Distinct Patient Profiles Research Articles

Patient Profiles in the Utilization of the CanGaroo® Envelope.

BackgroundThe CanGaroo® Envelope (Aziyo Biologics, Silver Spring, MD) is intended to securely hold a cardiovascular implantable electronic device (CIED) to create a stable environment when implanted in the body. Data on the utilization of this newly available product are limited.ObjectiveIn this study, our objective was to describe the specific profiles of patients who may benefit from the use of the CanGaroo® Envelope at the time of CIED implantation.Methods The utilization of the CanGaroo® Envelope was assessed from January 2019 to October 2019 among a series of patients who were either undergoing de-novo CIED implantation or replacement.ResultsAmong a total of 50 patients, the CanGaroo® Envelope was utilized in 15 (30%). Three distinct patient profiles were identified: profile 1: elderly patients with poor tissue turgor at risk of wound dehiscence or erosion; profile 2: patients with a history of previous device infection; and profile 3: patients at high risk of device infection having one or more of the following risk factors - chronic kidney disease, immunocompromised state, or diabetes mellitus. At a mean follow-up of 18 ±3 months, no CIED pocket erosion, dehiscence, or infection was noted.ConclusionsThree distinct profiles of patients who could potentially benefit from the use of the CanGaroo® Envelope were identified by the implanting physicians. Long-term follow-up data, including infection and wound dehiscence rates, are necessary to further analyze the optimal utilization of the device.

Use of Latent Class Analysis and k-Means Clustering to Identify Complex Patient Profiles

Medically complex patients are a heterogeneous group that contribute to a substantial proportion of health care costs. Coordinated efforts to improve care and reduce costs for this patient population have had limited success to date. To define distinct patient clinical profiles among the most medically complex patients through clinical interpretation of analytically derived patient clusters. This cohort study analyzed the most medically complex patients within Kaiser Permanente Northern California, a large integrated health care delivery system, based on comorbidity score, prior emergency department admissions, and predicted likelihood of hospitalization, from July 18, 2018, to July 15, 2019. From a starting point of over 5000 clinical variables, we used both clinical judgment and analytic methods to reduce to the 97 most informative covariates. Patients were then grouped using 2 methods (latent class analysis, generalized low-rank models, with k-means clustering). Results were interpreted by a panel of clinical stakeholders to define clinically meaningful patient profiles. Complex patient profiles, 1-year health care utilization, and mortality outcomes by profile. The analysis included 104 869 individuals representing 3.3% of the adult population (mean [SD] age, 70.7 [14.5] years; 52.4% women; 39% non-White race/ethnicity). Latent class analysis resulted in a 7-class solution. Stakeholders defined the following complex patient profiles (prevalence): high acuity (9.4%), older patients with cardiovascular complications (15.9%), frail elderly (12.5%), pain management (12.3%), psychiatric illness (12.0%), cancer treatment (7.6%), and less engaged (27%). Patients in these groups had significantly different 1-year mortality rates (ranging from 3.0% for psychiatric illness profile to 23.4% for frail elderly profile; risk ratio, 7.9 [95% CI, 7.1-8.8], P < .001). Repeating the analysis using k-means clustering resulted in qualitatively similar groupings. Each clinical profile suggested a distinct collaborative care strategy to optimize management. The findings suggest that highly medically complex patient populations may be categorized into distinct patient profiles that are amenable to varying strategies for resource allocation and coordinated care interventions.

Distinct Subgroups of Patients With Lung Cancer Receiving Chemotherapy: A Latent Transition Analysis.

ObjectivesTo identify subgroups of patients with lung cancer receiving chemotherapy based on the severity dimension of symptom experience, and to examine changes in membership between these subgroups over time.MethodsPatients who were scheduled to receive chemotherapy completed the Chinese version of the MD Anderson Symptom Inventory and the revised lung cancer module with a total of 19 symptom items. Data were collected at three time points: two weeks before chemotherapy (T1), after chemotherapy cycle 1 (T2), and after chemotherapy cycle 3 or above (T3). The latent profile analysis and latent transition analysis were used to identify underlying subgroups and describe changes in subgroup membership over time.ResultsFrom the total sample (N = 195), 160 patients completed the symptom assessment at T1, T2, and T3. Two distinct latent symptom profiles of patients could be identified at T1, T2, and T3, which were classified as “Mild” and “Moderate-Severe” profiles. From T1 to T2 and T3, members in the Mild profile were more likely to move to the Moderate-Severe profile. Chemotherapy protocols, prior surgery treatment, and level of education can predict the transitions.ConclusionResults provide a better understanding of the patient’s different symptom experiences and characteristics. These could help clinicians to anticipate symptom patterns and develop interventions in lung cancer patients who were scheduled to receive chemotherapy for the first time.

