Future Directions in Symptom Cluster Research

Physical Activity Intensity is Associated with Symptom Distress in the CNICS Cohort

Symptom distress remains a challenging aspect of living with HIV. Physical activity is a promising symptom management strategy, but its effect on symptom distress has not been examined in a large, longitudinal HIV-infected cohort. We hypothesized that higher physical activity intensity would be associated with reduced symptom distress. We included 5370 people living with HIV (PLHIV) who completed patient-reported assessments of symptom distress, physical activity, alcohol and substance use, and HIV medication adherence between 2005 and 2016. The most frequent and burdensome symptoms were fatigue (reported by 56%), insomnia (50%), pain (46%), sadness (45%), and anxiety (45%), with women experiencing more symptoms and more burdensome symptoms than men. After adjusting for age, sex, race, time, HIV medication adherence, alcohol and substance use, site, and HIV RNA, greater physical activity intensity was associated with lower symptom intensity. Although individual symptoms may be a barrier to physical activity (e.g. pain), the consistent association between symptoms with physical activity suggests that more intense physical activity could mitigate symptoms experienced by PLHIV.

Network Analysis of the Multidimensional Symptom Experience of Oncology

Oncology patients undergoing cancer treatment experience an average of fifteen unrelieved symptoms that are highly variable in both their severity and distress. Recent advances in Network Analysis (NA) provide a novel approach to gain insights into the complex nature of co-occurring symptoms and symptom clusters and identify core symptoms. We present findings from the first study that used NA to examine the relationships among 38 common symptoms in a large sample of oncology patients undergoing chemotherapy. Using two different models of Pairwise Markov Random Fields (PMRF), we examined the nature and structure of interactions for three different dimensions of patients’ symptom experience (i.e., occurrence, severity, distress). Findings from this study provide the first direct evidence that the connections between and among symptoms differ depending on the symptom dimension used to create the network. Based on an evaluation of the centrality indices, nausea appears to be a structurally important node in all three networks. Our findings can be used to guide the development of symptom management interventions based on the identification of core symptoms and symptom clusters within a network.

Is emotion regulation associated with cancer-related psychological symptoms?

OBJECTIVES

This study examined the cross-sectional and prospective relationships between subjective (cognitive reappraisal, expressive suppression and experiential avoidance) and objective (high-frequency heart rate variability [HF-HRV]) measures of emotion regulation (ER) and a set of psychological symptoms (anxiety, depression, fear of cancer recurrence [FCR], insomnia, fatigue, pain, and cognitive impairments) among women receiving radiation therapy for non-metastatic breast cancer.

DESIGN

Eighty-one participants completed a battery of self-report scales within 10 days before the start of radiotherapy (T1) and within 10 days after its end (T2; approximately 6 weeks after T1). HF-HRV at rest was measured at T1.

RESULTS

Canonical correlation analyses revealed that higher levels of experiential avoidance and expressive suppression were cross-sectionally associated with higher levels of all symptoms, except pain, at T1 and at T2 (both p's < 0.0001). Higher levels of suppression and reappraisal at T1 were marginally associated with reduced FCR and with increased depression and fatigue between T1 and T2 (p = 0.07). HF-HRV was not associated with symptoms cross-sectionally or prospectively.

CONCLUSIONS

Although preliminary, these results are consistent with the hypothesis that maladaptive ER strategies, assessed subjectively, may cross-sectionally act as a transdiagnostic mechanism underlying several cancer-related psychological symptoms.

Symptom Cluster Science in Chronic Kidney Disease: A Literature Review

The purpose of this review was to synthesize evidence on symptom clusters in patients with chronic kidney disease (CKD). The quality of studies was evaluated using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Twelve articles met inclusion criteria. Patients had CKD ranging from Stages 2 through 5. Most studies determined clusters using variable-centered approaches based on symptoms; however, one used a person-centered approach based on demographic and clinical characteristics. The number of clusters identified ranged from two to five. Several clusters were prominent across studies including symptom dimensions of fatigue/energy/sleep, neuromuscular/pain, gastrointestinal, skin, and uremia; however, individual symptoms assigned to clusters varied widely. Several clusters correlated with patient outcomes, including health-related quality of life and mortality. Identifying symptom clusters in CKD is a nascent field, and more research is needed on symptom measures and statistical methods for clustering. The clinical implications of symptom clusters remain unclear.

