| Coverage Policy Manual | |
| Policy #: | 2017019 |
| Category: | Medicine |
| Initiated: | June 2017 |
| Last Review: | June 2023 |
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| Molecular Testing in the Management of Pulmonary Conditions | |
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| Description: |
Pulmonary nodules are a common clinical problem that may be found incidentally on a chest x-ray or computed tomography (CT) scan or during lung cancer screening studies of smokers. The primary question after the detection of a pulmonary nodule is the probability of malignancy, with subsequent management of the nodule based on various factors such as the radiographic characteristics of the nodules (e.g., size, shape, density) and patient factors (e.g., age, smoking history, previous cancer history, family history, environmental/occupational exposures). The key challenge in the diagnostic workup for pulmonary nodules is appropriately ruling in patients for invasive diagnostic procedures and ruling out patients who should forgo invasive diagnostic procedures. However, due to the low positive predictive value of pulmonary nodules detected radiographically, many unnecessary invasive diagnostic procedures and/or surgeries are performed to confirm or eliminate the diagnosis of lung cancer.
Proteomics is the study of the structure and function of proteins. The study of the concentration, structure, and other characteristics of proteins in various bodily tissues, fluids, and other materials have been proposed as a method to identify and manage various diseases, including cancer. In proteomics, multiple test methods are used to study proteins. Immunoassays use antibodies to detect the concentration and/or structure of proteins. Mass spectrometry is an analytic technique that ionizes proteins into smaller fragments and determines mass and composition to identify and characterize them.
Plasma-Based Proteomic Screening for Pulmonary Nodules
Plasma-based proteomic screening has been investigated to risk-stratify pulmonary nodules as likely benign to increase the number of patients who undergo serial CT scans of their nodules (active surveillance), instead of invasive procedures such as CT-guided biopsy or surgery. Additionally, proteomic testing may also determine a likely malignancy in clinically low-risk or intermediate-risk pulmonary nodules, thereby permitting earlier detection in a subset of patients.
Nodify XL2 (BDX-XL2) is a plasma-based proteomic screening test that measures the relative abundance of proteins from multiple disease pathways associated with lung cancer using an analytic technique called multiple reaction monitoring mass spectroscopy. The tests helps physicians identify lung nodules that are likely benign or at a lower risk of cancer. If the test yields a “likely benign” or “reduced risk” result, patients may choose active surveillance via serial CT scans to monitor the pulmonary nodule Earlier generations of the Nodify XL2 test include Xpresys Lung® and Xpresys Lung 2®.
Nodify CDT® is a proteomic test that uses multi-analyte immunoassay technology to measure autoantibodies associated with tumor antigens. The test helps physicians identify lung nodules that are likely malignant or at higher risk of cancer. Patients with a "high level" Nodify CDT test result have a higher risk of malignancy than predicted by clinical factors alone; invasive diagnostic procedures would be indicated in these cases.
The Nodify XL2 and Nodify CDT tests are therefore only used in the management of pulmonary nodules to rule out or rule in, invasive diagnostic procedures; they do not diagnose lung cancer. These tests are offered together as Biodesix’s Nodify Lung® testing strategy, but physicians may also choose to order each test independently.
Gene Expression Profiling
Gene expression profiling is the measurement of the activity of genes with cells. Messenger RNA (mRNA) serves at the bridge between DNA and functional proteins. Multiple molecular techniques such as Northern blots, ribonuclease protection assay, in situ hybridization, spotted complementary DNA arrays, oligonucleotide arrays, reverse transcriptase polymerase chain reaction, and transcriptome sequencing are used in gene expression profiling. An important role of gene expression profiling in molecular diagnostics is to detect cancer-associated gene expression of clinical samples to assess for the risk for malignancy.
Gene Expression Profiling for an Indeterminate Bronchoscopy Result
The first generation Percepta® Bronchial Genomic Classifier is a 23-gene gene expression profiling test that analyzed genomic changes in the airways of current or former smokers to assess a patient’s risk of having lung cancer, without the direct testing of a pulmonary nodule. This classifier was designed to be a “rule-out” test for intermediate-risk patients. The second generation Percepta Genomic Sequencing Classifier was developed to serve as both a “rule-in” test and a “rule-out” test, thereby increasing its potential utility in improving risk stratification. The test is indicated for current and former smokers following an indeterminate bronchoscopy result to determine subsequent management of pulmonary nodules (e.g., active surveillance or invasive diagnostic procedures), and does not diagnose lung cancer.
