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

Trajectories and risk factors of fatigue following colorectal cancer diagnosis

AIM

This study sought to identify groups of colorectal cancer patients based upon trajectories of fatigue and examine how demographic, clinical and behavioural risk factors differentiate these groups.

METHOD

Patients were from six cancer centres in the United States and Germany. Fatigue was measured using the fatigue subscale of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) at five time points (baseline/enrolment and 3, 6, 12 and 24 months after diagnosis). Piecewise growth mixture models identified latent trajectories of fatigue. Logistic regression models examined differences in demographic, clinical and behavioural characteristics between fatigue trajectory groups.

RESULTS

Among 1615 participants (57% men, 86% non-Hispanic White, mean age 61 ± 13 years at diagnosis), three distinct groups were identified. In the high fatigue group (36%), fatigue significantly increased in the first 6 months after diagnosis and then showed statistically and clinically significant improvement from 6 to 24 months (P values < 0.01). Throughout the study period, average fatigue met or exceeded cutoffs for clinical significance. In the moderate (34%) and low (30%) fatigue groups, fatigue levels remained below or near population norms across the study period. Patients who were diagnosed with Stage II-IV disease and/or current smokers were more likely to be in the high fatigue than in the moderate fatigue group (P values < 0.05).

CONCLUSION

A large proportion of colorectal cancer patients experienced sustained fatigue after initiation of cancer treatment. Patients with high fatigue at the time of diagnosis may benefit from early supportive care.

A Group Intervention Combining Self-Hypnosis and Self-Care in Oncology: Implementation in Daily Life and Perceived Usefulness

Multicomponent mind-body interventions are increasingly studied in oncology to improve patients' quality of life (QOL). However, the respective usefulness of each of their components or their long-term use by the participants are rarely assessed. In this study, 95 women with different cancer diagnoses participated in a self-hypnosis and self-care group. Different questionnaires were administrated before (T1), right after (T2), 3 to 4 months after (T3), and 1 year after (T4) the intervention. After the intervention, 97.5% of the participants regularly practiced any kind of relaxation (vs. 50% at baseline), especially hypnosis. The different components of the intervention (i.e., being in a group, hypnosis exercises during the sessions and at home, self-care tasks, and discussions during the group sessions) were all considered to be very useful (M = 6.91-7.75/10). One year after the intervention, the 10 most used techniques were mainly concrete activities to take care of oneself. This intervention seems very relevant for women who had cancer. Our results allow a first reflection about the mechanisms of action of our intervention.Registration: ClinicalTrials.gov (NCT03144154). Registered on the 1st of May 2017.

[Latest Findings in Key Research Areas of Precision Nursing for Chronic Diseases in Older Adults]

The advent of the era of biomedical big data has helped promote the development of precision nursing. Precision nursing for chronic diseases in older adults is an interdisciplinary research field in which accurate individualized data are utilized to carry out early screening and health management of older adult populations at high risk for chronic diseases and early intervention of diseases, which plays an important role in improving the prognosis of diseases and the health level of the older adult population. Herein, we introduced the concept of precision nursing, and discussed the latest research findings in the key areas of precision nursing for chronic diseases in older adults, including precision symptom management in cancer patients and precision nursing in older patients with multimorbidity. At present, research concerning precise symptom management of cancer patients is mainly focused on prediction modelling for risks of symptoms, longitudinal change trajectories, core symptom identification, etc. Investigations in the precise nursing of cancer patients are conducted in the following areas, risk prediction, the timing of interventions, and intervention targets. Research on precision nursing for multimorbidity is mainly focused on assessment of chronic disease multimorbidity, multimorbidity pattern recognition, and health management of multimorbidity. We also discussed potential opportunities and challenges of precision nursing in the future, in order to provide a scientific basis for the improving the practice and theories of precision nursing. In the future, precision nursing will play an ever more important role in uncovering pathogenic information, the diagnosis and treatment of diseases, the health of the research population, and the promotion of medical research.

Distinct Profiles of Morning and Evening Fatigue Co-Occurrence in Patients During Chemotherapy

BACKGROUND

Morning and evening fatigue are distinct and distressing symptoms experienced during chemotherapy that demonstrate a large amount of interindividual variability.

OBJECTIVES

The objectives of this study were to identify subgroups of patients with distinct morning and evening fatigue co-occurrence profiles and evaluate for differences among these subgroups in demographic, clinical, and symptom characteristics and quality of life.

METHODS

Oncology patients ( n = 1,334) completed the Lee Fatigue Scale to self-report morning and evening fatigue, six times over two cycles of chemotherapy. Latent profile analysis was used to identify subgroups of patients with distinct morning and evening physical fatigue profiles.

RESULTS

Four distinct morning and evening fatigue profiles were identified (i.e., Both Low, Low Morning + Moderate Evening, Both Moderate, and Both High). Compared to the Both Low profile, the Both High profile was significantly younger, less likely to be married or partnered, more likely to live alone, had a higher comorbidity burden, and lower functional status. The Both High profile had higher levels of anxiety, depressive symptoms, sleep disturbance, and pain and lower levels of quality of life.

