Advancing Symptom Science Through Symptom Cluster Research: Expert Panel Proceedings and Recommendations

Laser interstitial thermal therapy as an adjunct therapy in brain tumors: A meta-analysis and comparison with stereotactic radiotherapy

BACKGROUND

Minimally invasive procedures are gaining widespread acceptance in difficult-to-access brain tumor treatment. Stereotactic radiosurgery (SRS) is the preferred choice, however, laser interstitial thermal therapy (LITT) has emerged as a tumor cytoreduction technique. The present meta-analysis compared current SRS therapy with LITT in brain tumors.

METHODS

A search was performed in Lilacs, PubMed, and Cochrane database. Patient's demographics, tumor location, therapy used, Karnofsky performance status score before treatment, and patient's outcome (median overall survival, progression-free survival, and adverse events) data were extracted from studies. The risk of bias was assessed by Cochrane collaboration tool.

RESULTS

Twenty-five studies were included in this meta-analysis. LITT and SRS MOS in brain metastasis patients were 12.8 months' versus 9.8 months (ranges 9.3-16.3 and 8.3-9.8; P = 0.02), respectively. In a combined comparison of adverse effects among LITT versus SRS in brain metastasis, we found 15% reduction in absolute risk difference (-0.16; 95% confidence interval P < 0.0001).

CONCLUSION

We could not state that LITT treatment is an optimal alternative therapy for difficult-to-access brain tumors due to the lack of systematic data that were reported in our pooled studies. However, our results identified a positive effect in lowering the absolute risk of adverse events compared with SRS therapy. Therefore, randomized trials are encouraged to ascertain LITT role, as upfront or postoperative/post-SRS therapy for brain tumor treatment.

Systematic Review of the Kynurenine Pathway and Psychoneurological Symptoms Among Adult Cancer Survivors

The co-occurrence of multiple psychoneurological symptoms, including pain, sleep disturbance, fatigue, depression, anxiety, and cognitive disturbance among adult cancer survivors led us to question which common biological mechanisms are shared among these conditions. Variances in tryptophan (Trp) levels and downstream metabolites of the kynurenine (Kyn) metabolic pathway are known to affect immune response and psychoneurological symptoms. The objective of this systematic review was to help us (a) better understand the role of the Kyn pathway in psychoneurological symptoms among adult cancer survivors and (b) identify common significant biomarkers across psychoneurological symptoms as a guide for future research. Some evidence has shown that decreased Trp levels and increased Kyn, Trp/Kyn ratio, and kynurenic acid/Trp ratio in parallel with immune activation are correlated with some psychoneurological symptoms among people undergoing cancer treatment, although discrepancies exist between studies. Kyn pathway activation could also be associated with psychoneurological symptoms among adult cancer survivors, but further research is needed to confirm its exact etiological role with respect to psychoneurological symptoms.

Pain, fatigue and depression symptom cluster in survivors of prostate cancer

PURPOSE

Pain, fatigue and depression are common sequelae of a cancer diagnosis. The extent to which these occur together in prostate cancer survivors is unknown. We (i) investigated prevalence of the pain-fatigue-depression symptom cluster and (ii) identified factors associated with experiencing the symptom cluster among prostate cancer survivors.

METHODS

Men in Ireland diagnosed with prostate cancer 2-18 years previously were identified from population-based cancer registries and sent postal questionnaires. Cancer-related pain and fatigue were measured using the EORTC QLQ-C30 and depression using the DASS-21. Cut-offs to define 'caseness' were pain ≥ 25, fatigue ≥ 39 and depression ≥ 10. Associations between survivor-related factors, clinical variables and specific prostate cancer physical symptoms and the symptom cluster were assessed using multivariate logistic regression.

RESULTS

A total of 3348 men participated (response rate = 54%). Twenty-four percent had clinically significant pain, 19.7% had clinically significant fatigue, and 14.4% had depression; 7.3% had all three symptoms. In multivariate analysis, factors significantly associated with the symptom cluster were living in Northern Ireland, experiencing back pain at diagnosis and being affected by incontinence, loss of sexual desire, bowel problems, gynecomastia and hot flashes post-treatment. There was a strong association between the cluster and health-related quality of life.

CONCLUSIONS

The pain-fatigue-depression symptom cluster is present in 1 in 13 prostate cancer survivors. Physical after-effects of prostate cancer treatment are associated with this cluster. More attention should be paid to identifying and supporting survivors who experience multiple symptoms; this may help health-related quality of life improve among the growing population of prostate cancer survivors.

Symptom clusters in head and neck cancer patients with endotracheal tube: Which symptom clusters are independently associated with health-related quality of life?

PURPOSE

The point of view of symptom clusters (SCs) may develop an efficient symptom management strategy to enhance health-related quality of life (HRQoL) in head and neck (HNC) patients with endotracheal tube (ETT). The study aims to investigate the possible SCs in HNC patients with ETT and determine whether there was an independent relationship between one or more SCs and HRQoL.

METHODS

A cross-sectional study design was adopted, and 203 HNC patients with ETT were recruited. They took measurements of General Information Questionnaire, MD Anderson Symptom Inventory-Head & Neck, and Twelve-Item Short-Form Health Survey (SF-12). Spearman correlations, partial correlations, and hierarchical cluster analysis were performed to determine latent number of SCs, and covariance analyses were used to determine independent associations between SCs and SF-12. This study followed STROBE Statement.

RESULTS

Pain SCs (pain, distressed, short of breath, and sadness), fatigue SCs (fatigue/weakness, restless, and sleepy), digestive SCs (appetite loss, constipation, and nausea), HNC-specific SCs (dry mouth and mucus), and tracheostomy-related SCs (difficulty swallowing and difficulty with voice and speech) were found. After adjusting covariant variables, this study found independent relationships of pain SCs and fatigue SCs with physical component summary of SF-12, and between fatigue SCs and mental component summary of SF-12.

CONCLUSIONS

Multiple SCs were found in those HNC patients. Pain SCs and fatigue SCs were independently associated with HRQoL. In process of caring HNC patients with ETT, it is vital to focus on SCs, especially on pain SCs and fatigue SCs, which might effectively improve patients' HRQoL.

Gut Microbiome Associated with the Psychoneurological Symptom Cluster in Patients with Head and Neck Cancers

Cancer patients experience a cluster of co-occurring psychoneurological symptoms (PNS) related to cancer treatments. The gut microbiome may affect severity of the PNS via neural, immune, and endocrine signaling pathways. However, the link between the gut microbiome and PNS has not been well investigated in cancer patients, including those with head and neck cancers (HNCs). This pilot study enrolled 13 patients with HNCs, who reported PNS using the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (CTCAEs). Stool specimens were collected to analyze patients' gut microbiome. All data were collected pre- and post-radiation therapy (RT). Associations between the bacterial abundances and the PNS clusters were analyzed using the linear discriminant analysis effect size; functional pathway analyses of 16S rRNA V3-V4 bacterial communities were conducted using Tax4fun. The high PNS cluster had a greater decrease in microbial evenness than the low PNS cluster from pre- to post-RT. The high and low PNS clusters showed significant differences using weighted UniFrac distance. Those individuals with the high PNS cluster were more likely to have higher abundances in phylum Bacteroidetes, order Bacteroidales, class Bacteroidia, and four genera (Ruminiclostridium9, Tyzzerella, Eubacterium_fissicatena, and DTU089), while the low PNS cluster had higher abundances in family Acidaminococcaceae and three genera (Lactococcus, Phascolarctobacterium, and Desulfovibrio). Both glycan metabolism (Lipopolysaccharide biosynthesis) and vitamin metabolism (folate biosynthesis and lipoic acid metabolism) were significantly different between the high and low PNS clusters pre- and post-RT. Our preliminary data suggest that the diversity and abundance of the gut microbiome play a potential role in developing PNS among cancer patients.

