. Author manuscript; available in PMC: 2017 Dec 27.

Published in final edited form as: Lupus. 2016 Jul 11;26(2):150–162. doi: 10.1177/0961203316655212

Table 3.

Description of reduced models to differentiate between unclear SLE and MCTD cases.

Reduced models for each classification criteria		Accuracy	Sensitivity	Specificity	p-value	Features included in the reduced models
SLE	*rSLICC*	81.1%	90.2%	69.2%	< 0.04	Malar rash^S, discoid rash^S, buccal ulcers^M, lymphopenia^M, ANA^S, anti-Sm^S
SLE	*rACR*	66.7%	76.9%	51.9%	< 0.007	Anti-Sm^S and Malar rash^S
*MCTD*	*rAlarcón-Segovia*	70.3%	95.7%	34.7%	< 0.04	Synovitis, Raynauds^M and acrosclerosis^M
	*rSharp*	77.6%	77.3%	78.3%	< 0.019	Severe myositis^M, Raynauds^M or esophageal^M hypomotylity^M, swollen hands^M or sclerodactyly^M and anti-Sm^S
	*rKasukawa*	87.9%	88.1%	87.5%	< 0.05	Raynauds^M, adenopaties^M, Malar rash^S, sclerodactylity^M, muscle weakness^M
	*rKahn*	64.9%	100%	0%	< 0.013	Raynauds^M and synovitis

SLICC and ACR stands for Systemic Lupus International Collaborating Clinics and American College of Rheumatology, respectively. Anti Nuclear Antibody positive (ANA) as well as positive antibody detection Smith protein (Sm) are indicated. Positive features associated with SLE or MCTD were superscripted with “S” or “M”, respectively, right next to the symptom. The analyses were performed using the binomial logistic regression (BLR) function in SPSS (version 18) and included 78 unclear SLE and 45 MCTD cases.