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Background: Manual systematic literature reviews are becoming increasingly challenging due to the sharp rise in publications. The task is particularly daunting when the study topic is complex. Objectives: The primary objective of this literature review was to compare manual and in-house computer software retrieval of publications on the cutaneous manifestations of primary Sjogren’s Syndrome (pSS). The secondary objective was to evaluate the prevalence of cutaneous manifestations in pSS. Methods: We compared manual searching and searching with the in-house computer software BIBOT (1) designed for article retrieval and analysis. Both methods were used for a systematic literature review on a complex topic i.e., the cutaneous manifestations of pSS. Articles published in French or English between 1 January 1990 and 30 May 2018 were sought. Results: The manual search retrieved 855 articles and BIBOT 1042 articles. In all, 202 articles were then selecting by applying exclusion criteria. Among them, 155 were retrieved by both methods, 33 by manual search only, and 14 by BIBOT only. Further selection was performed by reading the 202 articles, of which 54 were deemed relevant, including 23 providing data on the prevalence of one or more cutaneous signs in a cohort of patients with pSS. Cohort sizes and the nature and prevalence of cutaneous manifestations varied across publications. In all, 52 cutaneous manifestations were reported, of which the most common were cutaneous vasculitis (561 patients), xerosis (651 patients), and annular erythema (215 patients). Conclusion: Agreement was good between the two methods. BIBOT was faster and automatically classified the articles in a chart. Combining the two methods retrieved the largest number of publications. The prevalence of cutaneous manifestations in patients with pSS varied considerably across studies. The advanced machine learning techniques used in artificial intelligence hold promise for literature reviews. References [1] Foulquier N, Redou P, Le Gal C, Rouviere B, Pers J-O, Saraux A. Pathogenesis-based treatments in primary Sjogren’s syndrome using artificial intelligence and advanced machine learning techniques: a systematic literature review. Hum Vaccin Immunother2018;14:2553-2558. Disclosure of Interests: Laure Orgeolet: None declared, Nathan Foulquier: None declared, Laurent Misery: None declared, Pascal Redou: None declared, Jacques-Olivier Pers: None declared, Valerie Devauchelle-Pensec Grant/research support from: Roche-Chugai, Speakers bureau: MSD, BMS, UCB, Roche, Alain Saraux Consultant for: Roche SAS, Speakers bureau: Chugai Pharma France |
