Skip to main content

Predicting Individualized Lung Disease Progression in Treatment-Naive Patients With Lymphangioleiomyomatosis.

Publication ,  Journal Article
Palipana, AK; Gecili, E; Song, S; Johnson, SR; Szczesniak, RD; Gupta, N
Published in: Chest
June 2023

Lung function decline varies significantly in patients with lymphangioleiomyomatosis (LAM), impeding individualized clinical decision-making.Can we aid individualized decision-making in LAM by developing a dynamic prediction model that can estimate the probability of clinically relevant FEV1 decline in patients with LAM before treatment initiation?Patients observed in the US National Heart, Lung, and Blood Institute (NHLBI) Lymphangioleiomyomatosis Registry were included. Using routinely available variables such as age at diagnosis, menopausal status, and baseline lung function (FEV1 and diffusing capacity of the lungs for carbon monoxide [Dlco]), we used novel stochastic modeling and evaluated predictive probabilities for clinically relevant drops in FEV1. We formed predictive probabilities of transplant-free survival by jointly modeling longitudinal FEV1 and lung transplantation or death events. External validation used the UK Lymphangioleiomyomatosis Natural History cohort.Analysis of the NHLBI Lymphangioleiomyomatosis Registry and UK Lymphangioleiomyomatosis Natural History cohorts consisted of 216 and 185 individuals, respectively. We derived a joint model that accurately estimated the risk of future lung function decline and 5-year probabilities of transplant-free survival in patients with LAM not taking sirolimus (area under the receiver operating characteristic curve [AUC], approximately 0.80). The prediction model provided estimates of forecasted FEV1, rate of FEV1 decline, and probabilities for risk of prolonged drops in FEV1 for untreated patients with LAM with a high degree of accuracy (AUC > 0.80) for the derivation cohort as well as the validation cohort. Our tool is freely accessible at: https://anushkapalipana.shinyapps.io/testapp_v2/.Longitudinal modeling of routine clinical data can allow individualized LAM prognostication and assist in decision-making regarding the timing of treatment initiation.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

Chest

DOI

EISSN

1931-3543

ISSN

0012-3692

Publication Date

June 2023

Volume

163

Issue

6

Start / End Page

1458 / 1470

Related Subject Headings

  • Respiratory System
  • Lymphangioleiomyomatosis
  • Lung Transplantation
  • Lung Neoplasms
  • Lung
  • Humans
  • Forced Expiratory Volume
  • Disease Progression
  • 3202 Clinical sciences
  • 3201 Cardiovascular medicine and haematology
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Palipana, A. K., Gecili, E., Song, S., Johnson, S. R., Szczesniak, R. D., & Gupta, N. (2023). Predicting Individualized Lung Disease Progression in Treatment-Naive Patients With Lymphangioleiomyomatosis. Chest, 163(6), 1458–1470. https://doi.org/10.1016/j.chest.2022.12.027
Palipana, Anushka K., Emrah Gecili, Seongho Song, Simon R. Johnson, Rhonda D. Szczesniak, and Nishant Gupta. “Predicting Individualized Lung Disease Progression in Treatment-Naive Patients With Lymphangioleiomyomatosis.Chest 163, no. 6 (June 2023): 1458–70. https://doi.org/10.1016/j.chest.2022.12.027.
Palipana AK, Gecili E, Song S, Johnson SR, Szczesniak RD, Gupta N. Predicting Individualized Lung Disease Progression in Treatment-Naive Patients With Lymphangioleiomyomatosis. Chest. 2023 Jun;163(6):1458–70.
Palipana, Anushka K., et al. “Predicting Individualized Lung Disease Progression in Treatment-Naive Patients With Lymphangioleiomyomatosis.Chest, vol. 163, no. 6, June 2023, pp. 1458–70. Epmc, doi:10.1016/j.chest.2022.12.027.
Palipana AK, Gecili E, Song S, Johnson SR, Szczesniak RD, Gupta N. Predicting Individualized Lung Disease Progression in Treatment-Naive Patients With Lymphangioleiomyomatosis. Chest. 2023 Jun;163(6):1458–1470.

Published In

Chest

DOI

EISSN

1931-3543

ISSN

0012-3692

Publication Date

June 2023

Volume

163

Issue

6

Start / End Page

1458 / 1470

Related Subject Headings

  • Respiratory System
  • Lymphangioleiomyomatosis
  • Lung Transplantation
  • Lung Neoplasms
  • Lung
  • Humans
  • Forced Expiratory Volume
  • Disease Progression
  • 3202 Clinical sciences
  • 3201 Cardiovascular medicine and haematology