There is a lack of validated tools to measure fatigue in patients with inflammatory skin, neuropsychiatric, and medical disorders. The use of nonvalidated tools may compromise the quality of data. The purpose of this meta‐review was to evaluate existing fatigue scales commonly used to assess fatigue in other inflammatory conditions and to identify if there are scales that have been validated in dermatologic conditions. The PubMed/MEDLINE and SCOPUS databases were systematically searched from inception through March 10, 2020, in accordance with the PRISMA statement. Validated tools were identified and assessed according to their main measurement properties. The literature search identified 403 references, and eight studies were eligible and assessed in this review. The unidimensional fatigue scales included were the Functional Assessment of Chronic Illness Therapy – Fatigue (FACIT‐F), Brief Fatigue Inventory, Fatigue Severity Scale, Numerical Rating Scale – Fatigue, and Visual Analog Scale – Fatigue. The multidimensional fatigue scales found were the Checklist Individual Strength, Chalder Fatigue Scale, Multidimensional Assessment of Fatigue, Multidimensional Fatigue Inventory Scale, and Piper Fatigue Scale. To measure fatigue, a brief scale with the ability to detect change is needed as there is a growing interest in evaluating this dimension of treatment response. In addition, a good content validity is also needed. From this systematic review, none of the selected scales have had content validation, even though the FACIT was validated in patients with psoriatic arthritis. Validation studies in specific disorders are urgently warranted.
Background Psoriasis and psoriatic arthritis are common immune-mediated inflammatory conditions that primarily affect the skin, joints and entheses and can lead to significant disability and worsening quality of life. Although early recognition and treatment can prevent the development of permanent damage, psoriatic disease remains underdiagnosed and undertreated due in part to the disparity between disease prevalence and relative lack of access to clinical specialists in dermatology and rheumatology. Remote patient self-assessment aided by smartphone sensor technology may be able to address these gaps in care, however, these innovative disease measurements require robust clinical validation. Methods We developed smartphone-based assessments, collectively named the Psorcast suite, that can be self-administered to measure cutaneous and musculoskeletal signs and symptoms of psoriatic disease. The image and motion sensor data collected by these assessments was processed to generate digital biomarkers or machine learning models to detect psoriatic disease phenotypes. To evaluate these digital endpoints, a cross-sectional, in-clinic validation study was performed with 92 participants across two specialized academic sites consisting of healthy controls and participants diagnosed with psoriasis and/or psoriatic arthritis. Findings In the domain of skin disease, digital patient assessment of percent body surface area (BSA) affected with psoriasis demonstrated very strong concordance (CCC = 0.94, [95%CI = 0.91-0.96]) with physician-assessed BSA. Patient-captured psoriatic plaque photos were remotely assessed by physicians and compared to in-clinic Physician Global Assessment parameters for the same plaque with fair to moderate concordance (CCCerythema=0.72 [0.59-0.85]; CCCinduration=0.72 [0.62-0.82]; CCCscaling=0.60 [0.48-0.72]). Arm range of motion was measured by the Digital Jar Open assessment to classify physician-assessed upper extremity involvement with joint tenderness or enthesitis, demonstrating an AUROC = 0.68 (0.47-0.85). Patient-captured hand photos were processed with object detection and deep learning models to classify clinically-diagnosed nail psoriasis with an accuracy of 0.76, which is on par with remote physician rating of nail images (avg. accuracy = 0.63) with model performance maintaining accuracy when raters were too unsure or image quality was too poor for a remote assessment. Interpretation The Psorcast digital assessments, performed by patient self-measurement, achieve significant clinical validity when compared to in-person physical exams. These assessments should be considered appropriately validated for self-monitoring and exploratory research applications, particularly those that require frequent, remote disease measurements. However, further validation in larger cohorts will be necessary to demonstrate robustness and generalizability across populations for use in evidence-based medicine or clinical trial settings. The smartphone software and analysis pipelines from the Psorcast suite are open source and available to the scientific community. Funding This work is funded by the Psorcast Digital Biomarker Consortium consisting of Sage Bionetworks, Psoriasis and Psoriatic Arthritis Centers for Multicenter Advancement Network (PPACMAN), Novartis, UCB, Pfizer, and Janssen Pharmaceuticals. J.U.S work was supported by the Snyder Family Foundation and the Riley Family Foundation.
Background: The prevalence of Familial Hypercholesterolemia (FH) is estimated to be 1 in 250 US adults. The advent of PCSK9 inhibitors has led a to a paradigm shift in the management of these patients. The purpose of this study was to analyze the efficacy of PCSK9 inhibitors in patients with heterozygous or homozygous FH. Methods: Pubmed, EMBASE and clinicaltrials.gov were searched for randomized controlled trials of PCSK9 inhibitors. Trials that exclusively recruited FH patients or those that reported data separately for FH patients were included. The primary outcome of this analysis was mean difference in LDL-C in patients treated with a PCSK9 inhibitor compared with placebo. Secondary endpoints were change in other lipids and incidence of adverse events. A random effects model was used to analyze the pooled estimates. Results: A pooled analysis of 9 trials with a total of 1361 patients was performed. Overall the mean difference in LDL-C reduction with PCSK9 inhibition was -48.6% (95% CI: -51.3 to -45.9; p<0.001), as compared with placebo. There was no significant difference in LDL-C reduction between trials using alirocumab vs. those using evolocumab. There was significant heterogeneity among the included trials I 2 =75.9%. The risk of bias in all included studies was low. Conclusions: Among patients with FH, PCSK9 inhibitors were highly effective and reduced LDL-C levels by nearly 50% compared with placebo. No differences in magnitude of reduction were observed between alirocumab and evolocumab.
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