Evidence map›Paper›PMID 40144724›Full record

ArticleJHLT open2025

Radiological distribution patterns in restrictive chronic lung allograft dysfunction: Impact on survival across all phenotypes.

Taiki Fukuda, Yusei Nakamura, Shu-Chi Tseng, Yuki Ko, Staci M Gagne, Takeshi Johkoh, Yi Li, David C Christiani, Hiroya Ojiri, Lynette Sholl and 2 more

Abstract read
In one paragraph

Article in JHLT open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Taiki FukudaCenter for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.
Yusei NakamuraCenter for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.
Shu-Chi TsengDepartment of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou and Chang Gung University, Taoyuan City, Taiwan.
Yuki KoCenter for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.
Staci M GagneCenter for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.
Takeshi JohkohDepartment of Radiology, Kansai Rosai Hospital, Hyogo, Japan.
Yi LiDepartment of Biostatistics, University of Michigan, Ann Arbor, Michigan.
David C ChristianiDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts.
Hiroya OjiriDepartment of Radiology, The Jikei University School of Medicine, Tokyo, Japan.
Lynette ShollDepartment of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.
Mizuki NishinoCenter for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.
Hiroto HatabuCenter for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.

Funding

The Boston Lung Cancer Survival CohortU01CA209414 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI David C Christiani · 2017 to 2026
$12.2M
Statistical Methods for Analysis of Massive Genetic and Genomic Data in Cancer ResearchR35CA197449 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI XIHONG LIN · 2015 to 2026
$10.9M
New Statistical Methods for Modelling Cancer OutcomesR01CA249096 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Yi Li · 2021 to 2026
$2.5M
Detecting racial disparities in cancer survival by integrating multiple high-dimensional observational studiesR01CA269398 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GUHA, SUBHARUP, LI, YI · 2022 to 2025
$1.3M
NCI NIH HHS R01 CA249096NCI NIH HHS R01 CA269398NCI NIH HHS R35 CA197449NCI NIH HHS U01 CA209414
6 · The paper itself

Abstract

Background: Restrictive chronic lung allograft dysfunction (CLAD) demonstrates poor outcomes after lung transplantation. However, the impact of radiological patterns on survival within a restrictive CLAD under the new International Society for Heart and Lung Transplantation (ISHLT) criteria remains unclear. Methods: We analyzed retrospectively 241 bilateral lung transplant recipients between 2005 and 2021. CLAD was diagnosed and classified per the 2019 ISHLT criteria. Restrictive phenotype included restrictive allograft syndrome (RAS) and mixed phenotype. In these cases, RAS-like opacities (RLOs) were evaluated both qualitatively and semiquantitatively on computed tomography at CLAD diagnosis. RLOs were classified into upper-predominant and diffuse/lower-predominant distribution groups. Overall survival after CLAD diagnosis was assessed using Kaplan-Meier method with log-rank test and Cox proportional hazards models. Results: Eighty-three patients were diagnosed with CLAD after transplantation. Twenty-one (25.3%) had restrictive phenotype, which showed shorter survival compared to bronchiolitis obliterans syndrome (median survival: 19.8 vs 68.1 months; hazard ratio [HR], 4.53; 95% confidence interval [CI], 1.96-10.49; Conclusions: In restrictive phenotype CLAD, RLO distribution patterns determined survival outcomes, with diffuse/lower-predominant showing the poorest prognosis, while the extent of RLOs within each pattern did not correlate with prognosis.

Indexed as

chronic lung allograft dysfunctioncomputed tomographylung transplantprognosisrestrictive allograft syndrome

Identifiers

PMID40144724
PMCPMC11935435

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.