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Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT05125458
Other study ID # 417
Secondary ID
Status Completed
Phase
First received
Last updated
Start date April 1, 2021
Est. completion date November 30, 2022

Study information

Verified date November 2023
Source University of Campania "Luigi Vanvitelli"
Contact n/a
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

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.


Description:

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. 1. Shedding light on the interrelationships between mental and physical symptoms in chronic inflammatory diseases. 2. Clarifying mechanisms underlying the high frequency of comorbidity between common mental disorders and chronic inflammatory diseases. 3. Identifying mechanisms responsible for the vicious circle in which mental symptoms can be promoted by proinflammatory cytokines and immune deficiency; in their turn can stimulate the production of proinflammatory cytokines and down-regulate the cellular immune response, and can contribute to prolonged infection and delayed healing, as well as to functional decline. 4. Improving treatment planning by identifying key variables driving the causal chain of determinants of poor QoL. 5. Uncovering the possible influence of unmeasured ("latent") variables not included in the model. 6. Overcoming the main limitations of the current state of the art, through modelling the above-mentioned interrelationships in a large sample of patients by: a) performing a comprehensive psychopathological evaluation carried out by both self- and clinician-rated instruments; b) assessing cognitive functioning, stigma, coping styles and QoL; c) evaluating, besides plasma levels of inflammatory markers, tissue markers of subclinical inflammatory damage. 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. 1. To investigate the frequency of depressive and anxiety symptoms and disorders in 500 clinically stable, outpatients affected by one of the following dermatological diseases: psoriasis, hidradenitis suppurativa or atopic dermatitis, who are being treated for the disorder; as well as in 500 clinically stable outpatients with documented HIV or HBV infection, on treatment with antiviral therapy. 2. To demonstrate that in both samples the presence of clinically significant depressive or anxiety symptoms is associated with worse global health and QoL. 3. To identify mechanisms responsible for the vicious circle in which mental symptoms can be promoted by proinflammatory cytokines and immune deficiency; in their turn can stimulate the production of proinflammatory cytokines and down-regulate the cellular immune response, and can contribute to prolonged infection and delayed healing, as well as to functional decline. 4. To test the hypotheses listed below by the network analysis, using a machine-learning algorithm: 1. chronic inflammation causes both physical and mental symptoms; 2. mental symptoms contribute to inflammatory processes, which cause physical signs and symptoms; 3. inflammatory processes cause physical symptoms, which in their turn cause the mental ones; 4. physical symptoms contribute to both inflammatory processes and to mental symptoms; 5. physical symptoms are associated with inflammatory processes which cause mental symptoms; 6. physical symptoms cause mental symptoms and both are associated with an increase of proinflammatory cytokines and other indices of inflammatory processes. 5. To identify key determinants of disability and poor quality of life, and improve treatment planning by addressing possible unmet treatment targets. 6. To uncover the possible influence of unmeasured variables not included in the model and to be investigated in future studies. 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.


Recruitment information / eligibility

Status Completed
Enrollment 93
Est. completion date November 30, 2022
Est. primary completion date November 30, 2022
Accepts healthy volunteers No
Gender All
Age group 18 Years and older
Eligibility Inclusion criteria for subjects with dermatological diseases; - diagnosis of psoriasis, hidradenitis suppurativa, or atopic dermatitis, any grade of severity; - stability of the cutaneous disease; - ongoing treatment. Inclusion criteria for subjects with HIV or HBV: - documented HIV or HBV infection; - treatment with antiviral therapy; - viral suppression (HIV-RNA or HBV-DNA) for at least 6 months. Inclusion criteria for both groups: - age = 18 years - willingness to provide informed consent. Exclusion Criteria: - a history of intellectual disability, bipolar disorder, psychosis or schizophrenia, or current high suicide risk.

Study Design


Locations

Country Name City State
Italy Department of Psychiatry - University of Campania "Luigi Vanvitelli" Napoli

Sponsors (1)

Lead Sponsor Collaborator
University of Campania "Luigi Vanvitelli"

Country where clinical trial is conducted

Italy, 

References & Publications (65)

Adinolfi LE, Nevola R, Lus G, Restivo L, Guerrera B, Romano C, Zampino R, Rinaldi L, Sellitto A, Giordano M, Marrone A. Chronic hepatitis C virus infection and neurological and psychiatric disorders: an overview. World J Gastroenterol. 2015 Feb 28;21(8):2269-80. doi: 10.3748/wjg.v21.i8.2269. — View Citation

