Evidence map›Paper›PMID 36434574›Full record

ArticleBMC pulmonary medicine2022

Comparing modalities for risk assessment in patients with pulmonary lesions and nondiagnostic bronchoscopy for suspected lung cancer.

Diana H Yu, Majid Shafiq, Hitesh Batra, Marla Johnson, Bailey Griscom, Janna Chamberlin, Lori R Lofaro, Jing Huang, William A Bulman, Giulia C Kennedy and 3 more

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in BMC pulmonary medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 34% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Review
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

13 authors at 7 institutions in 1 country.

Diana H YuDepartment of Medicine, Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, University of California, San Francisco, San Francisco, USA, CA. diana.yu@ucsf.edu.
Majid ShafiqBrigham and Women's Hospital, Department of Medicine, Division of Pulmonary and Critical Care Medicine, Boston, MA, USA.
Hitesh BatraDepartment of Medicine, Division of Pulmonary and Critical Care Medicine Birmingham, University of Alabama at Birmingham, Birmingham, AL, USA.
Marla JohnsonVeracyte, Inc., South San Francisco, CA, USA.
Bailey GriscomVeracyte, Inc., South San Francisco, CA, USA.
Janna ChamberlinVeracyte, Inc., South San Francisco, CA, USA.
Lori R LofaroVeracyte, Inc., South San Francisco, CA, USA.
Jing HuangVeracyte, Inc., South San Francisco, CA, USA.
William A BulmanVeracyte, Inc., South San Francisco, CA, USA.
Giulia C KennedyVeracyte, Inc., South San Francisco, CA, USA.
Lonny B YarmusDivision of Pulmonary and Critical Care Medicine, Section of Interventional Pulmonology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Hans J LeeDivision of Pulmonary and Critical Care Medicine, Section of Interventional Pulmonology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
David Feller-KopmanDepartment of Medicine, Division of Pulmonary and Critical Care Medicine, Dartmouth College, Hanover, NH, USA.
Veracyte (United States) · USBrigham and Women's Hospital · USDartmouth College · USJohns Hopkins Medicine · USJohns Hopkins University · USUniversity of Alabama at Birmingham · USUniversity of California, San Francisco · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBronchoscopy is commonly utilized for non-surgical sampling of indeterminant pulmonary lesions, but nondiagnostic procedures are common. Accurate assessment of the risk of malignancy is essential for decision making in these patients, yet we lack tools that perform well across this heterogeneous group of patients. We sought to evaluate the accuracy of three previously validated risk models and physician-assessed risk (PAR) in patients with a newly identified lung lesion undergoing bronchoscopy for suspected lung cancer where the result is nondiagnostic.

methodsWe performed an analysis of prospective data collected for the Percepta Bronchial Genomic Classifier Multicenter Registry. PAR and three previously validated risk models (Mayo Clinic, Veteran's Affairs, and Brock) were used to determine the probability of lung cancer (low, intermediate, or high) in 375 patients with pulmonary lesions who underwent bronchoscopy for possible lung cancer with nondiagnostic pathology. Results were compared to the actual adjudicated prevalence of malignancy in each pre-test risk group, determined with a minimum of 12 months follow up after bronchoscopy.

resultsPAR and the risk models performed poorly overall in the assessment of risk in this patient population. PAR most closely matched the observed prevalence of malignancy in patients at 12 months after bronchoscopy, but all modalities had a low area under the curve, and in all clinical models more than half of all the lesions labeled as high risk were truly or likely benign. The studied risk model calculators overestimate the risk of malignancy compared to PAR, particularly in the subset in older patients, irregularly bordered nodules, and masses > 3 cm. Overall, the risk models perform only slightly better when confined to lung nodules < 3 cm in this population.

conclusionThe currently available tools for the assessment of risk of malignancy perform suboptimally in patients with nondiagnostic findings following a bronchoscopic evaluation for lung cancer. More accurate and objective tools for risk assessment are needed.

trial registrationnot applicable.

Indexed as

BronchoscopyLung NeoplasmsAgedHumansLungProspective StudiesRisk AssessmentBronchoscopyLung cancerRisk assessment

Identifiers

PMID36434574
PMCPMC9700899
OpenAlexW4310054404

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.