Misery Loves Company: Presenting Symptom Clusters to Urgent Care by Patients Receiving Antineoplastic Therapy

PURPOSE

The Centers for Medicare & Medicaid Services (CMS) identifies suboptimal management of treatment toxicities as a care gap and proposes the measurement of hospital performance on the basis of emergency department visits for 10 common symptoms. Current management strategies do not address symptom co-occurrence.

METHODS

We evaluated symptom co-occurrence in three patient cohorts that presented to a cancer hospital urgent care center in 2016. We examined both the CMS-identified symptoms and an expanded clinician-identified set defined as symptoms that could be safely managed in the outpatient setting if identified early and managed proactively. The cohorts included patients who presented with a CMS-defined symptom within 30 days of treatment, patients who presented within 30 days of treatment with a symptom from the expanded set, and patients who presented with a symptom from the expanded set within 30 days of treatment start. Symptom co-occurrence was measured by Jaccard index. A community detection algorithm was used to identify symptom clusters on the basis of a random walk process, and network visualizations were used to illustrate symptom dynamics.

RESULTS

There were 6,429 presentations in the CMS symptom-defined cohort. The network analysis identified two distinct symptom clusters centered around pain and fever. In the expanded symptom cohort, there were 5,731 visits and six symptom clusters centered around fever, emesis/nausea, fatigue, deep vein thrombosis, pain, and ascites. For patients who newly initiated treatment, there were 1,154 visits and four symptom clusters centered around fever, nausea/emesis, fatigue, and deep vein thrombosis.

CONCLUSION

Uncontrolled symptoms are associated with unplanned acute care. Recognition of the complexity of symptom co-occurrence can drive improved management strategies.

Biomarkers as Common Data Elements for Symptom and Self-Management Science

PURPOSE

Biomarkers as common data elements (CDEs) are important for the characterization of biobehavioral symptoms given that once a biologic moderator or mediator is identified, biologically based strategies can be investigated for treatment efforts. Just as a symptom inventory reflects a symptom experience, a biomarker is an indicator of the symptom, though not the symptom per se. The purposes of this position paper are to (a) identify a "minimum set" of biomarkers for consideration as CDEs in symptom and self-management science, specifically biochemical biomarkers; (b) evaluate the benefits and limitations of such a limited array of biomarkers with implications for symptom science; (c) propose a strategy for the collection of the endorsed minimum set of biologic samples to be employed as CDEs for symptom science; and (d) conceptualize this minimum set of biomarkers consistent with National Institute of Nursing Research (NINR) symptoms of fatigue, depression, cognition, pain, and sleep disturbance.

DESIGN AND METHODS

From May 2016 through January 2017, a working group consisting of a subset of the Directors of the NINR Centers of Excellence funded by P20 or P30 mechanisms and NINR staff met bimonthly via telephone to develop this position paper suggesting the addition of biomarkers as CDEs. The full group of Directors reviewed drafts, provided critiques and suggestions, recommended the minimum set of biomarkers, and approved the completed document. Best practices for selecting, identifying, and using biological CDEs as well as challenges to the use of biological CDEs for symptom and self-management science are described. Current platforms for sample outcome sharing are presented. Finally, biological CDEs for symptom and self-management science are proposed along with implications for future research and use of CDEs in these areas.

FINDINGS

The recommended minimum set of biomarker CDEs include pro- and anti-inflammatory cytokines, a hypothalamic-pituitary-adrenal axis marker, cortisol, the neuropeptide brain-derived neurotrophic factor, and DNA polymorphisms.

CONCLUSIONS

It is anticipated that this minimum set of biomarker CDEs will be refined as knowledge regarding biologic mechanisms underlying symptom and self-management science further develop. The incorporation of biological CDEs may provide insights into mechanisms of symptoms, effectiveness of proposed interventions, and applicability of chosen theoretical frameworks. Similarly, as for the previously suggested NINR CDEs for behavioral symptoms and self-management of chronic conditions, biological CDEs offer the potential for collaborative efforts that will strengthen symptom and self-management science.

CLINICAL RELEVANCE

The use of biomarker CDEs in biobehavioral symptoms research will facilitate the reproducibility and generalizability of research findings and benefit symptom and self-management science.

Congruence Between Latent Class and K-Modes Analyses in the Identification of Oncology Patients With Distinct Symptom Experiences

CONTEXT

Risk profiling of oncology patients based on their symptom experience assists clinicians to provide more personalized symptom management interventions. Recent findings suggest that oncology patients with distinct symptom profiles can be identified using a variety of analytic methods.