Anker JJ, Kummerfeld E, Rix A, Burwell SJ, Kushner MG. Causal Network Modeling of the Determinants of Drinking Behavior in Comorbid Alcohol Use and Anxiety Disorder. Alcohol Clin Exp Res. 2019 Jan;43(1):91-97. doi: 10.1111/acer.13914. Epub 2018 Nov 25. — View Citation

Ardigo M, Prow T, Agozzino M, Soyer P, Berardesca E. Reflectance confocal microscopy for inflammatory skin diseases. G Ital Dermatol Venereol. 2015 Oct;150(5):565-73. — View Citation

Argentiero A, Neglia C, Peluso A, di Rosa S, Ferrarese A, Di Tanna G, Caiaffa V, Benvenuto M, Cozma A, Chitano G, Agnello N, Paladini D, Baldi N, Distante A, Piscitelli P. The ability of lumbar spine DXA and phalanx QUS to detect previous fractures in young thalassemic patients with hypogonadism, hypothyroidism, diabetes, and hepatitis-B: A 2-year subgroup analysis from the Taranto Area of Apulia Region. J Pediatr Hematol Oncol. 2013 Aug;35(6):e260-4. doi: 10.1097/MPH.0b013e31828e6cab. — View Citation

Borsboom D, Cramer AO. Network analysis: an integrative approach to the structure of psychopathology. Annu Rev Clin Psychol. 2013;9:91-121. doi: 10.1146/annurev-clinpsy-050212-185608. — View Citation

Borsboom D. A network theory of mental disorders. World Psychiatry. 2017 Feb;16(1):5-13. doi: 10.1002/wps.20375. — View Citation

Boschloo L, van Borkulo CD, Rhemtulla M, Keyes KM, Borsboom D, Schoevers RA. The Network Structure of Symptoms of the Diagnostic and Statistical Manual of Mental Disorders. PLoS One. 2015 Sep 14;10(9):e0137621. doi: 10.1371/journal.pone.0137621. eCollection 2015. — View Citation

Bryant RA, Creamer M, O'Donnell M, Forbes D, McFarlane AC, Silove D, Hadzi-Pavlovic D. Acute and Chronic Posttraumatic Stress Symptoms in the Emergence of Posttraumatic Stress Disorder: A Network Analysis. JAMA Psychiatry. 2017 Feb 1;74(2):135-142. doi: 10.1001/jamapsychiatry.2016.3470. — View Citation

Buske-Kirschbaum A, Geiben A, Hollig H, Morschhauser E, Hellhammer D. Altered responsiveness of the hypothalamus-pituitary-adrenal axis and the sympathetic adrenomedullary system to stress in patients with atopic dermatitis. J Clin Endocrinol Metab. 2002 Sep;87(9):4245-51. doi: 10.1210/jc.2001-010872. — View Citation

Capuron L, Gumnick JF, Musselman DL, Lawson DH, Reemsnyder A, Nemeroff CB, Miller AH. Neurobehavioral effects of interferon-alpha in cancer patients: phenomenology and paroxetine responsiveness of symptom dimensions. Neuropsychopharmacology. 2002 May;26(5):643-52. doi: 10.1016/S0893-133X(01)00407-9. — View Citation

Capuron L, Raison CL, Musselman DL, Lawson DH, Nemeroff CB, Miller AH. Association of exaggerated HPA axis response to the initial injection of interferon-alpha with development of depression during interferon-alpha therapy. Am J Psychiatry. 2003 Jul;160(7):1342-5. doi: 10.1176/appi.ajp.160.7.1342. — View Citation

Capuron L, Ravaud A, Dantzer R. Early depressive symptoms in cancer patients receiving interleukin 2 and/or interferon alfa-2b therapy. J Clin Oncol. 2000 May;18(10):2143-51. doi: 10.1200/JCO.2000.18.10.2143. — View Citation

Capuron L, Ravaud A. Prediction of the depressive effects of interferon alfa therapy by the patient's initial affective state. N Engl J Med. 1999 Apr 29;340(17):1370. doi: 10.1056/NEJM199904293401716. No abstract available. — View Citation

Carver CS. You want to measure coping but your protocol's too long: consider the brief COPE. Int J Behav Med. 1997;4(1):92-100. doi: 10.1207/s15327558ijbm0401_6. — View Citation

Constant A, Castera L, Dantzer R, Couzigou P, de Ledinghen V, Demotes-Mainard J, Henry C. Mood alterations during interferon-alfa therapy in patients with chronic hepatitis C: evidence for an overlap between manic/hypomanic and depressive symptoms. J Clin Psychiatry. 2005 Aug;66(8):1050-7. doi: 10.4088/jcp.v66n0814. — View Citation