Symptom clusters in hospitalized older adults: Characteristics and outcomes

Hospital care in medical patients relies mostly on objective measures with limited assessment of subjective symptoms. We subgrouped 331 hospitalized older adults with medical diagnosis (age 75.5 ± 7.1) according to the severity of multiple symptoms to explore if these subgroups differed in health-related characteristics on admission and functional outcomes one month post-discharge. Cluster analysis identified three subgroups based on experiences with five highly distressing symptoms (fatigue, dyspnea, dizziness, sleep disturbance, pain): low levels of all symptoms, high levels of all symptoms; moderate levels of four symptoms with high dyspnea. Belonging in different subgroups was accompanied by different levels of cognitive and mental, but not physical or health status. Patients in the subgroup "Moderate Levels with High Dyspnea" had significantly lower risk of decline in post-discharge instrumental activities of daily living than other subgroups. Better understanding of older hospitalized adults' symptom profiles may yield important information on health condition and recovery.

Clinical Symptom Profiles After Mild-Moderate Stroke

Background

There is heterogeneity in the severity of domains affected in patients with stroke, resulting in differences in health‐related quality of life (hrQoL). Identifying different clinical profiles of stroke patients may provide a means for selecting patients for tailored interventions to improve hrQoL.

Methods and Results

This was an observational study of 496 patients with ischemic stroke or intracerebral hemorrhage seen in a cerebrovascular clinic from October 12, 2015, through June 11, 2018, who completed patient‐reported outcome measures using Patient‐Reported Outcome Measurement Information System (PROMIS) tools within 1 month of stroke. Latent profile analysis identified groups based on PROMIS domain scores—pain, depression, cognitive function, fatigue, social role satisfaction, and physical function—as well as clinician‐reported modified Rankin Scale (mRS). Five distinct profiles were identified. Group 1 (“excellent hrQoL,” n=106) had fewer symptoms in all domains than the general population. Group 2 (“disabled with mixed hrQoL,” n=17) had fewer symptoms than the general population in all domains except social role satisfaction and physical function, despite having moderate disability (median mRS score: 3). Group 3 (“mild limitations with average hrQoL,” n=189) had scores similar to the general population for all domains and minimal disability (median mRS score: 1). Group 4 (“mild limitations with poor hrQoL,” n=152) also had a median mRS score of 1 but had worse scores than group 3 on all domains. Group 5 (“disabled with poor hrQoL,” n=32) had worse symptoms than patients in the other profiles and a median mRS score of 3.

Conclusions

Patients with recent stroke have distinct clinical symptom profiles, even with similar levels of clinician‐reported disability. Symptom profiles provide a means of understanding patterns of outcomes in patients with stroke.

Exploring the interconnectedness of fatigue, depression, anxiety and potential risk and protective factors in cancer patients: a network approach

Researchers have extensively studied fatigue, depression and anxiety in cancer patients. Several risk and protective factors have been identified for these symptoms. As most studies address these constructs, independently from other symptoms and potential risk and protective factors, more insight into the complex relationships among these constructs is needed. This study used the multivariate network approach to gain a better understanding of how patients' symptoms and risk and protective factors (i.e. physical symptoms, social withdrawal, illness cognitions, goal adjustment and partner support) are interconnected. We used cross-sectional data from a sample of cancer patients seeking psychological care (n = 342). Using network modelling, the relationships among symptoms of fatigue, depression and anxiety, and potential risk and protective factors were explored. Additionally, centrality (i.e. the number and strength of connections of a construct) and stability of the network were explored. Among risk factors, the relationship of helplessness and physical symptoms with fatigue stood out as they were stronger than most other connections in the network. Among protective factors, illness acceptance was most centrally embedded within the network, indicating it had more and stronger connections than most other variables in the network. The network identified key connections with risk factors (helplessness, physical symptoms) and a key protective factor (acceptance) at the group level. Longitudinal studies should explore these risk and protective factors in individual dynamic networks to further investigate their causal role and the extent to which such networks can inform us on what treatment would be most suitable for the individual cancer patient.

Associations between symptom severity and treatment burden in people living with HIV

AIM

To examine the association between symptoms severity and treatment burden in people living with HIV.

DESIGN

Correlational, secondary analysis of data from participants diagnosed with HIV enrolled in a descriptive, cross-sectional study examining physical activity patterns.

METHODS

We analysed data from 103 men and women using self-report data collected between March 2016 - February 2017. Our primary statistical analyses consisted of explanatory multivariate modelling with individual PROMIS-29 scores representing symptom severity and treatment burden measured using the Treatment Burden Questionnaire-13.

RESULTS

Greater symptom severity was associated with higher levels of cumulative treatment burden as well as higher levels of task-specific medication and physical activity burden. Multivariate regression analyses revealed that fatigue was a risk factor of cumulative treatment burden as well as task-specific medication and physical activity treatment burden. Effect sizes of multivariate models ranged from small (0.11) to medium (0.16). Additionally, post hoc analyses showed strong correlations between fatigue and other measured symptoms.

CONCLUSION

Findings support extant treatment burden literature, including the importance of addressing symptom severity in conjunction with treatment burden screening in the clinical setting. Results also suggest clinical interventions focused on the reduction of fatigue could reduce treatment burden in people living with HIV. Strong correlations between fatigue and other symptoms indicate the potential for reducing fatigue by addressing other highly clustered symptoms, such as depression.

IMPACT

People living with HIV exhibiting higher levels of fatigue are at high risk for treatment burden and poorer self-management adherence. Clinicians should consider incorporating symptom and treatment burden assessments when developing, tailoring and modifying interventions to improve self-management of HIV and other co-morbid conditions.

Distinct Symptom Experience Among Subgroups of Patients With ESRD Receiving Maintenance Dialysis

CONTEXT

Patients with end-stage renal disease receiving dialysis experience multiple concurrent symptoms. A person-centered understanding of patients' symptom experiences may offer insights into individualized management.

OBJECTIVES

We identified subgroups of patients based on their symptom experiences and the characteristics that differentiated among these subgroups. Outcomes associated with these subgroups were evaluated.

METHODS

A total of 354 patients on dialysis were recruited at two regional hospitals in Hong Kong. While the Dialysis Symptom Index was adopted to assess symptoms, the Kidney Disease Quality of Life 36 and Karnofsky Performance Status Scale were used to evaluate the quality of life outcomes. Information on health care utilization and mortality were retrieved from medical records. Subgroups of patients were identified using latent class analysis based on the occurrence ratings. Differences in characteristics and outcomes were determined using Chi-squared test, analysis of variance, and Cox regression analysis.

RESULTS

Three latent classes were identified: low (37.8%), moderate physical-low psychological (29.7%), and moderate physical-high psychological (32.5%). Higher comorbidity burden and lower serum albumin levels differentiated between the low and moderate physical-low psychological classes. The moderate physical-high psychological class had the highest number of symptoms, poorest quality of life outcomes, and more unscheduled clinic visits. A shorter mean survival time (421 vs. 431 days) was also found.

CONCLUSION

Consistent with findings in other chronic conditions, subgroups of patients on dialysis have unique symptom experiences. Therefore, an individualized approach to symptom management is warranted. Our findings offer a phenotypic characterization for research on the underlying mechanisms for these symptom experiences.

Pain-Associated Clusters Among Nursing Home Residents and Older Adults Receiving Home Care in Germany

CONTEXT

There are no available data regarding pain-associated clusters among nursing home residents (NHRs) and older adults receiving home care with chronic pain.

OBJECTIVES

To identify and describe pain-associated clusters in NHRs and older adults receiving home care with chronic pain and to explore associations with clusters in both settings.

METHODS

We surveyed 137 NHRs and 205 older adults receiving home care. Clusters were identified using hierarchical agglomerative cluster analysis, using Ward's method with squared Euclidean distances in the proximities matrix. The clusters were characterized based on sociodemographic and clinical characteristics. Multinomial logistic regression was used to identify variables associated with different clusters.

