Table 2.

Stepwise backward regression of baseline characteristics to test for predictors of the presence of MS vs. sON.

	Variables	p	Odds ratio	95% confidence interval
				Lower value	Upper value
Step 1a	Dyschromatopsia	0.071	0.509	0.244	1.059
	Visual impairment	0.859	0.853	0.148	4.928
	Retrobulbar pain	0.092	0.529	0.252	1.108
	Age at presentation	0.343	0.982	0.947	1.019
	Sex	0.472	0.761	0.362	1.601
	Constant	0.485	2.388
Step 2a	Dyschromatopsia	0.066	0.505	0.244	1.046
	Retrobulbar pain	0.093	0.534	0.256	1.110
	Age at presentation	0.343	0.982	0.947	1.019
	Sex	0.467	0.759	0.361	1.595
	Constant	0.436	2.060
Step 3a	Dyschromatopsia	0.071	0.513	0.248	1.059
	Retrobulbar pain	0.092	0.534	0.257	1.109
	Age at presentation	0.317	0.982	0.946	1.018
	Constant	0.687	1.326
Step 4a	Dyschromatopsia	0.068	0.510	0.248	1.052
	Retrobulbar pain	0.115	0.559	0.272	1.152
	Constant	0.237	0.701
Step 5a	Dyschromatopsia	0.021	0.441	0.220	0.885
	Constant	0.020	0.548

Results of a binary logistic model with conditional stepwise backward regression to identify the strongest predictors from the baseline characteristics regarding the presence of MS. Included were age, sex, as well as the symptoms visual impairment, dyschromatopsia and retrobulbar pain. MS, multiple sclerosis; sON, suspected optic neuritis.

^aVariables entered in step 1: dyschromatopsia, visual impairment, retrobulbar pain, age at presentation, sex.