Distinct RT-PCR diagnosis profiles of father and son patients of COVID-19 using nasopharyngeal and alveolar lavage fluid samples

Distinct RT-PCR diagnosis profiles of father and son patients of COVID-19 using nasopharyngeal and alveolar lavage fluid samples

Patient Characteristics and Outcomes of Relapsed/Refractory Multiple Myeloma in Patients Treated with Proteasome Inhibitors in Germany

Introduction: Real-world data reflects treatments and outcomes in clinical practice in contrast with controlled clinical trials. This study evaluates real-life multiple myeloma (MM) patients receiving proteasome inhibitor (PI)-based treatments in the second or third therapy line in 2017 in Germany. Methods: This is a retrospective chart review on adult relapsed/refractory MM patients treated with ≥1 dose of a PI-based regimen in either the second or the third line of therapy. Participating physicians had ≥3 years of clinical experience in treating symptomatic MM patients and used PI according to the label. Results: Distinct patient profiles for each PI-based regimen emerged. Younger, fitter, transplant-eligible patients received novel PI triplets such as carfilzomib in combination with lenalidomide and dexamethasone (KRd) or IRd. Patients receiving lenalidomide in first-line therapy mostly received lenalidomide-free regimens in second-line therapy. In high-risk patients, no clear treatment patterns could be ascertained. The complete response rates were highest with KRd (13.0%), followed by carfilzomib in combination with dexamethasone (Kd) (5.7%) and bortezomib (4.8%). The very good partial response rates were highest with IRd (76.9%), followed by KRd (53.7%), Kd (25.7%), and bortezomib (20.5%). None of the KRd- or IRd-treated patients responded below a partial response. Discussion/Conclusion: Clear patient profiles for each PI type were observed. In second-line therapy, younger, fitter, transplant-eligible patients received novel-PI-based triplets, e.g., KRd or IRd. Patients treated with lenalidomide in first-line therapy mostly received lenalidomide-sparing regimens in second-line therapy. In high-risk patients no clear treatment patterns could be ascertained due to the limited sample size.

OP0257-PARE USING PATIENT HEALTH LITERACY PROFILES TO IDENTIFY SOLUTIONS TO CHALLENGES FACED IN RHEUMATOLOGY CARE

Background:The prevalence of limited health literacy (i.e. cognitive and social resources of individuals to access, understand and apply health information to promote and maintain good health) in the Netherlands is estimated to be over 36% [1]. Access to and outcomes of rheumatological care may be compromised by limited patient health literacy, yet little is known about how to address this, thus action is required. As influencing individual patients’ health literacy in the rheumatology context is often unrealistic, it is paramount for the health system to be tailored to the health literacy needs of its patients. The OPtimising HEalth LIteracy and Access (Ophelia) process offers a method to inform system change [2].Objectives:Following the Ophelia approach:a. Identify health literacy profiles reflecting strengths and weaknesses of outpatients with RA, SpA and gout.b. Use the health literacy profiles to facilitate discussions on challenges for patients and professionals in rheumatological care and identify possible solutions the health system could offer to address these challenges.Methods:Patients with RA, SpA and gout attending outpatient clinics in three centres in the Netherlands completed the Health Literacy Questionnaire (HLQ) and questions on socio-demographic and health-related characteristics. Hierarchical cluster analysis using Ward’s method identified clusters based on the nine HLQ domains. Three researchers jointly examined 24 cluster solutions for meaningfulness by interpreting HLQ domain scores and patient characteristics. Meaningful clusters were translated into health literacy profiles using HLQ patterns and demographic data. A patient research partner confirmed the identified profiles. Patient vignettes were designed by combining cluster analyses results with qualitative patient interviews. The vignettes were used in two two-hour co-design workshops with rheumatologists and nurses to discuss their perspective on health literacy-related challenges for patients and professionals, and generate ideas on how to address these challenges.Results:In total, 895 patients participated: 49% female, mean age 61 years (±13.0), 25% lived alone, 18% had a migrant background, 6.6% did not speak Dutch at home and 51% had low levels of education. Figure 1 shows a heat map of identified health literacy profiles, displaying the score distribution per profile across nine health literacy domains. Figure 2 shows an excerpt of a patient vignette, describing challenges for a patient with profile number 9. The workshops were attended by 7 and 14 nurses and rheumatologists. Proposed solutions included health literacy communication training for professionals, developing and improving (visual) patient information materials, peer support for patients through patient associations or group consultations, a clear referral system for patients who need additional guidance by a nurse, social worker, lifestyle coach, pharmacist or family doctor, and more time with rheumatology nurses for target populations. Moreover, several system adaptations to the clinic, such as a central desk for all patient appointments, were proposed.Conclusion:This study identified several distinct health literacy profiles of patients with rheumatic conditions. Engaging with health professionals in co-design workshops led to numerous bottom-up ideas to improve care. Next steps include co-design workshops with patients, followed by prioritising and testing proposed interventions.