RESULTS

In each setting, we identified three clusters: pain relieved, pain impaired, and suffering severe pain. In the nursing home study and home care study, respectively, the participant distributions were 46.72% and 11.71% in the pain-relieved cluster, 22.63% and 33.66% in the pain-impaired cluster, and 30.66% and 54.63% in the severe-pain cluster. Appropriate pain medication was only detected among pain-relieved NHRs.

CONCLUSION

Overall, differences in pain management exist within the two care settings presented here. There is potential for improvement in both settings. Moreover, there exists a need for clinical interventions aiming at shifting from pain-affected clusters to pain-relieved status.

Interventions for Managing a Symptom Cluster of Pain, Fatigue, and Sleep Disturbances During Cancer Survivorship: A Systematic Review

PROBLEM IDENTIFICATION

More than 40% of cancer survivors experience a symptom cluster of pain, fatigue, and sleep disturbances, which can greatly reduce quality of life.

LITERATURE SEARCH

A literature search was performed using CINAHL®, Google ScholarTM, PubMed®, PsycINFO®, and Web of Science. Articles included randomized controlled trials of interventions aimed at managing a symptom cluster of pain, fatigue, and sleep disturbances.

DATA EVALUATION

11 studies were assessed for quality, risk of bias, cancer type, sample size, intervention type, duration, and setting. For an intervention to be considered effective, the reduction of symptom severity or distress had to be statistically significant.

SYNTHESIS

Data from the 11 studies were summarized. Four interventions were found to be effective in managing the symptom cluster, but evidence on long-term effectiveness was insufficient.

IMPLICATIONS FOR NURSING

Oncology nurses can assess the patterns and characteristics of simultaneous symptoms experienced by cancer survivors and administer interventions to relieve symptom burden and improve quality of life.

An integrated model of multimorbidity and symptom science

BACKGROUND

Prevalence and complexity of persons with multiple chronic conditions (MCC), also known as multimorbidity, are shifting clinical practice from a single disease focus to one considering MCC and symptoms. Although symptoms are intricately bound to concepts inherent in MCC science, symptoms are largely ignored in multimorbidity research and literature.

PURPOSE

Introduce an Integrated Model of Multimorbidity and Symptom Science.

METHODS

Critical integrative review and synthesis process.

FINDINGS

The model comprises three primary domains: 1. Contributing/ Risk Factors; 2. Symptom/Disease/Treatment Interactions; and 3. Patient Outcomes.

DISCUSSION

The model highlights the multilevel nature of contributing factors and the recursive interactions among multiple etiologies, conditions, symptoms, therapies, and outcomes.

Consensus Recommendations From the Children's Oncology Group Nursing Discipline's State of the Science Symposium: Symptom Assessment During Childhood Cancer Treatment

Background: Recognizing and addressing illness-related distress has long been a priority for pediatric oncology nurses and the Children's Oncology Group. Although symptoms are known to be highly prevalent during treatment for childhood cancer, there is currently no guidance for how often symptoms should be assessed, which symptoms should be prioritized for assessment, and how the data should be collected. Methods: The Nursing Discipline, within Children's Oncology Group, hosted a one-day Interprofessional seminar titled "Symptom Assessment During Childhood Cancer Treatment: State of the Science Symposium." Following the symposium, an expert panel was assembled to review all available evidence, including information presented and collected during the symposium. Consensus-building discussions were held to identify common themes and to produce recommendations for clinical practice. Results: Four recommendations emerged including (1) the identification of priority "core" symptoms for assessment; (2) inclusion of the child's voice through self-report, when possible; (3) consistent documentation and communication of symptom assessment results; and (4) implementation of patient/family education related to symptoms. Discussion: Symptom recognition, through appropriate assessment, is the first step in symptom management. The goal for developing and sharing these recommendations is to promote consistent and comparable clinical practice across institutions in regard to symptom assessment during childhood cancer therapy. Integration of these recommendations will set the stage for future studies related to the frequency of symptoms across disease groups, projection of anticipated symptom trajectories, development of evidence-based teaching tools for common symptoms, and evaluation of patient outcomes with enhanced symptom assessment and management.

Identification of subgroups of chemotherapy patients with distinct sleep disturbance profiles and associated co-occurring symptoms

STUDY OBJECTIVES

Purposes of this study were to identify subgroups of patients with distinct sleep disturbance profiles and to evaluate for differences in demographic, clinical, and various sleep characteristics, as well for differences in the severity of co-occurring symptoms among these subgroups.

METHODS

Outpatients with breast, gynecological, gastrointestinal, or lung cancer (n = 1331) completed questionnaires six times over two chemotherapy cycles. Self-reported sleep disturbance was evaluated using the General Sleep Disturbance Scale (GSDS). Latent profile analysis was used to identify distinct subgroups.

RESULTS

Three latent classes with distinct sleep disturbance profiles were identified (Low [25.5%], High [50.8%], Very High [24.0%]) across the six assessments. Approximately 75% of the patients had a mean total GSDS score that was above the clinically meaningful cutoff score of at least 43 across all six assessments. Compared to the Low class, patients in High and Very High classes were significantly younger, had a lower functional status, had higher levels of comorbidity, and were more likely to be female, more likely to have childcare responsibilities, less likely to be employed, and less likely to have gastrointestinal cancer. For all of the GSDS subscale and total scores, significant differences among the latent classes followed the expected pattern (Low < High < Very High). For trait and state anxiety, depressive symptoms, morning and evening fatigue, decrements in attentional function, and decrements in morning and evening energy, significant differences among the latent classes followed the expected pattern (Low < High < Very High).

CONCLUSIONS

Clinicians need to perform in-depth assessments of sleep disturbance and co-occurring symptoms to identify high-risk patients and recommend appropriate interventions.

A Randomized, Placebo-Controlled, Double-Blind Study of Minocycline for Reducing the Symptom Burden Experienced by Patients With Advanced Pancreatic Cancer

CONTEXT

Although it is well known that patients with advanced pancreatic cancer (PC) experience significant symptom burden, few strategies for effective symptom intervention are available for them.

OBJECTIVES

To investigate the efficacy of minocycline, an anti-inflammatory agent, for symptom reduction in patients with advanced PC.

METHODS

We conducted Phase II, randomized, and placebo-controlled trial to obtain preliminary estimates of the effects on symptom reduction with 100 mg of minocycline or placebo given twice a day. Eligible patients had diagnosed advanced PC and were scheduled for standard chemotherapy. Patient-reported symptoms were measured weekly during the eight-week trial using the MD Anderson Symptom Inventory (MDASI) module in patients with gastrointestinal cancer. The primary outcome measure was the area under the curve values of the five most severe symptoms in the two arms.

RESULTS

Of the 44 patients recruited, 31 (71%) were evaluable for the primary efficacy analysis, with 18 received minocycline and 13 placebo. Fatigue, pain, disturbed sleep, lack of appetite, and drowsiness were the most severe symptoms reported by both groups. No significant differences in area under the curve values over time between the study arms were found for the composite MDASI score or single-item scores of the five most severe MDASI items. No treatment-related deaths were reported, and no Grade 3-4 toxicities were observed.

CONCLUSION

Minocycline is safe for use in patients receiving treatment for PC. There is no observed symptom reduction with minocycline on the major symptom burden associated with advanced PC compared with placebo. Attrition because of rapid disease progression impacted the study significantly.

Two Methods for Calculating Symptom Cluster Scores

BACKGROUND

Symptom clusters are conventionally distilled into a single score using composite scoring, which is based on the mathematical assumption that all symptoms are equivalently related to outcomes of interest; this may lead to a loss of important variation in the data.

OBJECTIVES

This article compares two ways of calculating a single score for a symptom cluster: a conventional, hypothesis-driven composite score versus a data-driven, reduced rank regression score that weights the symptoms based on their individual relationships with key outcomes.

