Predicting progression from undifferentiated connective tissue disease to definite connective tissue disease: A systematic review and meta-analysis

Undifferentiated connective tissue disease (UCTD) encapsulates a broad range of conditions including incomplete forms of systemic lupus erythematosus (SLE) and systemic sclerosis (SSc), some of whom progress to a formal clinical diagnosis over time. This systematic review (SR) and meta-analysis aimed to identify clinical and laboratory features and biomarkers that can predict progression of UCTD.A systematic literature search was carried out on MEDLINE, EMBASE and the Cochrane Central Register of Randomized Controlled Trials. Abstracts and full-text manuscripts were screened by two reviewers. Publications were included if they included at least 20 UCTD patients, a minimum of six months of follow up, and provided data on at least one risk factor for developing a defined CTD. The QUIPS tool was used to assess risk of bias (RoB) and GRADE for grading the quality of the evidence. The study is registered with PROSPERO (ID: CRD42021237725).Fifty-nine studies were included in the SR, and forty-one in the meta-analysis. The predictors for progression to SLE with the highest certainty of evidence included those with younger age (MD -5.96 [-11.05-0.87 years]), serositis (RR 2.69 [1.61-4.51]), or the presence of anti-dsDNA antibodies (RR 4.27 [1.92-9.51]). For SSc, the highest certainty of evidence included puffy fingers (RR [3.09 [1.48-6.43]), abnormal nailfold changes (NFC) (avascular areas [RR 5.71 (3.03-10.8)] or active or late SSc pattern [RR 2.24 (1.25-4.01)] and anti-topoisomerase-I (RR 1.83 [1.45-2.30]). No novel biomarkers were included in the meta-analysis; however HLA molecules, regulatory T cell shift, pro-inflammatory cytokines and complement activation products were identified as potential predictors for evolution of disease.Clinical and immunological parameters may predict which patients with UCTD progress to definitive disease; however, the heterogeneous nature and RoB in most studies limits the ability to apply these results in routine clinical practice. Limited data suggest that some novel biomarkers may provide additional predictive value but these will need larger well designed studies to fully delineate their clinical utility.