The relationship of cancer symptom clusters to depressive affect in the initial phase of palliative radiation

The feasibility of a Bayesian network model to assess the probability of simultaneous symptoms in patients with advanced cancer

Although patients with advanced cancer often experience multiple symptoms simultaneously, clinicians usually focus on symptoms that are volunteered by patients during regular history-taking. We aimed to evaluate the feasibility of a Bayesian network (BN) model to predict the presence of simultaneous symptoms, based on the presence of other symptoms. Our goal is to help clinicians prioritize which symptoms to assess. Patient-reported severity of 11 symptoms (scale 0-10) was measured using an adapted Edmonton Symptom Assessment Scale (ESAS) in a national cross-sectional survey among advanced cancer patients. Scores were dichotomized (< 4 and ≥ 4). Using fourfold cross validation, the prediction error of 9 BN algorithms was estimated (Akaike information criterion (AIC). The model with the highest AIC was evaluated. Model predictive performance was assessed per symptom; an area under curve (AUC) of ≥ 0.65 was considered satisfactory. Model calibration compared predicted and observed probabilities; > 10% difference was considered inaccurate. Symptom scores of 532 patients were collected. A symptom score ≥ 4 was most prevalent for fatigue (64.7%). AUCs varied between 0.60 and 0.78, with satisfactory AUCs for 8/11 symptoms. Calibration was accurate for 101/110 predicted conditional probabilities. Whether a patient experienced fatigue was directly associated with experiencing 7 other symptoms. For example, in the absence or presence of fatigue, the model predicted a 8.6% and 33.1% probability of experiencing anxiety, respectively. It is feasible to use BN development for prioritizing symptom assessment. Fatigue seems most eligble to serve as a starting symptom for predicting the probability of experiencing simultaneous symptoms.

Mindfulness-Based Movement Intervention to Improve Sleep Quality: A Meta-Analysis and Moderator Analysis of Randomized Clinical Trials

(1) Background: Given that the most effective dose, optimal type, and most beneficial population for improving sleep with mindfulness-based movement (MBM) remains unknown, we conducted a systematic review and meta-analysis with moderator analysis of randomized controlled trials (RCTs) to assess these effects. (2) Methods: Three electronic databases (PubMed, Web of Science, and EBSCO) were systematically searched for RCTs published through August 2021 for analysis. The risk of bias of the included studies was assessed with Review Manager 5.3, and the meta-analysis was performed in Stata 16.0. (3) Results: A meta-analysis of 61 RCTs with 2697 participants showed that MBM significantly improved sleep quality compared to controls (SMD = −0.794; 95% CI: −0.794 to −0.994, p < 0.001, I2 = 90.7%). Moderator analysis showed that a long-term MBM (SMD = −0.829; 95% CI: 0.945 to 0.712; p < 0.001) had a larger effect size on sleep than a short-term MBM (SMD = −0.714; 95% CI: 0.784 to 0.644; p < 0.001). Practicing at least twice per week (SMD = −0.793; 95% CI: −0.868 to −0.718; p < 0.001) was more effective compared to practicing once per week (SMD = −0.687; 95% CI: −0.804 to −0.570; p < 0.001). Studies with a total intervention time of more than 24 h also revealed better sleep quality improvement (SMD = −0.759; 95% CI: −0.865 to −0.653; p < 0.001). In addition, the healthy population and older adults gained more from MBM than the patients and younger adults. (4) Conclusions: MBM can effectively improve subjective sleep quality, and the optimal intervention dose of MBM can be utilized in future intervention studies to treat or improve sleep disturbance (MBM more than twice a week for more than three months, with a total intervention time of more than 24 h).

The effectiveness of non-pharmacological interventions in the management of symptom clusters in adult cancer patients: a systematic review protocol

REVIEW QUESTION/OBJECTIVE

To what extent are non-pharmacological interventions effective in reducing symptom clusters in terms of presence, frequency and severity, compared with standard care?More specifically, the objectives are to: CENTER CONDUCTING THE REVIEW:: The Hanoi Medical University Nursing Research Center for Evidence Based Health Care: a Collaborating Centre of the Joanna Briggs Institute; and Centre for Evidence-based Healthy Aging: an Affiliate Centre of the Joanna Briggs Institute, School of Nursing, Queensland University of Technology, Australia.

Los grupos de síntomas en personas con cáncer: una revisión integrativa

Objetivo: explorar el estado actual de desarrollo investigativo del área temática de grupos de síntomas en adultos con cáncer. Método: revisión integrativa de producción científica generada entre 2001 y 2016. Se incluyeron 61 artículos por su aporte en la comprensión del área temática. Resultados: el estudio de los grupos de síntomas en personas con cáncer se consolida como un área temática novedosa, pertinente y necesaria para la investigación y práctica de enfermería en oncología, con tendencias y retos que incluyen: (1) El desarrollo de marcos conceptuales que aporten a la fundamentación, atributos y efectos (2) La determinación de métodos y formas de crearlos y clasificarlos (3) La generación de estudios con poblaciones específicas por tipos de cáncer y tratamiento y la consolidación de intervenciones de enfermería. Conclusiones: los pacientes con cáncer experimentan múltiples síntomas de forma simultánea durante las distintas fases de la enfermedad. Es incipiente el estudio de este fenómeno, los retos para la enfermería se centran en la generación de respuestas que alivien la carga de los grupos de síntomas y mejoren la calidad de vida de estos pacientes. Es necesario validar escalas de carga del síntoma y explorar los grupos de síntomas incluyendo variables clínicas ligadas a los tratamientos oncológicos.

The role of ecodevelopmental context and self-concept in depressive and externalizing symptoms in Hispanic adolescents

The present study examined the extent to which self-concept is related to depressive and externalizing symptoms in Hispanic adolescents, in the presence of contextual variables. A sample of 167 Hispanic adolescents and their primary caregivers completed measures of family functioning, and of school bonding and competence. Adolescents completed measures of self-concept and peer antisocial behavior. Reports of depressive symptoms were gathered from adolescents only, whereas reports of externalizing symptoms were gathered from both adolescents and parents. Self-concept was directly and negatively related to adolescent reports of both depressive and externalizing symptoms, but not to parent reports of externalizing problems. The relationships of school bonding and peer antisocial behavior to adolescent-reported adjustment appeared to operate through self-concept, and the strong bivariate relationships of adolescent-reported family functioning to adolescent-reported adjustment appeared to operate through school bonding and self-concept. Implications for further research and for intervention are discussed.