METHODS

We conducted a secondary analysis of psychoneurological symptoms from a sample of 356 low-income mothers. Four of the psychoneurological symptoms (fatigue, cognitive dysfunction, sleep disturbance, and depressed mood) were measured with the Center for Epidemiological Studies Depression Scale; the fifth (pain) was measured using an item from the Medical Outcomes Study 12-item Short Form Health Survey (SF-12). Mothers' function was measured using the 12-item Short Form Health Survey. The composite score was calculated by summing standardized scores for each individual psychoneurological symptom. In contrast, reduced rank regression weighted the individual symptoms using their respective associations with mothers' function; the weighted individual symptom scores were summed into the reduced rank regression symptom score.

RESULTS

The composite score and reduced rank regression score were highly correlated at .93. The cluster of psychoneurological symptoms accounted for 53.7% of the variation in the mothers' function. Depressed mood and pain accounted for almost all the explained variation in mothers' function at 37.2% and 15.0%, respectively.

DISCUSSION

The composite score approach was simpler to calculate, and the high correlation with the reduced rank regression score indicates that the composite score reflected most of the variation explained by the reduced rank regression approach in this data set. However, the reduced rank regression analysis provided additional information by identifying pain and depressed mood as having the strongest association with a mother's function, which has implications for understanding which symptoms to target in future interventions. Future studies should also explore composite versus reduced rank regression approaches given that reduced rank regression may yield different insights in other data sets.

Natural language processing of symptoms documented in free-text narratives of electronic health records: a systematic review

OBJECTIVE

Natural language processing (NLP) of symptoms from electronic health records (EHRs) could contribute to the advancement of symptom science. We aim to synthesize the literature on the use of NLP to process or analyze symptom information documented in EHR free-text narratives.

MATERIALS AND METHODS

Our search of 1964 records from PubMed and EMBASE was narrowed to 27 eligible articles. Data related to the purpose, free-text corpus, patients, symptoms, NLP methodology, evaluation metrics, and quality indicators were extracted for each study.

RESULTS

Symptom-related information was presented as a primary outcome in 14 studies. EHR narratives represented various inpatient and outpatient clinical specialties, with general, cardiology, and mental health occurring most frequently. Studies encompassed a wide variety of symptoms, including shortness of breath, pain, nausea, dizziness, disturbed sleep, constipation, and depressed mood. NLP approaches included previously developed NLP tools, classification methods, and manually curated rule-based processing. Only one-third (n = 9) of studies reported patient demographic characteristics.

DISCUSSION

NLP is used to extract information from EHR free-text narratives written by a variety of healthcare providers on an expansive range of symptoms across diverse clinical specialties. The current focus of this field is on the development of methods to extract symptom information and the use of symptom information for disease classification tasks rather than the examination of symptoms themselves.

CONCLUSION

Future NLP studies should concentrate on the investigation of symptoms and symptom documentation in EHR free-text narratives. Efforts should be undertaken to examine patient characteristics and make symptom-related NLP algorithms or pipelines and vocabularies openly available.

Symptom cluster of pain, fatigue, and psychological distress in breast cancer survivors: prevalence and characteristics

PURPOSE

Breast cancer survivors may experience pain, fatigue, or psychological distress as a result of the treatment. These symptoms may co-occur and form a cluster. However little is known about symptom clusters (SCs) in long-term breast cancer survivors. This study aimed to identify subgroups of breast cancer survivors with the SC of pain, fatigue, and psychological distress, and to examine sociodemographic and clinical characteristics associated with this SC.

METHODS

Data were obtained from a nationwide survey of breast cancer survivors (N = 834). Exhaustive enumeration of possible combination of the three binary variables (pain, fatigue, psychological distress) was conducted. They were identified using the recommended threshold for the Hospital Anxiety and Depression Scale, the Fatigue Questionnaire, and a score of one or more on a numeric rating scale for pain. The SC was defined to include all the three variables, all other combinations were defined as no SC. Logistic regression analyses were conducted to examine the association between sociodemographic and clinical variables and the SC.

RESULTS

Of the 834 survivors, 13% had the SC. Younger age (OR 2.3, 95% CI 1.3-4.1, p = 0.003), lymphedema (OR 1.9, 95% CI 1.1-3.2, p = 0.02), working part-time (OR 2.9, 95% CI 1.6-5.3, p < 0.001), or being disabled (OR 4.1, 95% CI 2.2-7.8, p < 0.001) were all associated with the SC.

CONCLUSION

Thirteen percent of the survivors experienced the SC. It appears that premenstrual women are at greater risk, than postmenopausal women. Having this SC might have an impact on the survivors' ability to work.

Symptom cluster of pain, fatigue, and psychological distress in breast cancer survivors: prevalence and characteristics

PURPOSE

Breast cancer survivors may experience pain, fatigue, or psychological distress as a result of the treatment. These symptoms may co-occur and form a cluster. However little is known about symptom clusters (SCs) in long-term breast cancer survivors. This study aimed to identify subgroups of breast cancer survivors with the SC of pain, fatigue, and psychological distress, and to examine sociodemographic and clinical characteristics associated with this SC.

METHODS

Data were obtained from a nationwide survey of breast cancer survivors (N = 834). Exhaustive enumeration of possible combination of the three binary variables (pain, fatigue, psychological distress) was conducted. They were identified using the recommended threshold for the Hospital Anxiety and Depression Scale, the Fatigue Questionnaire, and a score of one or more on a numeric rating scale for pain. The SC was defined to include all the three variables, all other combinations were defined as no SC. Logistic regression analyses were conducted to examine the association between sociodemographic and clinical variables and the SC.

RESULTS

Of the 834 survivors, 13% had the SC. Younger age (OR 2.3, 95% CI 1.3-4.1, p = 0.003), lymphedema (OR 1.9, 95% CI 1.1-3.2, p = 0.02), working part-time (OR 2.9, 95% CI 1.6-5.3, p < 0.001), or being disabled (OR 4.1, 95% CI 2.2-7.8, p < 0.001) were all associated with the SC.

CONCLUSION

Thirteen percent of the survivors experienced the SC. It appears that premenstrual women are at greater risk, than postmenopausal women. Having this SC might have an impact on the survivors' ability to work.

Stability and Impact of Symptom Clusters in Patients With End-Stage Renal Disease Undergoing Dialysis

CONTEXT

Patients with end-stage renal disease undergoing dialysis experience multiple concurrent symptoms. These symptoms cluster together and have negative impacts on patient outcomes. However, information on changes in symptom clusters over time is limited.

OBJECTIVES

This longitudinal study examined the stability of symptom clusters and their impacts on health-related quality of life and functional status over a period of one year.

METHODS

Eligibility criteria were patients diagnosed with end-stage renal disease; had received dialysis consecutively for at least three months; and had given written informed consent. Dialysis Symptom Index, Kidney Disease Quality of Life 36, and Karnofsky Performance Status Scale were used to evaluate the impacts of symptom clusters and outcomes. Exploratory factor analyses and multiple regression analyses were used to determine symptom clusters and their associations with patient outcomes.

RESULTS

Among the 354 recruited patients, 271 completed the 12-month assessment. Four symptom clusters were identified across the three assessments, namely, uremic, gastrointestinal, skin, and emotional. Within each cluster, the specific symptoms were varied. The uremic symptom cluster accounted for the largest amount of variability. Across the three assessments, a higher uremic cluster factor score was associated with poorer physical well-being, whereas a higher emotional cluster factor score was consistently associated with poorer mental well-being.

CONCLUSION

Symptoms in patients on dialysis clustered in relatively stable patterns. The four symptom clusters identified had consistent negative effects on various aspects of patients' well-being. Our findings suggest the need for ongoing symptom assessment and early recognition of symptoms that may contribute to adverse patient outcomes.

A Biopsychosocial Model of Chronic Pain for Older Adults

Population

Comprehensive evaluation of chronic pain in older adults is multifaceted.

Objective and Methods

Research on chronic pain in older adults needs to be guided by sound conceptual models. The purpose of this paper is to describe an adaptation of the Biopsychosocial Model (BPS) of Chronic Pain for older adults. The extant literature was reviewed, and selected research findings that provide the empiric foundation for this adaptation of the BPS model of chronic pain are summarized. The paper concludes with a discussion of specific recommendations for how this adapted model can be used to guide future research.

