Prospective Longitudinal Evaluation of a Symptom Cluster in Breast Cancer

ContextSymptom cluster research expands cancer investigations beyond a focus on individual symptoms in isolation.ObjectivesWe conducted a prospective longitudinal study of sleep, fatigue, depression, anxiety, and perceived cognitive impairment in patients with breast cancer undergoing chemotherapy.MethodsPatient-reported outcome measures were administered prior to chemotherapy, at Cycle 4 Day 1, and six months after initiating chemotherapy. Participants were divided into four groups and assigned a symptom cluster index (SCI) score based on the number/severity of symptoms reported at enrollment.ResultsParticipants (N = 80) were mostly women (97.5%) with Stage II (69.0%) breast cancer, 29–71 years of age. Scores on all measures were moderately-highly correlated across all time points. There were time effects for all symptoms, except sleep quality (nonsignificant trend), with most symptoms worsening during chemotherapy, although anxiety improved. There were no significant group × time interactions; all four SCI groups showed a similar trajectory of symptoms over time. Worse performance status and quality of life were associated with higher SCI score over time.ConclusionWith the exception of anxiety, the coherence of the symptom cluster was supported by similar patterns of severity and change over time in these symptoms (trend for sleep quality). Participants with higher SCI scores prior to chemotherapy continued to experience greater symptom burden during and after chemotherapy. Early assessment and intervention addressing this symptom cluster (vs. individual symptoms) may have a greater impact on patient performance status and quality of life for patients with higher SCIs.     

Tryptophan and Kynurenine Pathway Metabolites and Psychoneurological Symptoms Among Breast Cancer Survivors

BackgroundAmong breast cancer survivors, pain, fatigue, depression, anxiety, and sleep disturbance are common psychoneurological symptoms that cluster together. Inflammation-induced activation of the tryptophan-kynurenine metabolomic pathway may play an important role in these symptoms.AimsThis study investigated the relationship between the metabolites involved in the tryptophan-kynurenine pathway and psychoneurological symptoms among breast cancer survivors.DesignCross-sectional study.SettingParticipants were recruited at the oncology clinic at the University of Illinois Hospital & Health Sciences System. Participants/Subjects: 79 breast cancer survivors after major cancer treatment.MethodsWe assessed psychoneurological symptoms with the PROMIS-29 and collected metabolites from fasting blood among breast cancer survivors after major cancer treatment, then analyzed four major metabolites involved in the tryptophankynurenine pathway (tryptophan, kynurenine, kynurenic acid, and quinolinic acid). Latent profile analysis identified subgroups based on the five psychoneurological symptoms. Mann-Whitney U tests and multivariable logistic regression compared targeted metabolites between subgroups.ResultsWe identified two distinct symptom subgroups (low, 81%; high, 19%). Compared with participants in the low symptom subgroup, patients in the high symptom subgroup had higher BMI (p = .024) and were currently using antidepressants (p = .008). Using multivariable analysis, lower tryptophan levels (p = .019) and higher kynurenine/tryptophan ratio (p = .028) were associated with increased risk of being in the high symptom subgroup after adjusting for BMI and antidepressant status.ConclusionThe tryptophan-kynurenine pathway and impaired tryptophan availability may contribute to the development of psychoneurological symptoms.     

Stable Symptom Clusters and Evolving Symptom Networks in Relation to Chemotherapy Cycles

