First-in-human, double-blind, randomized phase 1b study of peptide immunotherapy IMCY-0098 in new-onset type 1 diabetes: an exploratory analysis of immune biomarkers.

BACKGROUND: IMCY-0098, a synthetic peptide developed to halt disease progression via elimination of key immune cells in the autoimmune cascade, has shown a promising safety profile for the treatment of type 1 diabetes (T1D) in a recent phase 1b trial. This exploratory analysis of data from that trial aimed to identify the patient biomarkers at baseline associated with a positive response to treatment and examined the associations between immune response parameters and clinical efficacy endpoints (as surrogates for mechanism of action endpoints) using an artificial intelligence-based approach of unsupervised explainable machine learning. METHODS: We conducted an exploratory analysis of data from a phase 1b, dose-escalation, randomized, placebo-controlled study of IMCY-0098 in patients with recent-onset T1D. Here, a panel of markers of T cell activation, memory T cells, and effector T cell response were analyzed via descriptive statistics. Artificial intelligence-based analyses of associations between all variables, including immune responses and clinical responses, were performed using the Knowledge Extraction and Management (KEM®) v 3.6.2 analytical platform. RESULTS: The relationship between all available patient data was investigated using unsupervised machine learning implemented in the KEM® environment. Of 15 associations found for the dose C group (450 µg subcutaneously followed by 3 × 225 µg subcutaneously), seven involved human leukocyte antigen (HLA) type, all of which identified improvement/absence of worsening of disease parameters in DR4+ patients and worsening/absence of improvement in DR4- patients. This association with DR4+ and non-DR3 was confirmed using the endpoints normalized area under the curve C-peptide from mixed meal tolerance tests where presence of DR4 HLA haplotype was associated with an improvement in both endpoints. Exploratory immune analysis showed that IMCY-0098 dose B (150 µg subcutaneously followed by 3 × 75 µg subcutaneously) and dose C led to an increase in presumed/potentially protective antigen-specific cytolytic CD4+ T cells and a decrease in pathogenic CD8+ T cells, consistent with the expected mechanism of action of IMCY-0098. The analysis identified significant associations between immune and clinical responses to IMCY-0098. CONCLUSIONS: Promising preliminary efficacy results support the design of a phase 2 study of IMCY-0098 in patients with recent-onset T1D. TRIAL REGISTRATION: ClinicalTrials.gov NCT03272269; EudraCT: 2016-003514-27.

Predicting Trifluridine/Tipiracil Treatment Outcomes in Refractory Metastatic Colorectal Cancer Patients: A Multicenter Exploratory Analysis.

INTRODUCTION: There are no recommended biomarkers to identify patients with refractory metastatic colorectal cancer (mCRC) who would benefit the most from trifluridine/tipiracil (TTP). The exploratory analysis of the RECOURSE trial revealed that patients with low tumor burden and indolent disease derive greater benefit in terms of both progression-free survival (PFS) and overall survival (OS). Nevertheless, the final answer on the TTP real impact on the well-being of patients with late-stage mCRC will come from real-world data. METHODS: The aim of this retrospective exploratory study was to investigate the effectiveness of TTP in mCRC with regard to the duration of standard treatment and other influencing variables. The study included 260 patients from the three largest Croatian oncology centers who began treatment with TTP in the third or fourth line between 2018 and 2020. RESULTS: The median OS and PFS for the entire cohort were 6.53 and 2.50 months, respectively. Patients with more aggressive disease, defined as those whose time to progression on the first two lines of standard therapy was less than 18 months, had significantly shorter PFS (2.40 vs. 2.57 months, hazard ratio [HR] 1.34, 95% confidence interval [CI]: 1.03-1.84). There was also a tendency toward shorter OS (6.10 vs. 6.30 months, HR 1.32, 95% CI: 0.99-1.78) but without statistical significance. Patients with ECOG PS 0, without liver metastases, and with RAS mutation had both longer OS and PFS. No influence was detected from other variables including age, sex, primary tumor location, and tumor burden. CONCLUSION: With regard to the results of the previously conducted trials, the study concludes that indolent disease, good general condition, and absence of liver metastases are positive predictive factors for TTP treatment.

