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• W4220972015 abstract "Psoriasis is a chronic inflammatory disease affecting 3% of the US population (Armstrong et al., 2021Armstrong A.W. Mehta M.D. Schupp C.W. Gondo G.C. Bell S.J. Griffiths C.E.M. Psoriasis prevalence in adults in the United States.JAMA Dermatol. 2021; 157: 940-946Crossref PubMed Scopus (102) Google Scholar). The negative effect of psoriasis on health-related QOL is similar to that of other serious chronic diseases (Rapp et al., 1999Rapp S.R. Feldman S.R. Exum M.L. Fleischer Jr., A.B. Reboussin D.M. Psoriasis causes as much disability as other major medical diseases.J Am Acad Dermatol. 1999; 41: 401-407Abstract Full Text Full Text PDF PubMed Scopus (1319) Google Scholar). Data on the QOL burden of psoriasis among non-White populations are limited. This study evaluated racial/ethnic differences in the effect of psoriasis on health-related QOL, as measured by the Dermatology Life Quality Index (DLQI), among North American patients with psoriasis enrolled in Psoriasis Longitudinal Assessment and Registry (PSOLAR). PSOLAR (NCT00508547) is a prospective, observational, international study of patients with moderate-to-severe psoriasis who are receiving or are candidates for systemic therapy. Demographic, medical history, psoriasis severity and treatment, DLQI, and safety data are collected at enrolment and every 6 months for up to 8 years. Enrolment began in June 2007. The registry was fully enrolled at 12,090 patients in June 2013 (Papp et al., 2012Papp K.A. Strober B. Augustin M. Calabro S. Londhe A. Chevrier M. on behalf of the PSOLAR investigators and Steering CommitteePSOLAR: design, utility, and preliminary results of a prospective, international, disease-based registry of patients with psoriasis who are receiving, or are candidates for, conventional systemic treatments or biologic agents.J Drugs Dermatol. 2012; 11: 1210-1217PubMed Google Scholar; Kimball et al., 2014Kimball A.B. Leonardi C. Stahle M. Gulliver W. Chevrier M. Fakharzadeh S. et al.Demography, baseline disease characteristics and treatment history of patients with psoriasis enrolled in a multicentre, prospective, disease-based registry (PSOLAR).Br J Dermatol. 2014; 171: 137-147Crossref PubMed Scopus (101) Google Scholar). We performed a cross-sectional analysis of data collected at registry entry from North American patients enrolled in PSOLAR (n = 10,876); patients without DLQI scores (i.e., >1 missing DLQI item score; n = 769) were excluded, yielding a study population of 10,107 patients. The study population was limited to North American patients to ensure comparable social constructs of race and ethnicity. North American central Institutional Review Boards/Ethics Committees that approved the study protocol included Advarra, Chesapeake IRB, Institutional Review Board Services, and Research Review Board Inc. All patients/legally acceptable representatives provided written informed consent. The primary outcome measure was the DLQI score. DLQI is a validated 10-item questionnaire that measures the effect of skin disease on health-related QOL (Finlay and Khan, 1994Finlay A.Y. Khan G.K. Dermatology Life Quality Index (DLQI)--a simple practical measure for routine clinical use.Clin Exp Dermatol. 1994; 19: 210-216Crossref PubMed Scopus (3898) Google Scholar; Mazzotti et al., 2005Mazzotti E. Barbaranelli C. Picardi A. Abeni D. Pasquini P. Psychometric properties of the Dermatology Life Quality Index (DLQI) in 900 Italian patients with psoriasis.Acta Derm Venereol. 