Determinants of Distinct Trajectories of Fatigue in Patients Undergoing Chemotherapy for a Metastatic Colorectal Cancer: 6-Month Follow-up Using Growth Mixture Modeling

Baussard, Louise; Proust‐Lima, Cécile; Philipps, Vivianne; Portalès, Fabienne; Ychou, Marc; Mazard, Thibault; Cousson‐Gélie, Florence

doi:10.1016/j.jpainsymman.2021.06.019

Cited by 7 publications

(13 citation statements)

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“…. (Baussard et al, 2022). These results corroborate the literature underlying the relationship between emotional distress and fatigue (Blesch et al, 1991;Mols et al, 2012;Yennurajalingam et al, 2016), even in CRC patients (Mota et al, 2012;Tung et al, 2016).…”

Section: Introductionsupporting

confidence: 86%

“…Indeed, some authors have made recommendations for psycho-oncology researchers to study the role of personality in developing or coping with CRC cancer and the associated QoL (Sales et al, 2014 ). To better understand the psychological factors associated with fatigue in CRCm patients, a recent study highlighted distinct trajectories of fatigue in this specific population during the course of chemotherapy (Baussard et al, 2022 ). That study was theoretically based on the Transactional, Integrative and Multifactorial (TIM) model (Bruchon-Schweitzer and Boujut, 2014 ) which suggests that health issues are explained by sociodemographic, medical and dispositional variables (such as personality) and by contextual variables (such as resources, e.g., coping strategies, perceived control, etc.).…”

Section: Introductionmentioning

confidence: 99%

“…Results suggest that in CRCm patients undergoing chemotherapy, four distinct fatigue profiles were identified. The probability of belonging to each of these trajectories is explained by variables considered by the TIM model: tired patients are those reporting more emotional distress, little perceived control or inadequate coping strategies (Baussard et al, 2022 ). These results corroborate the literature underlying the relationship between emotional distress and fatigue (Blesch et al, 1991 ; Mols et al, 2012 ; Yennurajalingam et al, 2016 ), even in CRC patients (Mota et al, 2012 ; Tung et al, 2016 ).…”

Section: Introductionmentioning

confidence: 99%

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Hypnosis and cognitive behavioral therapy with online sessions to reduce fatigue in patients undergoing chemotherapy for a metastatic colorectal cancer: Rational and study protocol for a feasibility study

et al. 2022

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BackgroundIn metastatic colorectal cancer (CRCm), fatigue is pervasive, reduces quality of life, and is negatively associated with survival. Its course is explained in part by psychosocial variables such as emotional distress, coping strategies, or perceived control. Thus, to reduce fatigue, psychosocial interventions appear to be relevant. In some cancers, Cognitive Behavioral Therapies (CBT) reduce fatigue. Hypnosis is also used as a complementary therapy to reduce the side effects of cancer. While CBT requires specific training often reserved for psychologists, hypnosis has the advantage of being increasingly practiced by caregivers and is therefore less expensive (Montgomery et al., 2007). On the other hand, CBT and hypnosis remain understudied in the CRC, do not focus on the symptom of fatigue and in Europe such programs have never been evaluated.ObjectivesImplementing an intervention in a healthcare setting is complex (e.g., economic and practical aspects) and recruiting participants can be challenging. The primary objective will therefore be to study the feasibility of two standardized interventions (hypnosis and CBT) that aim to reduce fatigue in patients with CRCm treated in a French cancer center.Methods and designA prospective, single-center, randomized interventional feasibility study, using mixed methods (both quantitative and qualitative). A total of 60 patients will be allocated to each intervention group [Hypnosis (n = 30) and CBT (n = 30)]. Participants will be randomized into two parallel groups (ratio 1:1). Both programs will consist of 6 weekly sessions focusing on the CRF management over a period of 6 weeks. Trained therapists will conduct the program combining 3 face-to-face sessions and 3 online sessions. The feasibility and experience of interventions will be evaluated by the outcome variables, including the adhesion rate, the reasons for acceptability, relevance or non-adherence, the satisfaction, the fatigue evolution (with ecological momentary assessments), and the quality of life. All questionnaires will be self-assessment using an online application from the cancer center.DiscussionResults will highlight the barriers/facilitators to the implementation of the program and the relevance of the program to the patients, and will be used to generate hypotheses for a randomized control trial.Clinical trial registrationClinicalTrials.gov Identifier: NCT04999306; https://clinicaltrials.gov/ct2/show/NCT04999306.