Analysis, identification and visualization of subgroups in genomics.

MOTIVATION: Cancer is a complex and heterogeneous disease involving multiple somatic mutations that accumulate during its progression. In the past years, the wide availability of genomic data from patients' samples opened new perspectives in the analysis of gene mutations and alterations. Hence, visualizing and further identifying genes mutated in massive sets of patients are nowadays a critical task that sheds light on more personalized intervention approaches. RESULTS: Here, we extensively review existing tools for visualization and analysis of alteration data. We compare different approaches to study mutual exclusivity and sample coverage in large-scale omics data. We complement our review with the standalone software AVAtar ('analysis and visualization of alteration data') that integrates diverse aspects known from different tools into a comprehensive platform. AVAtar supplements customizable alteration plots by a multi-objective evolutionary algorithm for subset identification and provides an innovative and user-friendly interface for the evaluation of concurrent solutions. A use case from personalized medicine demonstrates its unique features showing an application on vaccination target selection. AVAILABILITY: AVAtar is available at: https://github.com/sysbio-bioinf/avatar. CONTACT: hans.kestler@uni-ulm.de, phone: +49 (0) 731 500 24 500, fax: +49 (0) 731 500 24 502.

Using theory to guide exploratory network analyses.

The use of exploratory network analysis has increased in psychopathology research over the past decade. A benefit of exploratory network analysis is the wealth of information it can provide; however, a single analysis may generate more inferences than what can be discussed in one manuscript (e.g., centrality indices of each node). This necessitates that authors choose which results to discuss in further detail and which to omit. Without a guide for this process, the likelihood of a biased interpretation is high. We propose that the integration of theory throughout the research process makes the interpretation of exploratory networks more manageable for the researcher and more likely to result in an interpretation that advances science. The goals of this paper are to differentiate between exploratory and confirmatory network analyses, discuss the utility of exploratory work, and provide a practical framework that uses theory as a guide to interpret exploratory network analyses.

Analysis of Metabolite and Lipid Association Networks Reveals Molecular Mechanisms Associated with 3-Month Mortality and Poor Functional Outcomes in Patients with Acute Ischemic Stroke after Thrombolytic Treatment with Recombinant Tissue Plasminogen Activator.

Here, we present an integrated multivariate, univariate, network reconstruction and differential analysis of metabolite-metabolite and metabolite-lipid association networks built from an array of 18 serum metabolites and 110 lipids identified and quantified through nuclear magnetic resonance spectroscopy in a cohort of 248 patients, of which 22 died and 82 developed a poor functional outcome within 3 months from acute ischemic stroke (AIS) treated with intravenous recombinant tissue plasminogen activator. We explored differences in metabolite and lipid connectivity of patients who did not develop a poor outcome and who survived the ischemic stroke from the related opposite conditions. We report statistically significant differences in the connectivity patterns of both low- and high-molecular-weight metabolites, implying underlying variations in the metabolic pathway involving leucine, glycine, glutamine, tyrosine, phenylalanine, citric, lactic, and acetic acids, ketone bodies, and different lipids, thus characterizing patients' outcomes. Our results evidence the promising and powerful role of the metabolite-metabolite and metabolite-lipid association networks in investigating molecular mechanisms underlying AIS patient's outcome.

Dietary patterns generated by the Treelet Transform and risk of stroke: a Danish cohort study.