OBJECTIVES

The objective of this study was to evaluate the concordance between the number and types of subgroups of patients with distinct symptom profiles using latent class analysis and K-modes analysis.

METHODS

Using data on the occurrence of 25 symptoms from the Memorial Symptom Assessment Scale, that 1329 patients completed prior to their next dose of chemotherapy (CTX), Cohen's kappa coefficient was used to evaluate for concordance between the two analytic methods. For both latent class analysis and K-modes, differences among the subgroups in demographic, clinical, and symptom characteristics, as well as quality of life outcomes were determined using parametric and nonparametric statistics.

RESULTS

Using both analytic methods, four subgroups of patients with distinct symptom profiles were identified (i.e., all low, moderate physical and lower psychological, moderate physical and higher Psychological, and all high). The percent agreement between the two methods was 75.32%, which suggests a moderate level of agreement. In both analyses, patients in the all high group were significantly younger and had a higher comorbidity profile, worse Memorial Symptom Assessment Scale subscale scores, and poorer QOL outcomes.

CONCLUSION

Both analytic methods can be used to identify subgroups of oncology patients with distinct symptom profiles. Additional research is needed to determine which analytic methods and which dimension of the symptom experience provide the most sensitive and specific risk profiles.

Stability of Symptom Clusters in Patients With Breast Cancer Receiving Chemotherapy

CONTEXT

Patients with breast cancer who undergo chemotherapy (CTX) experience between 10 and 32 concurrent symptoms. An evaluation of how these symptoms cluster together and how these symptom clusters change over time may provide insights into how to treat these multiple co-occurring symptoms.

OBJECTIVES

The purposes of this study were to determine the occurrence rates and severity ratings for 38 common symptoms, evaluate for differences in the number and types of symptom clusters, and evaluate for changes over time in these symptom clusters (i.e., before CTX, the week after CTX, and two weeks after CTX).

METHODS

At each of the assessments, a modified version of the Memorial Symptom Assessment Scale was used to assess the occurrence and severity of the 38 symptoms. Exploratory factor analyses were used to extract the symptom clusters.

RESULTS

Although across the two symptom dimensions (i.e., occurrence and severity) and the three assessments, eight distinct symptom clusters were identified, only five were relatively stable across both dimensions and across time (i.e., psychological, hormonal, nutritional, gastrointestinal, and epithelial). Two of the additional clusters varied by time but not by symptom dimension (i.e., sickness behavior and weight change). The CTX neuropathy cluster was identified only at the assessment performed in the week after CTX.

CONCLUSION

These findings provide insights into the most common symptom clusters in patients undergoing CTX for breast cancer. In addition, the most common symptoms within each cluster appear to be relatively stable across the two dimensions, as well as across time.

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.

Cytokine Gene Polymorphisms Associated With Symptom Clusters in Oncology Patients Undergoing Radiation Therapy

CONTEXT

Most of the reviews on the biological basis for symptom clusters suggest that inflammatory processes are involved in the development and maintenance of the symptom clusters. However, no studies have evaluated for associations between genetic polymorphisms and common symptom clusters (e.g., mood disturbance, sickness behavior).

OBJECTIVES

Examine the associations between cytokine gene polymorphisms and the severity of three distinct symptom clusters (i.e., mood-cognitive, sickness-behavior, treatment-related) in a sample of patients with breast and prostate cancer (n = 157) at the completion of radiation therapy.

METHODS

Symptom severity was assessed using the Memorial Symptom Assessment Scale. Symptom clusters were created using exploratory factor analysis. The associations between cytokine gene polymorphisms and the symptom cluster severity scores were evaluated using regression analyses.

RESULTS

Polymorphisms in C-X-C motif chemokine ligand 8 (CXCL8), interleukin (IL13), and nuclear factor kappa beta 2 (NFKB2) were associated with severity scores for the mood-cognitive symptom cluster. In addition to interferon gamma (IFNG1), the same polymorphism in NFKB2 (i.e., rs1056890) that was associated with the mood-cognitive symptom cluster score was associated with the sickness-behavior symptom cluster. Polymorphisms in interleukin 1 receptor 1 (IL1R1), IL6, and NFKB1 were associated with severity factor scores for the treatment-related symptom cluster.

CONCLUSION

Our findings support the hypotheses that symptoms that cluster together have a common underlying mechanism and the most common symptom clusters in oncology patients are associated polymorphisms in genes involved in a variety of inflammatory processes.