ContextThe existence of stable symptom clusters with variations or changes in cluster membership and the merging of symptom clusters over time urge us to investigate how symptom relationships change over time.ObjectivesTo identify stable symptom clusters and understand networks among symptoms using longitudinal data.MethodsSecondary data analysis was conducted using data from a nonblinded randomized clinical trial, which evaluated the effect and feasibility of the developed cancer symptom management system. For the present study, data from all participants of the original trial were analyzed (N = 249). The severity of 20 symptoms was measured before the start of chemotherapy (CTx) and during the initial four cycles of CTx. Symptom clusters were identified using principal component and hierarchical cluster analyses, and network analysis was used to explore the relationships among symptoms.ResultsThree common symptom clusters were identified. The first cluster consisted of anxiety, depression, sleep disturbance, pain, and dyspnea. Fatigue, difficulty concentrating, and drowsiness formed a second stable cluster throughout the CTx cycles. The third cluster comprised loss of appetite, taste change, nausea, and vomiting. In terms of the symptom networks, close relationships were recognized, irrespective of symptom severity level, between anxiety and depression, fatigue and drowsiness, and loss of appetite and taste change. Fatigue was the most central symptom with the highest strength. Edge thickening after starting CTx demonstrated evolving symptom networks in relation to CTx cycles.ConclusionStable symptom clusters and evolving networks were identified. The most central symptom was fatigue; however, the paucity of studies that investigated symptom networks and central symptoms calls for further investigations on these phenomena. Identification of central symptoms and underlying mechanisms will guide efficient symptom management. Future studies will need to focus on developing comprehensive interventions for managing symptom clusters or targeting central symptoms.     

Symptom clusters in cancer patients

Goals of work Cancer patients often experience multiple symptoms, many of which have been reported to correlate with each other. The goals of this study were to understand which cancer-related symptoms cluster together and to test the conceptual meanings of the revealed symptom clusters.Patients and methods Patients with various cancer diagnoses (N=151) were recruited from a medical center in northern Taiwan. The 13-item M.D. Anderson symptom inventory was used to assess patients’ symptom severity. Selected symptoms were factored using principal-axis factoring with oblique rotation. The known-group technique was used to validate the conceptual meanings of revealed factors.Main results Patients’ symptom severity ratings fit a three-factor solution that explained 55% of the variance. These three factors (symptom clusters) were named sickness symptom cluster, gastrointestinal symptom cluster, and emotional symptom cluster. Patients with pain and with advanced diseases had significantly higher mean scores in the sickness symptom cluster than patients without pain and with earlier-stage diseases. The patients’ functional status was negatively correlated with mean scores in the sickness symptom cluster. Patients under chemotherapy demonstrated significantly higher mean scores in the gastrointestinal symptom cluster than patients under other treatments. Patients with anxiety or depression also had significantly higher mean scores in the emotional symptom cluster than patients without anxiety or depression.Conclusions This study identified three underlying symptom clusters and verified their conceptual meaning in cancer patients. Knowing these symptom clusters may help healthcare professionals understand plausible mechanisms for the aggregation of symptoms.     

A Longitudinal Analysis of Symptom Clusters in Cancer Patients and Their Sociodemographic Predictors

ContextExploring the relationships between concurrent symptoms or “symptom clusters” (SCs) longitudinally may complement the knowledge gained from the traditional approach of examining individual symptoms or SCs crosssectionally.ObjectivesTo identify consistent SCs over the course of one year and determine the possible associations between SCs and demographic and medical characteristics, and between SCs and emotional distress.MethodsThis study was an exploratory longitudinal analysis of SCs in a large sample of newly diagnosed cancer patients. Patients provided symptom assessment data at baseline, three, six, and 12 months. A factor analysis was conducted (controlling for the patient over time) on pain, fatigue, anxiety, depression, sleep, weight change, and food intake items to identify clusters. A panel regression on each cluster explored associations with demographic and medical characteristics and distress.ResultsIn total, 877 patients provided baseline data, with 505 retained at 12 months. Three SCs explained 71% of the variance. The somatic cluster included pain, fatigue, and sleep; the psychological cluster included anxiety and depression; and the nutrition cluster consisted of weight and food intake. Low income and treatment with radiation or chemotherapy predicted higher somatic symptom burden. Younger age, being female, low income, and treatment with surgery predicted more psychological symptomatology. Older age and treatment with surgery predicted higher nutritional burden. Patients with higher somatic, psychological, and nutritional symptom burden reported higher distress.ConclusionThe presence of SCs across the first year of diagnosis supports the need for routine and ongoing screening for the range of symptoms that may be experienced by patients. Further work is needed to develop interventions that better target individual symptoms that cluster, as well as the entire cluster itself.     

