), and within 1 week after the end of each cycle (T1∼T6)).The CRF level was assessed by the Cancer Fatigue Scale. Growth mixture modeling was used to identify the latent classes of CRF trajectories. Group differences analyses were performed to determine characteristics of patients with different CRF trajectories, and multivariate regression analysis was adopted to identify predictors of CRF trajectories. The overall CRF level increased over time, with the greatest change from T0 to T1. Three CRF trajectories were identified: the acute fatigue group(Class1:23.8 %), the low fatigue group(Class2:59.8 %), and the gradually worsening fatigue group(Class3:16.4 %). Patients with pain or depression were more likely to be in the acute fatigue group, and female were more likely to be in the gradually worsening fatigue group, compared with the low fatigue group. The overall CRF trajectory and three sub-trajectories were identified. Patients with pain, depression, and being female are prone to CRF deterioration. Since CRF level increases fastest from T0 to T1, early prevention and management of CRF should be implemented in gastric cancer patients undergoing chemotherapy. • Cancer-related fatigue levels rose fastest from T0 to T1 in 6 chemotherapy cycles. • There were three cancer-related fatigue trajectories over six chemotherapy cycles. • Target populations of cancer-related fatigue management were found. • Priority populations were identified for cancer-related fatigue management. • This study also indicated the optimal timing for cancer-related fatigue management.
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