Symptom experiences and coping strategies among multi- ethnic solid tumor patients undergoing chemotherapy in Malaysia

BACKGROUND

This study was performed to assess patient symptoms prevalence, frequency and severity, as well as distress and coping strategies used, and to identify the relationships between coping strategies and psychological and physical symptoms distress and demographic data of cancer patients. This cross-sectional descriptive study involved a total of 268 cancer patients with various types of cancer and chemotherapy identified in the oncology unit of an urban tertiary hospital.

MATERIALS AND METHODS

Data were collected using questionnaires (demographic questionnaire, Medical characteristics, Memorial Symptom Assessment Scale (MSAS) and Brief COPE scales and analyzed for demographic, and disease-related variable effects on symptom prevalence, severity, distress and coping strategies.

RESULTS

Symptom prevalence was relatively high and ranged from 14.9% for swelling of arms and legs to 88.1% for lack of energy. This latter was the highest rated symptom in the study. The level of distress was found to be low in three domains. Problem-focused coping strategies were found to be more commonly employed compared to emotion-focused strategies, demonstrating significant associations with sex, age group, educational levels and race. However, there was a positive correlation between emotion-focused strategies and physical and psychological distress, indicating that patients would choose emotion-focused strategies when symptom distress increased.

CONCLUSIONS

These findings demonstrate that high symptom prevalence rates and coping strategies used render an improvement in current nursing management. Therefore development of symptoms management groups, encouraging the use of self-care diaries and enhancing the quality of psycho- oncology services provided are to be recommended.

Using an innovative multiple regression procedure in a cancer population (Part II): fever, depressive affect, and mobility problems clarify an influential symptom pair (pain-fatigue/weakness) and cluster (pain-fatigue/weakness-sleep problems)

Background

Most patients with advanced cancer experience symptom pairs or clusters among pain, fatigue, and insomnia. However, only combinations where symptoms are mutually influential hold potential for identifying patient subgroups at greater risk, and in some contexts, interventions with “cross-over” (multisymptom) effects. Improved methods to detect and interpret interactions among symptoms, signs, or biomarkers are needed to reveal these influential pairs and clusters. I recently created sequential residual centering (SRC) to reduce multicollinearity in moderated regression, which enhances sensitivity to detect these interactions.

Methods

I applied SRC to moderated regressions of single-item symptoms that interact to predict outcomes from 268 palliative radiation outpatients. I investigated: 1) the hypothesis that the interaction, pain × fatigue/weakness × sleep problems, predicts depressive affect only when fever presents, and 2) an exploratory analysis, when fever is absent, that the interaction, pain × fatigue/weakness × sleep problems × depressive affect, predicts mobility problems. In the fever context, three-way interactions (and derivative terms) of the four symptoms (pain, fatigue/weakness, fever, sleep problems) are tested individually and simultaneously; in the non-fever context, a single four-way interaction (and derivative terms) is tested.

Results

Fever interacts separately with fatigue/weakness and sleep problems; these comoderators each magnify the pain–depressive affect relationship along the upper or full range of pain values. In non-fever contexts, fatigue/weakness, sleep problems, and depressive affect comagnify the relationship between pain and mobility problems.

Conclusion

Different mechanisms contribute to the pain × fatigue/weakness × sleep problems interaction, but all depend on the presence of fever, a sign/biomarker/symptom of proinflammatory sickness behavior. In non-fever contexts, depressive affect is no longer an outcome representing malaise from the physical symptoms of sickness, but becomes a fourth symptom of the interaction. In outpatient subgroups at heightened risk, single interventions could potentially relieve multiple symptoms when fever accompanies sickness malaise and in non-fever contexts with mobility problems. SRC strengthens insights into symptom pairs/clusters.

Using an innovative multiple regression procedure in a cancer population (Part 1): detecting and probing relationships of common interacting symptoms (pain, fatigue/weakness, sleep problems) as a strategy to discover influential symptom pairs and clusters

Background

The majority of patients with advanced cancer experience symptom pairs or clusters among pain, fatigue, and insomnia. Improved methods are needed to detect and interpret interactions among symptoms or diesease markers to reveal influential pairs or clusters. In prior work, I developed and validated sequential residual centering (SRC), a method that improves the sensitivity of multiple regression to detect interactions among predictors, by conditioning for multicollinearity (shared variation) among interactions and component predictors.

Materials and methods

Using a hypothetical three-way interaction among pain, fatigue, and sleep to predict depressive affect, I derive and explain SRC multiple regression. Subsequently, I estimate raw and SRC multiple regressions using real data for these symptoms from 268 palliative radiation outpatients.

Results

Unlike raw regression, SRC reveals that the three-way interaction (pain × fatigue/weakness × sleep problems) is statistically significant. In follow-up analyses, the relationship between pain and depressive affect is aggravated (magnified) within two partial ranges: 1) complete-to-some control over fatigue/weakness when there is complete control over sleep problems (ie, a subset of the pain–fatigue/weakness symptom pair), and 2) no control over fatigue/weakness when there is some-to-no control over sleep problems (ie, a subset of the pain–fatigue/weakness–sleep problems symptom cluster). Otherwise, the relationship weakens (buffering) as control over fatigue/weakness or sleep problems diminishes.

Conclusion

By reducing the standard error, SRC unmasks a three-way interaction comprising a symptom pair and cluster. Low-to-moderate levels of the moderator variable for fatigue/weakness magnify the relationship between pain and depressive affect. However, when the comoderator variable for sleep problems accompanies fatigue/weakness, only frequent or unrelenting levels of both symptoms magnify the relationship. These findings suggest that a countervailing mechanism involving depressive affect could account for the effectiveness of a cognitive behavioral intervention to reduce the severity of a pain, fatigue, and sleep disturbance cluster in a previous randomized trial.

Systematic review of sleep disorders in cancer patients: can the prevalence of sleep disorders be ascertained?

Although sleep is vital to all human functioning and poor sleep is a known problem in cancer, it is unclear whether the overall prevalence of the various types of sleep disorders in cancer is known. The purpose of this systematic literature review was to evaluate if the prevalence of sleep disorders could be ascertained from the current body of literature regarding sleep in cancer. This was a critical and systematic review of peer-reviewed, English-language, original articles published from 1980 through 15 October 2013, identified using electronic search engines, a set of key words, and prespecified inclusion and exclusion criteria. Information from 254 full-text, English-language articles was abstracted onto a paper checklist by one reviewer, with a second reviewer randomly verifying 50% (k = 99%). All abstracted data were entered into an electronic database, verified for accuracy, and analyzed using descriptive statistics and frequencies in SPSS (v.20) (North Castle, NY). Studies of sleep and cancer focus on specific types of symptoms of poor sleep, and there are no published prevalence studies that focus on underlying sleep disorders. Challenging the current paradigm of the way sleep is studied in cancer could produce better clinical screening tools for use in oncology clinics leading to better triaging of patients with sleep complaints to sleep specialists, and overall improvement in sleep quality.

