An observational study in Chronic Infectious Disease, Chronic Skin Disease and Mental Disorders, sponsored by University of Campania Luigi Vanvitelli. Completed at 1 site in Italy. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2023-11-22.
Sponsored by University of Campania Luigi Vanvitelli · Observational
The prevalence of common mental disorders is high in patients with chronic inflammatory physical diseases(e.g., autoimmune or infectious diseases). The traditional explanatory causation model in which physical symptoms and related disability drive mental health problems is now called into question, and evidence has accumulated supporting more complex interactions whereby psychiatric disorders can both result from and contribute to the progression of physical diseases. In the present project, the investigators will focus on comorbidity of depression and anxiety symptoms or syndromes with chronic inflammatory skin diseases (psoriasis, hidradenitis suppurativa and atopic dermatitis) or chronic infectious diseases (chronic HBV and HIV infection).
The study is aimed to clarify the mechanisms underlying the high frequency of those comorbidities. It will overcome the main limitations of previous investigations and use innovative statistical tools to model complex interrelationships and causal links among the assessed variables.
The identification of key variables driving the causal chain of determinants of poor global health and quality of life may impact treatment outcome and models of care.
STATE OF ART:
Healthcare professionals often underestimate the effects of chronic inflammatory processes on patients' quality of life (QoL). The prevalence of common mental disorders, such as depression and anxiety, is high in patients with physical diseases entailing chronic inflammatory processes (e.g., autoimmune or infectious diseases), adding to the psychosocial burden of these disorders. In fact, mental symptoms may harm response to treatment and may have a negative impact on the physical diseases, which, in their turn, may worsen mental symptoms, and contribute, together with them, to undermine persons' QoL.
Associations of depression and anxiety with dermatological and infectious diseases (entailing chronic inflammatory processes) have been the subject of an extensive literature. Depression is reported in up to 42% and 60% of people with hidradenitis suppurativa (HS) and psoriasis (PS), respectively. Patients with atopic dermatitis (AD) and HS seem to have a high suicidal risk. High comorbidity with depression and anxiety is also reported in chronic infectious diseases such as chronic hepatitis C or B (HCV, HBV), and human immunodeficiency virus (HIV) infection. Prevalence of anxiety symptoms is as high as 80% in people living with HIV, with 20% meeting criteria for generalized anxiety disorder. HBV and HCV are associated with clinically significant depression in up to 30% of cases.
Research, so far, has not succeeded at fully clarifying mechanisms underlying the high frequency of comorbidity between common mental disorders and chronic inflammatory diseases.
The presence of mental disorders adds to the psychosocial burden of chronic inflammatory skin diseases or chronic infectious diseases, may harm response to treatment and may have a negative impact on the physical diseases themselves, which, in their turn, may worsen mental symptoms, and contribute, together with them, to undermine persons' QoL.
The project's ambitions are manifold and are listed below.
In addition, the investigators will use network analyses to model the complex interrelationships and causal links among the assessed variables. So far, no study modelled the comorbidity between mental and physical symptoms in chronic inflammatory diseases by using this approach. The network analysis does not rely on an a priori model of cause-effect relationships among variables, as current alternative statistical models (e.g., structural equation models) do; it is largely used in physical and communication sciences to study how complex interactions among sets of variables maintain complex systems. It has been used to improve knowledge on the complex phenomena of psychiatric comorbidity, and identify high value targets for interventions. More recently, network modeling algorithms have been used to study causal relationships among sets of variables and identify those variables that in the causal chain hold precedence and represent "activators,", "mediators,", and/or "products" within a syndromic condition. The identification of key variables in the network, and in particular of those that represent causal antecedents in the chain of variables leading to poor QoL, is crucial to design treatment programs that target those variables, increasing the likelihood to improve patients' QoL. In addition, as the analysis enables the possibility to identify the influence of unmeasured ("latent") variables not included in the model, the project's findings may guide further research in the field.
OBJECTIVES:
The project aims to clarify the mechanisms underlying the high frequency of comorbidity of physical diseases entailing chronic inflammatory processes (e.g., autoimmune or infectious diseases) with common mental disorders.
The traditional explanatory causation model in which physical symptoms and related disability drive mental health problems is called into question by the relevant literature, and evidence has accumulated supporting more complex interactions whereby psychiatric disorders can both result from and contribute to the progression of physical diseases. In this frame, recognizing the co-existence of physical and mental disease symptoms pertains not only to the need to treat both conditions, but also to the need to avoid a vicious circle in which mental symptoms may harm response to treatment and may have a negative impact on the physical ones that, in their turn, may worsen mental symptoms, and contribute, together with them, to undermine person's disability and quality of life.