Costantini M, Musso M, Viterbori P, Bonci F, Del Mastro L, Garrone O, Venturini M, Morasso G. Detecting psychological distress in cancer patients: validity of the Italian version of the Hospital Anxiety and Depression Scale. Support Care Cancer. 1999 May;7(3):121-7. doi: 10.1007/s005200050241. — View Citation

Cramer AO, Waldorp LJ, van der Maas HL, Borsboom D. Comorbidity: a network perspective. Behav Brain Sci. 2010 Jun;33(2-3):137-50; discussion 150-93. doi: 10.1017/S0140525X09991567. — View Citation

D'Abramo A, Zingaropoli MA, Oliva A, D'Agostino C, Al Moghazi S, De Luca G, Iannetta M, d'Ettorre G, Ciardi MR, Mastroianni CM, Vullo V. Higher Levels of Osteoprotegerin and Immune Activation/Immunosenescence Markers Are Correlated with Concomitant Bone and Endovascular Damage in HIV-Suppressed Patients. PLoS One. 2016 Feb 25;11(2):e0149601. doi: 10.1371/journal.pone.0149601. eCollection 2016. — View Citation

Dalgard FJ, Gieler U, Tomas-Aragones L, Lien L, Poot F, Jemec GBE, Misery L, Szabo C, Linder D, Sampogna F, Evers AWM, Halvorsen JA, Balieva F, Szepietowski J, Romanov D, Marron SE, Altunay IK, Finlay AY, Salek SS, Kupfer J. The psychological burden of skin diseases: a cross-sectional multicenter study among dermatological out-patients in 13 European countries. J Invest Dermatol. 2015 Apr;135(4):984-991. doi: 10.1038/jid.2014.530. Epub 2014 Dec 18. — View Citation

Dantzer R, O'Connor JC, Freund GG, Johnson RW, Kelley KW. From inflammation to sickness and depression: when the immune system subjugates the brain. Nat Rev Neurosci. 2008 Jan;9(1):46-56. doi: 10.1038/nrn2297. — View Citation

Dantzer R. Cytokine-induced sickness behavior: where do we stand? Brain Behav Immun. 2001 Mar;15(1):7-24. doi: 10.1006/brbi.2000.0613. — View Citation

Evans DL, Charney DS, Lewis L, Golden RN, Gorman JM, Krishnan KR, Nemeroff CB, Bremner JD, Carney RM, Coyne JC, Delong MR, Frasure-Smith N, Glassman AH, Gold PW, Grant I, Gwyther L, Ironson G, Johnson RL, Kanner AM, Katon WJ, Kaufmann PG, Keefe FJ, Ketter T, Laughren TP, Leserman J, Lyketsos CG, McDonald WM, McEwen BS, Miller AH, Musselman D, O'Connor C, Petitto JM, Pollock BG, Robinson RG, Roose SP, Rowland J, Sheline Y, Sheps DS, Simon G, Spiegel D, Stunkard A, Sunderland T, Tibbits P Jr, Valvo WJ. Mood disorders in the medically ill: scientific review and recommendations. Biol Psychiatry. 2005 Aug 1;58(3):175-89. doi: 10.1016/j.biopsych.2005.05.001. — View Citation

Farzanfar D, Dowlati Y, French LE, Lowes MA, Alavi A. Inflammation: A Contributor to Depressive Comorbidity in Inflammatory Skin Disease. Skin Pharmacol Physiol. 2018;31(5):246-251. doi: 10.1159/000490002. Epub 2018 Jun 28. — View Citation

Federici S, Meloni F, Mancini A, Lauriola M, Olivetti Belardinelli M. World Health Organisation Disability Assessment Schedule II: contribution to the Italian validation. Disabil Rehabil. 2009;31(7):553-64. doi: 10.1080/09638280802240498. — View Citation

Fredriksson T, Pettersson U. Severe psoriasis--oral therapy with a new retinoid. Dermatologica. 1978;157(4):238-44. doi: 10.1159/000250839. — View Citation

