Biomarkers in Pulmonary Nodule Diagnosis

FOR RELATED ARTICLE, SEE PAGE 491Lung cancer remains a leading cause of cancer deaths worldwide, with high mortality largely attributed to its diagnosis late in the disease process when cure is not possible.1Siegel R.L. Miller K.D. Jemal A. Cancer statistics, 2017.CA Cancer J Clin. 2017; 67: 7-30Crossref PubMed Scopus (12753) Google Scholar The National Lung Screening Trial (NLST) brought hope that screening high-risk patients with a yearly chest low-dose CT scan could lead to a 20% relative risk reduction in lung cancer deaths.2Aberle D.R. Adams A.M. et al.National Lung Screening Trial Research TeamReduced lung-cancer mortality with low-dose computed tomographic screening.N Engl J Med. 2011; 365: 395-409Crossref PubMed Scopus (6877) Google Scholar This decrease in mortality was paralleled by an increase in the diagnosis of stage I non-small cell lung cancer, implying that this screening paradigm leads to decreased mortality by shifting the stage at diagnosis to an earlier, curative stage. FOR RELATED ARTICLE, SEE PAGE 491 Coupled with the increase in chest CT scans performed for lung cancer screening, CT imaging is increasingly used for the diagnosis and evaluation of thoracic and extrathoracic disease, leading to increased identification of pulmonary nodules.3Gould M.K. Tang T. Liu I.L. et al.Recent trends in the identification of incidental pulmonary nodules.Am J Respir Crit Care Med. 2015; 192: 1208-1214Crossref PubMed Scopus (304) Google Scholar In the National Lung Screening Trial (NLST), 24% of screened patients were found to have a concerning pulmonary nodule with only 4% of those ultimately determined to be malignant, even in this high-risk population.2Aberle D.R. Adams A.M. et al.National Lung Screening Trial Research TeamReduced lung-cancer mortality with low-dose computed tomographic screening.N Engl J Med. 2011; 365: 395-409Crossref PubMed Scopus (6877) Google Scholar The current paradigm for management of pulmonary nodules > 8 mm in size is centered on pretest probability for malignancy. Those nodules with a high pretest probability (> 65%) are aggressively managed (typically surgical resection), whereas those at low risk (0%-5%) are managed conservatively. Intermediate-risk nodules (5%-65%), which constitute almost one-half of the pulmonary nodules identified by chest CT scan, require further diagnostic evaluation, including other imaging, bronchoscopy, percutaneous biopsy, or surgical biopsy.4Gould M.K. Donington J. Lynch W.R. et al.Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines.Chest. 2013; 143: e93S-e120SAbstract Full Text Full Text PDF PubMed Scopus (868) Google Scholar Even minimally invasive procedures carry significant risks and anxiety to patients, and the cost of diagnostic evaluation increases 28-fold when biopsy is performed.5Lokhandwala T. Bittoni M.A. Dann R.A. et al.Costs of diagnostic assessment for lung cancer: A Medicare claims analysis.Clin Lung Cancer. 2017; 18: e27-e34Abstract Full Text Full Text PDF PubMed Scopus (60) Google Scholar, 6Gareen I.F. Duan F. Greco E.M. et al.Impact of lung cancer screening results on participant health-related quality of life and state anxiety in the National Lung Screening Trial.Cancer. 2014; 120: 3401-3409Crossref PubMed Scopus (109) Google Scholar Patients with intermediate-risk nodules would therefore benefit from additional risk stratification tools to determine those in need of more aggressive evaluation, which has led to considerable recent interest in identifying proteomic biomarkers that can differentiate lung cancer from benign nodules or normal lung tissue.7Codreanu S.G. Hoeksema M.D. Slebos R.J. et al.Identification of proteomic features to distinguish benign pulmonary nodules from lung adenocarcinoma.J Proteome Res. 2017; 16: 3266-3276Crossref PubMed Scopus (27) Google Scholar In the Pulmonary Nodule Plasma Proteomic Classifier (PANOPTIC) trial, published in this issue of CHEST,8Silvestri G.A. Tanner N.T. Kearney P. et al.Assessment of plasma proteomics biomarker’s ability to distinguish benign from malignant lung nodules: results of the PANOPTIC (Pulmonary Nodule Plasma Proteomic Classifier) trial.Chest. 2018; 154: 491-500Abstract Full Text Full Text PDF PubMed Scopus (74) Google Scholar the authors investigate the impact of an integrated classifier using expression of two plasma proteins associated with lung cancer and cancer immune response, LG3BP and C163A, in addition to five clinical risk factors (age, smoking status, nodule diameter, shape, and location), to differentiate between benign and malignant pulmonary nodules. Although serum samples were prospectively obtained from all patients enrolled in this multicenter, observational validation study, the authors focus on the 178 patients with nodules classified as low to intermediate risk (0%-50%) of malignancy. The authors show as their primary end point that the integrated classifier is associated with a high sensitivity (97%) and high negative predictive value (98%) for distinguishing between malignant and benign pulmonary nodules.8Silvestri G.A. Tanner N.T. Kearney P. et al.Assessment of plasma proteomics biomarker’s ability to distinguish benign from malignant lung nodules: results of the PANOPTIC (Pulmonary Nodule Plasma Proteomic Classifier) trial.Chest. 