Symptom clusters in patients with advanced cancer: a systematic review of observational studies

CONTEXT

Advanced cancer patients typically experience multiple symptoms, which may influence patient outcomes synergistically. The composition of these symptom clusters (SCs) differs depending on various clinical variables and the timing and method of their assessment.

OBJECTIVES

The objective of this systematic review was to examine the composition, longitudinal stability, and consistency across methodologies of common SCs, as well as their common predictors and outcomes.

METHODS

A search of MEDLINE, CINAHL, Embase, Web of Science, and PsycINFO was conducted using variants of symptom clusters, cancer, and palliative care.

RESULTS

Thirty-three articles were identified and reviewed. Many SCs were identified, with four common groupings being anxiety-depression, nausea-vomiting, nausea-appetite loss, and fatigue-dyspnea-drowsiness-pain. SCs in most cases were not stable longitudinally. The various statistical methods used (most commonly principal component analysis, exploratory factor analysis, and hierarchical cluster analysis) tended to reveal different SCs. Different measurement tools were used in different studies, each containing a different array of symptoms. The predictors and outcomes of SCs were also inconsistent across studies. No studies of patient experiences of SCs were identified.

CONCLUSION

Although the articles reviewed revealed four groups of symptoms that tended to cluster, there is limited consistency in the way in which SCs and variables associated with them are identified. This is largely due to a lack of agreement about a robust, clinically relevant definition of SCs. Future research should focus on patients' subjective experience of SCs to inform a clinically relevant definition of SCs and how they are managed over time.

Symptoms and problem clusters in cancer and non-cancer patients in specialized palliative care-is there a difference?

CONTEXT

In clinical practice, some symptoms and problems frequently occur in combination, which may have consequences for symptom management.

OBJECTIVES

Facing a growing number of non-cancer patients in palliative care, this study aimed to differentiate symptom clusters in the non-cancer population from those in cancer patients.

METHODS

Inpatient data from the German Hospice and Palliative Care Evaluation between 2007 and 2011 were used for a cluster analysis of a 16-item symptom and problem checklist. An agglomerative hierarchical method was chosen. Coefficients from distance matrix ranging between 0 and 1 were calculated to indicate the interrelationship of clustered symptoms.

RESULTS

The analysis identified five clusters in cancer patients: 1) nausea and vomiting (d = 0.000); 2) anxiety, tension, and feeling depressed (d = 0.125); 3) wound care and disorientation/confusion (d = 0.229); 4) organization of care and overburdening of family (d = 0.202); and 5) weakness, tiredness, need for assistance with activities of daily living, and loss of appetite (d = 0.207). Five comparable clusters were identified in non-cancer patients: 1) nausea and vomiting (d = 0.000); 2) anxiety, tension, and feeling depressed (d = 0.166); 3) organization of care and overburdening of family (d = 0.187); 4) weakness and need for assistance with activities of daily living (d = 0.139); and 5) tiredness and loss of appetite (d = 0.182).

CONCLUSION

As symptom clusters do not significantly differ between cancer and non-cancer patients, specific frequent symptoms in non-cancer patients should be assessed. Identification of symptom clusters may help to target therapies and focus the use of medications to improve patients' quality of life.

Consistency of symptom clusters among advanced cancer patients seen at an outpatient supportive care clinic in a tertiary cancer center

OBJECTIVE

Advanced cancer patients often develop severe physical and psychological symptom clusters (SCs), but limited data exist on their consistency or severity after an outpatient interdisciplinary team consultation led by palliative care specialists. The primary aim of the study was to determine the consistency and severity of SCs in advanced cancer patients in this setting.

METHOD

A total of 1373 patients with advanced cancer who were referred to The University of Texas MD Anderson Cancer Center's Outpatient Supportive Care Center between January 2003 and October 2008 with a complete Edmonton Symptom Assessment Scale (ESAS; 0-10 scale) occurred at initial and first follow-up visit were reviewed (median 14 days, range 1-4 weeks). We used a Wilcoxon signed-rank test to determine whether symptoms changed over time, and a principal components factor analysis with varimax rotation to determine SCs at baseline and at first follow-up. The number of factors calculated was determined based upon the number of eigenvalues.

RESULTS

The patients' ratings of the following symptoms (mean, SD) at the initial and follow-up visits, respectively, were: fatigue 6.2 (2.3) and 5.7 (2.5, p < 0.0001), pain 5.4 (2.9) and 4.6 (3, p < 0.0001), nausea 2.2 (2.8) and 2.0 (2.6, p < 0.0001), depression 3.0 (2.9) and 2.5 (2.7, p < 0.0001), anxiety 3.4 (3.0) and 2.8 (2.8, p < 0.0001), drowsiness 4.8 (3.1) and 4.4 (3.1, p < 0.0001), dyspnea 3.0 (2.9) and 2.7 (2.8), p < 0.0001), loss of appetite 4.2 (2.7) and 3.9 (2.7, p < 0.0001), sleep disturbances 4.2 (2.6) and 3.8 (2.6, P < 0.0001), and well-being 4.3 (2.5) and 3.9 (2.3, p < 0.0001). Cluster composition differentiated into physical (fatigue, pain, nausea, drowsiness, dyspnea, and loss of appetite) and psychological (anxiety and depression) components at the initial visit, and these two SCs were consistent upon follow-up.

SIGNIFICANCE OF RESULTS

We conclude that SCs remain constant between baseline and near-term follow-up but that the severity of those symptoms lessened during that interval. This knowledge may allow palliative care teams to provide more targeted and higher-quality care, but further studies are needed.

Functional impairments as symptoms in the symptom cluster analysis of patients newly diagnosed with advanced cancer

CONTEXT

Symptoms and subsequent functional impairment have been associated with the biological processes of disease, including the interaction between disease and treatment in a measurement model of symptoms. However, hitherto cluster analysis has primarily focused on symptoms.

OBJECTIVES

This study among patients within 100 days of diagnosis with advanced cancer explored whether self-reported physical symptoms and functional impairments formed clusters at the time of diagnosis.

METHODS

We applied cluster analysis to self-reported symptoms and activities of daily living of 111 patients newly diagnosed with advanced gastrointestinal (GI), gynecological, head and neck, and lung cancers. Based on content expert evaluations, the best techniques and variables were identified, yielding the best solution.