Envisia Genomic Classifier (Veracyte, Inc) is a tissue based multi-analyte assay with algorithm analysis test for interstitial lung disease (ILD) patients who are suspected of idiopathic pulmonary fibrosis (IPF) and who do not have a definitive usual interstitial pneumonia (IUP) pattern by high resolution computed tomography (HRCT) or other known cause of ILD. Envisia testing is performed on less-invasive bronchosopcy transbronchial biopsy samples and is intended to provide a categorical UIP or Non-UIP result that along with clinical and radiographical information may guide treatment.
The EarlyCDT test is a blood test that detects the presence of autoantibodies associated with lung cancer (Oncimmune, 2023). The Early CDT test measures the antibodies of 6 tumor-associated antigens: p53, NY-ESO-1, CAGE, GBU4-5, Annexin1, and SOX2.
Regulatory Status
Clinical laboratories may develop and validate tests in-house and market them as a laboratory service; laboratory-developed tests must meet the general regulatory standards of the Clinical Laboratory Improvement Amendments (CLIA). Xpresys® Lung 2 now Nodify XL2 (BDX-XL2 (Integrated Diagnostics [Indi], purchased by Biodesix); Nodify CDT (Biodesix), and Percepta® Genomic Classifier (Veracyte) are available under the auspices of CLIA. Laboratories that offer laboratory-developed tests must be licensed by CLIA for high-complexity testing. To date, the U.S. Food and Drug Administration has chosen not to require any regulatory review of this test.
Coding
There are no specific CPT codes for these tests. They would likely be reported with nonspecific codes such as:
83520 Immunoassay for analyte other than infectious agent antibody or infectious agent antigen; quantitative, not otherwise specified
84999 Unlisted chemistry procedure
Effective 01/01/2021, there is a specific code for Envisia. It may be billed with the following codes.
81554 Pulmonary disease (idiopathic pulmonary fibrosis [IPF]), mRNA, gene expression analysis of 190 genes, utilizing transbronchial biopsies, diagnostic algorithm reported as categorical result (eg, positive or negative for high probability of usual interstitial pneumonia [UIP])
81479 Unlisted molecular pathology procedure
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Policy/ Coverage: |
Effective March 2021
Does Not Meet Primary Coverage Criteria Or Is Investigational For Contracts Without Primary Coverage Criteria
Plasma-based proteomic screening including but not limited to BDX-XL2 in patients with undiagnosed pulmonary nodules detected by computed tomography does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.
For members with contracts without primary coverage criteria, plasma-based proteomic screening including but not limited to BDX-XL2 in patients with undiagnosed pulmonary nodules detected by computed tomography is considered investigational. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
Gene expression profiling on bronchial brushings, including but not limited to Percepta® Bronchial
Genomic Classifier, in patients with indeterminate bronchoscopy results from undiagnosed pulmonary nodules does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.
For members with contracts without primary coverage criteria, Percepta® Bronchial Genomic Classifier, in patients with indeterminate bronchoscopy results from undiagnosed pulmonary nodules is considered investigational. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
Gene expression analysis, including but not limited to Envisia Genomic Classifier, on transbronchial or transthoracic biopsy specimens to aid in the diagnosis of idiopathic pulmonary fibrosis or any pulmonary disease does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.
For members with contracts without primary coverage criteria, gene expression analysis, including but not limited to Envisia Genomic Classifier on transbronchial or transthoracic biopsy specimens, to aid in the diagnosis of idiopathic pulmonary fibrosis or any pulmonary disease is considered investigational. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
Effective June 2019 to March 2021
Does Not Meet Primary Coverage Criteria Or Is Investigational For Contracts Without Primary Coverage Criteria
Plasma-based proteomic screening including but not limited to BDX-XL2 in patients with undiagnosed pulmonary nodules detected by computed tomography does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.