Conclusions

This adaptation of the BPS model of chronic pain for older adults provides a comprehensive framework to guide future research in this vulnerable population.

Stability of Symptom Clusters in Patients With Gastrointestinal Cancers Receiving Chemotherapy

CONTEXT

Limited evidence suggests that patients with gastrointestinal (GI) cancers receiving chemotherapy (CTX) experience an average of 13 co-occurring symptoms. An alternative to counting symptoms is to evaluate for symptom clusters.

OBJECTIVES

In a sample of patients with GI cancers receiving CTX (n = 399), we evaluated the occurrence, severity, and distress of 38 symptoms in the week before patients' second or third cycle of CTX (Time 1 [T1]), approximately one week after CTX (Time 2 [T2]), and approximately two weeks after CTX (Time 3 [T3]); evaluated for differences in the number and types of symptom clusters at each of these three assessments using ratings of occurrence, severity, and distress; and evaluated for changes in symptom clusters over time.

METHODS

Modified version of the Memorial Symptom Assessment Scale collected data on 38 common symptoms. Exploratory factor analyses were used to create the symptom clusters.

RESULTS

Five distinct symptom clusters were identified across the three symptom dimensions and the three assessments (i.e., psychological, CTX-related, weight change, GI, and epithelial). Psychological, CTX-related, and weight change clusters were relatively stable across all three symptom dimensions and time. Across all three symptom dimensions, GI cluster was identified only at T1 and epithelial cluster was identified at T2 and T3.

CONCLUSION

The number and types of symptom clusters appear to be relatively stable over time and across the symptom dimensions. Ongoing assessment and management of these clusters is warranted across the entire course of CTX. The underlying mechanism for these clusters warrants investigation.

Cross-classification of physical and affective symptom clusters and 180-day event-free survival in moderate to advanced heart failure

BACKGROUND

The relationship between physical and affective symptom clusters in heart failure (HF) is unclear.

OBJECTIVES

To identify associations between physical and affective symptom clusters in HF and to quantify outcomes and determinants of symptom subgroups.

METHODS

This was a secondary analysis of data from two cohort studies among adults with HF. Physical and affective symptom clusters were compared using cross-classification modeling. Cox proportional hazards modeling and multinomial logistic regression were used to identify outcomes and determinants of symptom subgroups, respectively.

RESULTS

In this young, mostly male sample (n = 274), physical and affective symptom clusters were cross-classified in a model with acceptable fit. Three symptom subgroups were identified: congruent-mild (69.3%), incongruent (13.9%), and congruent-severe (16.8%). Compared to the congruent-mild symptom group, the incongruent symptom group had significantly worse 180-day event-free survival.

CONCLUSION

Congruence between physical and affective symptom clusters should be considered when identifying patients at higher risk for poor outcomes.

The day after: correlates of patient-reported outcomes with actigraphy-assessed sleep in cancer patients at home (inCASA project)

Subjective sleep assessment in cancer patients poorly correlates with actigraphy parameters that usually encompass multiple nights. We aimed to determine the objective actigraphy measures that best correlated with subjective sleep ratings on a night-by-night basis in cancer patients. Thirty-one cancer patients daily self-rated sleep disturbances using the single dedicated item of the MD Anderson Symptom Inventory (0-10 scale) with 18 other items, and continuously wore a wrist actigraph for 30 days. Objective sleep parameters were computed from the actigraphy nighttime series, and correlated with subjective sleep disturbances reported on the following day, using repeated measures correlations. Multilevel Poisson regression analysis was performed to identify the objective and subjective parameters that affected subjective sleep rating. Poor subjective sleep score was correlated with poor sleep efficiency (rrm = -0.13, p = 0.002) and large number of wake episodes (rrm = 0.12, p = 0.005) on the rated night. Multilevel analysis demonstrated that the expected sleep disturbance score was affected by the joint contribution of the wake episodes (exp(β) = 1.01, 95% confidence interval = 1.00 to 1.02, p = 0.016), fatigue (exp(β) = 1.35, 95% confidence interval = 1.15 to 1.55, p < 0.001) and drowsiness (exp(β) = 1.70, 95% confidence interval = 1.19 to 2.62, p = 0.018), self-rated the following evening, and sleep disturbance experienced one night before (exp(β) = 1.77, 95% confidence interval = 1.41 to 2.22, p < 0.001). The night-by-night approach within a multidimensional home tele-monitoring framework mainly identified the objective number of wake episodes computed from actigraphy records as the main determinant of the severity of sleep complaint in cancer patients on chemotherapy. This quantitative information remotely obtained in real time from cancer patients provides a novel framework for streamlining and evaluating interventions toward sleep improvement in cancer patients.

Influence of Menopausal Status on the Symptom Experience of Women Before Breast Cancer Surgery

BACKGROUND

Breast cancer treatments can change women's hormonal milieu and alter their symptom experience. Little is known about associations between menopausal status and menopausal symptoms in women with breast cancer before surgery.

OBJECTIVE

The purpose of this study was to evaluate for differences in occurrence, severity, and distress of symptoms between premenopausal and postmenopausal women before breast cancer surgery.

METHODS

A total of 312 women with breast cancer completed the Menopausal Symptoms Scale, a self-report measure that evaluated the occurrence, severity, and distress of 46 common symptoms associated with menopause. Regression analyses were used to evaluate for between-group differences in these symptoms.

RESULTS

Of the 312 patients enrolled, 37.4% (n = 116) were premenopausal, and 62.6% (n = 196) were postmenopausal. In the multivariate analysis that adjusted for 7 covariates, premenopausal patients reported higher occurrence rates for urinary frequency (P = .006) and reported lower occurrence rates for joint pain/stiffness (P = .011), difficulty falling asleep (P = .025), and vaginal dryness (P = .002). A significant interaction was found between age and menopausal status for hot flashes (P = .002), wake during the night (P = .025), and headache (P = .040).

CONCLUSION

Regardless of menopausal status, women reported high occurrence rates for several menopausal symptoms. Associations between some symptom occurrence rates and menopausal status depended on the patients' age.

IMPLICATIONS FOR PRACTICE

As part of a preoperative symptom assessment, clinicians need to consider a woman's menopausal status and salient demographic and clinical characteristics. The identification of women with a higher symptom burden will assist with more effective management.

Symptom Clusters in Patients With Gastrointestinal Cancers Using Different Dimensions of the Symptom Experience

CONTEXT

Patients with gastrointestinal (GI) cancers undergoing chemotherapy (CTX) experience multiple cooccurring symptoms.

OBJECTIVES

The aim of this study was to describe the occurrence, severity, and distress of 38 symptoms and to identify symptom clusters based on three symptom dimensions (i.e., occurrence, severity, and distress) in patients with GI cancers receiving CTX (n = 399). We compared whether the numbers and types of symptom clusters differed based on the dimension of the symptom experience used to create the clusters.

METHODS

A modified version of the Memorial Symptom Assessment Scale was used to assess the occurrence, severity, and distress of 38 symptoms before the initiation of the patient's next dose of CTX. Exploratory factor analysis was used to determine the symptom clusters.

RESULTS

These patients experienced 13.0 (±7.1) symptoms before their second or third dose of CTX. For all three symptom dimensions, four symptom clusters were identified, namely psychological distress, CTX-related, GI, and weight change. The number and types of symptom clusters were relatively similar using all three symptom dimensions. However, some variability was found in the specific symptoms within each of the clusters.

CONCLUSION

Our findings suggest that patients with GI cancers experience multiple cooccurring symptoms. Consistent with previous studies of patients with a variety of cancer diagnoses, psychological and GI clusters are common. Clinicians need to assess for and tailor interventions for these symptom clusters.