OBJECTIVE: To relate empirically derived dietary patterns identified using the Treelet Transform (TT) to risk of stroke. DESIGN: A prospective cohort study using the Danish Diet, Cancer and Health cohort. Dietary information was obtained in 1993-1997 using a validated semi-quantitative FFQ. Incident stroke diagnoses, obtained from the Danish National Patient Register, were verified by record review. Dietary patterns were generated using TT, and participants were categorised into quintiles based on their adherence to each pattern. Sex-specific Cox proportional hazard models estimated associations between dietary patterns and stroke. SETTING: Denmark. PARTICIPANTS: 55 061 men and women aged 50-64 years at the time of enrolment. RESULTS: Three dietary patterns explaining 15·4 % of the total variance were identified: a Prudent pattern, a Western pattern and a Wine & Snacks pattern. During a follow-up time of 10 years, 1513 cases occurred. Comparing the highest to lowest quintiles of intake, adherence to a Prudent pattern was inversely associated with stroke (HRmen 0·74, 95 % CI 0·60, 0·91; HRwomen 0·82, 95 % CI 0·62, 1·08), while adherence to a Western pattern was associated with greater risk (HRmen 1·61, 95 % CI 1·23, 2·10; HRwomen 2·01, 95 % CI 1·48, 2·72). No association was found for a Wine & Snacks pattern for women, but a weak inverse association was found for men (HR 0·81, 95 % CI 0·67, 0·99). CONCLUSIONS: The results of this study are broadly in line with current recommendations for a healthy diet to prevent stroke.

The preregistration revolution.

Progress in science relies in part on generating hypotheses with existing observations and testing hypotheses with new observations. This distinction between postdiction and prediction is appreciated conceptually but is not respected in practice. Mistaking generation of postdictions with testing of predictions reduces the credibility of research findings. However, ordinary biases in human reasoning, such as hindsight bias, make it hard to avoid this mistake. An effective solution is to define the research questions and analysis plan before observing the research outcomes-a process called preregistration. Preregistration distinguishes analyses and outcomes that result from predictions from those that result from postdictions. A variety of practical strategies are available to make the best possible use of preregistration in circumstances that fall short of the ideal application, such as when the data are preexisting. Services are now available for preregistration across all disciplines, facilitating a rapid increase in the practice. Widespread adoption of preregistration will increase distinctiveness between hypothesis generation and hypothesis testing and will improve the credibility of research findings.

Maternal metal concentration during gestation and pediatric morbidity in children: an exploratory analysis.

BACKGROUND: The majority of studies linking exposure to metals with certain health outcomes focus on known toxic metals. Alternatively, this study assesses the extent to which exposure to a wider range of metals during gestation is associated with childhood morbidity. METHODS: We analyzed the concentrations of 25 metals found in urine samples of 111 pregnant women of Arab-Bedouin origin collected prior to birth. In addition, we collected medical records on their offspring for six years following birth, including every interaction with HMOs, local hospitals, and pharmacies. RESULTS: The main types of morbidities diagnosed and treated during this period were preterm births, malformations, asthma-like morbidity, cardiovascular and behavioral problems, and obesity. Multivariable analysis showed that offspring born before term were more likely to have been exposed to elevated maternal concentrations of zinc, thallium, aluminum, manganese, and uranium, all with adjusted relative risk above 1.40 for an increase by each quintile. Likewise, children with asthma had been exposed to higher levels of magnesium, strontium, and barium at gestation, while behavioral outcomes were associated with elevated biometals, i.e., sodium, magnesium, calcium, selenium, and zinc, as well as higher levels of lithium, cobalt, nickel, strontium, cadmium, vanadium, arsenic, and molybdenum. A heatmap of adjusted relative risk estimates indicates the considerable implications that exposure to metals may have for preterm birth and developmental outcomes. CONCLUSIONS: The current study shows that perinatal exposure to metals is adversely associated with pediatric morbidity. Further such analyses on additional samples are warranted.

What Medical Crowdfunding Campaigns Can Tell Us About Local Health System Gaps and Deficiencies: Exploratory Analysis of British Columbia, Canada.