RESULTS

The best cluster solution used a K-means algorithm and cosine similarity and yielded five clusters of physical as well as emotional symptoms and functional impairments. Cancer site formed the predominant organizing principle of composition for each cluster. The top five symptoms and functional impairments in each cluster were Cluster 1 (GI): outlook, insomnia, appearance, concentration, and eating/feeding; Cluster 2 (GI): appetite, bowel, insomnia, eating/feeding, and appearance; Cluster 3 (gynecological): nausea, insomnia, eating/feeding, concentration, and pain; Cluster 4 (head and neck): dressing, eating/feeding, bathing, toileting, and walking; and Cluster 5 (lung): cough, walking, eating/feeding, breathing, and insomnia.

CONCLUSION

Functional impairments in patients newly diagnosed with late-stage cancers behave as symptoms during the diagnostic phase. Health care providers need to expand their assessments to include both symptoms and functional impairments. Early recognition of functional changes may accelerate diagnosis at an earlier cancer stage.

Update on interventions focused on symptom clusters: what has been tried and what have we learned?

PURPOSE OF REVIEW

Although clinicians and researchers acknowledge symptom clusters, the focus has been on relieving a single symptom. This review summarizes the recent literature on interventions that focus on relief of symptom clusters in patients with cancer.

RECENT FINDINGS

Twelve intervention studies meeting inclusion criteria were published in 2011-2012. The timeframe was expanded to 2009-2012 and 24 studies met the criteria: 18 in early stage and 6 in advanced-stage cancer patients. Several cognitive behavioral therapy, complementary therapy, and exercise interventions demonstrated positive outcomes in relieving a variety of symptom clusters in several cancer types. Most psychoeducational interventions using traditional formats or those combined with automated clinician alerts demonstrated effectiveness in reducing a variety of clusters. Clusters that included fatigue and anxiety or depression were reduced by exercise in early stage patients and by methylphenidate in advanced-stage patients. Current NIH R01 funded studies verified the trends in the types of interventions being tested.

SUMMARY

Few interventions have been tested and found to be effective in relieving the specific symptom clusters in early and advanced-stage cancer patients. Future research needs to expand our understanding of the mechanisms that initiate co-occurring symptoms. Mechanism-targeted interventions need to be identified and tested in homogeneous samples with specific symptom clusters. Interventions need to be replicated before guidelines can be established.

Symptom clusters in patients with metastatic cancer: a literature review

This article reviews the literature reporting empirically determined symptom clusters in patients with metastatic cancer. A literature search was conducted on symptom clusters within heterogeneous metastatic cancer patient populations using MEDLINE, EMBASE, and CINAHL. Studies examining predetermined symptom clusters were excluded. A total of eight relevant studies published between 2005 and 2011 were identified. The number of symptom clusters extracted varied from two to eight clusters per study, comprising of two to eight symptoms per cluster. There were no clusters consistently identified within all eight studies. Notable differences in symptoms assessed, assessment tools, statistical analysis, patient demographics were observed between the studies. The lack of consensus among the inter-study symptom clusters are likely due to the differences in patient population as well as study methodology. Further exploration in metastatic symptom cluster research will ideally improve patient outcomes by facilitating improved symptom management in future clinical practice.

Symptom clusters in Chinese patients with primary liver cancer

PURPOSE/OBJECTIVES

To derive symptom clusters and their clinical meanings in Chinese patients with primary liver cancer (PLC), to examine the factors related to the identified symptom clusters, and to validate the impact of the identified symptom clusters on patients' quality of life (QOL).

DESIGN

Cross-sectional.

SETTING

Inpatient departments at a medical center for hepatobiliary disease in China.

SAMPLE

277 patients with PLC, aged 18-77 years.

METHODS

Data were collected from a number of measures, including demographic and disease characteristics, the MD Anderson Symptom Inventory, six additional symptom items specific to PLC, and the Functional Assessment of Cancer Therapy-Hepatobiliary questionnaire. Factor analysis was used to derive symptom clusters, independent-samples t test or one-way analysis of variance was performed to identify the factors related to each symptom cluster, and multivariate regression models were applied to examine the predictive impact of the identified symptom clusters on PLC.

MAIN RESEARCH VARIABLES

Demographic and medical variables, symptom clusters, and QOL.

FINDINGS

Three symptom clusters were identified: gastrointestinal sickness, neuropsychological, and liver dysfunction. Patients who received liver protection treatment, received more than one kind of treatment, and had poorer physical performance, worse liver function, and more advanced cancer scored higher in severity across all three symptom clusters. All of the symptom clusters explained 48% of the QOL variance, and the liver dysfunction symptom cluster (adjusted R2 = 0.425) showed a superior influence.

CONCLUSIONS

The liver dysfunction symptom cluster may be unique to Chinese patients with PLC. Patients with certain demographic and disease characteristics could be at risk for experiencing severe symptom clusters. In addition, a differential impact of the symptom clusters on QOL was noted in these patients.

IMPLICATIONS FOR NURSING

The factors related to severity should be considered when managing symptom clusters. Because the predictive impacts of the three individual symptom clusters on QOL were varied and ordered in magnitude, healthcare providers should first alleviate the primary symptom cluster. This approach could be cost-effective and improve QOL.

Pilot randomized controlled trial of a patient-controlled cognitive-behavioral intervention for the pain, fatigue, and sleep disturbance symptom cluster in cancer

CONTEXT

Pain, fatigue, and sleep disturbance commonly co-occur in patients receiving treatment for advanced cancer.

OBJECTIVES

A pilot randomized controlled trial was conducted to assess initial efficacy of a patient-controlled cognitive-behavioral (CB) intervention for the pain, fatigue, and sleep disturbance symptom cluster.

METHODS

Eighty-six patients with advanced lung, prostate, colorectal, or gynecologic cancers receiving treatment at a comprehensive cancer center were stratified by recruitment clinics (chemotherapy and radiation therapy) and randomized to intervention or control groups. Forty-three patients were assigned to receive training in and use of up to 12 relaxation, imagery, or distraction exercises delivered via an MP3 player for two weeks during cancer treatment. Forty-three patients were assigned to a waitlist control condition for the same two week period. Outcomes included symptom cluster severity and overall symptom interference with daily life measured at baseline (Time 1) and two weeks later (Time 2).

RESULTS

Eight participants dropped out; 78 completed the study and were analyzed (36 intervention and 42 control subjects). Participants used the CB strategies an average of 13.65 times (SD=6.98). Controlling for baseline symptom cluster severity and other relevant covariates, it was found that the symptom cluster severity at Time 2 was lower in the intervention group (M(Adj)=2.99, SE=0.29) than in the waitlist group (M(Adj)=3.87, SE=0.36), F(1, 65)=3.57, P=0.032. Symptom interference with daily life did not differ between groups. No significant adverse events were noted with the CB intervention.

