An overview of proceedings, findings, and recommendations from the workshop on "Advancing Symptom Science Through Symptom Cluster Research" sponsored by the National Institute of Nursing Research (NINR) and the Office of Rare Diseases Research, National Center for Advancing Translational Sciences, is presented. This workshop engaged an expert panel in an evidenced-based discussion regarding the state of the science of symptom clusters in chronic conditions including cancer and other rare diseases. An interdisciplinary working group from the extramural research community representing nursing, medicine, oncology, psychology, and bioinformatics was convened at the National Institutes of Health. Based on expertise, members were divided into teams to address key areas: defining characteristics of symptom clusters, priority symptom clusters and underlying mechanisms, measurement issues, targeted interventions, and new analytic strategies. For each area, the evidence was synthesized, limitations and gaps identified, and recommendations for future research delineated. The majority of findings in each area were from studies of oncology patients. However, increasing evidence suggests that symptom clusters occur in patients with other chronic conditions (eg, pulmonary, cardiac, and end-stage renal disease). Nonetheless, symptom cluster research is extremely limited and scientists are just beginning to understand how to investigate symptom clusters by developing frameworks and new methods and approaches. With a focus on personalized care, an understanding of individual susceptibility to symptoms and whether a "driving" symptom exists that triggers other symptoms in the cluster is needed. Also, research aimed at identifying the mechanisms that underlie symptom clusters is essential to developing targeted interventions.Patients with chronic conditions, such as cancer and other rare diseases, experience an array of multiple co-occurring symptoms (eg, pain, fatigue, sleep disturbance). When these symptoms remain underdiagnosed and undertreated, they have a negative impact on patient-reported outcomes (PROs) including functional performance, cognitive status, and quality of life (QOL). A reduction in symptom burden in these patients has the potential to improve their capacity to live well over their entire lives. To achieve this goal, a transformation is needed in how multiple co-occurring symptoms are assessed and managed in order to improve patient outcomes and stimulate a reduction in health care utilization and costs. A strategic plan that advances REVIEW

This report summarizes findings related to the psychometric properties (internal consistency and construct validity) of the Pittsburgh Sleep Quality Index (PSQI) and discusses issues related to its use based on data from two clinical studies with diverse samples of cancer patients. Subjects completed a questionnaire that included the PSQI, the Schwartz Cancer Fatigue Scale, and specific demographic, disease, and treatment variables. There were complete data on 170 (of 214) cases in Study 1 and 249 (of 259) cases in Study 2. The Cronbach's alpha for the Global Sleep Quality scale was 0.81 in Study 1 and 0.77 in Study 2 A comparison of Global Sleep Quality in two contrasting groups with low and high fatigue yielded statistically significant differences in both samples. Psychometric evaluation supports its internal consistency reliability and construct validity. However, the scoring is rather cumbersome and raises questions regarding level of measurement and appropriate analysis techniques.

All patients and caregivers need initial and ongoing screening for sleep/wake disturbances. When disturbed sleep/wakefulness is evident, further assessment and treatment are warranted. Nursing educational programs should include content regarding healthy and disrupted sleep/wake patterns. Research on sleep/wake disturbances in people with cancer should have high priority.

