Risk stratification in the investigation of pulmonary nodules in a high-risk cohort: positron emission tomography/computed tomography outperforms clinical risk prediction algorithms

Glenna Gibson; Aravind Ravi Kumar; Karin Steinke; Farzad Bashirzadeh; Rebecca Roach; Morgan Windsor; Robert Ware; David Fielding

doi:10.1111/imj.13576

Risk stratification in the investigation of pulmonary nodules in a high-risk cohort: positron emission tomography/computed tomography outperforms clinical risk prediction algorithms

Intern Med J. 2017 Dec;47(12):1385-1392. doi: 10.1111/imj.13576.

Authors

Glenna Gibson¹, Aravind Ravi Kumar², Karin Steinke¹, Farzad Bashirzadeh³, Rebecca Roach³, Morgan Windsor³, Robert Ware⁴, David Fielding³

Affiliations

¹ Department of Radiology, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia.
² Department of Nuclear Medicine, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia.
³ Department of Thoracic Medicine, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia.
⁴ School of Population Health, University of Queensland, Brisbane, Queensland, Australia.

PMID: 28782248
DOI: 10.1111/imj.13576

Abstract

Background: Clinical prediction models and 18-fluorine-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT) are used for the assessment of solitary pulmonary nodules (SPN); however, a biopsy is still required before treatment, which carries risk.

Aim: To determine the combined predictive benefit of one such model combined with modern PET/CT data to improve decision-making about biopsy prior to treatment and possibly reduce costs.

Methods: Patients with a SPN undergoing 18F-FDG-PET/CT from January 2011 to December 2012 were retrospectively identified; 143 patients met inclusion criteria. PET/CT studies were rated (5-point visual scale), and CT characteristics were determined. Tissue was obtained by endobronchial ultrasonography with guide sheath (EBUS-GS), CT-guided biopsy and/or surgery. EBUS-transbronchial needle aspiration (TBNA) was used instead of nodule biopsy if there were PET-positive sub-centimetre lymph nodes.

Results: The prediction model yielded an area under the receiver operating characteristic curve (AUC-ROC) of 64% (95% confidence interval (CI) 0.55-0.75). PET/CT increased this to 75% (95% CI 0.65-0.84). The 11% improvement is statistically significant. PET/CT score was the best single predictor for malignancy. A PET score of 1-2 had a specificity of 100% (CI 0.73-1.0), whereas a score of 4-5 had a sensitivity of only 76% (CI 0.68-0.84). No significant difference in clinical prediction scores between groups was noted. PET/CT showed the greatest benefit in true negatives and in detecting small mediastinal lymph nodes to allow EBUS-TBNA with a higher diagnostic rate. Cost analysis did not support a policy of resection-without-tissue diagnosis.

Conclusion: PET/CT improves the clinical prediction of SPN, but its greatest use is in proving benignity. High PET scores had high false positive rates and did not add to clinical prediction. PET should be incorporated early in decision-making to allow for more effective biopsy strategies.

Keywords: FDG-PET/CT; Solitary pulmonary nodule; clinical prediction model.

Publication types

Comparative Study

MeSH terms

Aged
Algorithms*
Cohort Studies
Female
Fluorodeoxyglucose F18*
Humans
Male
Middle Aged
Multiple Pulmonary Nodules / diagnostic imaging*
Multiple Pulmonary Nodules / epidemiology
Positron Emission Tomography Computed Tomography / methods
Positron Emission Tomography Computed Tomography / standards*
Retrospective Studies
Risk Assessment / methods

Substances

Fluorodeoxyglucose F18