Differences in Symptom Clusters Identified Using Ratings of Symptom Occurrence vs. Severity in Lung Cancer Patients Receiving Chemotherapy

CONTEXT

An important question in symptom clusters research is whether the number and types of symptom clusters vary based on the specific dimension of the symptom experience used to create the clusters.

OBJECTIVES

Given that lung cancer patients undergoing chemotherapy (CTX) report an average of 14 co-occurring symptoms and studies of symptom clusters in these patients are limited, the purpose of this study, in lung cancer patients undergoing CTX (n = 145), was to identify whether the number and types of symptom clusters differed based on whether symptom occurrence rates or symptom severity ratings were used to create the clusters.

METHODS

A modified version of the Memorial Symptom Assessment Scale was used to assess for the occurrence and severity of 38 symptoms, one week after the administration of CTX. Exploratory factor analysis was used to extract the symptom clusters.

RESULTS

Both the number and types of symptom clusters were relatively similar using symptom occurrence rates or symptom severity ratings. Five symptom clusters were identified using both symptom occurrence rates and severity ratings (i.e., sickness behavior, lung cancer specific, psychological, nutritional, and epithelial). Across these two dimensions, the specific symptoms within each of the symptom clusters were relatively similar.

CONCLUSIONS

Identification of symptom clusters in patients with lung cancer may assist with the development of more targeted symptom management interventions. Future studies are warranted to determine if symptom clusters change over a cycle of CTX in patients with lung cancer.

Symptom Trajectories in Children Receiving Treatment for Leukemia: A Latent Class Growth Analysis With Multitrajectory Modeling

CONTEXT

Cancer treatment symptoms play a major role in determining the health of children with cancer. Symptom toxicity often results in complications, treatment delays, and therapy dose reductions that can compromise leukemia therapy and jeopardize chances for long-term survival. Critical to understanding symptom experiences during treatment is the need for exploration of "why" inter-individual symptom differences occur; this will determine who may be most susceptible to treatment toxicities.

OBJECTIVES

This study examined specific symptom trajectories during the first 18 months of childhood leukemia treatment. Symptom measures included fatigue, sleep disturbances, pain, nausea, and depression.

METHODS

Symptom trajectories of 236 children with leukemia three to 18 years old were explored prospectively over four periods: initiation of post-induction therapy, four and eight post-induction therapy, and the last time point was at the beginning of maintenance/continuation therapy. Latent class growth analysis was used to classify patients into distinctive groups with similar symptom trajectories based on patients' response patterns on the symptom measures over time.

RESULTS

Three latent classes of symptom trajectories were identified and classified into mild, moderate, and severe symptom trajectories. The only demographic characteristic with a significant relationship to membership in the latent class symptom trajectories was race/ethnicity. All other demographic characteristics including leukemia risk levels showed no significant relationships.

CONCLUSION

This study is unique in that groups of patients with similar symptoms were identified rather than groups of symptoms. Further research using latent class growth analysis is needed.

Differences in symptom clusters identified using symptom occurrence rates versus severity ratings in patients with breast cancer undergoing chemotherapy

PURPOSE

One of the unanswered questions in symptom clusters research is whether the number and types of symptom clusters vary based on the dimension of the symptom experience used to create the clusters. Given that patients with breast cancer receiving chemotherapy (CTX), report between 10 and 32 concurrent symptoms and studies of symptom clusters in these patients are limited, the purpose of this study, in breast cancer patients undergoing CTX (n = 515), was to identify whether the number and types of symptom clusters differed based on whether symptom occurrence rates or symptom severity ratings were used to create the clusters.

METHODS

A modified version of the Memorial Symptom Assessment Scale was used to assess for the occurrence and severity of 38 symptoms, one week after the administration of CTX. Exploratory factor analysis was used to extract the symptom clusters.

RESULTS

Both the number and types of symptom clusters were similar using symptom occurrence rates or symptom severity ratings. Five symptom clusters were identified using symptom occurrence rates (i.e., psychological, hormonal, nutritional, gastrointestinal, epithelial). Six symptom clusters (i.e., psychological, hormonal, nutritional, gastrointestinal, epithelial, chemotherapy neuropathy) were identified using symptom severity ratings. Across the two dimensions, the specific symptoms within each of the symptom clusters were similar.

CONCLUSIONS

Identification of symptom clusters in patients with breast cancer may be useful in guiding symptom management interventions. Future studies are warranted to determine if symptom clusters remain stable over a cycle of CTX in patients with breast cancer.