Importance of fatigue and its measurement in chronic liver disease

The mechanisms of fatigue in the group of people with non-alcoholic fatty liver disease and non-alcoholic steatohepatitis are protean. The liver is central in the pathogenesis of fatigue because it uniquely regulates much of the storage, release and production of substrate for energy generation. It is exquisitely sensitive to the feedback controlling the uptake and release of these energy generation substrates. Metabolic contributors to fatigue, beginning with the uptake of substrate from the gut, the passage through the portal system to hepatic storage and release of energy to target organs (muscle and brain) are central to understanding fatigue in patients with chronic liver disease. Inflammation either causing or resulting from chronic liver disease contributes to fatigue, although inflammation has not been demonstrated to be causal. It is this unique combination of factors, the nexus of metabolic abnormality and the inflammatory burden of non-alcoholic fatty liver disease and non-alcoholic steatohepatitis that creates pathways to different types of fatigue. Many use the terms central and peripheral fatigue. Central fatigue is characterized by a lack of self-motivation and can manifest both in physical and mental activities. Peripheral fatigue is classically manifested by neuromuscular dysfunction and muscle weakness. Therefore, the distinction is often seen as a difference between intention (central fatigue) versus ability (peripheral fatigue). New approaches to measuring fatigue include the use of objective measures as well as patient reported outcomes. These measures have improved the precision with which we are able to describe fatigue. The measures of fatigue severity and its impact on usual daily routines in this population have also been improved, and they are more generally accepted as reliable and sensitive. Several approaches to evaluating fatigue and developing endpoints for treatment have relied of biosignatures associated with fatigue. These have been used singly or in combination and include: physical performance measures, cognitive performance measures, mood/behavioral measures, brain imaging and serological measures. Treatment with non-pharmacological agents have been shown to be effective in symptom reduction, whereas pharmacological agents have not been shown effective.

Symptom Science: Advocating for Inclusion of Functional Genetic Polymorphisms

Incorporating biologically based data into symptom science research can contribute substantially to understanding commonly experienced symptoms across chronic conditions. The purpose of this literature review was to identify functional polymorphisms associated with common symptoms (i.e., pain, sleep disturbance, fatigue, affective and cognitive symptoms) with the goal of identifying a parsimonious list of functional genetic polymorphisms with evidence to advocate for their inclusion in symptom science research. PubMed was searched to identify genes and functional polymorphisms associated with symptoms across chronic conditions, revealing eight functional genetic polymorphisms in seven different genes that showed evidence of association with at least three or more symptoms and/or symptom clusters: BDNF rs6265, COMT rs4680, FKBP5 rs3800373, IL-6 rs1800795, NFKB2 rs1056890, SLC6A4 5-HTTLPR+rs25531, and TNFA rs1799964 and rs1800629. Of these genes, three represent protein biomarkers previously identified as common data elements for symptom science research (BDNF, IL-6, and TNFA), and the polymorphisms in these genes identified through the search are known to impact secretion or level of transcription of these protein biomarkers. Inclusion of genotype data for polymorphisms offers great potential to further advance scientific knowledge of the biological basis of individual symptoms and symptom clusters across studies. Additionally, these polymorphisms have the potential to be used as targets to optimize precision health through the identification of individuals at risk for poor symptom experiences as well as the development of symptom management interventions.

Symptom Clusters in People Living With HIV: A Systematic Review

CONTEXT

An increasing number of studies regarding symptom management have begun to shift their focus from managing a single symptom to multiple symptom clusters. However, there is a lack of consistency of compositions among different studies and even in two different analyses reported in a single study within the same population.

OBJECTIVES

The aim of this systematic review was to summarize the compositions, measures, and data analysis techniques of symptom clusters in people living with HIV (PLWH).

METHODS

We conducted a comprehensive search to identify published studies about symptom clusters among PLWH. Databases including PubMed/MEDLINE, MEDLINE (Ovid), EMBASE (Ovid), CINAHL (EBSCO), Web of Science, and ProQuest Dissertations and Thesis were searched for studies published between January 2000 and December 2018.

RESULTS

Thirteen articles were eligible for inclusion. Five most commonly reported symptom clusters were found: 1) sad/depressed/loss of interest and nervous/anxious/worrying; 2) difficulty sleeping, problems with having sex, and fatigue/loss of energy; 3) fever/chills/sweat, nausea/vomiting, and loss of appetite; 4) numbness, muscle aches, and joint pain; and 5) dizziness and headache.

CONCLUSION

This systematic review summarized the compositions, measures, and analytical techniques of symptom clusters for PLWH. Although this review found unstable results on the compositions of symptom clusters and it was difficult to reach a definitive conclusion, the results still implicate the necessity of developing a threshold to decide what symptoms should be included in the clusters and the use of multiple data analysis techniques to obtain stable results.

Sleep disturbance and cancer-related fatigue symptom cluster in breast cancer patients undergoing chemotherapy

PURPOSE

Sleep disturbance and cancer-related fatigue (CRF) are among the most commonly reported symptoms associated with breast cancer and its treatment. This study identified symptom cluster groups of breast cancer patients based on multidimensional assessment of sleep disturbance and CRF prior to and during chemotherapy.

METHODS

Participants were 152 women with stage I-IIIA breast cancer. Data were collected before chemotherapy (T1) and during the final week of the fourth chemotherapy cycle (T2). Latent profile analysis was used to derive groups of patients at each timepoint who scored similarly on percent of the day/night asleep per actigraphy, the Pittsburgh Sleep Quality Index global score, and the five subscales of the Multidimensional Fatigue Symptom Inventory-Short Form. Bivariate logistic regression evaluated if sociodemographic/medical characteristics at T1 were associated with group membership at each timepoint.

RESULTS

Three groups (Fatigued with sleep complaints, Average, Minimal symptoms) were identified at T1, and five groups (Severely fatigued with poor sleep, Emotionally fatigued with average sleep, Physically fatigued with average sleep, Average, Minimal symptoms) at T2. The majority of individuals in a group characterized by more severe symptoms at T1 were also in a more severe symptom group at T2. Sociodemographic/medical variables at T1 were significantly associated with group membership at T1 and T2.

CONCLUSIONS

This study identified groups of breast cancer patients with differentially severe sleep disturbance and CRF symptom profiles prior to and during chemotherapy. Identifying groups with different symptom management needs and distinguishing groups by baseline sociodemographic/medical variables can identify patients at risk for greater symptom burden.

Music, heart rate variability, and symptom clusters: a comparative study

PURPOSE

This study aimed to explore the possible range of change of a single-session music intervention (SMI) on symptom clusters and neurological reactivity for women with breast cancer undergoing chemotherapy.

METHODS

A parallel and randomized, controlled study with repeated measures design was used. A total of 100 women with breast cancer were randomly assigned to the SMI or a control group. The outcome measurements of symptom cluster were collected using the Multidimensional Fatigue Symptom Inventory, Pittsburgh Sleep Quality Index, the Hospital Anxiety and Depression Scale, and the neurological reactivity with heart rate variability at four time points: before commencement of the intervention (T0), immediately afterward (T1), 1 week later (T2), and 3 weeks after the intervention (T3).

RESULTS

Of the 50 women in each group, 46 in the SMI and 48 in the control group completed the post-test at T3. Multivariate analysis of variance indicated that the SMI group had a medium effect in change of symptom clusters compared to the control group at T2. Moreover, after adjusting for baseline between normal and higher levels of sympathetic tone activity, significant differences existed in fatigue and depression at T2 and sleep disturbance at T3.

CONCLUSIONS

A single-session music intervention can be effectively used to reduce symptom clusters for women with breast cancer. Targeting those who have a higher level of sympathetic tone activity is recommended.

