Convergent Validity of Suffering and Quality of Life as Measured by The Hidradenitis Suppurativa Quality of Life

The Dermatology Life Quality Index (DLQI) used as the benchmark in validation of 101 quality-of-life instruments: A systematic review

BACKGROUND

The validation of psychometric measures requires use of other established and standardized validated measures. The Dermatology Life Quality Index (DLQI) is the most widely used tool to measure the burden of skin diseases and assess effectiveness of interventions based on patients' perspective.

OBJECTIVES

The objective of this study was to systematically analyse peer-reviewed publications describing use of the DLQI in validation of other patient-reported outcome (PRO) and quality-of-life (QoL) measures.

METHODS

Seven databases were searched for papers published between January 1994 and December 2022 for articles containing data using DLQI in the validation of other PRO/QoL measures. The methodology followed PRISMA guidelines. The protocol was prospectively registered on PROSPERO.

RESULTS

Of 1717 screened publications, 122 articles including 30,727 patients from 34 different countries with 41 diseases met the inclusion criteria. The DLQI was used in validation of 101 measures: 80 dermatology-specific QoL measures, mostly disease-specific, and 21 generic measures. Of these studies, 47 were cross-cultural adaptations, 116 single arm, 100 were cross-sectional, 18 longitudinal and six randomized placebo controlled. DLQI was used for 14 known group, and correlation for 10 construct, 101 convergent, 10 concurrent, 10 divergent/discriminant and three criterion validity tests using Mann-Whitney (2), Spearman's (80), Pearson's correlation (26) and Student's t-test (1). The DLQI was used in responsiveness analysis in 13 studies.

CONCLUSIONS

This review identified widespread use of the DLQI in validation of other dermatology PRO/QoL measures and confirmed the central role that the DLQI plays as a benchmark in instrument development and validation across dermatology and beyond. The use of the DLQI by so many developers of other instruments has provided a common standard for comparability.

Initial steps towards developing a predictive algorithm of disease progression for hidradenitis suppurativa (HS): results from a Cox proportional hazard regression analysis on disease progression among a cohort of 335 Danish patients with HS

BACKGROUND

Hidradenitis suppurativa (HS) is a chronic inflammatory and scarring disease with a wide spectrum of disease severity. The amount of scarring is proportional to the preceding tissue damage and poses a challenge to patients. Severe HS is most often treatment recalcitrant, but hypothetically avoidable through early biologic treatment. Early prediction of individual risk of disease progression is therefore essential for patient management.

OBJECTIVES

To investigate risk factors associated with disease progression and to design an algorithm capable of predicting disease -progression.

METHODS

A prospective cohort study of 335 Hurley III-naïve patients with HS, not treated with biologics, was followed for a median of 2 years. Potential risk factors covered basic demographics, HS anamnestic factors and clinical HS factors collected during physical examination. Two separate Cox proportional hazard regression (CPHR) analyses were conducted. A summated 'progression score' was calculated and used in the predictive algorithm of severe disease. Subsequent bootstrap sampling was used to validate the predictability of the predictive algorithm.

RESULTS

The CPHR analysis of Transition to severe disease found that active smoking [hazard ratio (HR) 4.01, 95% confidence interval (CI) 1.71-9.40, P = 0.001]; body mass index (BMI) points > 25 at baseline (each point: HR 1.06, 95% CI 1.02-1.09, P < 0.001); active disease in 2 (HR 4.26, 95% CI 1.23-14.84, P = 0.02) and ≥ 3 areas (HR 6.54, 95% CI 1.89-22.72, P = 0.003) all constituted substantial risk factors. Conversely, the CPHR analysis of Disease progression did not yield results of clinical relevance. A 'progression score' of 3.04 was used as a threshold in the predictive algorithm of Transition to severe disease and achieved the following test specifics: sensitivity = 0.51, specificity = 0.86, positive predictive value = 0.50, negative predictive value = 0.86.

CONCLUSIONS

We found a disparity between factors increasing the risk of simple Disease progression and those increasing the risk of Transition to severe disease. For the latter, active smoking, BMI points > 25, active disease in 2 or ≥ 3 areas were all shown to be the clinically relevant factors that could be used to construct an algorithm that correctly predicted progression to severe HS in more than half of all instances.