2018; 154: 491-500Abstract Full Text Full Text PDF PubMed Scopus (74) Google Scholar This was superior to a PET scan or other pretest prediction models, including the Mayo Clinic and Department of Veterans Affairs estimates. Finally, the authors extrapolate from the number of patients undergoing invasive diagnostic evaluations in this group to estimate the number of procedures decreased by applying this classifier to intermediate nodules. This trial addresses a critical question: Can a biomarker be used to risk stratify intermediate-risk pulmonary nodules? This study represents a well-designed and well-executed clinical validation study of the integrated classifier biomarker, already optimized during the discovery and analytic validation phases and now applied to the intended use population in an independent patient cohort. Physicians were blinded to the biomarker results; therefore, retrospective analysis of the estimated impact of the biomarker on clinical management provides a helpful measure on which to base the value of future clinical utility studies. A few aspects of this study deserve careful consideration. Notably, the patient population targeted to benefit from this biomarker consists of those at low to intermediate risk of cancer, as based on physician (pulmonologist and surgeon) estimates. Estimates of pretest probability may vary based on biases, including physician specialty, experience with management of pulmonary nodules, and region. This classifier was studied in a cohort of mixed lung cancer histologies but was composed predominantly of patients with non-small cell lung cancer, with other histologic types constituting a minority of the intention-to-treat cohort (only 7 of 178 patients). Further, a diagnosis of benign or malignant nodule was made by either histologic characterization (surgical or biopsy) or by lack of change on chest CT scan performed at 1-year follow-up, rather than the typical 2 years, raising the potential of missing slower-growing lung cancers. Although there is debate as to their clinical significance, this study may not represent the performance characteristics of the classifier for more slowly growing lung cancers.9Patz Jr., E.F. Pinsky P. Gatsonis C. et al.Overdiagnosis in low-dose computed tomography screening for lung cancer.JAMA Intern Med. 2014; 174: 269-274Crossref PubMed Scopus (559) Google Scholar Certainly limiting use of the integrated classifier to lower-risk nodules leads to increased sensitivity of the biomarker, and utilization of this biomarker outside of the cohort studied would likely yield different results. Finally, this study further supports the notion that better classifying systems can help avoid more aggressive procedures. They estimate that use of the biomarker in the intended population would lead to 40% fewer procedures on benign nodules while misclassifying 3% of malignant nodules. However, these estimates must be interpreted with some caution because recent studies have raised concerns over significant interfacility and interphysician variations in nodule management.10Tanner N.T. Aggarwal J. Gould M.K. et al.Management of pulmonary nodules by community pulmonologists: a multicenter observational study.Chest. 2015; 148: 1405-1414Abstract Full Text Full Text PDF PubMed Scopus (89) Google Scholar A clinical utility study, either using biomarker-stratified interventions or based on well-designed enrichment or strategy-based studies, will be needed to further support these estimates.11Mazzone P.J. Sears C.R. Arenberg D.A. et al.Evaluating molecular biomarkers for the early detection of lung cancer: When is a biomarker ready for clinical use? An Official American Thoracic Society Policy Statement.Am J Respir Crit Care Med. 2017; 196: e15-e29Crossref PubMed Scopus (62) Google Scholar So, is it time to put away the biopsy needle? Not quite yet. However, this well-conducted clinical validation study of two plasma biomarkers used in conjunction with well-defined clinical risk factors is a necessary step before determination of clinical utility. There are many lung cancer biomarkers at various stages of development, few of which have progressed to the point of clinical validation. Advantages of this integrated classifier are that the serum biomarkers are easily obtained, the clinical characteristics are readily available, and it could be combined with other risk stratification characteristics available now and in the future. This trial represents an important step in development of a molecular profile that will aid in classification of intermediate-risk nodules and hopefully avoid unnecessary procedures, anxiety, and costs. Assessment of Plasma Proteomics Biomarker’s Ability to Distinguish Benign From Malignant Lung Nodules: Results of the PANOPTIC (Pulmonary Nodule Plasma Proteomic Classifier) TrialCHESTVol. 154Issue 3PreviewLung nodules are a diagnostic challenge, with an estimated yearly incidence of 1.6 million in the United States. This study evaluated the accuracy of an integrated proteomic classifier in identifying benign nodules in patients with a pretest probability of cancer (pCA) ≤ 50%. Full-Text PDF Open Access