CONCLUSION

Findings suggest that the CB intervention may be an efficacious approach to treating the pain, fatigue, and sleep disturbance symptom cluster. Future research is planned to confirm efficacy and test mediators and moderators of intervention effects.

Determination of cutpoints for low and high number of symptoms in patients with advanced cancer

While patients with advanced cancer experience a wide range of symptoms, no work has been done to determine an optimal cutpoint for a low versus a high number of symptoms. Analytic approaches that established clinically meaningful cutpoints for the severity of cancer pain and fatigue provided the foundation for this study. The purpose of this study was to determine the optimal cutpoint for low and high numbers of symptoms using a range of potential cutpoints and to determine if those cutpoints distinguished between the two symptom groups on demographic and clinical characteristics and depression, anxiety, and quality of life (QOL). Patients with advanced cancer (n=110) completed a symptom assessment scale, and measures of depression, anxiety, and QOL. Combinations of cutpoints were tested to yield one- and two-cutpoint solutions. Using analysis of variance for QOL scores, the F-ratio that indicated the highest between-group difference was determined to be the optimal cutpoint between low and high number of symptoms. A cutpoint of ≤ 12 symptoms (i.e., 0-12 is low, 13-32 is high) was the optimal cutpoint for total number of symptoms. Significant differences in depression, anxiety, and QOL scores validated this cutpoint. Psychological symptoms had higher occurrence rates in the high symptom group. Findings suggest that a threshold exists between a low and a high number of symptoms in patients with advanced cancer. Psychological symptoms were significantly different between patients in the low versus high symptom groups and may play an important role in QOL outcomes in patients with advanced cancer.

Multidimensional predictors of fatigue among octogenarians and centenarians

BACKGROUND

Fatigue is a common and frequently observed complaint among older adults. However, knowledge about the nature and correlates of fatigue in old age is very limited.

OBJECTIVE

This study examined the relationship of functional indicators, psychological and situational factors and fatigue for 210 octogenarians and centenarians from the Georgia Centenarian Study.

METHODS

Three indicators of functional capacity (self-rated health, instrumental activities of daily living, physical activities of daily living), two indicators of psychological well-being (positive and negative affect), two indicators of situational factors (social network and social support), and a multidimensional fatigue scale were used. Blocked multiple regression analyses were computed to examine significant factors related to fatigue. In addition, multi-group analysis in structural equation modeling was used to investigate residential differences (i.e., long-term care facilities vs. private homes) in the relationship between significant factors and fatigue.

RESULTS

Blocked multiple regression analyses indicated that two indicators of functional capacity, self-rated health and instrumental activities of daily living, both positive and negative affect, and social support were significant predictors of fatigue among oldest-old adults. The multiple group analysis in structural equation modeling revealed a significant difference among oldest-old adults based on residential status.

CONCLUSION

The results suggest that we should not consider fatigue as merely an unpleasant physical symptom, but rather adopt a perspective that different factors such as psychosocial aspects can influence fatigue in advanced later life.

A review of the literature on multiple symptoms, their predictors, and associated outcomes in patients with advanced cancer

OBJECTIVE

The findings from several studies suggest that palliative care patients with advanced cancer experience multiple symptoms, and that these symptoms may be related to demographic and clinical factors as well as to patient outcomes. However, no systematic review has summarized the findings from studies that assessed multiple symptoms, predictors, and outcomes in these patients. The purposes of this review, focused on palliative care patients with advanced cancer, are to: 1) describe the relationships among multiple symptoms; 2) describe the predictors of multiple symptoms; and 3) describe the relationships between multiple symptoms and patient outcomes.

METHOD

Comprehensive literature searches were completed using the following databases: PubMed, Cumulative Index to Nursing and Allied Health Literature, and PsychInfo. The key words: cancer or advanced cancer or neoplasm, AND palliative care or terminal care or hospice or end-of-life, AND symptoms or multiple symptoms or symptom clusters were combined.

RESULTS

Twenty-two studies met the inclusion criteria and examined at least one of our purposes. The majority of these studies were descriptive and used one of four common symptom assessment scales. Fifty-six different signs and symptoms were evaluated across various dimensions (i.e., prevalence, severity, distress, frequency, control). Pain, dyspnea, and nausea were the only symptoms measured in all 22 studies. Relationships among concurrent symptoms were examined in nine studies. Relationships among symptoms and predictors (i.e., demographics, cancer type, healthcare delivery environment) were examined in seven studies. Relationships among symptoms and outcomes (i.e., functional status, psychological status, quality-of-life, survival time) were examined in 14 studies. Significant methodological variation was found among these studies.

SIGNIFICANCE OF RESULTS

It is difficult to draw conclusions about the relationships among multiple symptoms, predictors, and outcomes due to the heterogeneity of these studies. Future research is needed to determine which symptoms and symptom dimensions to assess in order to better understand how multiple symptoms relate to each other as well to as predictors and outcomes in palliative care patients with advanced cancer.

Mindfulness based stress reduction in post-treatment breast cancer patients: an examination of symptoms and symptom clusters

To investigate prevalence and severity of symptoms and symptom clustering in breast cancer survivors who attended MBSR(BC). Women were randomly assigned into MBSR(BC) or Usual Care (UC). Eligible women were ≥ 21 years, had been diagnosed with breast cancer and completed treatment within 18 months of enrollment. Symptoms and interference with daily living were measured pre- and post-MBSR(BC) using the M.D. Anderson Symptom Inventory. Symptoms were reported as highly prevalent but severity was low. Fatigue was the most frequently reported and severe symptom among groups. Symptoms clustered into 3 groups and improved in both groups. At baseline, both MBSR(BC) and the control groups showed similar mean symptom severity and interference; however, after the 6-week post-intervention, the MBSR(BC) group showed statistically-significant reduction for fatigue and disturbed sleep (P < 0.01) and improved symptom interference items, compared to the control group. For the between-group comparisons, 11 of 13 symptoms and 5 of 6 interference items had lower means in the MBSR(BC) condition than the control condition. These results suggest that MBSR(BC) modestly decreases fatigue and sleep disturbances, but has a greater effect on the degree to which symptoms interfere with many facets of life. Although these results are preliminary, MBSR intervention post-treatment may effectively reduce fatigue and related interference in QOL of breast cancer survivors.

