ArticleAnnals of Indian Academy of Neurology2026
The Indian Smell Identification Test for Parkinson's Disease: Limitations of Binary Scoring and Proposal of a Modified Graded Approach.
Article in Annals of Indian Academy of Neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
BACKGROUND AND
objectivesOlfactory dysfunction is a common nonmotor symptom and prodromal marker of Parkinson's disease (PD). Despite its early occurrence, hyposmia is frequently underrecognized, emphasizing the need for objective, culturally appropriate tools. The Indian smell identification test (INSIT) is widely used but relies on binary scoring, which may underestimate residual olfactory function. This study determines the prevalence of olfactory dysfunction in Indian persons with PD (PwPD) using INSIT and evaluates a modified version (mINSIT) with graded scoring as a preliminary proof-of-concept.
methodsTwo independent cohorts were recruited. Phase 1 included 129 PwPD and 129 age- and sex-matched healthy controls (HCs) assessed with INSIT. Phase 2 included 108 PwPD and 50 HCs tested with INSIT and mINSIT. INSIT used standard binary scoring, while mINSIT captured gradations: nonperception, perception without recognition, cued recognition, and spontaneous recognition.
resultsINSIT identified hyposmia in 62% of PwPD versus 32.5% of HCs in phase 1, and 59.3% versus 30% in phase 2 ( P < 0.001). mINSIT revealed that many PwPD who failed odor identification still perceived odors, demonstrating perception-identification dissociation in 19-86% of cases. Graded scoring provided a more nuanced assessment of olfactory function, with a broader distribution of scores compared with binary scoring. The odors most discriminative between groups were mango, cardamom, and lemon.
conclusionsINSIT is limited by its binary outcome design, whereas mINSIT provides a potentially useful, culturally relevant preliminary tool that captures gradations of olfactory function and may improve detection. It addresses limitations of conventional binary scoring; however, formal validation in larger cohorts is required before it can be recommended for clinical use.
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