Symptom clusters in patients with advanced cancers

Goals of work  It has been observed that certain cancer symptoms frequently occur together. Prior research on symptom patterns has focused mainly on inpatients, early stage cancers, or a single cancer type or metastatic site. Our aim was to explore symptom clusters among outpatients with different advanced cancers. Materials and methods  Symptom scores by the Edmonton Symptom Assessment Scale (ESAS) were routinely collected for patients attending the Oncology Palliative Care Clinics at Princess Margaret Hospital from January 2005 to October 2007. Principal component analysis (PCA) was performed for the entire patient cohort and within specific disease sites to determine inter-relationships of the nine ESAS symptoms. Main results  A total of 1,366 patients was included: 682 (50%) were male and 684 (50%) were female. The median age was 64 years (range 18 to 74 years). The most common primary cancer sites were gastrointestinal (27%), lung (14%), and breast (11%). The three most distressful symptoms were fatigue, poor general well-being, and decreased appetite. PCA of symptoms for the entire patient cohort revealed two major symptom clusters: cluster 1 included fatigue, drowsiness, nausea, decreased appetite, and dyspnea, which accounted for 45% of the total variance; cluster 2 included anxiety and depression, which accounted for 10% of the total variance. There was high internal reliability in the clusters (Cronbach’s alpha coefficient ∼0.80). PCA of symptoms within the various primary cancer sites revealed differences in the pattern of symptom clusters. Conclusions  In patients with advanced cancers, distinct symptom clusters can be identified, which are influenced by primary cancer site. Treatments directed at symptom clusters rather than individual symptoms may provide greater therapeutic benefit. Further prospective studies are warranted in order to develop more effective targeted palliative interventions for the advanced cancer patient population.     

Efficacy,Safety, and Tolerability of Telcagepant in the Treatment of Acute Migraine: A meta‐Analysis

Although triptans are widely used for treating acute migraine, they are contraindicated or not effective in a large proportion of patients. Hence, alternative treatments are needed. Calcitonin gene–related peptide receptor antagonists, such as telcagepant, have been under investigation as a treatment for acute migraine. A meta‐analysis of the efficacy of telcagepant vs. placebo and triptans (zolmitriptan or rizatriptan) was performed. Randomized controlled trials were indentified from databases using the following search terms: migraine; calcitonin gene‐related peptide; calcitonin gene‐related peptide receptor antagonists; efficacy; safety, and telcagepant. The primary outcome measure was pain freedom 2 hours after first treatment. The secondary outcome measure was pain relief 2 hours after first treatment. Eight trials were included in the meta‐analysis (telcagepant = 4011 participants). The difference in pain freedom at 2 hours significantly favored telcagepant over placebo (odds ratio = 2.70, 95% confidence interval = 2.27–3.21, P < 0.001) and triptans over telcagepant (odds ratio = 0.68, 95% confidence interval = 0.56–0.83, P < 0.001). The difference in pain relief at 2 hours significantly favored telcagepant over placebo (odds ratio = 2.48, 95% confidence interval = 2.18–2.81, P < 0.001). The difference in pain relief at 2 hours did not significantly favor telcagepant over triptans or vice versa (odds ratio = 0.76, 95% confidence interval = 0.57–1.01, P = 0.061). These findings indicate that telcagepant can be effective for treating acute migraine. Calcitonin gene‐related peptide receptor antagonists represent a potentially important alternative means of treating acute migraine.     

