Evidence map›Paper›PMID 42664215›Full record

ArticlePloS one2026

Electronic health record evidence suggests undercoding, underrecognition, and low antifibrotic use in progressive pulmonary fibrosis.

Bradley A Sheffield, Brian J Cassel, Apostolos Perelas, Patricia Sime, Peter Jackson

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Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Bradley A SheffieldVirginia Commonwealth University School of Medicine, Richmond, Virginia, United States of America.ORCID https://orcid.org/0009-0004-7491-9527
Brian J CasselDivision of Hematology, Oncology and Palliative Care, Virginia Commonwealth University, Richmond, Virginia, United States of America.
Apostolos PerelasDivision of Pulmonary and Critical Care Medicine, Virginia Commonwealth University, Richmond, Virginia, United States of America.
Patricia SimeDivision of Pulmonary and Critical Care Medicine, Virginia Commonwealth University, Richmond, Virginia, United States of America.
Peter JacksonDivision of Pulmonary and Critical Care Medicine, Virginia Commonwealth University, Richmond, Virginia, United States of America.

Funding

Wright Regional Center for Clinical and Translational ScienceUM1TR004360 · NCATS · VIRGINIA COMMONWEALTH UNIVERSITY · PI FREDERICK Gerard MOELLER · 2023 to 2026
$16.3M
NCATS NIH HHS UM1 TR004360
6 · The paper itself

Abstract

backgroundProgressive pulmonary fibrosis (PPF) is a heterogeneous group of non-IPF ILDs characterized by fibrotic progression and poor prognosis. Antifibrotic therapies slow disease progression, yet widely variable real-world prevalence estimates suggest that PPF may be undercoded and potentially underdiagnosed. In preliminary TriNetX analyses using ICD-10 code J84.170, PPF prevalence was markedly lower than previous estimates. To explore a potentially undiagnosed and/or uncoded PPF cohort, we adapted a published PPF proxy algorithm and compared demographic, clinical, and treatment differences between formally coded patients and proxy-identified patients.

methodsWe conducted a retrospective cohort study using the TriNetX U.S. Collaborative Network from 2021 to 2024. Coded PPF was defined by J84.170, excluding IPF. Three proxy PPF cohorts-sensitive, specific, and strict-were adapted from Olson et al. using the closest available TriNetX variables, combining non-IPF ILD diagnoses with progression criteria. Prevalence, antifibrotic use, demographics, and ILD subtype distributions were compared. Outcomes included respiratory failure, death, and lung transplant. Odds ratios (ORs) and hazard ratios (HRs) were calculated. Propensity matching included age, sex, race, and BMI; balance was assessed using standardized mean differences (SMD < 0.10).

resultsAmong 57,193,009 adults, coded PPF prevalence was 3.7 per 100,000 versus 250, 124, and 32 per 100,000 in the sensitive, specific, and strict proxy cohorts, respectively. Antifibrotic use was 18.3% in coded PPF, compared with 3.2% in the sensitive cohort (OR 0.15), 5.6% in the specific cohort (OR 0.34), and 8.6% in the strict cohort (OR 0.64). IPF treatment was higher than PPF treatment (28.5%; OR 1.97). Demographics and ILD subtype distributions were broadly similar, and clinical outcomes were comparable between coded and proxy cohorts. Relative to PPF, IPF had lower hazards of respiratory failure (HR 0.56) and death (HR 0.52), but higher transplant rates (HR 1.93).

conclusionsProxy-defined cohorts identified clinically similar but largely untreated populations, supporting the possibility of an uncoded and/or unrecognized PPF cohort. EHR-based proxy algorithms may serve as scalable screening tools to identify high-risk patients for further clinical evaluation. These findings should be interpreted cautiously given the use of EHR-derived proxy markers and evolving awareness and coding practices for PPF over time. Further validation with chart review and integrated clinical data is needed.

Indexed as

Antifibrotic AgentsElectronic Health RecordsPulmonary FibrosisAgedAlgorithmsDisease ProgressionFemaleHumansMaleMiddle AgedPrevalenceRetrospective StudiesAntifibrotic Agents

Identifiers

PMID42664215
PMCPMC13524242

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