Evidence map›Paper›PMID 36610667›Full record

ArticleChest2023

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

Anushka K Palipana, Emrah Gecili, Seongho Song, Simon R Johnson, Rhonda D Szczesniak, Nishant Gupta

Open access · greenAbstract read
In one paragraph

Article in Chest, 2023. 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
1.6field-weighted citation impact, top 18% of its field
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, 9 citations in OpenAlex.

  1. Review
  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

6 authors at 4 institutions in 2 countries.

Anushka K PalipanaDivision of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH; Division of Statistics and Data Science, University of Cincinnati, Cincinnati, OH.
Emrah GeciliDivision of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH.
Seongho SongDivision of Statistics and Data Science, University of Cincinnati, Cincinnati, OH.
Simon R JohnsonTranslational Medical Sciences, NIHR Biomedical Research Centre and Biodiscovery Institute, University of Nottingham, Nottingham University Hospitals NHS Trust, Nottingham, England; National Centre for Lymphangioleiomyomatosis, Nottingham University Hospitals NHS Trust, Nottingham, England.
Rhonda D SzczesniakDivision of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH; Department of Pediatrics, University of Cincinnati, Cincinnati, OH.
Nishant GuptaDivision of Pulmonary Critical Care and Sleep Medicine, University of Cincinnati, Cincinnati, OH; Medical Service, Veterans Affairs Medical Center, Cincinnati, OH. Electronic address: guptans@ucmail.uc.edu.
Cincinnati Children's Hospital Medical Center · USNottingham University Hospitals NHS Trust · GBUniversity of Cincinnati · USVeterans Health Administration · US

Funding

R01- Mapping environmental contributions to rapid lung disease progression in cystic fibrosisR01HL141286 · NHLBI · CINCINNATI CHILDRENS HOSP MED CTR · PI SZCZESNIAK, RHONDA · 2019 to 2023
$2.3M
Retinoic acid-dependent epigenetic and transcriptional mechanisms controlling heart developmentR01HL141186 · NHLBI · CINCINNATI CHILDRENS HOSP MED CTR · PI WAXMAN, JOSHUA · 2018 to 2021
$1.6M
NHLBI NIH HHS R01 HL141186NHLBI NIH HHS R01 HL141286
6 · The paper itself

Abstract

backgroundLung function decline varies significantly in patients with lymphangioleiomyomatosis (LAM), impeding individualized clinical decision-making. RESEARCH QUESTION: Can we aid individualized decision-making in LAM by developing a dynamic prediction model that can estimate the probability of clinically relevant FEV STUDY DESIGN AND

methodsPatients 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 (FEV

resultsAnalysis 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 FEV

interpretationLongitudinal modeling of routine clinical data can allow individualized LAM prognostication and assist in decision-making regarding the timing of treatment initiation.

Indexed as

Lung NeoplasmsLung TransplantationLymphangioleiomyomatosisDisease ProgressionForced Expiratory VolumeHumansLungmedical monitoringonline calculatorprognostic studypulmonary functionregistry data

Identifiers

PMID36610667
PMCPMC10258438
OpenAlexW4313493324

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.