2005; 85: 409-413Crossref PubMed Scopus (62) Google Scholar, Mazzotti et al., 2003Mazzotti E. Picardi A. Sampogna F. Sera F. Pasquini P. Abeni D. et al.Sensitivity of the Dermatology Life Quality Index to clinical change in patients with psoriasis.Br J Dermatol. 2003; 149: 318-322Crossref PubMed Scopus (81) Google Scholar; Hongbo et al., 2005Hongbo Y. Thomas C.L. Harrison M.A. Salek M.S. Finlay A.Y. Translating the science of quality of life into practice: what do dermatology life quality index scores mean?.J Invest Dermatol. 2005; 125: 659-664Abstract Full Text Full Text PDF PubMed Scopus (599) Google Scholar). DLQI scores range from 0–30; higher scores indicate greater health-related QOL impairment. DLQI scores were evaluated as continuous and dichotomous (no effect [range, 0–1] vs. at least small effect [range, 2–30] on a person’s life) outcomes. An increasing body of literature suggests that DLQI scores should be corrected for not relevant responses (Rencz et al., 2020Rencz F. Gulácsi L. Péntek M. Szegedi A. Remenyik É. Bata-Csörgő Z. et al.DLQI-R scoring improves the discriminatory power of the Dermatology Life Quality Index in patients with psoriasis, pemphigus and morphea.Br J Dermatol. 2020; 182: 1167-1175Crossref PubMed Scopus (19) Google Scholar, Rencz et al., 2018Rencz F. Gulácsi L. Péntek M. Poór A.K. Sárdy M. Holló P. et al.Proposal of a new scoring formula for the Dermatology Life Quality Index in psoriasis.Br J Dermatol. 2018; 179: 1102-1108Crossref PubMed Scopus (38) Google Scholar; van Winden et al., 2021van Winden M.E.C. Ter Haar E.L.M. Groenewoud J.M.M. van de Kerkhof P.C.M. de Jong E.M.G.J. Lubeek S.F.K. Quality of life, treatment goals, preferences and satisfaction in older adults with psoriasis: a patient survey comparing age groups.Br J Dermatol. 2021; 184: 759-762Crossref PubMed Scopus (8) Google Scholar; Barbieri et al., 2020Barbieri J.S. Shin D.B. Syed M.N. Takeshita J. Gelfand J.M. Evaluation of the frequency of not relevant responses on the Dermatology Life Quality Index by sociodemographic characteristics of patients with psoriasis.JAMA Dermatol. 2020; 156: 446-450Crossref PubMed Scopus (10) Google Scholar). Not relevant responses are common among individuals with psoriasis, and the use of uncorrected DLQI scores may result in the underestimation of health-related QOL burden, particularly among certain patient groups. Self-reported race/ethnicity was categorized as non-Hispanic White (reference), Black, Asian, or other race; or Hispanic/Latino ethnicity (any race). Other variables and potential confounders included sociodemographic characteristics, psoriasis disease and treatment history, and other medical history (body mass index, anxiety and depression [based on Hospital Anxiety and Depression Scale score], smoking status, alcohol consumption, and comorbidities). Univariable ANOVA or chi-squared test was performed to compare continuous or dichotomous DLQI scores, respectively, among racial/ethnic groups. If 1 DLQI item score was missing (n = 552), data were imputed with the missing item score set to 0, and the total score was included; if >1 DLQI item score was missing, the total score was not included. Univariable and multivariable logistic regression was performed to evaluate the association between race/ethnicity and the dichotomous DLQI outcome. All covariates that were significantly different across racial/ethnic groups and associated with the DLQI outcome were included in the multivariable model, and included age, sex, education, employment, geographic region, income, marital status, insurance, smoking status, alcohol use, medical history, psoriasis history, body mass index, and psoriasis severity. Sensitivity analyses were performed using DLQI-Relevant scores that correct for not relevant responses (Rencz et al., 2018Rencz F. Gulácsi L. Péntek M. Poór A.K. Sárdy M. Holló P. et al.Proposal of a new scoring formula for the Dermatology Life Quality Index in psoriasis.Br J Dermatol. 