The power of immune profiling: quantitative flow cytometry and informatics approaches to generate pooled biomarkers for therapeutic responsiveness to immune and cellular therapies

Background & Aim Enumerating circulating white blood cells in peripheral blood using flow cytometry is a popular method for tracking changes in the immune system. We have developed a methodology using quantitative flow cytometry to study 100+ phenotypes in combination with bioinformatic approaches to identify characteristic immune profiles or combinations of similarly expressed leukocytes among patient groups. Currently, aside from survival and degree of disease progression or treatment benefit there is a lack of methods for identifying active changes to the immune system and good markers for identify cause of adverse events, all problems which could be solved with the use of immune monitoring. Currently, the Mayo clinic has utilized this method in over 30% of their MSC, DC, and CAR-T clinical trials with the intent of monitoring all trials using this methodology. Thus far we have applied this analysis to disease patient groups such as amyotrophic lateral sclerosis, thyroid cancer, liver cancer, glioblastoma multiforme, and chronic lymphocytic leukemia. Methods, Results & Conclusion These analyses uncovered previously unidentified subgroups of ALS patients that predicted survival, biomarkers in diseased patients, and changes in the immune systems of those in clinical trials. When clustered with healthy volunteers, we found two distinct profiles of ALS patients, one that more closely resembled a healthy immune system and one that did not. Patients that profiled separately from healthy volunteers had unique phenotypic characteristics such as increased absolute counts of CD3+CD56+ (p>0.001), CD3+CD8+CD28+ (p>0.001), CD3+CD4+PD-1+ T cells, increased survival (p=0.012), and were more likely to have familial ALS rather than sporadic (p=0.011). Additionally, we have tested our system on a cohort of 130 healthy volunteers to see which immune parameters contribute most to clustering of non-diseased individuals. Thus, we believe that profiling patients based on their immune systems can aid in predicting which immune modulating therapies will be most effective and in the future help in tailoring immune therapies specific to the patient. Based on our work we have confidence that immune monitoring it is key in unlocking complex mechanisms between the various components of the immune system that are critical to wound repair, healing and regenerative medicine as well as an essential tool for clinical trials.

Profiling of Patients with COPD for Adequate Referral to Exercise-Based Care: The Dutch Model

A loss of physical functioning (i.e., a low physical capacity and/or a low physical activity) is a common feature in patients with chronic obstructive pulmonary disease (COPD). To date, the primary care physiotherapy and specialized pulmonary rehabilitation are clearly underused, and limited to patients with a moderate to very severe degree of airflow limitation (GOLD stage 2 or higher). However, improved referral rates are a necessity to lower the burden for patients with COPD and for society. Therefore, a multidisciplinary group of healthcare professionals and scientists proposes a new model for referral of patients with COPD to the right type of exercise-based care, irrespective of the degree of airflow limitation. Indeed, disease instability (recent hospitalization, yes/no), the burden of disease (no/low, mild/moderate or high), physical capacity (low or preserved) and physical activity (low or preserved) need to be used to allocate patients to one of the six distinct patient profiles. Patients with profile 1 or 2 will not be referred for physiotherapy; patients with profiles 3–5 will be referred for primary care physiotherapy; and patients with profile 6 will be referred for screening for specialized pulmonary rehabilitation. The proposed Dutch model has the intention to get the right patient with COPD allocated to the right type of exercise-based care and at the right moment.