Effect of progressive resistance training on health-related quality of life in the first year after breast cancer surgery - results from a randomized controlled trial

Aims: To examine the effect of progressive resistance training (PRT) on health related quality of life and a predefined symptom cluster of pain-sleep-fatigue. Methods: This study was a planned secondary analysis of a randomized controlled trial examining the effect of PRT on prevention of arm lymphedema in a population of women between 18 and 75 years undergoing breast cancer surgery with axillary lymph node dissection. Participants were allocated by computer randomization to usual care control or a PRT intervention in a 1:1 ratio. The intervention, initiated in the third post-operative week, consisted of three times PRT per week, supervised in groups in the first 20 weeks, and self-administered in the following 30 weeks. Questionnaire assessments were made at baseline, 20 weeks and 12 months, with the European Organization for Research and Treatment in Cancer Core questionnaire (EORTC QLQ C30) and the Functional Assessment of Chronic Illness Therapy-(FACIT) fatigue questionnaire. The symptom cluster of pain-sleep-fatigue was measured with a constructed score adding EORTC C30 subscales of insomnia, pain, and fatigue. Data were treated as repeated measurements and analyzed with mixed models. Results: Among 158 recruited participants, we found a clinically relevant increased emotional functioning with nine points at both follow-ups (p = .02), and 16 and 11 points at 20 weeks and 12 months respectively (p = .04) in social functioning. Furthermore, in the subgroup of women with the symptom cluster pain-sleep-fatigue present at baseline, a significant effect was found for global health status (p = .01) and social functioning (p = .02). Conclusion: To our knowledge, this is the first study to report clinically relevant effects of PRT on social and emotional functioning in the first postoperative year after breast cancer surgery. Furthermore, a subgroup of women with the pain-sleep-fatigue symptom cluster had particular benefit from PRT on global health status and social functioning.

Stability of Symptom Clusters in Patients With Lung Cancer Receiving Chemotherapy

CONTEXT

Patients with lung cancer who undergo chemotherapy (CTX) experience multiple symptoms. Evaluation of how these symptoms cluster together and how these symptom clusters change over time are salient questions in symptom clusters research.

OBJECTIVES

The purposes of this analysis, in a sample of patients with lung cancer (n = 145) who were receiving CTX, were to 1) evaluate for differences in the number and types of symptom clusters at three time points (i.e., before their next cycle of CTX, the week after CTX, and two weeks after CTX) using ratings of symptom occurrence and severity and 2) evaluate for changes in these symptom clusters over time.

METHODS

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

RESULTS

Across the two symptom dimensions (i.e., occurrence and severity) and the three assessments, six distinct symptom clusters were identified; however, only three of these clusters (i.e., lung cancer specific, psychological, nutritional) were relatively stable across both dimensions and across time. Two additional clusters varied by time but not by symptom dimension (i.e., epithelial/gastrointestinal and epithelial). A sickness behavior cluster was identified at each assessment with the exception of the week before CTX using only the severity dimension.

CONCLUSION

Findings provide insights into the most common symptom clusters in patients with lung cancer undergoing CTX. Most common symptoms within each cluster appear to be relatively stable across the two dimensions, as well as across time.

Estimating the Frequency, Severity, and Clustering of SPADE Symptoms in Chronic Painful Chemotherapy-Induced Peripheral Neuropathy

BACKGROUND

Patients undergoing treatment for cancer commonly experience symptoms such as sleep disturbance, pain, anxiety, depression, and low energy/fatigue (SPADE), subsequently altering physical function and complicating effective symptom management. However, little is known about the frequency, severity, and clustering of SPADE symptoms in individuals with chronic painful chemotherapy-induced peripheral neuropathy (CIPN). Aims/Design: The purpose of this cross-sectional, secondary analysis was to describe the frequency, severity, and clustering of SPADE symptoms and their association with physical function in individuals with chronic painful CIPN. Participants/Subjects: Sixty individuals with chronic painful CIPN were recruited from five academic and community oncology outpatient center to participate in a randomized controlled pilot trial designed to test the efficacy of a cognitive behavioral therapy-based pain management program.

METHODS

Participants completed the 0-10 Average CIPN Pain Numerical Rating Scale and Patient-Reported Outcome Measurement Information System measures for sleep-related impairment, anxiety, depression, fatigue, and pain interference via tablet before being randomly assigned to a study arm. The frequency, severity, and clustering of SPADE symptoms were calculated via descriptive statistics and Partitioning Around Medoids cluster analysis. Spearman rank correlation was performed to determine the association between number of SPADE symptoms and pain interference severity.

RESULTS AND CONCLUSIONS

Participants (n = 59) experienced numerous SPADE symptoms. 66.1% of participants experienced at least two SPADE symptoms concurrently. The cluster analysis revealed high (n = 36) and low (n = 23) severity subgroups. There was a moderate correlation (r = 0.48) between the number of SPADE symptoms and pain interference severity. Determining the clustering of SPADE symptoms in individuals with chronic painful CIPN may lead to targeted multifaceted interventions to improve physical function.

Comparison of Fatigue, Pain, and Depression in Patients With Advanced Kidney Disease and Cancer-Symptom Burden and Clusters

CONTEXT

Although symptom clusters have been studied in the context of cancer, few data exist in chronic and end-stage kidney disease (CKD/ESKD) patients.

OBJECTIVES

The objectives of this study were to 1) characterize and compare symptom cluster phenotypes in patients with advanced CKD, ESKD, and cancer and 2) explore predictors of symptom clusters.

METHODS

We conducted secondary data analysis of three prospective studies in which pain, depression, and fatigue were assessed in patients with Stage 4-5 CKD, ESKD, and gastrointestinal cancer. Tetrachoric correlations between these symptoms were quantified, and partitioning around medoids algorithm was used for symptom cluster analysis.

RESULTS

In the 82 CKD, 149 ESKD, and 606 cancer patients, no differences in the average fatigue (P = 0.17) or pain levels (P = 0.21) were observed. Over 80% of patients in each group had at least one symptom. Moderate or severe depressive symptoms were more common in patients with cancer (31% vs. 19% in ESKD vs. 9% in CKD; P < 0.001). Mild-moderate correlations were observed between the three symptoms in ESKD and cancer patients. Three distinct clusters were observed in each group. In ESKD, the HIGH cluster (with high probability of pain, depression, and fatigue) had higher body mass index (P < 0.001) and antidepressant use (P = 0.01). In cancer patients, the HIGH cluster patients were more likely to be female (P = 0.04), use antidepressants (P = 0.04), and have lower serum albumin (P < 0.001) and hemoglobin (P = 0.03) compared to the other two clusters.

CONCLUSION

Although the burden of fatigue, pain, and depressive symptoms for CKD and ESKD patients is similar to patients with gastrointestinal cancer, symptom cluster phenotypes differed between the groups as did the predictors of symptom clusters.

Nonmalignant Pain Symptom Subgroups in Nursing Home Residents

CONTEXT

Despite many nursing home residents experiencing pain, research about the multidimensional nature of nonmalignant pain in these residents is scant.

OBJECTIVES

To identify and describe pain symptom subgroups and to evaluate whether subgroups differed by sex.

METHODS

Using Minimum Data Set 3.0 data (2011-2012), we identified newly admitted nursing home residents reporting pain (n = 119,379). A latent class analysis included 13 indicators: markers for pain (i.e., severity, frequency, impacts sleep, and function) and depressive symptoms. Sex was evaluated as a grouping variable. Multinomial logistic models identified the association between latent class membership and covariates, including age and cognitive impairment.

RESULTS

Four latent subgroups were identified: severe (15.2%), moderate frequent (26.4%), moderate occasional with depressive symptoms (26.4%), and moderate occasional without depressive symptoms (32.0%). Measurement invariance by sex was ruled out. Depressed mood, sleep disturbances, and fatigue distinguished subgroups. Age ≥75 years was inversely associated with belonging to the severe, moderate frequent, or moderate occasional with depressive symptoms subgroups. Residents with severe cognitive impairment had reduced odds of membership in the severe pain subgroup (adjusted odds ratio [aOR]: 0.84; 95% confidence interval [CI]: 0.78-0.90) and moderate frequent pain subgroup (aOR: 0.60; 95% CI: 0.56-0.64) but increased odds in the moderate occasional pain with depressive symptoms subgroup (aOR: 1.12; 95% CI: 1.06-1.18).

CONCLUSION

Identifying subgroups of residents with different patterns of pain and depressive symptoms highlights the need to consider physical and psychological components of pain. Expanding knowledge about pain symptom subgroups may provide a promising avenue to improve pain management in nursing home residents.