For members with contracts without primary coverage criteria, plasma-based proteomic screening including but not limited to BDX-XL2 in patients with undiagnosed pulmonary nodules detected by computed tomography would be considered investigational and not covered for contracts without Primary Coverage Criteria. Investigational services are exclusion in the member benefit certificate.
Gene expression profiling on bronchial brushings, including but not limited to Percepta® Bronchial
Genomic Classifier, in patients with indeterminate bronchoscopy results from undiagnosed pulmonary nodules does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.
For members with contracts without primary coverage criteria, Percepta® Bronchial Genomic Classifier, in patients with indeterminate bronchoscopy results from undiagnosed pulmonary nodules would be considered investigational and not covered for contracts without Primary Coverage Critera. Investigational services are exclusion in the member benefit certificate.
Effective Prior to June 2019
Does Not Meet Primary Coverage Criteria Or Is Investigational For Contracts Without Primary Coverage Criteria
Plasma-based proteomic screening including but not limited to Xpresys® Lung in patients with undiagnosed pulmonary nodules detected by computed tomography does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.
For members with contracts without primary coverage criteria, plasma-based proteomic screening including but not limited to Xpresys® Lung in patients with undiagnosed pulmonary nodules detected by computed tomography would be considered investigational and not covered for contracts without Primary Coverage Criteria. Investigational services are exclusion in the member benefit certificate.
Gene expression profiling on bronchial brushings, including but not limited to Percepta® Bronchial
Genomic Classifier, in patients with indeterminate bronchoscopy results from undiagnosed pulmonary nodules does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.
For members with contracts without primary coverage criteria, Percepta® Bronchial Genomic Classifier, in patients with indeterminate bronchoscopy results from undiagnosed pulmonary nodules would be considered investigational and not covered for contracts without Primary Coverage Critera. Investigational services are exclusion in the member benefit certificate.
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| Rationale: |
This evidence review was originally created in May 2017 with a search of the MEDLINE database through March 30, 2017.
Plasma-Based Proteomic Screening of Pulmonary Nodules
Clinical Context and Test Purpose
The purpose of plasma-based proteomic screening in individuals with undiagnosed pulmonary nodule(s) is to stratify clinical risk for malignancy and eliminate or necessitate the need for invasive diagnostic procedures.
The relevant question addressed in this evidence review is: Does plasma-based proteomic screening appropriately eliminate or necessitate the need for invasive diagnostic procedures and lead to improved health outcomes?
The following PICOTS were used to select literature to inform this review.
Patients
The relevant population of interest includes individuals with undiagnosed pulmonary nodules. In particular, as outlined in the evidence-based 2013 American College of Chest Physicians (ACCP) Guidelines on the diagnosis and management of lung cancer, decision-making about a single indeterminate lung nodule 8 to 30 mm on computed tomography (CT) scan is complicated, requiring input about the patient’s pretest probability of lung cancer, the characteristics of the lung nodule on CT, and shared decision-making between the patient and physician about follow up (Gould, 2013). Therefore, additional information in the segment of patients with an indeterminate lung nodule, 8 to 30 mm in diameter would be particularly useful.
Interventions
The relevant intervention of interest is plasma-based proteomic screening. A particular focus was the Xpresys Lung test, which was the only commercially available test identified.
Comparators
The relevant comparator of interest is standard clinical management using clinical and radiographic risk factors.
Outcomes
The potential beneficial outcomes of primary interest are avoiding an unneeded invasive biopsy of a nodule that would be negative for lung cancer, or initiating a biopsy for a nodule that would otherwise have been followed with serial CTs.
Potential harmful outcomes are those resulting from false-positive or false-negative test results. False-positive test results can lead to unnecessary invasive diagnostic procedures and procedure-related complications. False-negative test results can lead to lack of pulmonary nodule surveillance or lack of appropriate invasive diagnostic procedures to diagnose malignancy.
Timing
The time frame for evaluating performance of the test varies the time from the initial CT scan to an invasive diagnostic procedure to up to 2 years, which would be the typical follow-up needed for some lung nodules.
Setting
The primary setting would be in outpatient pulmonology or primary care offices.
