# Development of Clinical Prediction Models for Pulmonary Outcomes in Sarcoidosis > **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2022 · $1,153,760 ## Abstract PROJECT ABSTRACT The purpose of this proposal is to develop clinical prediction tools to risk stratify patients with pulmonary sarcoidosis. Because the course of sarcoidal inflammation lasts for many years even in those with self-limiting sarcoid, the lack of prognostic indicators upon which to develop a management plan is not a trivial issue for both patient and physician. Thus, without prognostication tools, clinicians will not be able to improve the longitudinal care they provide for the types of outcomes that are used in the clinic. The conception of this study was motivated by the preliminary data showing that levels of blood protein and RNA transcripts related to interferon inflammation were predictive of future declines in lung function using Cox proportional hazards modeling. An important feature of the study design is the focus on clinically relevant outcomes and clinical variables so that results can be immediately translated into clinical practice. This goal is realized in Aim 1 in which we will deliver the best performing clinical prediction model that relies only on clinically available data and lab tests to predict a clinical outcome used in pulmonary clinics to define sarcoidosis disease progression. This outcome is a clinically meaningful decline in lung function. In Aim 2, we will measure the added value of incorporating novel blood-based interferon related markers into the clinical prediction models. The goal of this Aim is to identify which novel markers should be developed and moved into the clinical arena for use in sarcoidosis prognostication. Finally, in Aim 3 we will apply these models to an important clinical management problem in sarcoidosis which is identifying the optimal monitoring frequency for a given patient. Addressing this last question is the first step towards being able to better anticipate disease progression before extensive organ damage occurs. The team of sarcoidosis investigators are highly qualified to execute this study because they have a track record of performing sarcoidosis clinical research, have ongoing collaborations and have participated in prior studies that involve biospecimen collection from patients including NIH-sponsored consortium studies. To execute this study, the investigators will contribute longitudinal biospecimens and clinical data from 357 patients with sarcoidosis that have been enrolled in longitudinal cohorts at centers across the US. Two hundred additional patients will be enrolled and followed for up to 39 months leading to a total sample size of 557, of which a majority will be African American. Our team also includes a uniquely qualified biostatistician, Dr. Charles McCulloch, who has pioneered aspects of the longitudinal modeling approach we will be using. Therefore, the proposed Aims have a high likelihood of success for tackling this long-overdue clinical problem. ## Key facts - **NIH application ID:** 10446452 - **Project number:** 1R01HL157533-01A1 - **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO - **Principal Investigator:** LAURA L KOTH - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $1,153,760 - **Award type:** 1 - **Project period:** 2022-04-01 → 2026-03-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10446452 ## Citation > US National Institutes of Health, RePORTER application 10446452, Development of Clinical Prediction Models for Pulmonary Outcomes in Sarcoidosis (1R01HL157533-01A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10446452. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*