BACKGROUND: There are a range of perceived gaps and shortcomings in the publicly funded Canadian health system. These include wait times for care, lack of public insurance coverage for dental care and pharmaceuticals, and difficulties accessing specialist care. Medical crowdfunding is a response to these gaps where individuals raise funds from their social networks to address health-related needs. OBJECTIVE: This study aimed to investigate the potential of crowdfunding data to better understand what health-related needs individuals are using crowdfunding for, how these needs compare with the existing commentary on health system deficiencies, and the advantages and limitations of using crowdfunding campaigns to enhance or augment our understanding of perceived health system deficiencies. METHODS: Crowdfunding campaigns were scraped from the GoFundMe website. These campaigns were then limited to those originating in the metropolitan Vancouver region of two health authorities during 2018. These campaigns were then further limited to those raising funds to allow the treatment of a medical problem or related to needs arising from ill health. These campaigns were then reviewed to identify the underlying health issue and motivation for pursuing crowdfunding. RESULTS: We identified 423 campaigns for health-related needs. These campaigns requested CAD $8,715,806 (US $6,088,078) in funding and were pledged CAD $3,477,384 (US $2,428,987) from 27,773 donors. The most common underlying medical condition for campaign recipients was cancer, followed by traumatic injuries from collisions and brain injury and stroke. By far, the most common factor of motivation for crowdfunding was seeking financial support for wages lost because of illness (232/684, 33.9%). Some campaigns (65/684, 9.5%) sought help with purchasing medical equipment and supplies; 8.2% (56/684) sought to fund complementary, alternative, or unproven treatments including experimental interventions; 7.2% (49/684) sought financial support to cover travel-related costs, including in-province and out-of-province (49/684, 7.2%) travel; and 6.3% (43/684) campaigns sought help to pay for medication. CONCLUSIONS: This analysis demonstrates the potential of crowdfunding data to present timely and context-specific user-created insights into the perceived health-related financial needs of some Canadians. Although the literature on perceived limitations of the Canadian health system focuses on wait times for care and limited access to specialist services, among other issues, these campaigners were much more motivated by gaps in the wider social system such as costs related to unpaid time off work and travel to access care. Our findings demonstrate spatial differences in the underlying medical problems, motivations for crowdfunding, and success using crowdfunding that warrants additional attention. These differences may support established concerns that medical crowdfunding is most commonly used by individuals from relatively privileged socioeconomic backgrounds. We encourage the development of new resources to harness the power of crowdfunding data as a supplementary source of information for Canadian health system stakeholders.

Development and psychometric properties of the public attitude towards vaccination scale - Health belief model.

AIM: The aim of this study was to develop and psychometrically evaluate the Public Attitude Towards Vaccination Scale - Health Belief Model. DESIGN: A methodological and prospective psychometric study. METHOD: A three-phase construct was used to develop the Public Attitude Towards Vaccination Scale - Health Belief Model and to determine its psychometric properties: (1) creation of the item pool/conceptualization; (2) evaluation of the items; and (3) psychometric evaluation. This scale was tested using the construct validity (exploratory and confirmatory factor analyses) and the reliability analysis. A psychometric assessment of the scale was conducted with 586 individuals. Data were collected between January - April 2018. RESULTS: Items of the scale were obtained by appraising the literature concerning vaccination and the other Health Belief Model scale and conducting interviews with mothers. The content validity ratio of this scale calculated according to experts' opinions ranged between 0.769 and 1.00. According to the exploratory factor analysis, there were five factors with an eigenvalue higher than 1 in the scale. These five factors accounted for 68.9% of the total variance. In confirmatory factor analysis, values of fit indices were excellent or acceptable. This scale had high internal consistency and test-retest reliability. CONCLUSION: This study successfully developed the Public Attitude Towards Vaccination Scale - Health Belief Model. In addition to researchers, this scale can be used by nurses while providing counselling for people with vaccine hesitancy/refusal. IMPACT: This measurement tool can be used to understand and address 'vaccine hesitancy' by researchers. The results of the research using this measurement tool will provide valuable information to policymakers for preventing vaccine hesitancy. The validity and reliability of this scale can easily be conducted in different languages.

Ultra-Performance Liquid Chromatography-High-Resolution Mass Spectrometry and Direct Infusion-High-Resolution Mass Spectrometry for Combined Exploratory and Targeted Metabolic Profiling of Human Urine.