Abstract:Cancer patients may experience multiple concurrent symptoms caused by the cancer, cancer treatment, or their combination. The complex relationships between and among symptoms, as well as the clinical antecedents and consequences, have not been well described. This paper examines the literature on cancer symptom clusters focusing on the conceptualization, design, measurement, and analytic issues. The investigation of symptom clustering is in an early stage of testing empirically whether the characteristics defined in the conceptual definition can be observed in cancer patients. Decisions related to study design include sample selection, the timing of symptom measures, and the characteristics of symptom interventions. For self-report symptom measures, decisions include symptom dimensions to evaluate, methods of scaling symptoms, and the time frame of responses. Analytic decisions may focus on the application of factor analysis, cluster analysis, and path models. Studying the complex symptoms of oncology patients will yield increased understanding of the patterns of association, interaction, and synergy of symptoms that produce specific clinical outcomes. It will also provide a scientific basis and new directions for clinical assessment and intervention. Key Words: Symptoms, symptom clusters, symptom management, quality of life Article: INTRODUCTION Typical symptoms associated with cancer and its treatment include fatigue, nausea-vomiting, pain, depression, and difficulty sleeping. In cancer care, these symptoms can be caused by cancer, cancer treatment, or the combination of cancer and cancer treatment. Despite the knowledge that individuals undergoing cancer therapy are likely to experience multiple concurrent symptoms, most research on symptoms in cancer has examined individual symptoms.1 The relationship between and among cancer symptoms and the impact on quality of life have not been evaluated systematically. The purpose of this paper is to examine critical research issues related to the conceptualization, design, measurement, and analysis of multiple concurrent symptoms or symptom clusters in oncology. The Concept of a Symptom ClusterRecently, Dodd et al .2 called for consideration of the "symptom cluster" in oncology research to capture the complexity of the cancer symptom experience. The term "symptom cluster" has not

With advances in treatment, colorectal cancer is being transformed from a deadly disease to an illness that is increasingly curable. With this transformation has come increased interest in the unique problems, risks, needs, and concerns of survivors who have completed treatment and are cancer-free. Research has shown that physical and mental quality of life for colorectal cancer survivors was inferior when compared with age-matched individuals without cancer. Although issues and symptoms were most prominent during the first three years, long-term effects of treatment can persist and include fatigue, sleep difficulty, fear of recurrence, anxiety, depression, negative body image, sensory neuropathy, gastrointestinal problems, urinary incontinence, and sexual dysfunction. The unique challenges and issues of colorectal cancer survivors can and should be addressed by health care providers and the research community to ensure effective interventions and models of care to manage these problems. In this review, we discuss what is known about the long-term effects of colorectal cancer treatment on quality of life, the care of survivors, and existing models of survivorship care.

OBJECTIVE The purpose of this trial was to compare usual patient education plus the Internet-based, Personal Patient Profile-Prostate, versus usual education alone, on conflict associated with decision making, plus explore time-to-treatment and treatment choice. METHODS A randomized, multi-center clinical trial was conducted with measures at baseline, one and six months. Men with newly diagnosed localized prostate cancer who sought consultation at urology, radiation oncology or multi-disciplinary clinics in four geographically-distinct American cities were recruited. Intervention group participants used the Personal Patient Profile-Prostate, a decision support system comprised of customized text and video coaching regarding potential outcomes, influential factors, and communication with care providers. The primary outcome, patient-reported decisional conflict, was evaluated over time using Generalized Estimating Equations to fit generalized linear models. Additional outcomes, time-to-treatment, treatment choice and program acceptability/usefulness, were explored. RESULTS A total of 494 eligible men were randomized (266 intervention; 228 control). The intervention reduced adjusted decisional conflict over time as compared with the control group, for the uncertainty score (estimate −3.61; (confidence interval, −7.01,−0.22) and values clarity (estimate −3.57; confidence interval (−5.85,−1.30) Borderline effect was seen for the total decisional conflict score (estimate −1.75; confidence interval (−3.61,0.11). Time-to-treatment was comparable between groups, while undecided men in the intervention group chose brachytherapy more often than in the control group. Acceptability and usefulness were highly rated. CONCLUSION The Personal Patient Profile-Prostate is the first intervention to significantly reduce decisional conflict in a multi-center trial of American men with newly diagnosed localized prostate cancer. Our findings support efficacy of P3P for addressing decision uncertainty and facilitating patient selection of a prostate cancer treatment that is consistent with the patient values and preferences.

The results of the study provide researchers and clinicians with detailed comparisons of the performance of established fatigue measures in cancer patients undergoing treatment to use when selecting measures of CRF.

This information can be used by researchers and clinicians to guide the selection of symptom management strategies that are ideally targeted to the biological mechanisms that underlie this symptom cluster.