Association of Musculoskeletal Pain With Sedentary Behavior in Public School Teachers: The Role of Habitual Physical Activity

BackgroundSedentary behavior has been associated with musculoskeletal pain in school teachers. However, our hypothesis is that physical activity practice could mitigate this association.AimThe aim of this study was to investigate the relationship of musculoskeletal pain with high screen-based sedentary behavior among public school teachers and whether physical activity could mitigate this relationship.MethodA sample of 246 teachers from 13 public schools were assessed (45.0 ± 10.4 years, 76.0% of women). Musculoskeletal pain was assessed using the Nordic Musculoskeletal Questionnaire, screen-based sedentary behavior was measured considering the sum of screen time in television, computer, and smartphone/tablet, and physical activity using the Baecke habitual physical activity questionnaire. Binary logistic regression was used to verify the associations between high screen-based sedentary behavior and musculoskeletal pain in school teachers (Model 1-unadjusted; Model 2-adjusted by age, sex, and socioeconomic status; Model 3-variables of Model 2 + adjusted by physical activity).ResultsHigh screen-based sedentary behavior was associated with pain in neck (odds ratio = 2.09; 95%confidence interval = 1.08-4.04), upper back (odds ratio = 2.21; 95%confidence interval = 1.07-4.56), and low back (odds ratio = 1.91; 95%confidence interval = 1.00-3.65). However, after inserting the variables, including physical activity, these associations were mitigated.ConclusionsHigh screen-based sedentary behavior was associated with musculoskeletal pain in public school teachers. However, this relationship was mitigated after the inclusion of confounding variables, including physical activity.     

Applying the Rapid OPPERA Algorithm to Predict Persistent Pain Outcomes Among a Cohort of Women Undergoing Breast Cancer Surgery

Persistent postmastectomy pain after breast surgery is variable in duration and severity across patients, due in part to interindividual variability in pain processing. The Rapid OPPERA Algorithm (ROPA) empirically identified 3 clusters of patients with different risk of chronic pain based on 4 key psychophysical and psychosocial characteristics. We aimed to test this type of group-based clustering within in a perioperative cohort undergoing breast surgery to investigate differences in postsurgical pain outcomes. Women (N = 228) scheduled for breast cancer surgery were prospectively enrolled in a longitudinal observational study. Pressure pain threshold (PPT), anxiety, depression, and somatization were assessed preoperatively. At 2-weeks, 3, 6, and 12-months after surgery, patients reported surgical area pain severity, impact of pain on cognitive/emotional and physical functioning, and pain catastrophizing. The ROPA clustering, which used patients’ preoperative anxiety, depression, somatization, and PPT scores, assigned patients to 3 groups: Adaptive (low psychosocial scores, high PPT), Pain Sensitive (moderate psychosocial scores, low PPT), and Global Symptoms (high psychosocial scores, moderate PPT). The Global Symptoms cluster, compared to other clusters, reported significantly worse persistent pain outcomes following surgery. Findings suggest that patient characteristic-based clustering algorithms, like ROPA, may generalize across diverse diagnoses and clinical settings, indicating the importance of “person type” in understanding pain variability.PerspectiveThis article presents the practical translation of a previously developed patient clustering solution, based within a chronic pain cohort, to a perioperative cohort of women undergoing breast cancer surgery. Such preoperative characterization could potentially help clinicians apply personalized interventions based on predictions concerning postsurgical pain.     

Pretreatment Psychoneurological Symptoms and Their Association With Longitudinal Cognitive Function and Quality of Life in Older Breast Cancer Survivors

Context

Symptoms affect quality of life (QOL), functional status, and cognitive function in cancer survivors, but older survivors are understudied.