The application of metabolic phenotyping to epidemiological studies involving thousands of biofluid samples presents a challenge for the selection of analytical platforms that meet the requirements of high-throughput precision analysis and cost-effectiveness. Here direct infusion-nanoelectrospray (DI-nESI) was compared with an ultra-performance liquid chromatography (UPLC)-high-resolution mass spectrometry (HRMS) method for metabolic profiling of an exemplary set of 132 human urine samples from a large epidemiological cohort. Both methods were developed and optimized to allow the simultaneous collection of high-resolution urinary metabolic profiles and quantitative data for a selected panel of 35 metabolites. The total run time for measuring the sample set in both polarities by UPLC-HRMS was 5 days compared with 9 h by DI-nESI-HRMS. To compare the classification ability of the two MS methods, we performed exploratory analysis of the full-scan HRMS profiles to detect sex-related differences in biochemical composition. Although metabolite identification is less specific in DI-nESI-HRMS, the significant features responsible for discrimination between sexes were mostly the same in both MS-based platforms. Using the quantitative data, we showed that 10 metabolites have strong correlation (Pearson's r > 0.9 and Passing-Bablok regression slope of 0.8-1.3) and good agreement assessed by Bland-Altman plots between UPLC-HRMS and DI-nESI-HRMS and thus can be measured using a cheaper and less sample- and time-consuming method. A further twenty metabolites showed acceptable correlation between the two methods with only five metabolites showing weak correlation (Pearson's  r < 0.4) and poor agreement due to the overestimation of the results by DI-nESI-HRMS.

Interpreting the dimensions of neural feature representations revealed by dimensionality reduction.

Recent progress in understanding the structure of neural representations in the cerebral cortex has centred around the application of multivariate classification analyses to measurements of brain activity. These analyses have proved a sensitive test of whether given brain regions provide information about specific perceptual or cognitive processes. An exciting extension of this approach is to infer the structure of this information, thereby drawing conclusions about the underlying neural representational space. These approaches rely on exploratory data-driven dimensionality reduction to extract the natural dimensions of neural spaces, including natural visual object and scene representations, semantic and conceptual knowledge, and working memory. However, the efficacy of these exploratory methods is unknown, because they have only been applied to representations in brain areas for which we have little or no secondary knowledge. One of the best-understood areas of the cerebral cortex is area MT of primate visual cortex, which is known to be important in motion analysis. To assess the effectiveness of dimensionality reduction for recovering neural representational space we applied several dimensionality reduction methods to multielectrode measurements of spiking activity obtained from area MT of marmoset monkeys, made while systematically varying the motion direction and speed of moving stimuli. Despite robust tuning at individual electrodes, and high classifier performance, dimensionality reduction rarely revealed dimensions for direction and speed. We use this example to illustrate important limitations of these analyses, and suggest a framework for how to best apply such methods to data where the structure of the neural representation is unknown.

Treatment-emergent hypertension and efficacy in the phase 3 Study of (E7080) lenvatinib in differentiated cancer of the thyroid (SELECT).

BACKGROUND: Hypertension (HTN) is an established class effect of vascular endothelial growth factor receptor (VEGFR) inhibition. In the phase 3 Study of (E7080) Lenvatinib in Differentiated Cancer of the Thyroid (SELECT) trial, HTN was the most frequent adverse event of lenvatinib, an inhibitor of VEGFR1, VEGFR2, VEGFR3, fibroblast growth factor receptor 1 (FGFR1), FGFR2, FGFR3, FGFR4, platelet-derived growth factor receptor α (PDGFRα), ret proto-oncogene (RET), and stem cell factor receptor (KIT). This exploratory analysis examined treatment-emergent hypertension (TE-HTN) and its relation with lenvatinib efficacy and safety in SELECT. METHODS: In the multicenter, double-blind SELECT trial, 392 patients with progressive radioiodine-refractory differentiated thyroid cancer (RR-DTC) were randomized 2:1 to lenvatinib (24 mg/d on a 28-day cycle) or placebo. Survival endpoints were assessed with Kaplan-Meier estimates and log-rank tests. The influence of TE-HTN on progression-free survival (PFS) and overall survival (OS) was analyzed with univariate and multivariate Cox proportional hazards models. RESULTS: Overall, 73% of lenvatinib-treated patients and 15% of placebo-treated patients experienced TE-HTN. The median PFS for lenvatinib-treated patients with (n = 190) and without TE-HTN (n = 71) was 18.8 and 12.9 months, respectively (hazard ratio [HR], 0.59; 95% confidence interval [CI], 0.39-0.88; P = .0085). For lenvatinib-treated patients, the objective response rate was 69% with TE-HTN and 56% without TE-HTN (odds ratio, 1.72; 95% CI, 0.98-3.01). The median change in tumor size for patients with and without TE-HTN was -45% and -40%, respectively (P = .2). The median OS was not reached for patients with TE-HTN; for those without TE-HTN, it was 21.7 months (HR, 0.43; 95% CI, 0.27-0.69; P = .0003). CONCLUSIONS: Although HTN is a clinically significant adverse event that warrants monitoring and management, TE-HTN was significantly correlated with improved outcomes in patients with RR-DTC, indicating that HTN may be predictive for lenvatinib efficacy in this population. Cancer 2018;124:2365-72. © 2018 American Cancer Society.