To these aims, the present project will pursue the following objectives.
To test the hypotheses listed below by the network analysis, using a machine-learning algorithm:
STATISTICAL ANALYSIS
Data will be checked for missing values, inconsistencies, and outliers. Continuous variables will be summarized by the following descriptive statistics: number of observations, mean, standard deviation, median, minimum, and maximum; while categorical ones by counts of patients and percentages.
The normality assumption will be tested with Shapiro-Wilk test. Pairwise correlations between continuous study measures will be calculated using Pearson correlation coefficients or Spearman rank correlation coefficients if needed.
The statistical testing will be conducted at the two-sided a = 0.05 and 95% confidence interval (CI) will be computed, unless otherwise specified.
For continuous variables, differences among groups will be tested by means of t-test or one-way ANOVA and Mann-Whitney or Kruskal-Wallis tests when appropriate. For categorical variables, differences among groups will be tested by means of chi-square or Fisher's exact test when needed.
The study hypotheses will be tested in the overall sample and separately in the two subgroups of patients with dermatological diseases or infectious diseases using network analysis, an exploratory technique that is increasingly used to identify causal relationships within and between manifestations of psychiatric disorders.
A causal network is represented graphically as a set of nodes (variables) connected through edges (directed arrows), that may be interpreted as causal relations. Specifically, the complex relationships among variables will be investigated by means of partial ancestral graphs (PAGs), which use an enriched set of edge types to convey both edge orientation and the possible influence of unmeasured variables not represented in the model. Analyses will be conducted using the machine-learning Greedy Fast Causal Inference (GFCI) algorithm, which uses a 2-step process to make causal inferences that can be represented in graphical format as PAGs. In the first step, all possible non-recursive causal relationships among the variables will be searched automatically to establish which variable pairs are potentially causally related using a method called Fast Greedy Equivalence Search. In the second step, the preliminary assessment will be refined by performing a series of conditional independence tests to iteratively rule out causal models that imply conditional independence statements not found to be true of the data. At the end of this process, it will be possible to interpret the links between pairs of variables as direct causal relationships, indirect causal relationships, possible causal relationship confounded by unmeasured variables, or correlations, in which the direction of causality cannot be defined. Thus, the GFCI algorithm will help understand which of the study hypotheses is/are more plausible and compatible with the data.
All statistical analyses and data processing will be performed using R version 3.3.3 (R Foundation for Statistical Computing).
Sample size considerations:
Among constraint-based causal search algorithms, GFCI showed better results in terms of precision and good performance in the simulations with a sample size of 200. Our sample size of 1000 patients (500 patients for each subsample) is adequate to detect causal relationships among the study variables, with a ratio patients/variables of about 30/1 in each subgroup.
IMPLEMENTATION: PERFORMANCE OF THE INTERMEDIATE AND FINAL OBJECTIVES
During the first 3 months of the project, the following procedures will be completed: enrollment of five research assistants (one biologist or one psychiatrist with experience in procedures for assessment of plasma biomarkers of inflammation, two dermatologists, one infectious disease specialist and one statistician for data quality control); acquisition of equipment and consumables for the study (7.5 Mhz probe for color-doppler instrument, bone quantitative ultrasound device, ELISA kits for dosage of blood markers; computerized neurocognitive test battery CANTAB; 5 portable computers, 1 personal computer, 3 iPAD, 3 STATA/SE version 15; stationery); implementation and testing of the study database by a computer engineer under the supervision of the coordinating unit; training of the researchers to the use of the study instruments and to the correct study procedures, carried out by each research unit for the respective assessments.
At the beginning of month 4, the recruitment of the subjects will start and will be carried out during the following 18 months.
Confirmation of patients' eligibility will be done by associate professors and researchers of Psychiatry, Dermatology and Infectious diseases research units, who will review the inclusion/exclusion criteria relevant to their discipline, such as the diagnosis of skin diseases or infectious diseases listed in the inclusion criteria, as well as lifetime psychiatric diagnoses. Associate professors and researchers from the Dermatology and Infectious diseases research unit will also obtain informed consent from eligible patients.
Trainees in Psychiatry from the Psychiatry research unit will collect data relevant to socio-demographic characteristics, psychopathology, disability, quality of life, cognition, coping skills and stigma.
Assessment of dermatological indices will be performed by the dermatologists enrolled as research assistants in the project, as well as by the researcher and trainee of the Dermatology research unit.
