alexa Abstract | The Niemann-Pick Disease Type C Suspicion Index: Development of a New Tool to Aid Diagnosis

Journal of Rare Disorders: Diagnosis & Therapy
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Abstract Background: The Niemann-Pick disease Type C (NP-C) Suspicion Index (SI) identifies patients warranting testing for NP-C. Risk prediction scores (RPS) are based on individual signs and symptoms; however, it was hypothesised that symptom combinations would support more accurate prediction. We aimed to refine the NP-C SI tool to aid rapid, reliable screening. Methods and Findings: Retrospective analyses of the NP-C SI dataset (n=71 NP-C cases; n=64 non-cases; n=81 controls) were conducted, assessing individual patient symptom presentation and strength of relationships between symptoms. Statistical modelling determined RPS for individual symptoms and combinations, based on frequency. The five highest values were weighted for calculation of total RPS and development of a new model. Further analysis of combinations identified seven key discriminatory signs and symptoms, which allowed development of a simplified model. The new NP-C SI model provides a probability analysis for NP-C and quantitative assessment of suspicion. The simplified 2/7 Score assigns high suspicion when two of seven key signs are present, or when a patient has vertical supranuclear gaze palsy, an important indicator of NP-C. Both models discriminated well between NP -C cases, non-cases and controls. For the new NP-C SI model, receiver operating characteristic curve analysis confirmed excellent performance versus the original NP-C SI (NP-C cases versus controls, AUC 0.923 [95% CI 0.877, 0.960] versus 0.941 [95% CI 0.906, 0.976] for the original tool and new model, respectively). Results were validated in an additional patient cohort. Conclusions: Based on these models, a new online NP-C SI tool will be developed. The new online NP-C SI tool is anticipated to improve screening and increase detection rates, identifying individuals who should undergo NP-C diagnostic testing. Abbreviations: AUC: Area under the curve; CI: Confidence interval; FAS: Full analysis set; NP-C Niemann-Pick disease Type C; ROC: Receiver operating characteristic; RPS: Risk prediction score; SI: Suspicion Index; ULR: Univariable logistic regression; VSGP: Vertical supranuclear gaze palsy

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Author(s): Christian J Hendriksz Mercedes Pineda Michael FaheyMark Walterfang Miriam Stampfer Heiko Runz Marc C Patterson Juan V Torres and Stefan A Kolb


Orphan Diseases, Orphan Drugs, Rare metabolic disorders

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