Interpreting interactions of ordinal or continuous variables in moderated regression using the zero slope comparison: tutorial, new extensions, and cancer symptom applications

Moderated multiple regression (MMR) can model behaviours as multiple interdependencies within a system. When MMR reveals a statistically significant interaction term composed of ordinal or continuous variables, a follow-up procedure is required to interpret its nature and strength across the primary predictor (x) range. A follow-up procedure should probe when interactions reveal magnifier (or aggravating) effects and/or buffering (or relieving) effects that qualify the x-y relationship, especially when interpreting multiple interactions, or a complex interaction involving curvilinearity or multiple co-moderator variables. After a tutorial on the zero slope comparison (ZSC), a rarely used, quick approach for interpreting linear interactions between two ordinal or continuous variables, I derive novel extensions to interpret curvilinear interactions between two variables and linear interactions among three variables. I apply these extensions to interpret how co-occurring cancer symptoms at different levels influence one another - based on their interaction - to predict feelings of sickness malaise.

Feasibility of a patient-controlled cognitive-behavioral intervention for pain, fatigue, and sleep disturbance in cancer

PURPOSE/OBJECTIVES

To evaluate the feasibility of a patient-controlled cognitive-behavioral intervention for pain, fatigue, and sleep disturbance during treatment for advanced cancer and to assess initial efficacy of the intervention.

DESIGN

One group pre- and post-test design.

SETTING

Outpatient oncology clinics at a comprehensive cancer center in the midwestern United States.

SAMPLE

30 adults with advanced (recurrent or metastatic) colorectal, lung, prostate, or gynecologic cancer receiving chemotherapy or radiotherapy.

METHODS

Participants completed baseline measures (e.g., demographics, symptom inventory) and received education and training to use an MP3 player loaded with 12 cognitive-behavioral strategies (e.g., relaxation exercises, guided imagery, nature sound recordings). Participants used the strategies as needed for symptom management for two weeks, keeping a log of symptom ratings with each use. Following the two-week intervention, participants completed a second symptom inventory and an evaluation of the intervention.

MAIN RESEARCH VARIABLES

Feasibility, patient-controlled cognitive-behavioral intervention, pain, fatigue, and sleep disturbance.

FINDINGS

Thirty of 43 eligible patients (73%) agreed to participate; of them, 27 (90%) completed the study. Most reported that they enjoyed the intervention, had learned useful skills, and perceived improvement in their symptoms. Symptom scores at two weeks did not differ significantly from baseline; however, significant reductions in pain, fatigue, and sleep disturbance severity were found in ratings made immediately before and after use of a cognitive-behavioral strategy.

CONCLUSIONS

The patient-controlled cognitive-behavioral intervention appears to be feasible for additional study and could reduce day-to-day severity of co-occurring pain, fatigue, and sleep disturbance.

IMPLICATIONS FOR NURSING

A randomized, controlled trial is needed to test efficacy of the intervention for co-occurring pain, fatigue, and sleep disturbance. Meanwhile, based on previous efficacy studies, cognitive-behavioral strategies can be recommended for certain individual symptoms.

Cancer Symptom Clusters: Old Concept But New Data

Individuals with cancer have multiple symptoms, which frequently co-occur. A nonrandom distribution of symptoms suggests a common mechanism. Symptom clusters (SCs) were considered part of various syndromes in the early years of medicine. The SC concept in clinical medicine is old. Symptom clusters were commonly described in the psychology/psychiatry and neurology literature. Symptom cluster may be defined either clinically or statistically. Statistically derived clusters can differ from clinically defined clusters. The clinical importance of statistically derived clusters is unclear. Pain-insomnia-fatigue and pain-depression-fatigue are commonly recognized clinical clusters. Nausea-vomiting and anxiety-depression are also statistically observed clusters. The longitudinal stability of clusters is unknown. Certain SCs, appear to have a greater adverse influence on outcomes (such as performance status and survival) than others. Comorbidities probably influence symptoms at different levels, but their effect on cancer clusters is unknown. Comprehensive symptom assessment is crucial to cluster identification. The potential use of the cluster concept to abbreviate symptom assessment tools needs validation. Symptom cluster can be disease and/or treatment related and may change as individuals undergo antitumor therapies. Polypharmacy in symptom management is frequent but could be minimized if 1 drug could be used to treat cluster symptoms. Symptom cluster appears to vary with the assessment tool, disease stage, symptom domain used to cluster, cluster methodology, and number of symptoms assessed. The validity and reliability of SCs need universally accepted statistical methods, assessment tools, and symptom domains. For now, nausea-vomiting is recognized as a consistent cluster across multiple studies. Pain-depression-fatigue and pain-insomnia-fatigue are also well recognized. Symptom clusters may help in cancer diagnosis, symptom management, and prognostication. However, the cluster method, reliability, and validity need to be established before assessment or treatment guidelines are established. Symptom clusters require further research before becoming part of routine medical symptom assessment and management.

Depression assessment and classification in palliative cancer patients: a systematic literature review

The objective of this study was to review the literature on depression in palliative cancer care in order to identify which assessment methods and classification systems have been used in studies of depression. Extensive electronic database searches in PubMed, CancerLit, CINAHL, PsychINFO, EMBASE and AgeLine as well as hand search were carried out. In the 202 included papers, 106 different assessment methods were used. Sixty-five of these were only used once. All together, the Hospital Anxiety and Depression Scale (HADS) was the most commonly used assessment method. However, there were regional differences and while the HADS dominated in Europe it was quite seldom used in Canada or in the USA. Few prevalence and intervention studies used assessment methods with an explicit reference to a diagnostic system. There were in total few case definitions of depression. Among these, the classifications were in general based on cut-off scores (77%) and not according to diagnostic systems. The full range of the DSM-IV diagnostic criteria was seldom assessed, i.e. less than one-third of the assessments in the review took into account the duration of symptoms and 18% assessed consequences and impact upon patient functioning. A diversity of assessment methods had been used. Few studies classified depression by referring to a diagnostic system or by using cut-off scores. Evidently, there is a need for a consensus on how to assess and conceptualize depression and related conditions in palliative care.

Functional interference clusters in cancer patients with bone metastases: a secondary analysis of RTOG 9714

PURPOSE

To explore the relationships (clusters) among the functional interference items in the Brief Pain Inventory (BPI) in patients with bone metastases.

METHODS

Patients enrolled in the Radiation Therapy Oncology Group (RTOG) 9714 bone metastases study were eligible. Patients were assessed at baseline and 4, 8, and 12 weeks after randomization for the palliative radiotherapy with the BPI, which consists of seven functional items: general activity, mood, walking ability, normal work, relations with others, sleep, and enjoyment of life. Principal component analysis with varimax rotation was used to determine the clusters between the functional items at baseline and the follow-up. Cronbach's alpha was used to determine the consistency and reliability of each cluster at baseline and follow-up.