A multi-level assessment of shared decision making: An evaluation of clinician and patient attitudes and behaviors and the identification of predictive profiles

The objective of this study was to gain a greater understanding of shared decision making (SDM) by identifying the behaviors and attitudes of healthcare professionals (HCP) and patients that are associated with varying levels of SDM performance. The study centered on HCP and patient surveys that assessed a participant’s degree of endorsement of SDM favorable behaviors by asking them to predict how they might address a specific decision point in various healthcare interactions. Using quantitative (descriptive analytics, predictive and mixture modeling) and qualitative methods (grounded theory) to analyze the data, SDM skills were quantified in HCP and patient populations, and demographic and attitudinal factors that facilitate or hinder successful implementation of SDM were identified. Distinct HCP profiles (Motivated but Cautious, Insufficiently Engaged, and Pro-Autonomous) and patient profiles (Pro-Paternalistic, Pro-Autonomous, and Unconcerned but Open-Minded) were then defined. By characterizing these distinct profiles and the attitudes and preferences that are associated with one another, these results can be directly utilized by educational providers interested in teaching SDM skills to enable HCPs to individualize their SDM approach based on the recognition of these profiles while also providing the self-assessment needed to modify their own behaviors.

Distinct biomarker and behavioral profiles of human papillomavirus-related oropharynx cancer patients by age.

HPV-positive oropharynx squamous cell cancer (HPV-OPC) patients were initially described as younger, however incidence has increased among older age-groups. It is unknown why some patients present at a younger age and others at a later age. Multi-institutional prospective study of HPV-OPC cases (n=163) and matched controls (n=345) with detailed behavioral survey, and serum tested for HPV antibodies by fluorescent bead-based technology. Age at diagnosis was used to stratify patients into younger (≤50years), middle-age (51-65), and older (>65). By age, demographic characteristics were largely similar, but HPV biomarkers and sexual acts differed. Younger cases were more likely to be HPV16-positive than older cases (100% vs 77%, p=0.009). Similarly, younger cases were more likely to be HPV16 E6 or E7 seropositive (100% vs 82%, p=0.03). Younger cases had a higher number of oral sex partners per year, a marker of sexual intensity (sex-years, p=0.003), but a similar number of lifetime oral sex partners (measure of cumulative sexual exposure), compared to older cases. While sex-years were higher for younger cases and controls, cases had significantly higher sex-years than matched controls in each age-group (p<0.001). Younger patients were also more likely to perform oral sex at sexual debut, and were younger at sexual debut (each p<0.03). Younger, middle-age and older HPV-OPC have distinct biomarker and behavioral profiles. Younger HPV-OPC cases have higher intensity of sexual exposure than older cases and controls, which may in part explain earlier disease onset. The distribution of HPV16-positive tumors among HPV-OPC differs by age group.

Latent Profiles of Cognitive Control, Episodic Memory, and Visual Perception Across Psychiatric Disorders Reveal a Dimensional Structure.

Although meta-analyses suggest that schizophrenia (SZ) is associated with a more severe neurocognitive phenotype than mood disorders such as bipolar disorder, considerable between-subject heterogeneity exists in the phenotypic presentation of these deficits across mental illnesses. Indeed, it is unclear whether the processes that underlie cognitive dysfunction in these disorders are unique to each disease or represent a common neurobiological process that varies in severity. Here we used latent profile analysis (LPA) across 3 distinct cognitive domains (cognitive control, episodic memory, and visual integration; using data from the CNTRACS consortium) to identify distinct profiles of patients across psychotic illnesses. LPA was performed on a sample of 223 psychosis patients (59 with Type I bipolar disorder, 88 with SZ, and 76 with schizoaffective disorder). Seventy-three healthy control participants were included for comparison but were not included in sample LPA. Three latent profiles ("Low," "Moderate," and "High" ability) were identified as the underlying covariance across the 3 domains. The 3-profile solution provided highly similar fit to a single continuous factor extracted by confirmatory factor analysis, supporting a unidimensional structure. Diagnostic ratios did not significantly differ between profiles, suggesting that these profiles cross diagnostic boundaries (an exception being the Low ability profile, which had only one bipolar patient). Profile membership predicted Brief Psychiatric Rating Scale and Young Mania Rating Scale symptom severity as well as everyday communication skills independent of diagnosis. Biological, clinical and methodological implications of these findings are discussed.

Using item response theory with health system data to identify latent groups of patients with multiple health conditions.

