Evidence map›Paper›PMID 40749261›Full record

ArticleLung cancer (Amsterdam, Netherlands)2025

Robotic-assisted bronchoscopy for histopathologic subtyping of primary lung adenocarcinoma.

Or Kalchiem-Dekel, Rastko Rakočević, Nicolas Toumbacaris, Kay See Tan, Tejaswi R Nadig, Prasad S Adusumilli, Joseph Dycoco, Robert P Lee, Catherine L Oberg, Katherine D Gray and 9 more

Abstract read
In one paragraph

Article in Lung cancer (Amsterdam, Netherlands), 2025. 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
–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

1 citing paper in PubMed.

  1. 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

19 authors.

Or Kalchiem-DekelSection of Interventional Pulmonology, Pulmonary Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Weill Cornell Medical College, New York, NY, USA. Electronic address: kalchieo@mskcc.org.
Rastko RakočevićSection of Interventional Pulmonology, Pulmonary Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Weill Cornell Medical College, New York, NY, USA.
Nicolas ToumbacarisDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Kay See TanDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Tejaswi R NadigSection of Interventional Pulmonology, Pulmonary Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Prasad S AdusumilliWeill Cornell Medical College, New York, NY, USA; Thoracic Surgery Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Joseph DycocoDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Robert P LeeSection of Interventional Pulmonology, Pulmonary Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Weill Cornell Medical College, New York, NY, USA.
Catherine L ObergSection of Interventional Pulmonology, Pulmonary Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Weill Cornell Medical College, New York, NY, USA.
Katherine D GrayWeill Cornell Medical College, New York, NY, USA; Thoracic Surgery Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Bernard J ParkWeill Cornell Medical College, New York, NY, USA; Thoracic Surgery Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Gaetano RoccoWeill Cornell Medical College, New York, NY, USA; Thoracic Surgery Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Jaime E ChaftWeill Cornell Medical College, New York, NY, USA; Thoracic Oncology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Stephen B SolomonWeill Cornell Medical College, New York, NY, USA; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
David R JonesWeill Cornell Medical College, New York, NY, USA; Thoracic Surgery Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Mohit ChawlaSection of Interventional Pulmonology, Pulmonary Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Weill Cornell Medical College, New York, NY, USA.
Bryan C HustaSection of Interventional Pulmonology, Pulmonary Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Marina K BaineWeill Cornell Medical College, New York, NY, USA; Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Matthew J BottWeill Cornell Medical College, New York, NY, USA; Thoracic Surgery Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SELWYN M VICKERS · 1985 to 2026
$347.4M
Exploring the combinatorial efficacy between chemotherapy and T cell checkpoint inhibition and the role of cellular senescenceK08CA245206 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI BOTT, MATTHEW J · 2020 to 2024
$1.3M
NCI NIH HHS K08 CA245206NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

backgroundThe identification of high-grade patterns and mucinous features of invasive primary lung adenocarcinoma on biopsy specimens can have implications on therapeutic decisions across all stages of disease. Shape sensing robotic-assisted bronchoscopy (ssRAB) is an emerging modality for the concomitant diagnosis and staging of lung cancer. We evaluated the performance of ssRAB for adenocarcinoma pattern identification, and particularly high-grade patterns, as well as the histopathologic concordance between biopsy and surgical resection specimens.

methodsPatients with lung adenocarcinoma diagnosed via ssRAB forceps or cryobiopsy specimens between October 2019 and December 2023 were included in the analysis. Biopsy specimens were evaluated for the identification of histopathologic patterns and mucinous features. A generalized linear mixed model quantified the association between pre- and intra-operative factors and successful pattern identification on biopsy. The concordance between high-grade patterns and mucinous features on ssRAB-acquired biopsy and poorly differentiated grade and mucinous features on subsequent surgical resection was determined.

resultsA total of 242 ssRAB-acquired specimens were included in the final analysis. The biopsy specimen was sufficient to identify adenocarcinoma histopathologic patterns in 71 %. In a multivariable analysis, sampling by cryobiopsy was positively associated with pattern identification (OR 3.54, CI: 1.02-12.30; P = 0.04), as compared with forceps biopsy. A corresponding surgical resection specimen was available in 66 cases. The sensitivity, specificity, positive, and negative predictive values of biopsy were 63, 72, 61, and 74 %, respectively for the presurgical detection of poorly differentiated adenocarcinoma, and 87, 100, 100, and 96 %, respectively for the presurgical detection of mucinous features.

conclusionThis study is the first to report the performance of ssRAB-acquired biopsy for identification of adenocarcinoma patterns and its concordance with surgical resection. Our findings align with those previously reported for percutaneous lung biopsy. ssRAB emerges as a viable tool for the identification of adenocarcinoma patterns. Future studies are needed to confirm these findings in larger patient cohorts.

Indexed as

Adenocarcinoma of LungBronchoscopyLung NeoplasmsRobotic Surgical ProceduresAgedBiopsyFemaleHumansMaleMiddle AgedRetrospective StudiesAdenocarcinomaHistopathologyLung cancerRobotic assisted bronchoscopy

Identifiers

PMID40749261
PMCPMC12379800

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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.