2018; 179: 1102-1108Crossref PubMed Scopus (38) Google Scholar), excluding patients with psoriatic arthritis, and restricting the study population to US patients. ORs with 95% confidence intervals were reported. P-values were not adjusted for multiplicity. The study included 10,107 North American patients: 82.5% White, 4.0% Black, 4.3% Asian, 6.6% Hispanic/Latino, and 2.6% other race. Several demographic, socioeconomic, psoriasis, and medical history characteristics differed by race/ethnicity (Table 1).Table 1Demographic, Socioeconomic, Psoriasis, and Medical/Social History Characteristics by Race/Ethnicity at Registry EntryCharacteristicWhite (n = 8,338)Black (n = 404)Asian (n = 436)Hispanic/Latino (n = 668)Other (n = 261)P-Value1P-values were from ANOVA (continuous variables) or chi-squared tests (categorical variables) to determine if all four racial/ethnic groups were equal (not adjusted for multiplicity).Age (y), mean ± SD49.2 ± 13.949.6 ± 13.645.4 ± 14.245.9 ± 13.344.8 ± 13.5<0.001Male sex4,418 (53.0)187 (46.3)299 (68.6)409 (61.2)154 (59.0)<0.001Education level <High school324 (3.9)22 (5.5)22 (5.1)90 (13.5)14 (5.4)<0.001 High school2,497 (30.0)126 (31.2)95 (21.8)232 (34.7)57 (21.8) >High school5,472 (65.6)247 (61.1)315 (72.3)318 (47.6)184 (70.5) Missing45 (0.5)9 (2.2)4 (0.9)28 (4.2)6 (2.3)Employment Full-time4,704 (56.4)193 (47.8)251 (57.6)362 (54.2)153 (58.6)<0.001 Part-time855 (10.3)37 (9.2)44 (10.1)75 (11.2)21 (8.1) Retired1,347 (16.2)62 (15.4)48 (11.0)60 (9.0)24 (9.2) School150 (1.8)10 (2.5)13 (3.0)15 (2.3)10 (3.8) Missing1,282 (15.4)102 (25.3)80 (18.4)156 (23.4)53 (20.3)Annual income <$41,0002,362 (28.3)208 (51.5)175 (40.1)317 (47.5)96 (36.8)<0.001 $41,000 to <$111,0003,641 (43.7)122 (30.2)161 (36. 9)235 (35.2)93 (35.6) ≥$111,0001,607 (19.3)32 (7.9)64 (14.7)57 (8.5)42 (16.1) Missing728 (8.7)42 (10.4)36 (8.3)59 (8.8)30 (11.5)Married/Committed5,503 (66.0)174 (43.1)298 (68.4)434 (65.0)151 (57.9)<0.001Health insurance Public only1,065 (12.8)79 (19.6)88 (20.2)86 (12.9)36 (13.8)<0.001 Private only6,064 (72.7)243 (60.2)304 (69.7)422 (63.2)176 (67.4) Both664 (8.0)30 (7.4)5 (1.2)19 (2.8)12 (4.6) None545 (6.5)52 (12.9)39 (8.9)141 (21.1)37 (14.2)PsO characteristicsPsO duration (per 5 y), mean ± SD3.7 ± 2.82.3 ± 2.12.6 ± 2.12.6 ± 2.22.7 ± 2.2<0.001PsO arthritis3,111 (37.3)138 (34.2)133 (30.5)246 (36.8)91 (34.9)0.041BSA (%) 0% to <3%3,134 (37.6)117 (29.0)103 (23.6)212 (31.7)74 (28.4)<0.001 3% to 10%3,080 (36.9)136 (33.7)137 (31.4)211 (31.6)84 (32.2) >10%2,124 (25.5)151 (37.4)196 (45.0)245 (36.7)103 (39.5)PGA 0/12,923 (35.1)158 (39.1)144 (33.0)236 (35.3)75 (28.7)<0.001 2/34,706 (56.4)205 (50.7)256 (58.7)345 (51.7)160 (61.3) 4/5709 (8.5)41 (10.2)36 (8.3)87 (13.0)26 (10.0)PsO treatment historyNumber of biologics used 15,381 (64.5)299 (74.0)326 (74.8)460 (68.9)177 (67.8)<0.001 2+2,957 (35.5)105 (26.0)110 (25.2)208 (31.1)84 (32.2)Immunomodulator use2This category includes immunomodulators such as methotrexate, cyclosporine, mycophenolate mofetil, and tacrolimus; this category does not include oral corticosteroids.3,935 (47.2)170 (42.1)175 (40.1)246 (36.8)123 (47.1)<0.001Systemic steroid use1,298 (15.6)42 (10.4)60 (13.8)85 (12.7)36 (13.8)0.015History of phototherapy4,563 (54.7)182 (45.1)239 (54.8)299 (44.8)138 (52.9)<0.001Medical/social historyBMI <25 kg/m21,522 (18.3)46 (11.4)181 (41.5)89 (13.3)56 (21.5)<0.001 25 to <30 kg/m22,593 (31.1)120 (29.7)154 (35.3)193 (28.9)88 (33.7) ≥30 kg/m24,223 (50.7)238 (58.9)101 (23.2)386 (57.8)117 (44.8)HADS-D ≥ 8965 (11.6)73 (18.1)68 (15.6)137 (20.5)42 (16.1)<0.001HADS-A ≥ 82,303 (27.6)122 (30.2)138 (31.7)230 (34.4)76 (29.1)0.002Comorbid disease Cardiovascular disease3,323 (39.9)195 (48.3)130 (29.8)206 (30.8)104 (39.9)<0.001 Pulmonary disease1,332 (16.0)79 (19.6)41 (9.4)70 (10.5)32 (12.3)<0.001 Psychiatric illness1,970 (23.6)66 (16.3)33 (7.6)122 (18.3)42 (16.1)<0.001 Skin cancer664 (8.0)0 (0)1 (0.2)11 (1.7)3 (1.2)<0.001 Other cancer365 (4.4)15 (3.7)3 (0.7)19 (2.8)7 (2.7)<0.001 Endocrine disease1,626 (19.5)106 (26.2)60 (13.8)129 (19.3)56 (21.5)<0.001 Infection/prescription3Infection/prescription denotes patients who had a history of an infection that required prescription medication within 3 years before enrollment.2,261 (27.1)94 (23.3)71 (16.3)131 (19.6)60 (23.0)<0.001 Tuberculosis111 (1.3)10 (2.5)54 (12.4)39 (5.8)19 (7.3)<0.001Smoking status Never3,409 (40.9)226 (55.9)248 (56.9)388 (58.1)127 (48.7)<0.001 Current1,987 (23.8)91 (22.5)76 (17.4)102 (15.3)58 (22.2) Past2,940 (35.3)87 (21.5)112 (25.7)178 (26.7)76 (29.1) Missing2 (0.0)0 (0)0 (0)0 (0)0 (0)Alcohol use Never1,429 (17.1)103 (25.5)162 (37.2)174 (26.1)65 (24.9)<0.001 Current5,719 (68.6)224 (55.5)214 (49.1)357 (53.4)150 (57.5) Past1,187 (14.2)76 (18.8)60 (13.8)137 (20.5)46 (17.6) Missing3 (0.0)1 (0.3)0 (0)0 (0)0 (0)Abbreviations: BMI, body mass index; BSA, body surface area; HADS-A: Hospital Anxiety and Depression Scale – Anxiety; HADS-D: Hospital Anxiety and Depression Scale – Depression; PGA, Physician Global Assessment; PsO, psoriasis.Data are presented as number (%), unless otherwise indicated.1 P-values were from ANOVA (continuous variables) or chi-squared tests (categorical variables) to determine if all four racial/ethnic groups were equal (not adjusted for multiplicity).2 This category includes immunomodulators such as methotrexate, cyclosporine, mycophenolate mofetil, and tacrolimus; this category does not include oral corticosteroids.3 Infection/prescription denotes patients who had a history of an infection that required prescription medication within 3 years before enrollment. Open table in a new tab Abbreviations: BMI, body mass index; BSA, body surface area; HADS-A: Hospital Anxiety and Depression Scale – Anxiety; HADS-D: Hospital Anxiety and Depression Scale – Depression; PGA, Physician Global Assessment; PsO, psoriasis. Data are presented as number (%), unless otherwise indicated. Mean total DLQI score was significantly different across racial/ethnic groups. White patients had the lowest score (5.6), and Black patients had the highest score (8.3; P < 0.001 across groups; Table 2). The proportion of patients with DLQI total score ≥2 was lowest among White patients (68.6%), followed by Hispanic/Latino (76.2%), Asian (79.1%), and Black (80.0%) patients (P < 0.001 across groups). In adjusted analyses, compared with White patients, Black (OR = 1.74, 95% confidence interval = 1.29–2.34), Asian (OR = 1.52, 95% confidence interval = 1.14–2.03), and Hispanic/Latino (OR = 1.42, 95% confidence interval = 1.12–1.79) patients each had higher odds of having a DLQI score ≥2 (Table 2). These associations were robust to the sensitivity analyses performed (results from the DLQI Relevant sensitivity analysis are shown in Supplementary Table S1). Other covariates that were significantly associated with DLQI total score ≥2 are shown in Supplementary Table S2.Table 2DLQI Scores by Race/Ethnicity at Registry Entry: Descriptive Statistics and Modeled AnalysesRace/EthnicityTotal DLQI Score,1P < 0.001, univariable analysis of variance. Mean ± SDDLQI ≥2 (Any Effect),2P < 0.001, chi-squared test. n (%)Unadjusted OR (95% CI) DLQI Any EffectAdjusted OR (95% CI), DLQI Any Effect White5.6 (6.1)5,719 (68.6)ReferenceReference Black8.3 (7.6)323 (80.0)1.82 (1.42–2.33)1.74 (1.29–2.34) Asian7.9 (7.4)345 (79.1)1.74 (1.37–2.20)1.52 (1.14–2.03) Hispanic/Latino8.0 (7.6)509 (76.2)1.47 (1.22–1.76)1.42 (1.12–1.79) Other8.0 (7.6)191 (73.2)1.25 (0.95–1.65)0.88 (0.62–1.23)Abbreviations: CI, confidence interval; DLQI, Dermatology Life Quality Index.OR: measure of association between an outcome and an exposure.1 P < 0.001, univariable analysis of variance.2 P < 0.001, chi-squared test. Open table in a new tab Abbreviations: CI, confidence interval; DLQI, Dermatology Life Quality Index. OR: measure of association between an outcome and an exposure. This study of >10,000 North American patients with psoriasis enrolled in PSOLAR found that Black, Asian, and Hispanic/Latino patients each reported a greater effect of psoriasis on health-related QOL, as measured by the DLQI, than White patients. Results were independent of disease severity, treatment, and other sociodemographic and medical factors. This study lends support to a previous study of clinical trial participants that also found psoriasis to have a larger effect on health-related QOL, based on DLQI score, among racial/ethnic minority versus White participants (Shah et al., 2011Shah S.K. Arthur A. Yang Y.C. Stevens S. Alexis A.F. A retrospective study to investigate racial and ethnic variations in the treatment of psoriasis with etanercept.J Drugs Dermatol. 2011; 10: 866-872PubMed Google Scholar). Our findings are particularly relevant in the setting of known racial disparities in healthcare utilization for (Fischer et al., 2018Fischer A.H. Shin D.B. Gelfand J.M. Takeshita J. Health care utilization for psoriasis in the United States differs by race: an analysis of the 2001–2013 Medical Expenditure Panel Surveys.J Am Acad Dermatol. 2018; 78: 200-203Abstract Full Text Full Text PDF PubMed Scopus (14) Google Scholar) and treatment of (Takeshita et al., 2015Takeshita J. Gelfand J.M. Li P. Pinto L. Yu X. Rao P. et al.Psoriasis in the US medicare population: prevalence, treatment, and factors associated with biologic use.J Invest Dermatol. 2015; 135: 2955-2963Abstract Full Text Full Text PDF PubMed Scopus (101) Google Scholar) psoriasis. Together, these data highlight a disproportionate burden of psoriasis among racial/ethnic minorities that deserves more attention and may warrant more aggressive treatment. Study limitations include unmeasured confounding factors that may affect the relationship between race/ethnicity and DLQI score, and underrepresentation of non-White individuals relative to the overall North American population, despite the inclusion of a larger number of racial/ethnic minority individuals than previous studies. Findings from this study may not be generalizable to individuals with psoriasis who are not receiving healthcare or who have mild disease. In conclusion, to optimize care and outcomes for all individuals with psoriasis, clinicians should consider measuring the QOL burden of psoriasis for every patient and recognize racial/ethnic differences in the effect of psoriasis on QOL that may warrant different treatment strategies. Further studies are needed to identify the causes of racial/ethnic differences in the QOL burden of psoriasis; these may include qualitative studies to better understand the effect of psoriasis on the lives of individuals from different racial/ethnic groups. This work is critical to reducing disparities and guiding individualized treatment of psoriasis. Datasets related to this article are not currently publicly available because the registry is still ongoing but will be available by request when the study concludes. Junko Takeshita: http://orcid.org/0000-0002-9650-9738 Matthias Augustin: http://orcid.org/0000-0002-4026-8728 Elke M.G.J. de Jong: http://orcid.org/0000-0003-3872-5704 Kimberly Parnell Lafferty: http://orcid.org/0000-0001-9804-2740 Wayne Langholff: http://orcid.org/0000-0001-9247-338X Alan Menter: https://orcid.org/0000-0002-9314-0007 Andrew F. Alexis: https://orcid.org/0000-0002-1351-9165 JT has received a research grant from Pfizer Inc. (to the Trustees of the University of Pennsylvania) for work that is unrelated to this study. MA has served as a consultant and/or paid speaker for clinical trials sponsored by AbbVie, Almirall, Amgen, Biogen, Boehringer Ingelheim, Celgene, Centocor, Eli Lilly, Fresenius, Galderma, GlaxoSmithKline, Janssen-Cilag, LEO Pharma, Medac, Merck, MSD, Novartis, Pfizer, UCB, and XenoPort. EMGJdJ has received research grants for the independent research fund of the Department of Dermatology of the Radboud University Medical Centre, Nijmegen, the Netherlands from AbbVie, Janssen, LEO Pharma, Novartis, and UCB; she has acted as a consultant and/or paid speaker and/or participated in research sponsored by AbbVie, Almirall, Celgene, Eli Lilly, Janssen, LEO Pharma, Novartis, and UCB. KPL is employed by Janssen Scientific Affairs, LLC, and owns stock in Johnson & Johnson, of which Janssen is a subsidiary. WL is employed by Janssen Research & Development, LLC, and owns stock in Johnson & Johnson, of which Janssen is a subsidiary. RGL has served and has received compensation in the form of grant funding and/or honoraria, as principal investigator for and is on the scientific advisory board or served as a speaker for AbbVie, Amgen, Boehringer Ingelheim, Celgene, Eli Lilly, Janssen, LEO Pharma, Merck, Novartis, Pfizer, Sun Pharma, and UCB. AM has received grants and/or honoraria as an advisory board member, consultant, principal investigator, and/or speaker from Abbott Labs, Amgen, Boehringer Ingelheim, Celgene, Eli Lilly, Janssen Biotech, Inc., Leo Pharma, Merck, Novartis, Sienna, and UCB. AFA has received grants (funds to institution) and/or served as a consultant/advisor for AbbVie, Allergan, Almirall, Amgen, Arcutis, AstraZeneca, Beiersdorf, Bristol Myers Squibb, Cara, Dermavant, Galderma, Janssen, Leo, Lilly, L’Oreal, Menlo, Novartis, Pfizer, Regeneron, Sanofi-Genzyme, Sol-Gel, UCB, Valeant (Bausch Health), and Vyne; and has served on the advisory board or consulted for Leo, Galderma, Pfizer, Sanofi-Regeneron, Dermavant, Beiersdorf, Valeant, L’Oreal, BMS, Bausch health, UCB, Vyne, Arcutis, Janssen, Allergan, Almirall, AbbVie, Sol-Gel, Amgen, and VisualDx; and has served as a speaker for Regeneron, Sanofi-Genzyme, and Pfizer. The authors thank Cynthia Arnold, Cherie Koch, and Dan Chen, all of Janssen Scientific Affairs, LLC (Horsham, PA) for their editorial and writing support, and Joel Gelfand (Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA) and the PSOLAR Scientific Advisory Committee for their critical review of the analytical plan. This study was funded by Janssen Scientific Affairs, LLC. JT is supported by NIAMS K23-AR068433. Conceptualization: JT, KPL, WL, AFA; Formal Analyses: WL; Writing - Original Draft Preparation: JT, MA, EMGJdJ, KPL, WL, RGL, AM, AFA; Writing - Review and Editing: JT, MA, EMGJdJ, KPL, WL, RGL, AM, AFA Supplementary Table S1DLQI-R Scores by Race/Ethnicity at Registry Entry: Descriptive Statistics and Modeled AnalysesRace/EthnicityTotal DLQI-R Score, Mean ± SDDLQI-R ≥ 2 (Any Effect), n (%)Unadjusted OR (95% CI), DLQI Any EffectAdjusted OR (95% CI), DLQI Any Effect White6.2 (6.7)5,781 (69.3)ReferenceReference Black9.1 (8.0)326 (80.7)1.84 (1.43–2.37)1.73 (1.28–2.34) Asian8.5 (7.7)345 (79.1)1.68 (1.33–2.12)1.43 (1.07–1.91) Hispanic/Latino8.8 (8.0)518 (77.5)1.53 (1.27–1.84)1.49 (1.17–1.89) Other8.7 (8.0)193 (74.0)1.26 (0.95–1.66)0.88 (0.62–1.24)Abbreviations: CI, confidence interval; DLQI-R, Dermatology Life Quality Index-Relevant.OR: measure of association between an outcome and an exposure. Open table in a new tab Supplementary Table S2Multivariable Logistic Regression Model Results: OR for Reporting at Least a Small Effect on Health-Related QOL (DLQI ≥2)CharacteristicOR95% CIAge per 10-y (older vs. younger)0.85(0.81–0.90)Sex MaleReference Female1.72(1.53–1.92)BMI <25Reference 25 to <301.10(0.95–1.28) ≥301.13(0.97–1.30)Education <High schoolReference High school1.29(0.99–1.68) >High school1.56(1.20–2.04) Missing0.77(0.45–1.34)Employment Full-timeReference Part-time1.00(0.84–1.20) Retired1.18(0.98–1.42) School1.03(0.68–1.57) Unknown1.03(0.87–1.22)Region USA NortheastReference USA Midwest1.20(1.00–1.43) USA South0.99(0.84–1.16) USA West1.19(1.00–1.43) CAN Atlantic0.87(0.66–1.13) CAN Ontario1.08(0.86–1.35) CAN Quebec1.03(0.75–1.41) CAN West1.29(0.93–1.79)Income <$40,200Reference $40,200 to $110,9990.92(0.80–1.06) ≥$111,0001.07(0.89–1.28) Missing0.94(0.77–1.16)Marital status Not married/committedReference Married/committed0.94(0.83–1.06)Insurance PublicReference Private1.16(0.97–1.40) Both public/private0.99(0.78–1.26) None1.05(0.81–1.35)Smoking NeverReference Current1.16(1.01–1.34) Past1.10(0.97–1.24)Alcohol NeverReference Current1.01(0.87–1.17) Past1.04(0.86–1.25)Medical history (Y vs. N) Cardiovascular1.14(1.01–1.28) Pulmonary1.15(0.99–1.34) Psychiatric illness1.02(0.89–1.17) Hepatic1.15(0.88–1.52) Skin cancer0.89(0.73–1.09) Other cancer1.33(1.01–1.74) Endocrine0.95(0.82–1.09) Infection/prescription1Infection/prescription denotes patients who had a history of an infection that required prescription medication within 3 years before enrollment.1.18(1.04–1.33) Psoriatic arthritis1.30(1.17–1.46)Duration of psoriasis per 5 y0.93(0.91–0.95)PGA 0/1Reference 2/32.93(2.62–3.28) 4/56.91(5.01–9.53)BSA (%) 0 to <3Reference 3–102.96(2.62–3.33) >105.88(4.97–6.95)HADS-D (range) 1–7Reference ≥81.99(1.60–2.48) Missing1.29(0.92–1.81)HADS-A (range) 1–7Reference ≥82.03(1.77–2.33) Missing1.09(0.78–1.52)Number of biologics: >1 versus 11.00(0.89–1.13)Current biologics (Y vs. N)0.56(0.49–0.63)History of immunomodulators (Y vs. N)0.94(0.84–1.06)History of systemic steroids (Y vs. N)1.04(0.88–1.23)Current systemic steroids (Y vs. N)1.03(0.64–1.66)History of phototherapy (Y vs. N)0.98(0.88–1.10)Abbreviations: BMI, Body Mass Index; BSA, Body Surface Area; CAN, Canada; CI, confidence interval; DLQI, Dermatology Life Quality Index; HADS-A, Hospital Anxiety and Depression Scale – Anxiety; HADS-D, Hospital Anxiety and Depression Scale – Depression; N, No; PGA, Physician Global Assessment; USA, United States of America; Y, Yes.OR: measure of association between an outcome and an exposure.1 Infection/prescription denotes patients who had a history of an infection that required prescription medication within 3 years before enrollment. Open table in a new tab Abbreviations: CI, confidence interval; DLQI-R, Dermatology Life Quality Index-Relevant. OR: measure of association between an outcome and an exposure. Abbreviations: BMI, Body Mass Index; BSA, Body Surface Area; CAN, Canada; CI, confidence interval; DLQI, Dermatology Life Quality Index; HADS-A, Hospital Anxiety and Depression Scale – Anxiety; HADS-D, Hospital Anxiety and Depression Scale – Depression; N, No; PGA, Physician Global Assessment; USA, United States of America; Y, Yes. OR: measure of association between an outcome and an exposure." @default.
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