A critical step toward tailoring effective interventions for heterogeneous and medically complex patients is to identify clinically meaningful subgroups on the basis of their comorbid conditions. We applied Item Response Theory (IRT), a potentially useful tool to identify clinically meaningful subgroups, to characterize phenotypes within a cohort of high-risk patients. This was a retrospective cohort study using 68,400 high-risk Veteran’s Health Administration (VHA) patients. Thirty-one physical and mental health diagnosis indicators based on ICD-9 codes from patients’ inpatient, outpatient VHA and VA-paid community care claims. Results revealed 6 distinct subgroups of high-risk patients were identified: substance use, complex mental health, complex diabetes, liver disease, cancer with cardiovascular disease, and cancer with mental health. Multinomial analyses showed that subgroups significantly differed on demographic and utilization variables which underscored the uniqueness of the groups. Using IRT models with clinical diagnoses from electronic health records permitted identification of diagnostic constellations among otherwise undifferentiated high-risk patients. Recognizing distinct patient profiles provides a framework from which insights into medical complexity of high-risk patients can be explored and effective interventions can be tailored.

Distinct Aqueous Humour Cytokine Profiles of Patients with Pachychoroid Neovasculopathy and Neovascular Age-related Macular Degeneration

This study investigated the pathophysiological features of pachychoroid neovasculopathy (PNV) and neovascular age-related macular degeneration (nAMD) by analysing and comparing cytokine profiles in aqueous humour (AH) collected from 18 PNV, 18 nAMD and 11 control patients. Responses to intravitreal injection of aflibercept were also analysed in the PNV and nAMD groups. In the PNV group, vascular endothelial growth factor (VEGF)-A was significantly lower than in the nAMD group (p = 0.03) but was almost identical to that in the control group (p = 0.86). The nAMD group showed positive correlations between interleukin (IL)-6 and IL-8 (r = 0.78, p < 0.001), IL-6 and monocyte chemoattractant protein (MCP)-1 (r = 0.68, p = 0.002) and IL-8 and MCP-1 (r = 0.68, p = 0.002). In the nAMD group, eyes with dry maculae one month after the first aflibercept injection showed significantly lower VEGF-A and placental growth factor (PlGF) at baseline than those with wet maculae (p = 0.02 for both). However, there was no significant difference between dry and wet maculae in the PNV group. The results suggest that angiogenic factors and proinflammatory cytokines may play the distinct roles in the pathogenesis of PNV and nAMD.

Art therapy and underlying fMRI brain patterns in military TBI: A case series

ABSTRACTTBI and PTSD are global issues and are often referred to as signature wounds of the Iraq and Afghanistan wars. Art therapy can provide unique insights into military service members’ injuries and states of mind via externalisation within an art product; however, interpretation of results is complex and subjective. Advance neuroimaging tools such as resting state fMRI can be employed to demonstrate objective measures of brain structure and activity. This case series highlights two distinct patient profiles, suggesting a relationship between resting state connectivity maps and dynamic thalamic connectivity (as well as PCL-C and NSI scores and brain scars) and the corresponding visual elements of masks made during art therapy treatment. Ultimately, this study indicates a need for future research examining potential neurological changes pre- and post-art therapy treatment.

Differential protein profiling as a potential multi-marker approach for obese patients with heart failure: A retrospective study

Identification of novel circulating biomarkers predicting death and major cardio-metabolic events in obese patients with heart failure (HF) remains a research priority. In this study, we compared multi-marker profile of non-obese (NOB) and obese (OB) HF patients in relation to mortality outcome. The new multiplex proximity extension assay technology was used to analyze the levels of 92 proteins in plasma samples from HF patients according to body mass index (BMI) categories. At 2-year follow-up, all-cause mortality rates were significantly greater in NOB patients (BMI < 30 kg/m2) compared to the OB patients (BMI > 30 kg/m2) with HF (odds ratio 26; 95% CI: 1.14–624, p < 0,04). Quantitative proteomic analysis revealed thirteen distinct proteins expression profiles of OB and NOB HF patients. Among these proteins, RAGE, CXCL6, CXCL1, CD40, NEMO, VEGF-A, KLK6, PECAM1, PAR1, MMP1, BNP and NTproBNP were down-regulated, whereas leptin was up-regulated in OB HF patients. In addition, an inverse correlation between plasma BNP levels and leptin in OB HF patients was observed (r = −0.58 p = 0.02). This study identifies specific plasma protein signature in OB and NOB patients with HF in relation to mortality outcome.