Cancer-Related Symptom Clusters,Eosinophils, and Survival in Hepatobiliary Cancer: An Exploratory Study

ContextThe study of symptom clusters is gaining increased attention in the field of oncology in an attempt to improve the quality of life of patients diagnosed with cancer.ObjectivesThe aims of the present study were to 1) determine the prevalence and distribution of pain, fatigue, and symptoms of depression and their covariation as a cluster in people with hepatobiliary carcinoma (HBC), 2) characterize how variation in each individual symptom and/or their covariation as a cluster are associated with changes in immunity, and 3) determine if the symptom clusters, and associated biomarkers, are related to survival in people diagnosed with HBC.MethodsTwo hundred six participants diagnosed with HBC completed a battery of standardized questionnaires measuring cancer-related symptoms. Peripheral blood leukocytes were measured at diagnosis and at three- and six-month follow-ups. Survival was measured from the date of diagnosis to death.ResultsCancer-related symptoms were prevalent and two-step hierarchical cluster analyses yielded three symptom clusters. High levels of pain, fatigue, and depression were found to be associated with elevated eosinophil percentages (F[1,78] = 3.1, P = 0.05) at three- and six-month follow-up using repeated-measures analysis of variance. Using multivariate latent growth curve modeling, pain was the primary symptom associated with elevated eosinophil percentages between diagnosis and six months (z = 2.24, P = 0.05). Using Cox regression, vascular invasion and age were negatively associated with survival (Chi-square = 21.6, P = 0.03). While stratifying for vascular invasion, Kaplan-Meier survival analysis was performed, and eosinophil levels above the median for the sample were found to be related to increased survival in patients with and without vascular invasion (Breslow Chi-square = 4.9, P = 0.03). Symptom clusters did not mediate the relationship between eosinophils and survival.ConclusionCancer-related symptoms, particularly pain and depression, were associated with increased percentages of eosinophils. The presence of symptoms may reflect tumor cell death and be indicative of response to treatment, or other processes, in patients with HBC.     

Symptom priority and course of symptomatology in specialized palliative care

The study aim was to explore which symptoms/problems cancer patients in palliative care consider most distressing, and to investigate how prioritization at first contact was associated with patient-assessed symptom intensity and change in intensity over time. Initially, 175 patients named and prioritized their five most distressing symptoms. Weekly, they completed the following self-assessment questionnaires: European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-C30, Edmonton Symptom Assessment System, and the Hospital Anxiety and Depression Scale. Initial symptom intensity scores and weekly changes were calculated and compared with prioritization of the same symptom. Pain, fatigue, physical function, appetite, nausea/vomiting, dyspnea, and depression were the symptoms most often prioritized. Priority was associated with initial scoring of pain, appetite, nausea/vomiting, dyspnea, constipation, depression, and anxiety, but not with fatigue, physical function, role function, or inactivity. Priority was associated with change in symptom intensity for pain, reduced appetite, nausea/vomiting, and constipation. Symptom prioritization may be a useful guide to choice of treatment as well as to longitudinal symptom evaluation.     

Symptom clusters in women with relapsing-remitting multiple sclerosis

The purpose of this secondary analysis was to investigate the relationships among a set of symptoms (fatigue, depression, impaired cognitive function, sleep disturbance) with pain severity and demographic variables. The sample of 40 women with relapsing-remitting multiple sclerosis completed instruments of pain, fatigue, depression, sleep disturbance, and an objective cognitive measure. Analysis identified one symptom cluster of pain, fatigue, depression, sleep disturbance, and impaired cognitive function, whereas a relationship between that symptom cluster and employment status existed. Pain severity correlated with fatigue, sleep disturbance, depression, and impaired cognitive function. Preliminary findings support providing education on symptoms to women with relapsing-remitting multiple sclerosis to ultimately guide their care.     

Association Between Pretreatment Sleep Disturbance and Radiation Therapy-Induced Pain in 573 Women With Breast Cancer