Assessment of markers of subclinical inflammatory damage will be done by the associate professor and research assistant of the Infectious Diseases research unit. Measurement of plasma levels of inflammatory markers will be done by a research assistant enrolled in the project (a biologist or a psychiatrist with experience in procedures for assessment of plasma biomarkers) under the supervision of a researcher of the Psychiatry research unit.
Trainees will fill in data collected for their respective research unit in the electronic database.
To control for missing data or insufficient sample size, every three months, recruitment strategies and subject enrollment will be reviewed by an ad hoc appointed internal audit committee. Incomplete data for any recruited subject will be allowed in the measure of 5%. Subjects missing all data in one of the main assessment areas (biomarkers, mental symptoms, physical and primary disease assessments) will be replaced.
Intermediate objectives of the study are the followings: 1) recruitment of at least 400 patients (200 from the Dermatological unit and 200 from the Infection disease unit) by the end of month 12; 2) Study registration and publication of the study protocol and its dissemination in national and international congresses by the end of month 9; 3) publication of two systematic reviews on the comorbidity of common mental disorders with chronic inflammatory skin and infectious diseases by month 12.
Final objectives of the project are: 1) the recruitment of at least 700 subjects with complete data by month 21; 2) consultation with a statistician with specific expertise in network analysis and completion of final statistical analyses by the end of month 22; 3) publication of the results in high-impact international journals and their dissemination in national and international congresses.
4,452 studies on the registry are indexed under Communicable Diseases; 521 are open to participants now.
This study's enrollment of 93 is below the median of 244 across 1,499 observational studies indexed under Communicable Diseases.
Browse Communicable Diseases studies →University of Campania Luigi Vanvitelli is the lead sponsor of 170 studies on the registry; 26 are open to participants now.
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Clinically stable outpatients among those attending the Dermatology or Infectious disease outpatient clinics of the University of Campania Hospital.
Inclusion criteria for subjects with dermatological diseases;
Inclusion criteria for subjects with HIV or HBV:
Inclusion criteria for both groups:
Exclusion Criteria:
500 Subjects attending the Dermatology outpatient clinic of the Vanvitelli University hospital with a diagnosis of psoriasis or hidradenitis suppurativa or atopic dermatitis of any grade of severity.
500 Subjects attending the Infectious diseases outpatient clinic of the Vanvitelli University hospital and with HIV or HBV infection.
Socio-demographic Data
A clinical form will be filled in to collect socio-demographic and clinical data such as age, education level, marital status, employment, age of onset and treatments.
Time frame: At recruitment (T0)
Assessment of psoriasis
The Psoriasis Area and Severity Index (PASI) will be used to assess the severity of psoriasis. According to this tool, psoriatic plaques are graded based on three criteria: redness, thickness, and scaliness. Severity is rated for each index on a 0-4 scale (0 for no involvement up to 4 for severe involvement). The body is divided into four regions comprising head, upper extremities, trunk, and lower extremities. In each of these areas, the fraction of total surface area affected is graded on a 0-6 scale (0 for no involvement, 6 for greater than 90% involvement). Various body regions are weighted to reflect their respective proportion of body surface area (BSA). The composite PASI score can then be calculated by multiplying the sum of the individual-severity scores for each region by the weighted area-of-involvement score for that respective region, and then summing the four resulting values. The highest potential PASI score is 72; the lowest is 0.
Time frame: At recruitment (T0)
Assessment of hidradenitis suppurativa
Severity of hidradenitis suppurativa will be evaluated by using the Hurley staging system. It classifies patients into three stages: I, single or multiple abscesses without sinus tracts and cicatrization; II, single or multiple, recurrent, widely separated abscesses with tract formation and cicatrization; III, diffuse involvement, or multiple interconnected tracts.
Time frame: At recruitment (T0)
Assessment of atopic dermatitis
Severity of atopic dermatitis will be assessed by means of the Eczema Area and Severity Index (EASI). It evaluates four body regions: head/neck, trunk, upper and lower extremities. Each of them is separately assessed for erythema (redness), induration/papulation/edema (thickness), excoriation (scratching), and lichenification. The average degree of severity of each sign in each regions is scored from 0 to 3. Symptoms (e.g. pruritus) and secondary signs (e.g. xerosis, scaling) are excluded from the area assessments. For each region, the clinician evaluates the intensity for each of the four signs and calculates the severity score. For each region, the severity score is multiplied by the area score and by a multiplier, that is different for each body site. The final EASI score is the sum of total scores of the four regions. The minimum EASI score is 0, the maximum is 72.
Time frame: At recruitment (T0)
Lifetime psychiatric comorbidity
The Mini International Neuropsychiatric Interview-Plus (MINI-PLUS) will be administered to all subjects to assess lifetime comorbidity with Axis I psychiatric disorders.