RESULTS

There were 448 male and 461 female patients, with a median age of 67 years. There were two functional interference clusters at baseline, which accounted for 71% of the total variance. The first cluster (physical interference) included normal work and walking ability, which accounted for 58% of the total variance. The second cluster (psychosocial interference) included relations with others and sleep, which accounted for 13% of the total variance. The Cronbach's alpha statistics were 0.83 and 0.80, respectively. The functional clusters changed at week 12 in responders but persisted through week 12 in nonresponders.

CONCLUSION

Palliative radiotherapy is effective in reducing bone pain. Functional interference component clusters exist in patients treated for bone metastases. These clusters changed over time in this study, possibly attributable to treatment. Further research is needed to examine these effects.

Managing symptoms among patients with breast cancer during chemotherapy: results of a two-arm behavioral trial

PURPOSE

In this study, we compare symptom response and times to response among patients with breast cancer who were assigned to either a cognitive behavioral Nurse-Administered Symptom Management intervention or an Automated Telephone Symptom Management (ATSM) intervention.

PATIENTS AND METHODS

Patients with breast cancer were identified from a larger trial. Baseline equivalence existed between arms, and there was no differential attrition by arm. Anchor-based definition of response using mild, moderate, and severe categories of symptom severity were used. Responses and times to response for 15 symptoms were investigated in relation to trial arm, comorbid conditions, treatment protocols, and metastatic versus localized disease.

RESULTS

The ATSM arm was more effective among patents with metastatic disease. Compared with patients receiving combination chemotherapy protocols, those treated with single agents had greater response and shorter time to response.

CONCLUSION

An educational information intervention delivered via an automated voice response system that assesses symptoms and refers patients to a Symptom Management Guide is more effective than a complex cognitive behavioral approach in terms of producing greater symptom responses in shorter time intervals among patients with metastatic disease.

The changing causal foundations of cancer-related symptom clustering during the final month of palliative care: a longitudinal study

BACKGROUND

Symptoms tend to occur in what have been called symptom clusters. Early symptom cluster research was imprecise regarding the causal foundations of the coordinations between specific symptoms, and was silent on whether the relationships between symptoms remained stable over time. This study develops a causal model of the relationships between symptoms in cancer palliative care patients as they approach death, and investigates the changing associations among the symptoms and between those symptoms and well-being.

METHODS

Complete symptom assessment scores were obtained for 82 individuals from an existing palliative care database. The data included assessments of pain, anxiety, nausea, shortness of breath, drowsiness, loss of appetite, tiredness, depression and well-being, all collected using the Edmonton Symptom Assessment System (ESAS). Relationships between the symptoms and well-being were investigated using a structural equation model.

RESULTS

The model fit acceptably and explained between 26% and 83% of the variation in appetite, tiredness, depression, and well-being. Drowsiness displayed consistent effects on appetite, tiredness and well-being. In contrast, anxiety's effect on well-being shifted importantly, with a direct effect and an indirect effect through tiredness at one month, being replaced by an effect working exclusively through depression at one week.

CONCLUSION

Some of the causal forces explaining the variations in, and relationships among, palliative care patients' symptoms changed over the final month of life. This illustrates how investigating the causal foundations of symptom correlation or clustering can provide more detailed understandings that may contribute to improved control of patient comfort, quality of life, and quality of death.

Conceptual issues in symptom clusters research and their implications for quality-of-life assessment in patients with cancer

The majority of the research on the various aspects of symptom management has focused on individual symptoms. However, patients with cancer often experience multiple symptoms simultaneously as a result of their disease and treatment. In 2001, symptom management researchers began to study the impact of symptom clusters on patient outcomes. Over the past 6 years, a number of conceptual reviews as well as several research studies have been published on symptom clusters in oncology patients. This paper summarizes the conceptual basis for symptom cluster research, describes two conceptual approaches to symptom cluster research, and discusses the implications of symptom clusters for quality-of-life research. The paper concludes with an enumeration of the critical considerations that need to be addressed if this area of scientific inquiry is to move forward.

The elusive concept of the symptom cluster

PURPOSE/OBJECTIVES

To provide an integration and synthesis of literature on the definition and importance of the symptom cluster, theoretical frameworks to explain it, analysis strategies to identify it, interventions to alleviate it, and suggestions for future research.

DATA SOURCES

A literature review from 1995-2007 was conducted using MEDLINE. Clinical guidelines, descriptive research, intervention studies of multiple symptoms, and theoretical and conceptual articles were examined. Articles were reviewed if at least two of the four symptoms of interest were examined in relation to one or more other symptoms. Conceptual models were included if they explained or allowed for the notion of a symptom cluster.

DATA SYNTHESIS

Four symptoms were examined as a candidate symptom cluster for this analysis: fatigue, insomnia, pain, and depression. Symptom clusters were identified by expert opinion, group comparisons, shared variance among symptoms (including factor analysis and mediation analysis), identification of subgroups, influence of symptoms on patient outcomes, or the identification of a common underlying mechanism. Regardless of the method chosen for identifying a symptom cluster, the substantial evidence showed that various combinations of the target symptoms formed a symptom cluster.

CONCLUSIONS

Although the findings suggest that fatigue, insomnia, pain, and depression constitute a viable cluster for further study, more research is needed to define the cluster and describe its underlying mechanisms. Addressing multiple symptoms is beneficial in reducing negative patient outcomes; however, more work needs to be done to understand the efficacy of intervention for symptom clusters.

IMPLICATIONS FOR NURSING

When conducting symptom assessment, healthcare providers should address the four symptoms (fatigue, insomnia, pain, and depression) targeted in this review because evidence of clustering exists. Guidelines provided by the National Comprehensive Cancer Network for fatigue and distress provide algorithms and decision trees for assessment and management.

Is there a biological basis for the clustering of symptoms?

OBJECTIVES

To examine symptom clusters in oncology patients; to determine if these symptom clusters might share a common biologic mechanism; and to describe potential biologic mechanisms that warrant investigation.

DATA SOURCES

Synthesis of the theoretical and research papers on symptom clusters.

CONCLUSION

Definitive conclusions about whether there is a biologic basis for the clustering of symptoms cannot be determined at this time. The animal model of sickness behavior holds promise as a potential biologic mechanism for clustering symptoms.

IMPLICATIONS FOR NURSING PRACTICE

Until more definitive studies of symptom clusters are performed, clinicians need to monitor patients for the co-occurrence of multiple symptoms and develop appropriate management plans.