Galderisi S, Rucci P, Kirkpatrick B, Mucci A, Gibertoni D, Rocca P, Rossi A, Bertolino A, Strauss GP, Aguglia E, Bellomo A, Murri MB, Bucci P, Carpiniello B, Comparelli A, Cuomo A, De Berardis D, Dell'Osso L, Di Fabio F, Gelao B, Marchesi C, Monteleone P, Montemagni C, Orsenigo G, Pacitti F, Roncone R, Santonastaso P, Siracusano A, Vignapiano A, Vita A, Zeppegno P, Maj M; Italian Network for Research on Psychoses. Interplay Among Psychopathologic Variables, Personal Resources, Context-Related Factors, and Real-life Functioning in Individuals With Schizophrenia: A Network Analysis. JAMA Psychiatry. 2018 Apr 1;75(4):396-404. doi: 10.1001/jamapsychiatry.2017.4607. — View Citation

Garin O, Ayuso-Mateos JL, Almansa J, Nieto M, Chatterji S, Vilagut G, Alonso J, Cieza A, Svetskova O, Burger H, Racca V, Francescutti C, Vieta E, Kostanjsek N, Raggi A, Leonardi M, Ferrer M; MHADIE consortium. Validation of the "World Health Organization Disability Assessment Schedule, WHODAS-2" in patients with chronic diseases. Health Qual Life Outcomes. 2010 May 19;8:51. doi: 10.1186/1477-7525-8-51. — View Citation

Gupta MA, Gupta AK. Psychiatric and psychological co-morbidity in patients with dermatologic disorders: epidemiology and management. Am J Clin Dermatol. 2003;4(12):833-42. doi: 10.2165/00128071-200304120-00003. — View Citation

Haag C, Robinaugh DJ, Ehlers A, Kleim B. Understanding the Emergence of Chronic Posttraumatic Stress Disorder Through Acute Stress Symptom Networks. JAMA Psychiatry. 2017 Jun 1;74(6):649-650. doi: 10.1001/jamapsychiatry.2017.0788. No abstract available. — View Citation

HAMILTON M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960 Feb;23(1):56-62. doi: 10.1136/jnnp.23.1.56. No abstract available. — View Citation

HAMILTON M. The assessment of anxiety states by rating. Br J Med Psychol. 1959;32(1):50-5. doi: 10.1111/j.2044-8341.1959.tb00467.x. No abstract available. — View Citation

Hart BL. Biological basis of the behavior of sick animals. Neurosci Biobehav Rev. 1988 Summer;12(2):123-37. doi: 10.1016/s0149-7634(88)80004-6. — View Citation

Hoffman LK, Ghias MH, Garg A, Hamzavi IH, Alavi A, Lowes MA. Major gaps in understanding and treatment of hidradenitis suppurativa. Semin Cutan Med Surg. 2017 Jun;36(2):86-92. doi: 10.12788/j.sder.2017.024. — View Citation

Holsboer F. Corticotropin-releasing hormone modulators and depression. Curr Opin Investig Drugs. 2003 Jan;4(1):46-50. — View Citation

Irwin MR, Miller AH. Depressive disorders and immunity: 20 years of progress and discovery. Brain Behav Immun. 2007 May;21(4):374-83. doi: 10.1016/j.bbi.2007.01.010. Epub 2007 Mar 13. — View Citation

Jones PJ, Mair P, Riemann BC, Mugno BL, McNally RJ. A network perspective on comorbid depression in adolescents with obsessive-compulsive disorder. J Anxiety Disord. 2018 Jan;53:1-8. doi: 10.1016/j.janxdis.2017.09.008. Epub 2017 Nov 2. — View Citation

Kodraliu G, Mosconi P, Groth N, Carmosino G, Perilli A, Gianicolo EA, Rossi C, Apolone G. Subjective health status assessment: evaluation of the Italian version of the SF-12 Health Survey. Results from the MiOS Project. J Epidemiol Biostat. 2001;6(3):305-16. doi: 10.1080/135952201317080715. — View Citation

Louden BA, Pearce DJ, Lang W, Feldman SR. A Simplified Psoriasis Area Severity Index (SPASI) for rating psoriasis severity in clinic patients. Dermatol Online J. 2004 Oct 15;10(2):7. — View Citation

Maggi P, Bellacosa C, Leone A, Volpe A, Ricci ED, Ladisa N, Cicalini S, Grilli E, Viglietti R, Chirianni A, Bellazzi LI, Maserati R, Martinelli C, Corsi P, Celesia BM, Sozio F, Angarano G. Cardiovascular risk in advanced naive HIV-infected patients starting antiretroviral therapy: Comparison of three different regimens - PREVALEAT II cohort. Atherosclerosis. 2017 Aug;263:398-404. doi: 10.1016/j.atherosclerosis.2017.05.004. Epub 2017 May 5. — View Citation

