Evidence map›Paper›PMID 34689816›Full record

ArticleOrphanet journal of rare diseases2021

Multivariate data analysis identifies natural clusters of Tuberous Sclerosis Complex Associated Neuropsychiatric Disorders (TAND).

Petrus J de Vries, Loren Leclezio, Sugnet Gardner-Lubbe, Darcy Krueger, Mustafa Sahin, Steven Sparagana, Liesbeth De Waele, Anna Jansen

Abstract read
In one paragraph

Article in Orphanet journal of rare diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Petrus J de VriesDivision of Child and Adolescent Psychiatry, University of Cape Town, 46 Sawkins Road, Rondebosch, Cape Town, 7700, South Africa. petrus.devries@uct.ac.za.ORCID 0000-0002-8915-1571
Loren LeclezioDivision of Child and Adolescent Psychiatry, University of Cape Town, 46 Sawkins Road, Rondebosch, Cape Town, 7700, South Africa.
Sugnet Gardner-LubbeDepartment of Statistics and Actuarial Science, Stellenbosch University, Stellenbosch, South Africa.
Darcy KruegerCincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, USA.
Mustafa SahinDepartment of Neurology, Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Boston, USA.
Steven SparaganaDepartment of Neurology, Scottish Rite for Children, The University of Texas Southwestern Medical Center, Dallas, USA.
Liesbeth De WaeleDepartment of Pediatric Neurology, University Hospitals Leuven, Leuven, Belgium.
Anna JansenPediatric Neurology Unit, Department of Pediatrics, UZ Brussel, Vrije Universiteit Brussel, Brussels, Belgium.

Funding

Toward better characterization and clinical trial readiness for targeting neuropsychiatric manifestations in PTEN pathogenic variantsU54NS092090 · NINDS · BOSTON CHILDREN'S HOSPITAL · PI MUSTAFA SAHIN · 2014 to 2026
$20.1M
Genetic Analysis and Manipulation Core (GAEC)P50HD105351 · NICHD · BOSTON CHILDREN'S HOSPITAL · PI SCOTT Loren POMEROY, MUSTAFA SAHIN · 2021 to 2026
$9.4M
NICHD NIH HHS P50 HD105351NINDS NIH HHS U54 NS092090
6 · The paper itself

Abstract

backgroundTuberous Sclerosis Complex (TSC), a multi-system genetic disorder, is associated with a wide range of TSC-Associated Neuropsychiatric Disorders (TAND). Individuals have apparently unique TAND profiles, challenging diagnosis, psycho-education, and intervention planning. We proposed that identification of natural TAND clusters could lead to personalized identification and treatment of TAND. Two small-scale studies showed cluster and factor analysis could identify clinically meaningful natural TAND clusters. Here we set out to identify definitive natural TAND clusters in a large, international dataset.

methodCross-sectional, anonymized TAND Checklist data of 453 individuals with TSC were collected from six international sites. Data-driven methods were used to identify natural TAND clusters. Mean squared contingency coefficients were calculated to produce a correlation matrix, and various cluster analyses and exploratory factor analysis were examined. Statistical robustness of clusters was evaluated with 1000-fold bootstrapping, and internal consistency calculated with Cronbach's alpha.

resultsWard's method rendered seven natural TAND clusters with good robustness on bootstrapping. Cluster analysis showed significant convergence with an exploratory factor analysis solution, and, with the exception of one cluster, internal consistency of the emerging clusters was good to excellent. Clusters showed good clinical face validity.

conclusionsOur findings identified a data-driven set of natural TAND clusters from within highly variable TAND Checklist data. The seven natural TAND clusters could be used to train families and professionals and to develop tailored approaches to identification and treatment of TAND. Natural TAND clusters may also have differential aetiological underpinnings and responses to molecular and other treatments.

Indexed as

Tuberous SclerosisChecklistCross-Sectional StudiesData AnalysisHumansMultivariate AnalysisAutism spectrum disorderCluster analysisFactor analysisNatural TAND clustersNeuropsychiatricPrecision medicineTANDTuberous Sclerosis Complex

Identifiers

PMID34689816
PMCPMC8543869

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.