A method for data-driven exploration to pinpoint key features in medical data and facilitate expert review.

PURPOSE: To develop a method for data-driven exploration in pharmacovigilance and illustrate its use by identifying the key features of individual case safety reports related to medication errors. METHODS: We propose vigiPoint, a method that contrasts the relative frequency of covariate values in a data subset of interest to those within one or more comparators, utilizing odds ratios with adaptive statistical shrinkage. Nested analyses identify higher order patterns, and permutation analysis is employed to protect against chance findings. For illustration, a total of 164 000 adverse event reports related to medication errors were characterized and contrasted to the other 7 833 000 reports in VigiBase, the WHO global database of individual case safety reports, as of May 2013. The initial scope included 2000 features, such as patient age groups, reporter qualifications, and countries of origin. RESULTS: vigiPoint highlighted 109 key features of medication error reports. The most prominent were that the vast majority of medication error reports were from the United States (89% compared with 49% for other reports in VigiBase); that the majority of reports were sent by consumers (53% vs 17% for other reports); that pharmacists (12% vs 5.3%) and lawyers (2.9% vs 1.5%) were overrepresented; and that there were more medication error reports than expected for patients aged 2-11 years (10% vs 5.7%), particularly in Germany (16%). CONCLUSIONS: vigiPoint effectively identified key features of medication error reports in VigiBase. More generally, it reduces lead times for analysis and ensures reproducibility and transparency. An important next step is to evaluate its use in other data.

Exploratory Failure Time Analysis in Large Scale Genomics.

In large scale genomic analyses dealing with detecting genotype-phenotype associations, such as genome wide association studies (GWAS), it is desirable to have numerically and statistically robust procedures to test the stochastic independence null hypothesis against certain alternatives. Motivated by a special case in a GWAS, a novel test procedure called correlation profile test (CPT) is developed for testing genomic associations with failure-time phenotypes subject to right censoring and competing risks. Performance and operating characteristics of CPT are investigated and compared to existing approaches, by a simulation study and on a real dataset. Compared to popular choices of semiparametric and nonparametric methods, CPT has three advantages: it is numerically more robust because it solely relies on sample moments; it is more robust against the violation of the proportional hazards condition; and it is more flexible in handling various failure and censoring scenarios. CPT is a general approach to testing the null hypothesis of stochastic independence between a failure event point process and any random variable; thus it is widely applicable beyond genomic studies.

Impact of baseline microbiological status on clinical outcomes in generalized aggressive periodontitis patients treated with or without adjunctive amoxicillin and metronidazole: an exploratory analysis from a randomized controlled clinical trial.