DISCUSSION

The variability in the morning and evening severity scores among the four profiles supports the hypothesis that morning and evening fatigue are distinct but related symptoms. Clinically meaningful levels of both morning and evening fatigue were reported by 50.4% of our sample, which suggests that the co-occurrence of these two symptoms is relatively common. Patients in Both Moderate and Both High profiles experienced an extremely high symptom burden that warrants ongoing assessments and aggressive symptom management interventions.

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

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.

Trajectories of Learned Helplessness in Maintenance Haemodialysis Patients and Their Predictive Effects on Self-Management: A Latent Growth Mixture Modeling Approach

Background

Learned helplessness (LH) is an essential psychological factor influencing maintenance haemodialysis (MHD) patients' health behaviour and is closely related to prognosis of the disease. This study aimed to identify potential trajectories of LH in MHD patients and assess their predictive role in self-management.

Methods

This study was conducted in strict compliance with national laws, the Declaration of Istanbul, and the Declaration of Helsinki. A total of 347 MHD patients at a blood purification centre in Hunan Province, China, were selected as the study population. Four longitudinal surveys (baseline and second/fourth/sixth month after baseline) were conducted using the General Information Questionnaire for MHD patients, the Chinese version of the Learned Helplessness Scale for MHD patients, and the Self-Management Scale for Haemodialysis. Latent growth mixture model (LGMM) analysis was used to identify LH trajectories, and their predictors were analysed using multinomial logistic regression. The predictive role of LH trajectory on self-management was analysed using linear regression.

Results

This study identified three LH trajectories in MHD patients, named the "high-decreasing group" (57.9%), "low-increasing group" (21.3%), and "low-stability group" (20.7%). The results of the univariate analysis showed that sex (χ²=33.777, P < 0.001), age (χ²=10.605, P<0.05), and subjective social status (SSS) (χ²=12.43, P<0.01) were associated with LH trajectory classes. Multinomial logistic regression further demonstrated that gender, age, and SSS were predictors of different LH trajectories. The intercept and slope of the overall LH trajectory were negatively correlated with self-management (β=-0.273, P<0.001; β=-0.234, P<0.01).

Conclusion

MHD patients show three different LH trajectories. The initial level and developmental rate of LH can negatively predict future self-management. It is necessary to screen MHD patients' LH and develop targeted interventions for them with different LH trajectories at specific stages.

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

Background

In 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.

Objectives

Implementing 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 design

A 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.

Discussion

Results 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 registration

ClinicalTrials.gov Identifier: NCT04999306; https://clinicaltrials.gov/ct2/show/NCT04999306.

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

Background

Cancer-related fatigue (CRF) is common in patients with advanced solid tumors and several risk factors are described. The possible role of depression is reported by clinicians despite the association with CRF being unclear.

Material and methods

In this monocentric, cross-sectional, prospective study we recruited patients with advanced solid tumors who were hospitalized at Fondazione IRCCS Istituto Nazionale dei Tumori of Milan. The primary objective was to assess the correlation between CRF and depression. Secondary objectives were the estimation of CRF and depression prevalence and the identification of associated clinical risk factors. CRF and depression were evaluated through the Functional Assessment of Cancer Therapy-Fatigue subscale and the Zung Self Depression Scale (ZSDS) questionnaires. The Cochran-Armitage trend test was used to demonstrate the primary hypothesis. Univariate and multivariate logistic regression models were used to investigate the impact of clinical variables.

Results

A total of 136 patients were enrolled. The primary analysis found a linear correlation (P < 0.0001) between CRF and depression. The prevalence of CRF and of moderate to severe depressive symptoms was 43.5% and 29.2%, respectively. In univariate analysis, patients with poor Eastern Cooperative Oncology Group performance status (ECOG PS), anemia, distress, pain, and receiving oncological treatment were at a significantly higher risk for CRF, whereas poor ECOG PS, pain, and distress were risk factors for depression. In multivariate analysis, high levels of ZSDS were confirmed to be correlated to CRF: odds ratio of 3.86 [95% confidence interval (CI) 0.98-15.20) and 11.20 (95% CI 2.35-53.36) for ZSDS of 50-59 and 60-100, respectively (P value for trend 0.002). Moreover, the ECOG PS score was confirmed to be significantly associated with CRF (OR 7.20; 95% CI 1.73-29.96; P = 0.007).

Conclusions

Our data suggest a strong correlation between CRF and depression in patients with advanced solid tumors. Further investigations are needed to better understand this relationship and if depressive disorder therapeutic strategies could also impact on CRF.

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Validated patient-reported outcome measures were used for screening CRF and depression in advanced cancer patients.

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A direct strong correlation between CRF and depression was found in these patients, often unconsidered by clinicians.

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Other different clinical risk factors for the onset and worsening of CRF were identified.

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A comprehensive evaluation of cancer patients, that should also consider mood disorders, could improve CRF management.