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. 2019 Jun;107(6):1600-1606.
doi: 10.1016/j.athoracsur.2018.12.041. Epub 2019 Jan 30.

Prediction Model for Nodal Disease Among Patients With Non-Small Cell Lung Cancer

Francys C Verdial  1 , David K Madtes  2 , Billanna Hwang  3 , Michael S Mulligan  3 , Katherine Odem-Davis  4 , Rachel Waworuntu  3 , Douglas E Wood  1 , Farhood Farjah  5
Affiliations

Prediction Model for Nodal Disease Among Patients With Non-Small Cell Lung Cancer

Francys C Verdial et al. Ann Thorac Surg. 2019 Jun.

Abstract

Background: We characterized the performance characteristics of guideline-recommended invasive mediastinal staging (IMS) for lung cancer and developed a prediction model for nodal disease as a potential alternative approach to staging.

Methods: We conducted a prospective cohort study of adults with suspected/confirmed non-small cell lung cancer without evidence of distant metastatic disease (by computed tomography/positron emission tomography) who underwent nodal evaluation by IMS and/or at the time of resection. The true-positive rate was the proportion of patients with true nodal disease selected to undergo IMS based on guideline recommendations, and the false-positive rate was the proportion of patients without true nodal disease selected to undergo IMS. Logistic regression was used to predict nodal disease using radiographic predictors.

Results: Among 123 eligible subjects, 31 (25%) had pathologically confirmed nodal disease. A guideline-recommended invasive staging strategy had a true-positive rate and false-positive rate of 100% and 65%, respectively. The prediction model fit the data well (goodness-of-fit test, p = 0.55) and had excellent discrimination (optimism corrected c-statistic, 0.78; 95% confidence interval, 0.72 to 0.89). Exploratory analysis revealed that use of the prediction model could achieve a false-positive rate of 44% and a true-positive rate of 97%.

Conclusions: A guideline-recommended strategy for IMS selects all patients with true nodal disease and most patients without nodal disease for IMS. Our prediction model appears to maintain (within a margin of error) the sensitivity of a guideline-recommended invasive staging strategy and has the potential to reduce the use of invasive procedures.

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Conflict of interest statement

Presented at the CHEST® annual meeting in Toronto, Canada November 1, 2017.

CONFLICT-OF-INTEREST STATEMENT: Dr. Mulligan reports consultant fees from Covidien. Dr. Wood reports consultant fees from Olympus Respiratory America and GRAIL.

Figures

Figure 1.
Figure 1.
Patient accrual and cohort selection. Vascular endothelial growth factor C (VEGFC), Positron emission tomography (PET), Computed tomography (CT), Non-small Cell Lung Cancer (NSCLC)
Figure 2.
Figure 2.
Receiver Operating Characteristics, Optimism-correction is a statistical method used to mitigate bias arising from validation of a prediction model in the cohort in which it was derived[25], [26].
Figure 3.
Figure 3.
Calibration Pot, Optimism-correction is a statistical method used to mitigate bias arising from validation of a prediction model in the cohort in which it was derived[25], [26].
See this image and copyright information in PMC

Comment in

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