Profile of musculoskeletal pain in patients with inflammatory bowel disease: a study protocol for assessing the multidimensional experience of self-reported pain

Background: Pain is known to affect over 70% of individuals with inflammatory bowel disease (IBD), with abdominal and musculoskeletal (MSK) pain representing the most common complaints in this population. Although possible mediating and overlapping pathways have been proposed in the development of MSK pain in IBD, the multifactorial nature of painful conditions is not well understood nor fully captured.Aims: Primary aims are to characterize MSK pain in individuals with IBD through a national survey, in order to identify patient subgroups based on self-reported features of pain and assess how these subgroups differ with regards to demographics, comorbidity, and IBD characteristics.Methods: The present study is a cross-sectional online survey of adults with IBD and self-reported pain, living in New Zealand. The survey includes a range of measures examining demographics and comorbidity, IBD status (type, activity, and severity of IBD course), and pain status (intensity, location, interference, and quality). Latent class analysis will be used to generate mechanism-based subgroups of pain in this populationDiscussion: The present study will gather data on the multidimensional experience of self-reported MSK pain in IBD, and describe subgroups of pain in this population. Subgrouping has been shown to generate distinct profiles of patients with similar attributes, while permitting comparison of features between subgroups. Use of mechanism-based classification provides the opportunity to understand differing and potentially overlapping contributions of pathophysiological pain mechanisms. Results from the present study will be used to develop a clinical framework for assessing and describing MSK pain in IBD.

Profiles of patient and tumour characteristics in relation to health-related quality of life after oesophageal cancer surgery.

Strong deterioration in health-related quality of life (HRQOL) is a major concern in a sub-group of long-term oesophageal cancer survivors. This study aimed to identify potential clustering of patients and tumour variables that predicts such deterioration. Patient and tumour variables were collected in a prospective cohort of patients who underwent surgery for oesophageal cancer in Sweden 2001–2005. Latent cluster analysis identified statistically significant clustering of these variables. Multivariable logistic regression adjusted for age, BMI, tumour stage and marital status was used to determine odds ratios (ORs) with 95% confidence intervals (CIs) between patient profiles and HRQOL at 3 and 5 years from surgery. Among 155 included patients at 3 years, three patient profiles were identified: 1) ‘reference profile’ (males, younger age, employed, upper secondary education, co-habitating, urban dwellers, adenocarcinoma and advanced tumour stage) (n = 47;30%), 2) ‘adenocarcinoma profile’ (middle age, unemployed/retired, males, low education, co-habitating, adenocarcinoma, advanced tumour stage, tumour in lower oesophagus/cardia, and co-morbidities (n = 79;51%), and 3) ‘squamous-cell carcinoma profile’ (unemployed/retired, middle-age, males, low BMI, urban dwellers, squamous-cell carcinoma, tumour in upper/middle oesophagus (n = 29;19%). These profiles did not differ regarding most HRQOL measures. Exceptions were the squamous-cell carcinoma profile, reporting more constipation (OR = 5.69; 95%CI: 1.34–24.28) and trouble swallowing saliva (OR = 4.87; 95%CI: 1.04–22.78) and the adenocarcinoma profile reporting more dyspnoea (OR = 2.60; 95%CI: 1.00–6.77) and constipation (OR = 3.31; 95%CI: 1.00–10.97) compared to the reference profile. Three distinct patient profiles were identified but these could not explain the substantial deterioration in HRQOL observed in the sub-sample of survivors.

The dissociative post-traumatic stress disorder (PTSD) subtype: A treatment outcome cohort study in veterans with PTSD.