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Section: Introductionsupporting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Hypnosis and cognitive behavioral therapy with online sessions to reduce fatigue in patients undergoing chemotherapy for a metastatic colorectal cancer: Rational and study protocol for a feasibility study

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“…Previously, numerous studies have been conducted aiming to explore this association, and different hypotheses have been formulated. 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 According to Reuter and Härter, 46 CRF could be interpreted as part of a depressive disorder where somatic symptoms play a central role. Conversely, Jacobsen et al.…”

Section: Discussionmentioning

confidence: 99%

“… 31 , 32 , 33 Previous studies documented that CRF and depression could coexist in cancer patients, however their possible association and interconnection remain not well established. 15 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 Results of these studies have, in fact, demonstrated that when CRF was considered as a one-dimensional construct, it could be a simple symptom of depression; on the contrary, considering CRF in a multidimensional way, it resulted in a syndrome with complex relationships with depressive disorders. In particular, emotional aspects and the inner tension of patients with fatigue present similarities with anhedonia and psychomotor agitation, typical of depressive syndromes.…”

Section: Introductionmentioning

confidence: 99%

Cancer-related fatigue and depression: a monocentric, prospective, cross-sectional study in advanced solid tumors

et al. 2022

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Clustering on longitudinal quality‐of‐life measurements using growth mixture models for clinical prognosis: Implementation on CCTG/AGITG CO.20 trial

Zhang

Kong

et al. 2022

Cancer Medicine

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Introduction Analyzing longitudinal cancer quality‐of‐life (QoL) measurements and their impact on clinical outcomes may improve our understanding of patient trajectories during systemic therapy. We applied an unsupervised growth mixture modeling (GMM) approach to identify unobserved subpopulations (“patient clusters”) in the CO.20 clinical trial longitudinal QoL data. Classes were then evaluated for differences in clinico‐epidemiologic characteristics and overall survival (OS). Methods and Materials In CO.20, 750 chemotherapy‐refractory metastatic colorectal cancer (CRC) patients were randomized to receive Brivanib+Cetuximab (n = 376, experimental arm) versus Cetuximab+Placebo (n = 374, standard arm) for 16 weeks. EORTC‐QLQ‐C30 QoL summary scores were calculated for each patient at seven time points, and GMM was applied to identify patient clusters (termed “classes”). Log‐rank/Kaplan–Meier and multivariable Cox regression analyses were conducted to analyze the survival performance between classes. Cox analyses were used to explore the relationship between baseline QoL, individual slope, and the quadratic terms from the GMM output with OS. Results In univariable analysis, the linear mixed effect model (LMM) identified sex and ECOG Performance Status as strongly associated with the longitudinal QoL score (p < 0.01). The patients within each treatment arm were clustered into three distinct QoL‐based classes by GMM, respectively. The three classes identified in the experimental (log‐rank p‐value = 0.00058) and in the control arms (p < 0.0001) each showed significantly different survival performance. The GMM's baseline, slope, and quadratic terms were each significantly associated with OS (p < 0.001). Conclusion GMM can be used to analyze longitudinal QoL data in cancer studies, by identifying unobserved subpopulations (patient clusters). As demonstrated by CO.20 data, these classes can have important implications, including clinical prognostication.

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Determinants of Distinct Trajectories of Fatigue in Patients Undergoing Chemotherapy for a Metastatic Colorectal Cancer: 6-Month Follow-up Using Growth Mixture Modeling

Cited by 7 publications

References 22 publications

Hypnosis and cognitive behavioral therapy with online sessions to reduce fatigue in patients undergoing chemotherapy for a metastatic colorectal cancer: Rational and study protocol for a feasibility study

Hypnosis and cognitive behavioral therapy with online sessions to reduce fatigue in patients undergoing chemotherapy for a metastatic colorectal cancer: Rational and study protocol for a feasibility study

Cancer-related fatigue and depression: a monocentric, prospective, cross-sectional study in advanced solid tumors

Clustering on longitudinal quality‐of‐life measurements using growth mixture models for clinical prognosis: Implementation on CCTG/AGITG CO.20 trial

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