Time frame: At recruitment (T0)
The Hospital Anxiety and Depression
The Hospital Anxiety and Depression Scale (HADS), a tool designed to assess anxiety and depression in physically ill patients, will be used. It is a 14-item self-assessment scale including two subscales, respectively composed by seven items measuring anxiety and seven measuring depression. Responses are scored from 0 to 3, with subscale total scores ranging from 0 to 21 points (score ranges for severity: 0-7 = normal; 8-10 = mild; 11-14 = moderate; 15-21 = severe).
Time frame: At recruitment (T0)
Anxiety
The Hamilton Anxiety Rating Scale (HAM-A), a clinician-administered rating scale of 14 items, will be used to measure both psychic anxiety (mental agitation and psychological distress) and somatic anxiety (physical complaints related to anxiety). Each item is scored on a scale of 0 (not present) to 4 (severe), with a total score ranging from 0 to 56 (score ranges for severity of anxiety: \<17 = mild; 18-24 = mild to moderate; \>25 = moderate to severe).
Time frame: At recruitment (T0)
Depression
The Hamilton Depression Rating Scale (HAM-D-17) will be used to assess severity of depressive symptoms. It is a clinician-administered rating scale including 17 items pertaining to symptoms of depression experienced over the past week. Eight items are scored on a 5-point scale, ranging from 0 = not present to 4 = severe, while the remaining nine items are scored from 0 to 2. Sum of item scores ranges from 0 to 50 (score ranges for severity of depression: 0-7 = absent; 8-13 = mild; 14-18 = moderate; 19-22 = severe; ≥ 23 = very severe).
Time frame: At recruitment (T0)
Global Physical Assessments: Patient Global Assessment
The Patient Global Assessment Visual-Analogic Scale, a self-administered scale, will be used to evaluate how physical condition is considered subjectively from the patient. The scale consist of a simple, single item (with no subscale) that measures the overall impact of the disease on the global health of the patient at a specific point in time. It is scored using a visual analogue scale (VAS), anchored on an unnumbered 10-cm horizontal line. Higher scores represent a higher level of disease activity and a worse global health. The proposed definition of "low global assessment" is ≤2.0 (scale 0-10).
Time frame: At recruitment (T0)
Global Physical Assessments: Physician Assessment
The global severity of the physical diseases listed in the inclusion criteria will be assessed using the Physician Global Assessment Visual-Analogic Scale, a scale administered by the clinician. This scale consist of a simple, single item (with no subscale) that measures the overall impact of the disease on the global health of the patient at a specific point in time as evaluated by the physician. It is scored using a visual analogue scale (VAS), anchored on an unnumbered 10-cm horizontal line. Higher scores represent a higher level of disease activity and a worse global health. The proposed definition of "low global assessment" is ≤2.0 (scale 0-10).
Time frame: At recruitment (T0)
Global Physical Assessments: severity of physical diseases
The assessment of the severity of physical diseases will be performed using the Modified Cumulative Illness Rating Scale (CIRS). It includes elements related to 13 clinical areas: heart; hypertension; circulation; respiratory system; head and neck; upper digestive tract; lower digestive tract; liver; kidney; genitourinary system; musculoskeletal and integumentary systems; nervous system and endocrine-metabolic system. For each system, in case two or more pathologies are present, only the one with the greatest clinical impact or associated with the greatest disability will be scored; each score ranges from 0 (the system is not affected by any pathology,) to 4 (very serious pathology and/or need for urgent treatment and/or organ failure and/or severe functional disability). The scale will generate four scores: total score, number of affected systems, severity index (total score/number of affected systems) and number of affected systems with scores of 4-5 (serious or extremely serious).
Time frame: At recruitment (T0)
Assessment of disability
The World Health Organization Disability Assessment Schedule 2.0 (WHO-DAS-II) will be used to assess disability. It is a 36-item self-administered questionnaire on health-related difficulties experienced in the previous month. The instrument evaluates six domains: communication, mobility, self-care, getting along with people, life activities (divided into household and work) and participation in society. Answers are rated on a 5-point scale, from "no difficulties" to "cannot do the activity". Total and subscale scores are calculated, with higher scores reflecting greater disability.
Time frame: At recruitment (T0)
Assessment of quality of life
The 12-Item Short Form Health Survey (SF-12), a brief, self-administered questionnaire, will assess health-related quality of life, including eight domains: physical functioning, role limitations due to physical health, pain, general health, vitality (energy/fatigue), social functioning, role limitations due to mental health. Items are rated on a dichotomous or a Likert scale. The score of each dimension is computed and transformed into a scale from zero (worst health) to 100 (best health). The 8 scales can be summarized into a mental component summary (MCS) score and a physical component summary (PCS) score, that are expressed as T-scores.