Dissociation is a prevalent phenomenon among veterans with post-traumatic stress disorder (PTSD) that may interfere with the effectiveness of treatment. This study aimed to replicate findings of a dissociative PTSD subtype, to identify corresponding patterns in coping style, symptom type, and symptom severity, and to investigate its impact on post-traumatic symptom improvement. Latent profile analysis (LPA) was applied to baseline data from 330 predominantly (97%) male treatment-seeking veterans (mean age 39.5years) with a probable PTSD. Multinomial logistic models were used to identify predictors of dissociative PTSD. Eighty veterans with PTSD that commenced with psychotherapy were invited for a follow-up measure after 6months. The majority (n=64, 80% response rate) completed the follow-up measure. Changes in post-traumatic stress between baseline and follow-up were explored as a continuous distal outcome. Latent profile analysis revealed four distinct patient profiles: 'low' (12.9%), 'moderate' (33.2%), 'severe' (45.1%), and 'dissociative' (8.8%) PTSD. The dissociative PTSD profile was characterized by more severe pathology levels, though not post-traumatic reactions symptom severity. Veterans with dissociative PTSD benefitted equally from PTSD treatment as veterans with non-dissociative PTSD with similar symptom severity. Within a sample of veterans with PTSD, a subsample of severely dissociative veterans was identified, characterized by elevated severity levels on pathology dimensions. The dissociative PTSD subtype did not negatively impact PTSD treatment. The present findings confirmed the existence of a distinct subgroup veterans that fit the description of dissociative PTSD. Patients with dissociative PTSD subtype symptoms uniquely differed from patients with non-dissociative PTSD in the severity of several psychopathology dimensions. Dissociative and non-dissociative PTSD patients with similar post-traumatic severity levels showed similar levels of improvement after PTSD treatment. The observational design and small sample size caution interpretation of the treatment outcome data. The IES-R questionnaire does not assess all PTSD DSM-IV diagnostic criteria (14 of 17), although it is considered a valid measure for an indication of PTSD.

A Longitudinal Study of PROMIS Pediatric Symptom Clusters in Children Undergoing Chemotherapy

ContextChildren in treatment for cancer experience multiple, troubling, and interrelated symptoms. Analyzing the interrelatedness of symptoms and how that changes during treatment could yield clinically relevant patient profiles to guide patient care. ObjectivesThe aims were to identify pediatric profiles with respect to Patient-Reported Outcomes Measurement Information System® (PROMIS®; U.S. Department of Health and Human Services, National Institutes of Health) symptom measures, changes in profile status throughout a chemotherapy cycle, and if a baseline single-item fatigue measure could significantly predict symptom profile status and its changes. MethodsIn a longitudinal, single-site, three data point (T1, T2, and T3) design, children between 8 and 18 years completed the PROMIS Pediatric short form measures for fatigue, depression, anxiety, and pain and one fatigue item from the Symptom Distress Scale. Latent profile analysis and latent transition analysis were conducted. ResultsAbout 96 children participated; 58.3% were between 13 and 18 years, and 54.2% were males. Two latent profiles (less severe symptoms and severe symptoms) were identified. The prevalence of the severe symptom profile remained relatively unchanged from T1 to T2 but significantly declined at T3. The baseline single-item fatigue score significantly predicted the child's profile membership and its changes. ConclusionChildren experiencing troubling symptoms during cancer treatment are heterogeneous. With respect to the PROMIS symptom measures, two a priori unknown distinct latent profiles of patients were identified in a course of chemotherapy, and the transitions in the profile status were significantly predicted by a baseline single-item fatigue measure.

Comprehensive immune profiling reveals substantial immune system alterations in a subset of patients with amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a median lifespan of 2–3 years after diagnosis. There are few meaningful treatments that alter progression in this disease. Preclinical and clinical studies have demonstrated that neuroinflammation may play a key role in the progression rate of ALS. Despite this, there are no validated biomarkers of neuroinflammation for use in clinical practice or clinical trials. Biomarkers of neuroinflammation could improve patient management, provide new therapeutic targets, and possibly help stratify clinical trial selection and monitoring. However, attempts to identify a singular cause of neuroinflammation have not been successful. Here, we performed multi-parameter flow cytometry to comprehensively assess 116 leukocyte populations and phenotypes from lymphocytes, monocytes, and granulocytes in a cohort of 80 ALS patients. We identified 32 leukocyte phenotypes that were altered in ALS patients compared to age and gender matched healthy volunteers (HV) that included phenotypes of both inflammation and immune suppression. Unsupervised hierarchical clustering and principle component analysis of ALS and HV immunophenotypes revealed two distinct immune profiles of ALS patients. ALS patients were clustered into a profile distinct from HVs primarily due to differences in a multiple T cell phenotypes, CD3+CD56+ T cells and HLA-DR on monocytes. Patients clustered into an abnormal immune profile were younger, more likely to have a familial form of the disease, and survived longer than those patients who clustered similarly with healthy volunteers (344 weeks versus 184 weeks; p = 0.012). The data set generated from this study establishes an extensive accounting of immunophenotypic changes readily suitable for biomarker validation studies. The extensive immune system changes measured in this study indicate that normal immune homeostatic mechanisms are disrupted in ALS patients, and that multiple immune states likely exist within a population of patients with ALS.