. Author manuscript; available in PMC: 2021 Mar 1.

Published in final edited form as: J Geriatr Oncol. 2019 Dec 9;11(2):297–303. doi: 10.1016/j.jgo.2019.11.007

Table 3:

Optimal cut-off score prediction of impairment measured by neuropsychological tests

Categories	Property
Criteria 1: ≤ −1.5 SD below normative means in at least one domain	Prevalence %	86%
	Optimal MoCA cut-off score	≤25
	AUC	0.745
	Sensitivity	0.795
	Specificity	0.571
Criteria 2: ≤ −1.5 SD below normative means in two or more domains	Prevalence %	53%
	Optimal MoCA cut-off score	≤20
	AUC	0.672
	Sensitivity	0.40
	Specificity	0.96
Criteria 4: ≤ −1.5 SD in two or more domains or ≤ −2.0 SD below normative means in at least one domain^*	Prevalence %	70.6%
	Optimal MoCA cut-off score	≤22
	AUC	0.691
	Sensitivity	0.5
	Specificity	0.867

Criteria 3: ≤ −2.0 SD below normative means in at least one domain yields the same prevalence and optimal cut-off score as Criteria 4 (data not shown).