Analytic Validity
Analytic validity is the ability of a test to accurately and reliably measure the marker of interest. Measures of analytic validity include sensitivity (detection rate), specificity (false-positive rate), reliability (repeatability of test results), and assay robustness (resistance to small changes in preanalytic or analytic variables).
Li and colleagues described an integrated quantification (InteQuan) method to better control preanalytic and analytic variability compared to a quantification method using stable isotope-labeled standard peptides (SISQuan) (Li, 2015). Sixteen lung cancer biomarker candidates in human plasma samples in 3 assessment studies, using immunoaffinity depletion coupled with multiple reaction monitoring mass spectrometry was used. InteQuan performed better than SISQuan in precision in all 3 studies and tolerated a 2-fold difference in sample loading. The 3 studies lasted over 6 months and encountered major changes in experimental settings. Plasma proteins in low nanogram per milliliter to low microgram per milliliter concentrations were measured with a median technical coefficient of variation of 11.9% using InteQuan. The corresponding median coefficient of variation using SISQuan was 15.3% after linear fitting.
Section Summary: Analytic Validity
The analytic validity of mass spectrometry has been demonstrated in a research setting and is expected to be high. However, direct evidence for the analytic validity of Xpresys Lung or other plasma-based proteomic screening tests used in patients with pulmonary nodules is lacking.
Clinical Validity
Pecot and colleagues validated a 7-peak matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) proteomic signature in 2 prospective cohorts of patients with 1 or more pulmonary nodules on chest CT (total N=379 [cohort A: n=265; mean nodule size, 31.2 mm; cohort B: n=114; mean nodule size, 19.4 mm]) (Pecot, 2012). The area under the curve (AUC) for the MALDI score alone for cohort A was 0.64 (95% confidence interval [CI], 0.58 to 0.71) and for cohort B was 0.64 (95% CI, 0.52 to 0.75). For cohort A, adding the proteomic signature to clinical and chest CT data did not significantly improve prognostic value. For cohort B, however, prognostic ability improved when the proteomic signature was added to clinical and chest CT data, as measured by the integration discrimination improvement (IDI) index (IDI=20%, p<0.001). Similarly, in a subgroup of 100 nodules from 5 to 200 mm in diameter, the proteomic signature added prognostic value (IDI=15%, p<0.001).
Two studies were identified that reported on the development and validation of slightly different versions of a plasma-based classifier test to predict malignancy (Xpresys Lung), one with 13 proteins and one with 11.
Li and colleagues reported on the development and validation of the 13-protein version, proposed to differentiate benign from malignant pulmonary lung nodules (Li, 2013). The test identifies classifier proteins likely modulated by a few transcription regulators (NF2L2, AHR, MYC, and FOS) associated with lung cancer and inflammation. The classifier was developed in a set of 143 serum samples from subjects with either benign or stage IA lung cancer, with a nodule size 4 to 30 mm. The test was locked and validated in a set of 52 benign and 52 tumor samples. Test characteristics are shown in Table 1. These results were independent of age, nodule size, or smoking history.
Vachani and colleagues reported on the validation of an 11-protein plasma classifier designed to identify likely benign lung nodules in a sample of 141 plasma samples associated with indeterminate pulmonary nodules 8 to 30 mm in diameter (Vachani, 2015-04). The analysis was a retrospective, blinded analysis of existing samples. The 11 proteins in this assay were reported to be derived from the 13-protein sample in Li and colleagues (above). The performance of the classifier in identifying benign nodules was tested at predefined reference values. For example, using a population, based non-small-cell lung cancer prevalence estimate of 23% for indeterminate pulmonary nodules 8 to 30 mm in diameter, the classifier identified likely benign lung nodules with a 90% negative predictive value (NPV) and a 26% positive predictive value, at 92% sensitivity and 20% specificity, with the lower bound of the classifier’s performance at 70% sensitivity and at 48% specificity. Additional sample diagnostic characteristics, selected to keep the study’s target NPV of 90%, are shown below. Classifier scores for the overall cohort were statistically independent of patient age, tobacco use, nodule size, and chronic obstructive pulmonary disease diagnosis. The classifier also demonstrated incremental diagnostic performance in combination with a 4-parameter clinical model.