Primary skin abscess microbiota a systematic review

An abscess is a collection of pus forming a cavity in the tissue, for example, the skin. They are generally perceived as the result of infection but infection is not mandatory for the diagnosis. Skin abscesses may occur independently (primary) or be part of other diseases such as the recurrent inflammatory skin disease hidradenitis suppurativa (HS). HS is noninfectious but nevertheless abscesses are a common differential diagnosis. The purpose of this study is to review the microbiome of bacteria positive primary skin abscesses in order to explore the reported microbiota. EMBASE, MEDLINER, and COCHRANE LIBRABRY were searched on 9th of October 2021 for microbiome, skin, and abscesses. Studies with more than 10 patients reporting the microbiome in human skin-abscesses were included and studies with abscess microbiota sampled from HS patients, microbiota not sampled from skin-abscesses, missing information on microbiome data, sampling bias, studies in other language than English or Danish, reviews and meta-analyses were excluded. In total 11 studies were included for further analysis. S. aureus is likely to dominate the microbiome of bacteria positive primary skin abscesses in contrast to the polymicrobial microbiome of HS.

Unmet Medical Needs in Chronic, Non-communicable Inflammatory Skin Diseases

An estimated 20-25% of the population is affected by chronic, non-communicable inflammatory skin diseases. Chronic skin inflammation has many causes. Among the most frequent chronic inflammatory skin diseases are atopic dermatitis, psoriasis, urticaria, lichen planus, and hidradenitis suppurativa, driven by a complex interplay of genetics and environmental factors. Autoimmunity is another important cause of chronic skin inflammation. The autoimmune response may be mainly T cell driven, such as in alopecia areata or vitiligo, or B cell driven in chronic spontaneous urticaria, pemphigus and pemphigoid diseases. Rare causes of chronic skin inflammation are autoinflammatory diseases, or rheumatic diseases, such as cutaneous lupus erythematosus or dermatomyositis. Whilst we have seen a significant improvement in diagnosis and treatment, several challenges remain. Especially for rarer causes of chronic skin inflammation, early diagnosis is often missed because of low awareness and lack of diagnostics. Systemic immunosuppression is the treatment of choice for almost all of these diseases. Adverse events due to immunosuppression, insufficient therapeutic responses and relapses remain a challenge. For atopic dermatitis and psoriasis, a broad spectrum of innovative treatments has been developed. However, treatment responses cannot be predicted so far. Hence, development of (bio)markers allowing selection of specific medications for individual patients is needed. Given the encouraging developments during the past years, we envision that many of these challenges in the diagnosis and treatment of chronic inflammatory skin diseases will be thoroughly addressed in the future.

Evidence of gene-gene interaction in Hidradenitis suppurativa - A nationwide register study of Danish twins

BACKGROUND

Hidradenitis suppurativa (HS) is a recurrent inflammatory skin disease that, apart from rare causative loss-of-function mutations, has a widely unknown genetic aetiology. Our objective was to estimate the relative importance of genetic and environmental factors underlying HS susceptibility.

METHODS

Through the Danish Twin Registry and the Danish National Patient Registry we joined information on zygosity with that of HS status. HS cases were identified by International Code of Diseases 8 (705.91) and 10 (L73.2). Heritability was assessed by the classic biometric model and the possibility of gene-gene interaction through the multi-locus modeling approach.

RESULTS

Amongst 100,044 registered twins, we found 170 twins (from 163 pairs) diagnosed with HS. The seven concordant pairs were all monozygotic, and monozygotic twins had a casewise concordance rate of 28% (95% CI: 7%; 49%), corresponding to a familial risk of 73 (95% CI 13; 133) times that of the background population. The biometrical modelling suggested a heritability of 0.80 (95% CI 0.67; 0.93), and the multilocus index estimate was 230 (95% CI: 60; 400). This is highly indicative of gene-gene interactions, with the possibility of up to six interacting loci.

CONCLUSION

This twin study is substantially larger, and employs a more valid phenotype than prior studies. Genetics account for the majority of the HS susceptibility, and HS is most likely caused by gene-gene interactions rather than monogenetic mutations or solely additive genetic factors. New approaches aimed at assessing potential interactions at a SNP-SNP level should be implemented in future HS genome-wide association studies.