AIM: To explore whether subjects harbouring A. actinomycetemcomitans, P. gingivalis or T. forsythia at baseline showed increased clinical benefits with the adjunctive use of systemic amoxicillin and metronidazole (AMX-MET) during non-surgical treatment of generalized aggressive periodontitis (GAgP). MATERIAL AND METHODS: Forty one subjects were included in this 6-month randomized placebo-controlled clinical trial using a 7-day course of systemic AMX-MET or placebo as adjuncts to non-surgical periodontal therapy. Clinical and microbiological parameters were collected at baseline, 2 and 6 months after treatment. Microbiological cultures were processed for pooled subgingival samples and identities of isolates were determined by PCR for A. actinomycetemcomitans, P. gingivalis and T. forsythia RESULTS: At 6 months, the test treatment resulted in significant additional improvements in the primary outcome variable compared to placebo, and the effect of the adjunctive antimicrobials was not modified by the baseline microbiological status in the primary analysis. However, secondary exploratory subgroup analyses showed improved clinical outcomes in subjects harbouring A. actinomycetemcomitans at baseline compared to subjects who did not harbour this pathogen. CONCLUSIONS: All subjects benefited from the tested adjunctive antimicrobial regimen, although subjects who harboured A. actinomycetemcomitans at baseline may show greater clinical benefits. Larger appropriately powered studies are needed to confirm whether adjunctive AMX-MET is more beneficial for GAgP patients who harbour A. actinomycetemcomitans, along with other key periodontal pathogens.

Factors affecting overall care experience for people living with rare conditions in the UK: exploratory analysis of a quantitative patient experience survey.

BACKGROUND: Although individually rare, collectively, rare conditions are common and affect a large number of people and are often chronic, life threatening and affect multiple body systems; the majority of them have no effective treatment. The literature has identified many specific challenges for those living with rare conditions, however, we do not know which of these in combination are most likely to impact how someone rates their overall experience of care. The aim of this study is to do further exploratory analysis of the Genetic Alliance UK 2020 Rare Experience survey data to identify which variables are most strongly associated with respondents' overall care experience. RESULTS: There were strong associations between most of the selected survey variables and the overall rated experience of care variable. In the multiple linear regression only nine variables remained in the best fit model: 'Trust and confidence in hospital staff involved in ongoing care'; 'Satisfaction with information provided by healthcare professionals-following diagnosis'; 'The professionals providing care work as a team'; 'Feel care is coordinated effectively'; 'The timing and frequency of appointments are convenient for the patient/carer/family'; 'Whether or not there is a specific healthcare professional to ask questions of about the rare/undiagnosed condition'; 'Experience of searching for a diagnosis'; 'Knowledge of whether there is a specialist centre for the condition'; and 'Number of different clinics attend for the condition'. CONCLUSIONS: Our findings indicate the challenges that play the largest part in explaining the varied experiences with rare disease healthcare in the UK for our survey respondents. These challenges should be further investigated with a broader sample of people affected by rare conditions, ideally through the implementation of a comprehensive national rare condition patient registry. Our findings highlight an important potential gap in the Framework, 'trust and confidence in healthcare professionals'; further research is required to fully understand the foundations of trust and confidence.

Internal Psychometric Validation of an International Burden of Illness Survey for Idiopathic Multicentric Castleman Disease.

INTRODUCTION: Idiopathic multicentric Castleman disease (iMCD) is a rare, chronic, debilitating lymphoproliferative disorder where the mainstay of treatment is symptom management. Our recent international patient survey showed that patients with iMCD have a high symptom burden that has a significant negative patient-reported impact on several aspects of daily life. As part of our ongoing work towards the development of an iMCD symptom burden scale, assessing the survey's psychometric properties is a critical step in understanding its adequacy, relevance, and usefulness. As iMCD is a rare disease, there are challenges to conducting such psychometric analyses which we describe. METHODS: As part of the exploratory psychometric analysis, three a priori hypothesis sets (HS) were generated by interviewing an iMCD-experienced clinician, a patient, and a caregiver to explore the iMCD patient survey's internal construct validity, given no gold standard iMCD measure exists for external construct validation. HS-1 hypothesized that a convergent or discriminant relationship exists with the patients' self-assessment of symptom effect on daily life between two potentially related or unrelated symptoms, respectively. HS-2 hypothesized that having a greater number of symptoms has a positive convergent relationship with the patients' assessment of symptoms' effect on daily life. Finally, HS-3 hypothesized that patients receiving treatment versus no treatment was associated with patients reporting less effect of symptom burden on their daily life. Spearman's rank absolute correlation strength (ACS) was used for HS-1 and HS-2 (convergent relationship, ACS ≥ 0.3 and p value < 0.05; divergent relationship, ACS < 0.3), and Cohen's d to quantify standardized absolute effect sizes (AES) for HS-3 (AES ≥ 0.5 and p value < 0.05). RESULTS: Our analyses partially supported HS-1. None of the three positive convergent relationships were supported. Of the six discriminant relationships, only dizziness with impaired cognitive function and tiredness with dizziness were supported. HS-2 analyses showed there was convergent validity between the number of symptoms and their effect on aspects of daily life. HS-3 analyses did not provide evidence to support the hypothesis. CONCLUSION: These internal psychometric construct analyses provide initial support for the bespoke iMCD patient survey and will guide additional work towards the development of the first iMCD-specific symptom burden scale.