ContextPain can be a debilitating side effect of radiation therapy (RT). Data from the general population have shown that sleep disturbance can influence pain incidence and severity; however, less is known about this relationship in patients with breast cancer receiving RT.ObjectivesThis secondary analysis examined the association of pretreatment moderate/severe levels of sleep disturbance with subsequent RT-induced pain after adjusting for pre-RT pain.MethodsWe report on 573 female patients with breast cancer undergoing RT from a previously completed Phase II clinical trial for radiation dermatitis. Sleep disturbance, total pain, and pain subdomains—sensory pain, affective pain, and perceived pain intensity were assessed at pre-RT and post-RT. At pre-RT, patients were dichotomized into two groups: those with moderate/severe sleep disturbance (N = 85) vs. those with no/mild sleep disturbance (control; N = 488).ResultsAt pre-RT, women with moderate/severe sleep disturbance were younger, less likely to be married, more likely to have had mastectomy and chemotherapy, and more likely to have depression/anxiety disorder and fatigue than the control group (all Ps < 0.05). Generalized estimating equations model, after controlling for pre-RT pain and other covariates (e.g., trial treatment condition and covariates that were significantly correlated with post-RT pain), showed that women with moderate/severe sleep disturbance at pre-RT vs. control group had significantly higher mean post-RT total pain as well as sensory, affective, and perceived pain (effect size = 0.62, 0.60, 0.69, and 0.52, respectively; all Ps < 0.05).ConclusionThese findings suggest that moderate/severe disturbed sleep before RT is associated with increased pain from pre-to-post-RT in patients with breast cancer.     

Symptom Clusters in Women With Breast Cancer During the First 18 Months of Adjuvant Therapy

ContextWomen with breast cancer treated with aromatase inhibitor (AI) therapy experience multiple concurrent symptoms or symptom clusters. Understanding of the symptom experience and identifying symptom clusters before and during AI therapy are important for the development of interventions to improve clinical outcomes.ObjectivesThe aim of this study was to identify symptom clusters experienced by women with breast cancer treated with AI therapy from pre–adjuvant therapy up to 18 months of adjuvant therapy using a broad scope of symptoms assessment.MethodsForty-seven symptoms were evaluated in postmenopausal women with breast cancer (N = 354) who received AI therapy or chemotherapy followed by AI therapy. Symptoms were assessed at four semiannual time points with the Breast Cancer Prevention Trial Symptom Checklist, Patient's Assessment of Own Functioning Inventory, Beck Depression Inventory-II, and Profile of Mood States Tension/Anxiety and Fatigue/Inertia subscales. Exploratory factor analyses were conducted at each time point to identify symptom clusters.ResultsFour stable symptom clusters (i.e., musculoskeletal, vasomotor, urinary, sexual) and three relatively stable symptom clusters (i.e., psychological, neurocognitive, weight) were identified across the 18-month follow-up period. The gastrointestinal symptom cluster only appeared at after six months of adjuvant therapy (postchemotherapy).ConclusionThis study helps us to better understand the most common symptom clusters over the first 18 months of adjuvant therapy among postmenopausal women with early-stage breast cancer. It is critical for health care providers to know the symptom clusters commonly experienced by women receiving AI therapy with or without chemotherapy and manage them properly over time.     

The Role of Inflammation in the Pain,Fatigue, and Sleep Disturbance Symptom Cluster in Advanced Cancer

Context

Symptom researchers have proposed a model of inflammatory cytokine activity and dysregulation in cancer to explain co-occurring symptoms including pain, fatigue, and sleep disturbance.

Symptom Interactions as Mechanisms Underlying Symptom Pairs and Clusters

PURPOSE: To present a summary of the potential shared or interactive mechanisms underlying an exemplar symptom pair: sleep disturbances and pain. ORGANIZING CONSTRUCT: Understanding of the multidimensional shared and interactive mechanisms underlying symptoms pairs and clusters has the potential to enhance symptom management. METHODS: Reviews of the literature were conducted to search for information on shared or interactive mechanisms underlying sleep disturbances and pain; minimal data were available. Relevant information about individual symptoms was outlined and categorized in areas often used to describe the multidimensional nature of symptoms, including the physiological, psychological, behavioral, and sociocultural domains. This information was examined for relationships and commonalities. CONCLUSIONS: Many potential shared and interactive mechanisms underlying the symptom pair of sleep disturbances and pain were identified. These results indicate the need for further work and theory development in this area. The symptom interactional framework is a beginning conceptual perspective designed to facilitate this work. Implications for interdisciplinary translational research designed to optimize symptom management are discussed.     