A systematic review of natural language processing and text mining of symptoms from electronic patient-authored text data

OBJECTIVE

In this systematic review, we aim to synthesize the literature on the use of natural language processing (NLP) and text mining as they apply to symptom extraction and processing in electronic patient-authored text (ePAT).

MATERIALS AND METHODS

A comprehensive literature search of 1964 articles from PubMed and EMBASE was narrowed to 21 eligible articles. Data related to purpose, text source, number of users and/or posts, evaluation metrics, and quality indicators were recorded.

RESULTS

Pain (n = 18) and fatigue and sleep disturbance (n = 18) were the most frequently evaluated symptom clinical content categories. Studies accessed ePAT from sources such as Twitter and online community forums or patient portals focused on diseases, including diabetes, cancer, and depression. Fifteen studies used NLP as a primary methodology. Studies reported evaluation metrics including the precision, recall, and F-measure for symptom-specific research questions.

DISCUSSION

NLP and text mining have been used to extract and analyze patient-authored symptom data in a wide variety of online communities. Though there are computational challenges with accessing ePAT, the depth of information provided directly from patients offers new horizons for precision medicine, characterization of sub-clinical symptoms, and the creation of personal health libraries as outlined by the National Library of Medicine.

CONCLUSION

Future research should consider the needs of patients expressed through ePAT and its relevance to symptom science. Understanding the role that ePAT plays in health communication and real-time assessment of symptoms, through the use of NLP and text mining, is critical to a patient-centered health system.

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.

Capturing the complexity of mental disorders in the medically ill: the network approach on behavioral medicine

Since Descartes introduced dualism, body and mind have been seen as separate entities. The latent disease model, the view that symptoms are caused by an underlying disease, was possible within the dualistic paradigm. This paradigm, although successful in some aspects of medicine, is also assumed to underlie psychiatric disorders. As an alternative to the latent disease model, the network approach conceptualizes disorders as complex networks of causally connected symptoms. It offers a new way of understanding psychiatric disorders by directing attention away from the underlying cause and towards the symptoms and their functional interconnectedness, making the distinction between mental and physical symptoms obsolete. This article discusses how the network perspective helps us to overcome some of the problems we have faced when diagnosing and treating psychopathology in the medically ill. Furthermore, we describe how the network perspective can stimulate new research to better understand psychopathology in medically ill patients and how it can help deliver the most suitable treatment to the individual patient.

Acute Coronary Syndrome Symptom Clusters: Illustration of Results Using Multiple Statistical Methods

Researchers have employed various methods to identify symptom clusters in cardiovascular conditions, without identifying rationale. Here, we test clustering techniques and outcomes using a data set from patients with acute coronary syndrome. A total of 474 patients who presented to emergency departments in five United States regions were enrolled. Symptoms were assessed within 15 min of presentation using the validated 13-item ACS Symptom Checklist. Three variable-centered approaches resulted in four-factor solutions. Two of three person-centered approaches resulted in three-cluster solutions. K-means cluster analysis revealed a six-cluster solution but was reduced to three clusters following cluster plot analysis. The number of symptoms and patient characteristics varied within clusters. Based on our findings, we recommend using (a) a variable-centered approach if the research is exploratory, (b) a confirmatory factor analysis if there is a hypothesis about symptom clusters, and (c) a person-centered approach if the aim is to cluster symptoms by individual groups.

Identification of Distinct Latent Classes Related to Sleep, PTSD, Depression, and Anxiety in Individuals Diagnosed With Severe Alcohol Use Disorder

Objective/Background: Alcohol use disorders (AUDs) are often accompanied by comorbid physiologic and psychosocial conditions, including sleep disturbances. Sleep disturbances in these individuals may be associated with increased risk of relapse to drinking following detoxification and rehabilitation. Participants: The sample of inpatient treatment-seeking individuals with AUDs (N = 164) was 70.1% male and 47.6% African American with a mean age of 45.6 years (±9.5 years). Methods: Latent class analysis (LCA) was used to identify unmeasured class membership based on seven indicators: maximum Clinical Institute Withdrawal Assessment (CIWA) scores; sleep efficiency (actigraphy); sleep disturbances (Pittsburgh Sleep Quality Index-PSQI); anxiety or depression (Comprehensive Psychopathological Rating Scale [CPRS]); and current and lifetime posttraumatic stress disorder (PTSD). Results: The average number of drinking days in the 90 days preceding admission was 72.0 (±22.0 days), with an average of 13.16 drinks per day (±5.70 drinks). Nearly one quarter (24.4%) of respondents reported lifetime PTSD. Three latent classes were identified: Sleep Disturbance (SD); Sleep Disturbance, Anxiety and Depression (SD/AD); and Sleep Disturbance, Anxiety and Depression, and PTSD (SD/AD/PTSD). Members of the SD/AD/PTSD group were more likely to be female and had the highest withdrawal and sleep disturbance scores of all three groups. Conclusion: Findings support the use of LCA to identify subgroups of individuals with AUDs and accompanying sleep disturbances. Class identification may provide clinicians with insight into the integrative tailoring of interventions that meet the varied needs of individuals with AUDs, accompanying comorbidities, and sleep disturbances.

Using Cluster Analysis to Identify Subgroups of College Students at Increased Risk for Cardiovascular Disease

BACKGROUND AND PURPOSE

 To examine the co-occurrence of cardiovascular risk factors and cluster subgroups of college students for cardiovascular risks.

METHODS

A cross sectional descriptive study was conducted using co-occurrence patterns and hierarchical clustering analysis in 158 college students.

RESULTS

The top co-occurring cardiovascular risk factors were overweight/obese and hypertension (10.8%, n = 17). Of the total 34 risk factors that co-occurred, 30 of them involved being overweight/obese. A six-cluster-solution was obtained, two clusters displayed elevated levels of lifetime and 30-year cardiovascular disease risks.

CONCLUSIONS

The hierarchical cluster analysis identified that single White males with a family history of heart disease, overweight/obese, hypertensive or diabetes, and occasionally (weekly) consumed red meat, take antihypertensive medication, and hyperlipidemia were considered the higher risk group compared to other subgroups.

Why do I have to suffer? Symptom management, views and experiences of persons with a CPTSD: a grounded theory approach

BACKGROUND

For the 11th version of the International Classification of Diseases, a new stress related diagnosis has been proposed: complex post-traumatic stress disorder (CPTSD). It is described as a chronic condition with several severe and concurrent symptoms. In the literature, these symptoms are discussed as a common reason for seeking psychiatric treatment as they can influence and impair the quality of life not only for affected persons but also for their social and familial system.

AIM

This research studies symptom management in everyday life by exploring and reconstructing the views, perceptions, experiences, facilitators and barriers of adults with CPTSD.

METHODS

A theoretical sampling was used to recruit 18 to 65 years old patients diagnosed with CPTSD from an inpatient setting. The 17 semi-structured interviews were audio recorded and transcribed verbatim. The transcriptions were uploaded into MAXQDA, and a Grounded Theory method based on Corbin and Strauss was used to analyse the data.

RESULTS

We provide a process model with 5 interacting phases: trauma experience, emotional ignorance, overcompensation, paroxysm, and perspectives. Each phase is specified with subcategories.

CONCLUSIONS

The participants did not recognise their symptoms as such and were unaware of their diagnosis for many years. Nevertheless, they used various resources and were able to develop skills and techniques to deal with their symptoms and to function on a day-to-day basis. Overall, the process of symptom management was extremely exhausting for the participants and they felt left alone with it. The participants were eager to gain support from healthcare professionals and, when necessary, financial support from the government. Thus, these results indicate an essential need to develop support and tailored interventions for the symptom management of persons with a CPTSD.

TRIAL REGISTRATION

Ethical approval was obtained from the Swiss Cantonal Ethic Commission (Nr 201,500,096). This research was also registered at the World Health Organization Clinical Trials Search Portal through the German Clinical Trial Register, Trial DRKS00012268 .