Mannes ZL, Hearn LE, Zhou Z, Janelle JW, Cook RL, Ennis N. The association between symptoms of generalized anxiety disorder and appointment adherence, overnight hospitalization, and emergency department/urgent care visits among adults living with HIV enrolled in care. J Behav Med. 2019 Apr;42(2):330-341. doi: 10.1007/s10865-018-9988-6. Epub 2018 Nov 1. — View Citation

Martin DA, Towne JE, Kricorian G, Klekotka P, Gudjonsson JE, Krueger JG, Russell CB. The emerging role of IL-17 in the pathogenesis of psoriasis: preclinical and clinical findings. J Invest Dermatol. 2013 Jan;133(1):17-26. doi: 10.1038/jid.2012.194. Epub 2012 Jun 7. — View Citation

Matsunaga MC, Yamauchi PS. IL-4 and IL-13 Inhibition in Atopic Dermatitis. J Drugs Dermatol. 2016 Aug 1;15(8):925-9. — View Citation

McNally RJ. Networks and Nosology in Posttraumatic Stress Disorder. JAMA Psychiatry. 2017 Feb 1;74(2):124-125. doi: 10.1001/jamapsychiatry.2016.3344. No abstract available. — View Citation

Miller MD, Paradis CF, Houck PR, Mazumdar S, Stack JA, Rifai AH, Mulsant B, Reynolds CF 3rd. Rating chronic medical illness burden in geropsychiatric practice and research: application of the Cumulative Illness Rating Scale. Psychiatry Res. 1992 Mar;41(3):237-48. doi: 10.1016/0165-1781(92)90005-n. — View Citation

Modabbernia A, Ashrafi M, Malekzadeh R, Poustchi H. A review of psychosocial issues in patients with chronic hepatitis B. Arch Iran Med. 2013 Feb;16(2):114-22. — View Citation

Molina Y, Choi SW, Cella D, Rao D. The stigma scale for chronic illnesses 8-item version (SSCI-8): development, validation and use across neurological conditions. Int J Behav Med. 2013 Sep;20(3):450-60. doi: 10.1007/s12529-012-9243-4. — View Citation

Nicholas MN, Gooderham MJ. Atopic Dermatitis, Depression, and Suicidality. J Cutan Med Surg. 2017 May/Jun;21(3):237-242. doi: 10.1177/1203475416685078. Epub 2017 Jan 9. — View Citation

Ogarrio JM, Spirtes P, Ramsey J. A Hybrid Causal Search Algorithm for Latent Variable Models. JMLR Workshop Conf Proc. 2016 Aug;52:368-379. — View Citation

Paiardini M, Muller-Trutwin M. HIV-associated chronic immune activation. Immunol Rev. 2013 Jul;254(1):78-101. doi: 10.1111/imr.12079. — View Citation

Pinzone MR, Castronuovo D, Di Gregorio A, Celesia BM, Gussio M, Borderi M, Maggi P, Santoro CR, Madeddu G, Cacopardo B, Nunnari G. Heel quantitative ultrasound in HIV-infected patients: a cross-sectional study. Infection. 2016 Apr;44(2):197-203. doi: 10.1007/s15010-015-0842-2. Epub 2015 Sep 9. — View Citation

Prince M, Patel V, Saxena S, Maj M, Maselko J, Phillips MR, Rahman A. No health without mental health. Lancet. 2007 Sep 8;370(9590):859-77. doi: 10.1016/S0140-6736(07)61238-0. — View Citation

Rao D, Choi SW, Victorson D, Bode R, Peterman A, Heinemann A, Cella D. Measuring stigma across neurological conditions: the development of the stigma scale for chronic illness (SSCI). Qual Life Res. 2009 Jun;18(5):585-95. doi: 10.1007/s11136-009-9475-1. Epub 2009 Apr 25. — View Citation

Ricci G, Dondi A, Patrizi A. Useful tools for the management of atopic dermatitis. Am J Clin Dermatol. 2009;10(5):287-300. doi: 10.2165/11310760-000000000-00000. — View Citation

Sahakian BJ, Morris RG, Evenden JL, Heald A, Levy R, Philpot M, Robbins TW. A comparative study of visuospatial memory and learning in Alzheimer-type dementia and Parkinson's disease. Brain. 1988 Jun;111 ( Pt 3):695-718. doi: 10.1093/brain/111.3.695. — View Citation