Fatigue in Individuals With Advanced Cancer in Active Treatment and Palliative Settings

Fatigue is associated with cancer, but it also occurs in other illnesses and in work and leisure activities. This article is a report of part of a project comparing fatigue across ill and non-ill populations aimed at identifying the unique features of fatigue in individuals with cancer. The first stage of this work suggested that fatigue is 3 distinct but related concepts-tiredness, fatigue, and exhaustion-which led to the development of the Fatigue Adaptation Model. In this article, the authors report the findings of a qualitative study of fatigue in individuals with advanced cancer in active treatment and palliative settings. It is the first in a series of 5 papers intended to make the boundaries between tiredness, fatigue, and exhaustion more explicit. Here, the authors show that although tiredness, fatigue, and exhaustion are all manifested by the same 5 attributes (changes in emotional, cognitive, and muscular function; decreasing control over body processes; and decreased social interaction), the qualitative differences in the manifestations support the assertion that they are distinct states. This distinction is important, as interventions that could prevent, or at least delay, progression from tiredness to fatigue may be inappropriate for the prevention or delay of progression from fatigue to exhaustion.

Symptom Burden: A Concept Analysis and Implications for Oncology Nurses

PURPOSE/OBJECTIVES

To analyze the concept of symptom burden and discuss implications for symptom research and symptom management.

DATA SOURCES

MEDLINE, CINAHL, PsycINFO, Cochrane Reviews, and published literature.

DATA SYNTHESIS

Through Rodgers's evolutionary method of concept analysis, attributes of symptom burden were identified as dynamic, multidimensional, quantifiable, subjective, and physiologic. The major antecedent was multiple symptoms related to worsening disease status. Consequences of symptom burden included decreased survival, poor prognosis, delay or termination of treatment, increased hospitalizations and medical costs, decreased functional status, and lowered self-reported quality of life. Symptom burden is defined as the subjective, quantifiable prevalence, frequency, and severity of symptoms placing a physiologic burden on patients and producing multiple negative, physical, and emotional patient responses.

CONCLUSIONS

Symptom burden is an important concept in the symptoms experience, separate from symptom distress and other related terms. The continued differentiation of symptom concepts is important for sound methodologic research and meaningful interventions that affect and improve patient experiences.

IMPLICATIONS FOR NURSING

Clarifying multiple symptom concepts in the symptoms experience, determining appropriate measurement methodologies for the concepts, and identifying appropriate strategies will lessen the burden of symptoms and contribute to improved quality of life and better patient outcomes.

Clinical Management of Symptom Clusters

OBJECTIVES

To discuss the current evidence for the management of symptoms in clusters and future directions in symptom cluster management research.

DATA SOURCES

Research and review articles.

CONCLUSION

Currently no research has been reported on management of formally identified symptom clusters in oncology. Several researchers have described psychoeducational and exercise interventions that have decreased multiple concurrent symptoms. Understanding common biological mechanisms that underlie symptom clusters, such as inflammatory pathways, may suggest more effective treatments for symptom clusters.

IMPLICATIONS FOR NURSING PRACTICE

Clinicians and researchers need to collaborate to better understand symptom clusters and develop effective interventions.

Symptom Clusters and Physical Function for Patients Receiving Chemotherapy

OBJECTIVES

To examine the literature on symptom clusters and the impact of co-occurring symptoms on the physical function of patients with cancer during treatment.

DATA SOURCES

Research and review articles.

CONCLUSION

Unmanaged symptoms occur in what are often called symptom clusters. A focus on known and frequently present co-occurring symptoms, such as pain, fatigue, and sleep disturbance, might be the most efficient and effective way to manage specific symptoms and improve patient functioning.

IMPLICATIONS FOR NURSING PRACTICE

Nurses should select assessments that identify multiple symptoms and define their co-occurrence.

Symptom clusters in cancer patients with bone metastases

PURPOSE

The purpose of this study is to explore whether bone pain "clusters" with other symptoms in patients with bone metastases.

MATERIALS AND METHODS

Patients with bone metastases referred to a palliative radiotherapy clinic were asked to rate their symptom distress using the Edmonton Symptom Assessment Scale (ESAS). Analgesic consumption during the previous 24 h was captured at initial consultation. To determine interrelationships between symptoms, a principal component analysis (PCA) with "varimax rotation" was performed on the nine ESAS symptoms. This study defined a "symptom cluster" as two or more symptoms that occur together, are stable, and are relatively independent of other clusters. Patients were followed 1, 2, 4, 8, and 12 weeks post-radiation treatment by telephone. Statistical analysis was performed at each time point for both responders and nonresponders to radiation (response was defined in accordance to the International Bone Metastases Consensus Working Party).

RESULTS

Five hundred eighteen patients with bone metastases provided complete baseline data using the ESAS. The four most prevalent symptoms were poor sense of well-being (93.5%), fatigue (92.3%), pain (84.1%), and drowsiness (81.8%). Three clusters were identified and accounted for 66% of the total variance at baseline. Cronbach's alpha coefficient demonstrated high internal reliability in the clusters, with a coefficient ranging from 0.61 to 0.81. It was observed that the clusters changed post-radiation in both responders and nonresponders and that pain clustered with different symptoms (or remained a separate symptom in responders). In nonresponders, three symptom clusters were consistently present, except in week 8.

CONCLUSION

Radiotherapy influenced the structure of symptom clusters in both responders and nonresponders. There was evidence that pain clustered out in responders of radiation to pain. It was found that pain clustered with fatigue, drowsiness, and poor sense of well-being at baseline. However, these findings must be heeded with caution, as more work is needed to clearly define symptom clusters and to understand the effects of radiation in the symptom experience of patients with bone metastases.

Cancer-Related Fatigue

PURPOSE

Cancer-related fatigue contributes to negative outcomes relative to psychosocial and symptom distress, functional status, and quality of life, and yet it is often underdiagnosed and management is frequently suboptimal.

DESIGN

Systematic database searches were conducted, and primary research reports and meta-analyses of quantitative studies of interventions for fatigue published in English were identified and critically examined.

RESULTS

This paper reviews the etiology and evaluation of cancer-related fatigue and analyzes current empirical evidence supporting pharmacologic and nonpharmacologic techniques for its management.

DISCUSSION

A variety of pharmacologic and nonpharmacologic techniques to manage cancer-related fatigue have been studied, although most of the evidence is from single-arm pilot studies with small sample sizes, rather than from adequately powered, multicenter, randomized controlled trials. Continued research in ethnically and racially diverse samples is needed to identify the interventions that are most effective in specific cancer subpopulations and to develop and test interventions for fatigue at each phase in the illness trajectory.