Summary of Diagnostic Performance Studies for Proteomic Tests to Predict Malignancy
Li and colleagues:
Vachani and colleagues:
In 2015 Vachani and colleagues reported on a multicenter prospective-retrospective study of patients with indeterminate pulmonary nodules (IPNs) (Vachani, 2015-12). A plasma protein classifier was used on 475 patients with nodules 8 to 30 mm in diameter who had an invasive procedure to confirm diagnosis. Using the classifier, 32.0% (95% CI, 19.5% to 46.7%) of surgeries and 31.8% (95% CI, 20.9% to 44.4%) of invasive procedures (biopsy and/or surgery) on benign nodules could have been avoided, while 24.0% (95% CI, 19.2% to 29.4%) of patients with malignancy would have been triaged to CT surveillance. In comparison, a rate of 24.5% (95% CI, 16.2% to 34.4%) patients with malignancy routed to CT surveillance by standard clinical practice has been reported.
Section Summary: Clinical Validity
Clinical validation studies were identified for 2 proteomic classifiers, 2 of which appear to be related to the development and validation of closely related versions of the Xpresys test. In general, the classifier has been designed to have a high NPV. However, its clinical validity is uncertain given that studies have reported on slightly different versions of the test. In addition, studies have not reported how it reclassifies patients relative to clinical classifiers in terms of risk. Proteomic classifiers may aid in the clinical assessment of cancer risk for indeterminate pulmonary nodules.
Clinical Utility
No evidence directly demonstrating improved outcomes in patients managed with the Xpresys Lung was identified.
Therefore, a chain of indirect evidence was developed, which addresses 2 key questions: (1) does the use of a proteomic classifier with high NPV in patients with undiagnosed pulmonary nodules detected by CT change clinical management (in this case, reduction of invasive procedures)? (2) Do those management changes improve outcomes relative to a clinical classifier?
Changes in Management
The clinical setting in which a proteomic classifier with high NPV is used is individuals with undiagnosed pulmonary nodules detected by CT.
Indirect evidence suggests that 32.0% of surgeries and 31.8% of invasive procedures (biopsy and/or surgery) on benign nodules could have been avoided, while 24.0% of patients with malignancy would have been triaged to CT surveillance (Vachani, 2015-12).
Improved Outcomes
Indirect evidence suggests that use of a proteomic classifier with high NPV has the potential to reduce the number of unnecessary invasive procedures to definitively diagnose benign disease versus malignancy. Compared to the standard care plan, some patients without cancer will have avoided an unnecessary invasive procedure, which is weighed against the increase in missed cancers in patients who had lung cancer but tested as negative on the a proteomic classifier with high NPV test.
Whether the tradeoff between avoiding unneeded surgeries and the potential for missed cancer is worthwhile depends, in part, on patient and physician preferences. Missed malignancies would likely be continued to be followed by active surveillance by low dose CT imaging. In the context of lung cancers, overall survival is dependent on detection of lung cancer at early, more treatable stages.
Avoiding invasive procedures in situations where patients are at very low likelihood of having lung cancer is likely beneficial, given the known complications of invasive procedures (e.g. pneumothorax). However, reductions in unnecessary invasive procedures must be weighed against outcomes and harms associated with a missed diagnosis of lung cancer at earlier, more treatable stages.
Section Summary: Clinical Utility
Indirect evidence suggests that a proteomic classifier with high NPV has the potential to reduce the number of unnecessary invasive procedures to definitively diagnose benign disease versus malignancy. However, stronger clinical validity data is needed to make a rely on indirect evidence for clinical utility.
Gene Expression Profiling of Indeterminate Bronchoscopy Results
Clinical Context and Test Purpose
The purpose of gene expression profiling on bronchial brushings in individuals who undergo bronchoscopy for the diagnosis of suspected lung cancer but who have an indeterminate cytology result is to stratify the clinical risk for malignancy and eliminate the need for invasive diagnostic procedures.
The relevant question addressed in this evidence review is: Does gene expression profiling on bronchial brushings reduce the need for invasive diagnostic procedures and lead to improved health outcomes?
The following PICOTS were used to select literature to inform this review.
