# Patient centered outcome measures and prediction tools in lymphangioleiomyomatosis

> **NIH NIH R21** · UNIVERSITY OF CINCINNATI · 2024 · $150,155

## Abstract

ABSTRACT: Lymphangioleiomyomatosis (LAM) is a progressive, female-predominant, cystic lung disease
caused by mutations in the tuberous sclerosis complex genes. In a recent phase 3 trial, treatment with sirolimus
was shown to stabilize lung function (FEV1) decline and improve quality of life in patients with LAM. However,
treatment with sirolimus is suppressive rather than remission inducing and doesn’t work for everyone,
highlighting the need to develop new therapies in LAM. Pivotal trials of such therapies must overcome the ceiling
effect of FEV1, as sirolimus-containing combination regimens are compared with sirolimus alone. For these trials
to be successful, two critical needs must be met: 1) the development of a cohort enrichment strategy to identify
patients at risk for progression and suboptimal treatment response; and 2) the identification of a sensitive clinical
outcome assessment (COA) for use as an endpoint.
 There is wide inter-individual variability in disease progression and response to sirolimus in patients with
LAM. Developing a modeling-based prediction system that make accurate, dynamic predictions of future FEV1
can aid individualized prognostication, foster timely therapeutic decision-making, and identify patients at greatest
risk for progression or suboptimal treatment response to enrich future trial cohorts. Given the relative stability of
lung function on sirolimus, FEV1 decline is unlikely to be a practical primary endpoint in future LAM trials. We
submit that a reliable, valid, responsive, LAM-specific patient-reported outcome measure (PROM) that assesses
symptoms and health-related quality of life (HRQOL) is likely to be the most meaningful COA to meet this need.
 The Multicenter International Durability and Safety of Sirolimus in LAM (MIDAS) Registry contains
longitudinal physiological and patient-reported HRQOL data on ~400 LAM patients with an average length of
follow up of ~4 years. We postulate that: 1) by employing novel stochastic modeling we can accurately identify
impending FEV1 decline in untreated patients with LAM and predict the likelihood of response to treatment in
patients on sirolimus, and 2) successful validation of a LAM-specific PROM that captures clinically meaningful
outcomes will result in the development of a high-tier novel endpoint for future therapeutic trials in LAM.
 To test our hypotheses, we will use the MIDAS data to pursue the following specific aims: 1) Characterize
heterogeneous treatment effects and develop a data-driven approach to optimize treatment initiation in patients
with LAM, and 2) Validate the use of a LAM-specific PROM to identify clinically meaningful outcomes. Successful
completion of Aim 1 will facilitate optimal treatment decisions and provide a mechanism for cohort enrichment in
LAM trials. Successful completion of Aim 2 will yield systematic analysis of a LAM-specific PROM’s measurement
properties and support its reliability, validity, and responsiveness for capturing p...

## Key facts

- **NIH application ID:** 10795201
- **Project number:** 1R21HL172156-01
- **Recipient organization:** UNIVERSITY OF CINCINNATI
- **Principal Investigator:** Nishant Gupta
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $150,155
- **Award type:** 1
- **Project period:** 2024-01-01 → 2025-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10795201

## Citation

> US National Institutes of Health, RePORTER application 10795201, Patient centered outcome measures and prediction tools in lymphangioleiomyomatosis (1R21HL172156-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10795201. Licensed CC0.

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