A Model Implied Instrumental Variable Approach to Exploratory Factor Analysis (MIIV-EFA).

Spearman (Am J Psychol 15(1):201-293, 1904. https://doi.org/10.2307/1412107 ) marks the birth of factor analysis. Many articles and books have extended his landmark paper in permitting multiple factors and determining the number of factors, developing ideas about simple structure and factor rotation, and distinguishing between confirmatory and exploratory factor analysis (CFA and EFA). We propose a new model implied instrumental variable (MIIV) approach to EFA that allows intercepts for the measurement equations, correlated common factors, correlated errors, standard errors of factor loadings and measurement intercepts, overidentification tests of equations, and a procedure for determining the number of factors. We also permit simpler structures by removing nonsignificant loadings. Simulations of factor analysis models with and without cross-loadings demonstrate the impressive performance of the MIIV-EFA procedure in recovering the correct number of factors and in recovering the primary and secondary loadings. For example, in nearly all replications MIIV-EFA finds the correct number of factors when N is 100 or more. Even the primary and secondary loadings of the most complex models were recovered when the sample sizes were at least 500. We discuss limitations and future research areas. Two appendices describe alternative MIIV-EFA algorithms and the sensitivity of the algorithm to cross-loadings.

Irruption of Network Analysis to Explain Dietary, Psychological and Nutritional Patterns and Metabolic Health Status in Metabolically Healthy and Unhealthy Overweight and Obese University Students: Ecuadorian Case.

BACKGROUND: The association between dietary nutritional patterns, psychological factors, and metabolic health status has not been investigated in university students. There are studies that include numerous variables to test hypotheses from various theoretical bases, but due to their complexity, they have not been studied in combination. The scientific community recognizes the use of Gaussian graphical models (GGM) as a set of novel methods capable of addressing this. OBJECTIVE: To apply GGMs to derive specific networks for groups of healthy and unhealthy obese individuals that represent nutritional, psychological, and metabolic patterns in an Ecuadorian population. METHODOLOGY: This was a quantitative, non-experimental, cross-sectional, correlational study conducted on a sample of 230 obese/overweight university students, selected through a multi-stage random sampling method. To assess usual dietary intake, a Food Frequency Questionnaire (FFQ) was used; to evaluate psychological profiles (anxiety, depression, and stress), the DASS-21 scale was employed; blood pressure and anthropometric data were collected; and insulin levels, lipid profiles, and glucose levels were determined using fasting blood samples. The International Diabetes Federation (IDF) criteria were applied to identify metabolically healthy and unhealthy individuals. Statistical analysis relied on univariate methods (frequencies, measures of central tendency, and dispersion), and the relationships were analyzed through networks. The Mann-Whitney U test was used to analyze differences between groups. RESULTS: In metabolically unhealthy obese individuals, GGMs identified a primary network consisting of the influence of waist circumference on blood pressure and insulin levels. In the healthy obese group, a different network was identified, incorporating stress and anxiety variables that influenced blood pressure, anthropometry, and insulin levels. Other identified networks show the dynamics of obesity and the effect of waist circumference on triglycerides, anxiety, and riboflavin intake. CONCLUSIONS: GGMs are an exploratory method that can be used to construct networks that illustrate the behavior of obesity in the studied population. In the future, the identified networks could form the basis for updating obesity management protocols in Primary Care Units and supporting clinical interventions in Ecuador.