Predictive factors for malignancy in incidental pulmonary nodules detected in breast cancer patients at baseline CT
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Pulmonary nodules are commonly encountered at staging CTs in patients with extrathoracic malignancies, but their significance on a per-patient basis remains uncertain.
We undertook a retrospective analysis of pulmonary nodules identified in patients with a diagnosis of breast cancer from 2010 – 2015, evaluating nodules present at a baseline CT (i.e. prevalent nodules). We reviewed 211 patients with 248 individual nodules.
The rate of malignancy in prevalent nodules is low, approximately 13 %. Variables associated with metastasis include pleural studding, hilar lymphadenopathy and the presence of extrapulmonary metastasis, as well as number of nodules, nodule size and nodule shape. Using a combination of these factors, we have developed an evidence-based multivariate decision tree to predict which nodules are malignant in these patients, which is 91 % accurate and 100 % sensitive for metastasis.
We propose a simplified clinical prediction algorithm to guide radiologists and oncologists in managing patients with breast cancer and incidental pulmonary nodules.
• Incidental pulmonary nodules are common on computed tomography in breast cancer patients.
• Nodules present at baseline have a lower malignancy risk than incident nodules.
• We present an evidence-based decision algorithm predicting which nodules are likely malignant.
• This algorithm can help direct patient management.
KeywordsBreast cancer Significance of lung nodules Prediction algorithm Incident lung nodule Prevalent lung nodule
The scientific guarantor of this publication is Eduardo Barbosa. The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article. The authors state that this work has not received any funding. The authors have significant statistical expertise. Institutional Review Board approval was obtained. Written informed consent was waived by the Institutional Review Board. Methodology: retrospective, diagnostic study, performed at one institution. Author contributions: MMH collected the data. MMH and EB analysed the data and wrote the manuscript.
- 12.Munden RF, Erasmus JJ, Wahba H, Fineberg NS (2010) Follow-up of small (4 mm or less) incidentally detected nodules by computed tomography in oncology patients: a retrospective review. J Thorac Oncol Off Publ Int Assoc Study Lung Cancer 5:1958–1962Google Scholar
- 16.Quyn AJ, Matthews A, Daniel T et al (2012) The clinical significance of radiologically detected indeterminate pulmonary nodules in colorectal cancer. Colorectal Dis Off J Assoc Coloproctology G B Irel 14:828–831Google Scholar
- 18.Varol Y, Varol U, Karaca B et al (2012) The frequency and significance of radiologically detected indeterminate pulmonary nodules in patients with colorectal cancer. Med Princ Pract Int J Kuwait Univ Health Sci Cent 21:457–461Google Scholar
- 19.Surveillance Research Program, NCI’s Division of Cancer Control and Population Sciences SEER Stat Fact Sheets: Female Breast Cancer. http://seer.cancer.gov/statfacts/html/breast.html. Accessed 6 Feb 2016
- 20.National Comprehensive Cancer Network Breast Cancer Panel (2016) NCCN clinical practice guidelines in oncology. Breast CancerGoogle Scholar
- 22.American Joint Committee on Cancer (2009) Breast cancer stagingGoogle Scholar
- 25.Quinlan JR (1993) C4.5: programs for machine learning. Morgan Kaufmann Publishers Inc, San FranciscoGoogle Scholar