Chest
Volume 145, Issue 3, March 2014, Pages 464-472
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Original Research: Lung Cancer
The Utility of Nodule Volume in the Context of Malignancy Prediction for Small Pulmonary Nodules

https://doi.org/10.1378/chest.13-0708Get rights and content

Background

An estimated 150,000 pulmonary nodules are identified each year, and the number is likely to increase given the results of the National Lung Screening Trial. Decision tools are needed to help with the management of such pulmonary nodules. We examined whether adding any of three novel functions of nodule volume improves the accuracy of an existing malignancy prediction model of CT scan-detected nodules.

Methods

Swensen's 1997 prediction model was used to estimate the probability of malignancy in CT scan-detected nodules identified from a sample of 221 patients at the Medical University of South Carolina between 2006 and 2010. Three multivariate logistic models that included a novel function of nodule volume were used to investigate the added predictive value. Several measures were used to evaluate model classification performance.

Results

With use of a 0.5 cutoff associated with predicted probability, the Swensen model correctly classified 67% of nodules. The three novel models suggested that the addition of nodule volume enhances the ability to correctly predict malignancy; 83%, 88%, and 88% of subjects were correctly classified as having malignant or benign nodules, with significant net improved reclassification for each (P < .0001). All three models also performed well based on Nagelkerke R2, discrimination slope, area under the receiver operating characteristic curve, and Hosmer-Lemeshow calibration test.

Conclusions

The findings demonstrate that the addition of nodule volume to existing malignancy prediction models increases the proportion of nodules correctly classified. This enhanced tool will help clinicians to risk stratify pulmonary nodules more effectively.

Section snippets

Subjects

Consecutive subjects with at least one newly diagnosed pulmonary nodule were recruited between February 1, 2006, and May 1, 2010, from our institution's pulmonary clinic and were included if they had a thoracic CT scan, at least one nodule < 15 mm in diameter detected on the scan, and images satisfactory for volume assessment (slice thickness ≤ 2.5 mm). Although we had no lower limit cutoff per se, on the basis of detectability, no nodules were < 3 mm in size. The Institutional Review Board at

Results

Two hundred thirty-three nodules were observed among 221 subjects, with 37% being malignant. The average ± SD age was 62.4 ± 10.2 years, and 79% were classified as ever smokers. Prior extrathoracic cancers were noted in 34% of subjects. The average nodule diameter and volume were 9.2 ± 3.2 mm (range, 3.0-14.9 mm) and 723 mm3, respectively. Table 1 shows a comparison between study subjects with benign nodules and those with malignant nodules; no significant differences between groups were noted

Discussion

This study is one of the first, to our knowledge, to focus on malignancy prediction in nodules measuring < 15 mm in diameter and has several important findings. First, the addition of nodule volume to the Swensen model significantly enhances its predictive ability. The novel models incorporating nodule volume, volume to diameter ratio, and sphericity index performed relatively similar to one another. All three outperformed the original Swensen model and correctly classified more subjects as

Acknowledgments

Author contributions: Dr Silvestri had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Dr Mehta: contributed to the study design, data collection, and manuscript writing.

Dr Ravenel: contributed to the study design, data collection, and manuscript writing.

Ms Shaftman: contributed to the study design, statistical analysis, and manuscript writing.

Dr Tanner: contributed to the study design, data collection, and

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For editorial comment 440

Funding/Support: This study was supported by the Department of Defense [award W81XWH-05-1-0378], the National Cancer Institute [award 5K24CA120494], and the National Center for Research Resources [award 5UL1RR029882].

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians. See online for more details.

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