Scott PJ, Huskisson EC. Measurement of functional capacity with visual analogue scales. Rheumatol Rehabil. 1977 Nov;16(4):257-9. doi: 10.1093/rheumatology/16.4.257. — View Citation

Seldrup J. Comparison between physician and patient completed visual analogue scales. J Int Med Res. 1977;5(1 Suppl):55-60. — View Citation

Shavit E, Dreiher J, Freud T, Halevy S, Vinker S, Cohen AD. Psychiatric comorbidities in 3207 patients with hidradenitis suppurativa. J Eur Acad Dermatol Venereol. 2015 Feb;29(2):371-376. doi: 10.1111/jdv.12567. Epub 2014 Jun 9. — View Citation

Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, Hergueta T, Baker R, Dunbar GC. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry. 1998;59 Suppl 20:22-33;quiz 34-57. — View Citation

Strogatz SH. Exploring complex networks. Nature. 2001 Mar 8;410(6825):268-76. doi: 10.1038/35065725. — View Citation

Swaab DF, Bao AM, Lucassen PJ. The stress system in the human brain in depression and neurodegeneration. Ageing Res Rev. 2005 May;4(2):141-94. doi: 10.1016/j.arr.2005.03.003. — View Citation

Swindells K, Burnett N, Rius-Diaz F, Gonzalez E, Mihm MC, Gonzalez S. Reflectance confocal microscopy may differentiate acute allergic and irritant contact dermatitis in vivo. J Am Acad Dermatol. 2004 Feb;50(2):220-8. doi: 10.1016/j.jaad.2003.08.005. — View Citation

Thorlacius L, Cohen AD, Gislason GH, Jemec GBE, Egeberg A. Increased Suicide Risk in Patients with Hidradenitis Suppurativa. J Invest Dermatol. 2018 Jan;138(1):52-57. doi: 10.1016/j.jid.2017.09.008. Epub 2017 Sep 20. — View Citation

Vitiello B, Burnam MA, Bing EG, Beckman R, Shapiro MF. Use of psychotropic medications among HIV-infected patients in the United States. Am J Psychiatry. 2003 Mar;160(3):547-54. doi: 10.1176/appi.ajp.160.3.547. — View Citation

Vitiello P, Taramasso L, Ricci E, Maggi P, Martinelli C, Gabrielli C, Vittorio De Socio G, Di Cristo V, Rusconi S, Falasca K, Menzaghi B, Tebini A, Di Biagio A. Use of quantitative ultrasound as bone mineral density evaluation in an Italian female population living with HIV: A real-life experience. J Women Aging. 2019 Mar-Apr;31(2):176-188. doi: 10.1080/08952841.2018.1428100. Epub 2018 Jan 25. — View Citation

Weigle N, McBane S. Psoriasis. Am Fam Physician. 2013 May 1;87(9):626-33. — View Citation

* Note: There are 65 references in allClick here to view all references

Outcome

Type Measure Description Time frame Safety issue
Primary 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. At recruitment (T0)
Primary 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. At recruitment (T0)
Primary 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. At recruitment (T0)
Primary 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. At recruitment (T0)
Primary 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. At recruitment (T0)
Primary 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). At recruitment (T0)
Primary 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). At recruitment (T0)
Primary 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). At recruitment (T0)
Primary 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). At recruitment (T0)
Primary 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). At recruitment (T0)
Primary 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). At recruitment (T0)
Primary 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. At recruitment (T0)
Primary 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. At recruitment (T0)
Primary 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. At recruitment (T0)
Primary 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. At recruitment (T0)
Primary 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. At recruitment (T0)
Primary Plasma levels of IL-1a Plasma concentration of IL-1a 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. At recruitment (T0)
Primary 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. At recruitment (T0)
Primary Plasma levels of TNF-a Plasma concentration of TNF-a 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. At recruitment (T0)
Primary 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. At recruitment (T0)
Primary 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. At recruitment (T0)
Primary Assessment of D-dimers levels D-dimers will be assessed in the clinical and molecular laboratory services of the University Hospital. At recruitment (T0)
Primary Assessment of Fibrogen levels Fibrinogen levels will be assessed in the clinical and molecular laboratory services of the University Hospital. At recruitment (T0)
Primary 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. At recruitment (T0)
Primary Assessment of PLT levels PLT levels will be assessed in the clinical and molecular laboratory services of the University Hospital. At recruitment (T0)
Primary 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. At recruitment (T0)
Primary 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. At recruitment (T0)
Primary 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. At recruitment (T0)
Primary 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. At recruitment (T0)
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