Hierarchical cluster analysis based on disease-associated manifestations of patients with lymphangioleiomyomatosis: An analysis of the national database of designated intractable diseases of Japan.
Cluster analysis
Database
Lymphangioleiomyomatosis
Manifestation
Treatment
Journal
Respiratory investigation
ISSN: 2212-5353
Titre abrégé: Respir Investig
Pays: Netherlands
ID NLM: 101581124
Informations de publication
Date de publication:
Jul 2022
Jul 2022
Historique:
received:
15
01
2022
revised:
09
03
2022
accepted:
10
03
2022
pubmed:
17
4
2022
medline:
14
7
2022
entrez:
16
4
2022
Statut:
ppublish
Résumé
Lymphangioleiomyomatosis (LAM) is a rare multisystem disease with variable manifestations and differing rates of progression among individuals. Classification of its phenotypes is an issue for consideration. We hypothesized that clinical manifestations associated with LAM cluster together and identifying these associations would be useful for identifying phenotypes. Using cross-sectional data from the National Database of Designated Intractable Diseases of Japan, we performed a hierarchical cluster analysis based on disease-associated manifestations. Four clusters were identified from 404 patients (50.4% of 801 LAM patients registered in 2016). Patients in cluster 1 had only dyspnea on exertion, relatively low lung function, the earliest onset age, and the lowest prevalence of tuberous sclerosis complex (TSC). Those in cluster 2 had various manifestations with the highest prevalence of TSC. Patients in cluster 3 had major respiratory symptoms (cough, sputum, or dyspnea on exertion) or fatigue and the lowest lung function. Those in cluster 4 were asymptomatic and had the latest onset age, shortest disease duration, and relatively high prevalence of TSC. Patients in cluster 1 had the highest rate of receiving mechanistic target of rapamycin (mTOR) inhibitor treatment, suggesting that cluster 1 included those with declining lung function for which mTOR inhibitor treatment was required. Hierarchical cluster analysis based on manifestations data identified four clusters. The characteristics of cluster 1 are noteworthy in relation to the indication for mTOR inhibitor treatment. A cluster analysis of accumulated and longitudinal data that allows valid clustering and outcome comparisons is required in the future.
Sections du résumé
BACKGROUND
BACKGROUND
Lymphangioleiomyomatosis (LAM) is a rare multisystem disease with variable manifestations and differing rates of progression among individuals. Classification of its phenotypes is an issue for consideration. We hypothesized that clinical manifestations associated with LAM cluster together and identifying these associations would be useful for identifying phenotypes.
METHODS
METHODS
Using cross-sectional data from the National Database of Designated Intractable Diseases of Japan, we performed a hierarchical cluster analysis based on disease-associated manifestations.
RESULTS
RESULTS
Four clusters were identified from 404 patients (50.4% of 801 LAM patients registered in 2016). Patients in cluster 1 had only dyspnea on exertion, relatively low lung function, the earliest onset age, and the lowest prevalence of tuberous sclerosis complex (TSC). Those in cluster 2 had various manifestations with the highest prevalence of TSC. Patients in cluster 3 had major respiratory symptoms (cough, sputum, or dyspnea on exertion) or fatigue and the lowest lung function. Those in cluster 4 were asymptomatic and had the latest onset age, shortest disease duration, and relatively high prevalence of TSC. Patients in cluster 1 had the highest rate of receiving mechanistic target of rapamycin (mTOR) inhibitor treatment, suggesting that cluster 1 included those with declining lung function for which mTOR inhibitor treatment was required.
CONCLUSIONS
CONCLUSIONS
Hierarchical cluster analysis based on manifestations data identified four clusters. The characteristics of cluster 1 are noteworthy in relation to the indication for mTOR inhibitor treatment. A cluster analysis of accumulated and longitudinal data that allows valid clustering and outcome comparisons is required in the future.
Identifiants
pubmed: 35428607
pii: S2212-5345(22)00028-4
doi: 10.1016/j.resinv.2022.03.003
pii:
doi:
Substances chimiques
TOR Serine-Threonine Kinases
EC 2.7.11.1
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
570-577Informations de copyright
Copyright © 2022 The Japanese Respiratory Society. Published by Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Conflict of Interest None of the authors have any conflicts of interest.