A Prediction Model to Optimize Invasive Mediastinal Staging Procedures for Non-small Cell Lung Cancer in Patients With a Radiologically Normal Mediastinum: The Quebec Prediction Model.


Journal

Chest
ISSN: 1931-3543
Titre abrégé: Chest
Pays: United States
ID NLM: 0231335

Informations de publication

Date de publication:
12 2021
Historique:
received: 21 01 2021
revised: 04 05 2021
accepted: 23 05 2021
pubmed: 14 6 2021
medline: 20 1 2022
entrez: 13 6 2021
Statut: ppublish

Résumé

Current guideline-recommended criteria for invasive mediastinal staging in patients with a radiologically normal mediastinum fail to identify a significant proportion of patients with occult mediastinal disease (OMD), despite it leading to a large number of invasive staging procedures. Which variables available before surgery predict the probability of OMD in patients with a radiologically normal mediastinum? We identified all cTxN0/N1M0 non-small cell lung cancer tumors staged by CT imaging and PET with CT imaging in our institution between 2014 and 2018 who underwent gold standard surgical lymph node dissection or were demonstrated to have OMD before surgery by invasive mediastinal staging techniques and divided them into a derivation and an independent validation cohort to create the Quebec Prediction Model (QPM), which allows calculation of the probability of OMD. Eight hundred three patients were identified (development set, n = 502; validation set, n = 301) with a prevalence of OMD of 9.1%. The developed prediction model included largest mediastinal lymph node size (P < .001), tumor centrality (P = .23), presence of cN1 disease (P = .29), and lesion standardized uptake value (P = .09). Using a calculated probability of more than 10% as a threshold to identify OMD, this model had a sensitivity, specificity, positive predictive value, and negative predictive value in the derivation cohort of 73.9% (95% CI, 58.9%-85.7%), 81.1% (95% CI, 77.2%-84.6%), 28.3% (95% CI, 23.4%-33.8%), and 96.8% (95% CI, 95.0%-98.1%), respectively. It performed similarly in the validation cohort (P = .77, Hosmer-Lemeshow test; P = .5163, Pearson χ The QPM allows the clinician to integrate available information from CT and PET imaging to minimize invasive staging procedures that will not modify management, while also minimizing the risk of unforeseen mediastinal disease found at surgery.

Sections du résumé

BACKGROUND
Current guideline-recommended criteria for invasive mediastinal staging in patients with a radiologically normal mediastinum fail to identify a significant proportion of patients with occult mediastinal disease (OMD), despite it leading to a large number of invasive staging procedures.
RESEARCH QUESTION
Which variables available before surgery predict the probability of OMD in patients with a radiologically normal mediastinum?
STUDY DESIGN AND METHODS
We identified all cTxN0/N1M0 non-small cell lung cancer tumors staged by CT imaging and PET with CT imaging in our institution between 2014 and 2018 who underwent gold standard surgical lymph node dissection or were demonstrated to have OMD before surgery by invasive mediastinal staging techniques and divided them into a derivation and an independent validation cohort to create the Quebec Prediction Model (QPM), which allows calculation of the probability of OMD.
RESULTS
Eight hundred three patients were identified (development set, n = 502; validation set, n = 301) with a prevalence of OMD of 9.1%. The developed prediction model included largest mediastinal lymph node size (P < .001), tumor centrality (P = .23), presence of cN1 disease (P = .29), and lesion standardized uptake value (P = .09). Using a calculated probability of more than 10% as a threshold to identify OMD, this model had a sensitivity, specificity, positive predictive value, and negative predictive value in the derivation cohort of 73.9% (95% CI, 58.9%-85.7%), 81.1% (95% CI, 77.2%-84.6%), 28.3% (95% CI, 23.4%-33.8%), and 96.8% (95% CI, 95.0%-98.1%), respectively. It performed similarly in the validation cohort (P = .77, Hosmer-Lemeshow test; P = .5163, Pearson χ
INTERPRETATION
The QPM allows the clinician to integrate available information from CT and PET imaging to minimize invasive staging procedures that will not modify management, while also minimizing the risk of unforeseen mediastinal disease found at surgery.

Identifiants

pubmed: 34119514
pii: S0012-3692(21)01103-X
doi: 10.1016/j.chest.2021.05.062
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2283-2292

Informations de copyright

Copyright © 2021 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Auteurs

Julien Guinde (J)

Department of Pulmonology and Thoracic Surgery, Institut Universitaire de Cardiologie et de Pneumologie de Québec, Laval University, Quebec City, QC, Canada; Department of Thoracic Oncology, Pleural Diseases and Interventional Pulmonology, North University Hospital, Marseille, France.

Etienne Bourdages-Pageau (E)

Department of Pulmonology and Thoracic Surgery, Institut Universitaire de Cardiologie et de Pneumologie de Québec, Laval University, Quebec City, QC, Canada.

Marie-May Collin-Castonguay (MM)

Department of Pulmonology and Thoracic Surgery, Institut Universitaire de Cardiologie et de Pneumologie de Québec, Laval University, Quebec City, QC, Canada.

Laurie Laflamme (L)

Department of Pulmonology and Thoracic Surgery, Institut Universitaire de Cardiologie et de Pneumologie de Québec, Laval University, Quebec City, QC, Canada.

Alexandra Lévesque-Laplante (A)

Department of Pulmonology and Thoracic Surgery, Institut Universitaire de Cardiologie et de Pneumologie de Québec, Laval University, Quebec City, QC, Canada.

Sabrina Marcoux (S)

Department of Pulmonology and Thoracic Surgery, Institut Universitaire de Cardiologie et de Pneumologie de Québec, Laval University, Quebec City, QC, Canada.

Pascalin Roy (P)

Department of Pulmonology and Thoracic Surgery, Institut Universitaire de Cardiologie et de Pneumologie de Québec, Laval University, Quebec City, QC, Canada.

Paula Antonia Ugalde (PA)

Department of Pulmonology and Thoracic Surgery, Institut Universitaire de Cardiologie et de Pneumologie de Québec, Laval University, Quebec City, QC, Canada.

Yves Lacasse (Y)

Department of Pulmonology and Thoracic Surgery, Institut Universitaire de Cardiologie et de Pneumologie de Québec, Laval University, Quebec City, QC, Canada.

Marc Fortin (M)

Department of Pulmonology and Thoracic Surgery, Institut Universitaire de Cardiologie et de Pneumologie de Québec, Laval University, Quebec City, QC, Canada. Electronic address: marc.fortin@criucpq.ulaval.ca.

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