Are Psychological Predictors of Chronic Postsurgical Pain Dependent on the Surgical Model? A Comparison of Total Knee Arthroplasty and Breast Surgery for Cancer

Anxiety, depression, and catastrophizing are generally considered to be predictive of chronic postoperative pain, but this may not be the case after all types of surgery, raising the possibility that the results depend on the surgical model. We assessed the predictive value of these factors for chronic postsurgical pain in 2 different surgical models: total knee arthroplasty for osteoarthritis (89 patients, 65% women, age = 69 ± 9 years, baseline pain intensity = 4.7 ± 2.1) and breast surgery for cancer (100 patients, 100% women, age = 55 ± 12 years, no preoperative pain). Data were collected before surgery, then 2 days and 3 months after surgery. Anxiety, depression, and catastrophizing were measured with the Spielberger State-Trait Anxiety Inventory, Beck Depression Inventory, and Pain Catastrophizing Scale, respectively. Pain was assessed with the Brief Pain Inventory. Neuropathic pain was detected with the DN4 questionnaire. Multivariate logistic regression analyses for the total knee arthroplasty and breast surgery models considered together indicated that the presence of clinically meaningful chronic pain at 3 months (pain intensity ≥3/10) was predicted independently by age (P = .04), pain intensity on day 2 (P = .009), and state anxiety (P = .001). Linear regression models also showed that pain magnification, one of the dimensions of catastrophizing, independently predicted chronic pain intensity (P = .04). These results were not affected by the surgical model or by the neuropathic characteristics of the pain. Thus, state anxiety and pain magnification seem to constitute psychological risk factors for chronic postsurgical pain relevant in all surgical models.PerspectiveThis prospective study performed in patients with total knee arthroplasty or breast surgery for cancer shows that state anxiety, amplification of pain, and acute postoperative pain independently predict postsurgical pain at 3 months and that this does not depend on the surgical model.     

Mind-Body Treatments for the Pain-Fatigue-Sleep Disturbance Symptom Cluster in Persons with Cancer

ContextCo-occurring pain, fatigue, and sleep disturbance comprise a common symptom cluster in patients with cancer. Treatment approaches that target the cluster of symptoms rather than just a single symptom need to be identified and tested.ObjectivesTo synthesize evidence regarding mind-body interventions that have shown efficacy in treating two or more symptoms in the pain-fatigue-sleep disturbance cancer symptom cluster.MethodsA literature search was conducted using CINAHL, Medline, and PsychInfo databases through March 2009. Studies were categorized based on the type of mind-body intervention (relaxation, imagery/hypnosis, cognitive-behavioral therapy/coping skills training [CBT/CST], meditation, music, and virtual reality), and a preliminary review was conducted with respect to efficacy for pain, fatigue, and sleep disturbance. Mind-body interventions were selected for review if there was evidence of efficacy for at least two of the three symptoms. Forty-three studies addressing five types of mind-body interventions met criteria and are summarized in this review.ResultsImagery/hypnosis and CBT/CST interventions have produced improvement in all the three cancer-related symptoms individually: pain, fatigue, and sleep disturbance. Relaxation has resulted in improvements in pain and sleep disturbance. Meditation interventions have demonstrated beneficial effects on fatigue and sleep disturbance. Music interventions have demonstrated efficacy for pain and fatigue. No trials were found that tested the mind-body interventions specifically for the pain-fatigue-sleep disturbance symptom cluster.ConclusionEfficacy studies are needed to test the impact of relaxation, imagery/hypnosis, CBT/CST, meditation, and music interventions in persons with cancer experiencing concurrent pain, fatigue, and sleep disturbance. These mind-body interventions could help patients manage all the symptoms in the cluster with a single treatment strategy.