肿瘤预防与治疗2026，Vol.39Issue(8)：685-692,8.DOI:10.3969/j.issn.1674-0904.2026.08.008
食管癌患者癌因性疲乏变化轨迹的潜类别增长模型分析及影响因素研究
Change Trajectories of Cancer-Related Fatigue in Esophageal Cancer Pa-tients:A Latent Class Growth Model Analysis and Associated Factors
摘要
Abstract
Objective:To identify the trajectories of cancer-related fatigue and their influencing factors in esophageal cancer patients based on a latent class growth mod-el(LCGM).Methods:The study enrolled 105 patients with unresectable locally advanced esophageal cancer who were admitted to our hospital from February 2023 to January 2025.Up-on admission,participants completed a survey comprising a general information questionnaire,the Social Support Rating Scale(SSRS),the Connor-Davidson Resilience Scale(CD-RISC),the Pittsburgh Sleep Quality Index(PSQI),the Re-vised Piper Fatigue Scale(PFS-R),and other relevant measures.PFS-R scores were assessed at the following time points:before chemotherapy(T0),1 month after chemotherapy(T1),3 months after chemotherapy(T2),6 months after chemo-therapy(T3),and 9 months after chemotherapy(T4).The trajectories of cancer-related fatigue in esophageal cancer pa-tients were identified using LCGM,and their influencing factors were analyzed via multivariable Logistic regression.Results:As the number of latent classes increased,the AIC(Akaike Information Criterion),BIC(Bayesian Information Criterion),and aBIC(adjusted BIC)values progressively decreased.The 3-class model exhibited the highest entropy value,and the Bootstrap Likelihood Ratio Test was significant for all class solutions(P<0.05),indicating good class separation and high classification accuracy.The 3-class model demonstrated the best fit,with AIC,BIC,and aBIC continuing to decline as the number of classes increased.Accordingly,three distinct trajectories were retained and labeled as:the severe fatigue with slow relief group(22.86%),the moderate fatigue with moderate relief group(43.81%),and the mild fatigue with rapid re-lief group(33.33%).There were statistically significant differences among the three patient categories in terms of chemo-therapy frequency,sleep disturbances,psychological resilience,SSRS scores,Hamilton Depression Scale(HAMD)scores,and Hamilton Anxiety Scale(HAMA)scores(F/χ2 values of 9.657,7.838,15.258,7.439,116.549,and 64.514,respectively;all P<0.05).Logistic regression analysis showed that chemotherapy frequency(OR=5.937,95%CI:1.679～20.991,P<0.001),sleep disturbances(OR=5.853,95%CI:2.319～9.387,P<0.001),and psycholog-ical resilience(OR=0.894,95%CI:0.846～0.944,P<0.001),SSRS score(OR=0.198,95%CI:0.072～0.549,P<0.001),HAMD scores(OR=1.065,95%CI:1.027～1.104,P=0.001),and HAMA scores(OR=7.001,95%CI:3.109～10.893,P<0.001)were all factors influencing the CRF trajectory.Conclusion:Esophageal cancer patients exhibit three distinct trajectories of cancer-related fatigue,demonstrating individual variability and evolving over time,with most patients maintaining high PFS-R scores.Factors influencing the trajectory of cancer-related fatigue in esophageal cancer patients include chemotherapy frequency,sleep disturbances,psychological resilience,SSRS scores,and negative affective states.Healthcare providers are advised to offer personalized interventions tailored to the distinct develop-mental characteristics and influencing factors of different trajectory groups.关键词
潜类别增长模型/食管癌/癌因性疲乏/变化轨迹/社会支持Key words
Latent class growth model/Esophageal cancer/Cancer-related fatigue/Trajectories/Social support分类
医药卫生引用本文复制引用
李珍,张景俊,张俊..食管癌患者癌因性疲乏变化轨迹的潜类别增长模型分析及影响因素研究[J].肿瘤预防与治疗,2026,39(8):685-692,8.基金项目
This study was supported by grants from Beijing Medical Award Foundation(No.YXL-2023-0227-0130). 北京医学奖励基金会研究项目(编号:YXL-2023-0227-0130) （No.YXL-2023-0227-0130）