Time frame: At recruitment (T0)
Neurocognitive domains
Neurocognition will be evaluated by means of the Cambridge Neuropsychological Test Automated Battery (CANTAB), a computer-based cognitive assessment system. It consists of a battery of neuropsychological tests that can be administered via an iPad.
Time frame: At recruitment (T0)
Coping skills
Coping skills will be assessed using the Coping Orientation to Problems Experienced inventory - Brief (Brief-COPE) including 28 items and 14 subscales: positive reframing, self-distraction, expression, use of instrumental support, active coping, denial, religion, humor, behavioral disengagement, use of emotional support, substance use, acceptance, planning, self-blame. Sum of item scores ranges from 28 to 112.
Time frame: At recruitment (T0)
Stigma
The Stigma Scale for Chronic Illness-8 (SSCI-8) will be used to assess internalized stigma (patient feelings and thoughts concerning his/her condition) and externalized stigma (instances of actual discrimination related to the disease) related to chronic diseases.
Time frame: At recruitment (T0)
Plasma levels of IL-1α
Plasma concentration of IL-1α will be measured by ELISA kits. The assay will be run in duplicate for each patient, along with a standard curve from which plasma concentrations of the analytes will be derived.
Time frame: At recruitment (T0)
Plasma levels of IL-6
Plasma concentration of IL-6 will be measured by ELISA kits. The assay will be run in duplicate for each patient, along with a standard curve from which plasma concentrations of the analytes will be derived.
Time frame: At recruitment (T0)
Plasma levels of TNF-α
Plasma concentration of TNF-α will be measured by ELISA kits. The assay will be run in duplicate for each patient, along with a standard curve from which plasma concentrations of the analytes will be derived.
Time frame: At recruitment (T0)
Plasma levels of ICAM-1
Plasma concentration of ICAM-1 will be measured by ELISA kits. The assay will be run in duplicate for each patient, along with a standard curve from which plasma concentrations of the analytes will be derived.
Time frame: At recruitment (T0)
Plasma levels of VCAM-1
Plasma concentration of VCAM-1 will be measured by ELISA kits. The assay will be run in duplicate for each patient, along with a standard curve from which plasma concentrations of the analytes will be derived.
Time frame: At recruitment (T0)
Assessment of D-dimers levels
D-dimers will be assessed in the clinical and molecular laboratory services of the University Hospital.
Time frame: At recruitment (T0)
Assessment of Fibrogen levels
Fibrinogen levels will be assessed in the clinical and molecular laboratory services of the University Hospital.
Time frame: At recruitment (T0)
Assessment of white blood cells levels
White blood cells (WBC) levels will be assessed in the clinical and molecular laboratory services of the University Hospital.
Time frame: At recruitment (T0)
Assessment of PLT levels
PLT levels will be assessed in the clinical and molecular laboratory services of the University Hospital.
Time frame: At recruitment (T0)
Assessment CD4 and CD8
Levels of CD4 and CD8 will be assessed by calculating the CD4/CD8 ratio through plasma analysis in the clinical and molecular laboratory services of the University Hospital.
Time frame: At recruitment (T0)
Assessment of hs-CRP levels
Levels of a high-sensitivity C-reactive protein (hs-CRP) will be assessed through plasma analysis in the clinical and molecular laboratory services of the University Hospital.
Time frame: At recruitment (T0)
Markers of subclinical inflammatory damage: assessment of subclinical endothelial damage
To assess markers of subclinical endothelial damage, an Ultrasonography of the epi-aortic vessels will be performed by using a power colour-Doppler instrument with 7.5 MHz probes. Characteristics of the intima will be evaluated. A minimum of three measurements will be collected on the common carotid artery (1 cm before the carotid bifurcation and at carotid bifurcation) and on the internal carotid (1 cm after the carotid bifurcation and 2 cm after the carotid bifurcation). An intima-media thickness (IMT) of \>1 mm will be considered to be pathological. Atherosclerotic plaques, if present, will be described. All images will be photographed and properly archived.
Time frame: At recruitment (T0)
Markers of subclinical inflammatory damage: assessment of bone quality
Markers of bone quality will be evaluated by means of Bone quantitative ultrasound (QUS), a technique based on high frequency sound waves generated by the device to determine bone health status. T-scores and Z-scores will be calculated.
Time frame: At recruitment (T0)
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University of Campania Luigi Vanvitelli