Patients
The relevant population of interest, according to the manufacturer, includes individuals with physician-assessed low or intermediate pre-test risk of malignancy who are current or former smokers with inconclusive bronchoscopy results for suspected lung cancer.
Interventions
The relevant intervention of interest is gene expression profiling of bronchial brushings.
Comparators
The relevant comparator of interest is standard clinical management without gene expression profiling. The management of patients with suspected lung cancer with who have an indeterminate bronchoscopy result is no entirely standardized. However, according it is likely that in standard practice many patients would have a surgical biopsy, transthoracic needle aspiration (TTNA), or other testing, depending on the location of the nodule. According to 2013 guidelines from the American College of Chest Physicians, in patients with suspected lung cancer with a central lesion, bronchoscopy is recommended to confirm the diagnosis. If bronchoscopy results are non-diagnostic and there is still a suspicion of lung cancer remains, additional testing is recommended (Grade 1B recommendation) (Rivera, 2013).
Outcomes
The potential beneficial outcomes of primary interest are avoiding an unneeded invasive biopsy of a nodule hat would be negative for lung cancer.
Potential harmful outcomes are those resulting from false-positive or false-negative test results. False-positive test results can lead to unnecessary invasive diagnostic procedures and procedure-related complications. False-negative test results can lead to lack of pulmonary nodule surveillance or lack of appropriate invasive diagnostic procedures to diagnose malignancy.
Timing
The time frame for outcomes measures varies from short-term development of invasive diagnostic procedure-related complications to long-term procedure-related complications, development of malignancy, or overall survival.
Setting
The primary setting would be in outpatient pulmonology offices.
Analytic Validity
Hu and colleagues reported on the analytic performance of GEP to characterize the stability of RNA in bronchial brushing specimens during collection and shipment, the analytical specificity (i.e., potentially interfering substances) as tested on blood, and genomic DNA and assay performance studies including intrarun, interrun, and interlaboratory reproducibility (Hu, 2016). RNA content within bronchial brushing specimens preserved in RNA protect cell reagent is stable for up to 20 days at 4°C with no changes in RNA yield or integrity. Analytic sensitivity studies have demonstrated tolerance to variation in RNA input (157-243 ng). Analytic specificity studies using cancer-positive and cancer-negative samples mixed with either blood (up to 10% input mass) or genomic DNA (up to 10% input mass) have demonstrated no assay interference. The test is reproducible from RNA extraction through to Percepta test result, including variation across operators, runs, reagent lots, and laboratories (SD=0.26 for scores on >6-unit scale).
Section Summary: Analytic Validity
One published study has reported on the analytic performance on the Percepta Bronchial Genomic Classifier and included sample stability, reproducibility, analytic sensitivity, and analytic specificity. The analytic performance and reproducibility are expected to be high based, and, in the context of testing of clinical samples, is expected to yield accurate and reproducible results.
Clinical Validity
Whitney and colleagues reported on the development and initial validation of an RNA-based gene expression classifier from airway epithelial cells designed to be predictive of cancer in current and former smokers undergoing bronchoscopy for suspected lung cancer (Whitney, 2015). Samples were from patients in the AEGIS trials (Airway Epithelium Gene Expression in the Diagnosis of Lung Cancer), which were 2 prospective, observational, cohort studies (AEGIS-1, AEGIS-2), for current or former smokers undergoing bronchoscopy for suspected lung cancer. The details of the cohorts are described further with Silvestri and colleagues below. A total of 299 samples from AEGIS-1 (223 cancer-positive and 76 cancer-free subjects) were used to derive the classifier. Data from 123 patients in a prior study with a nondiagnostic bronchoscopy were used as an independent test set. In the final model, the classifier included 17 genes, patient age, and gene expression correlates, and was reported out as a dichotomous score (≥0.65 as cancer positive and <0.65 as cancer negative).
Silvestri and colleagues reported on the diagnostic performance of the gene expression classifier developed in Whitney and colleagues in a sample of 639 patients enrolled in 2 multicenter prospective studies (AEGIS-1, n=298; and AEGIS-2, n=341 patients) (Silvestri, 2015). The study enrolled patients who were undergoing clinically indicated bronchoscopy for a diagnosis of possible lung cancer and had a history of smoking. Before the bronchoscopy, the treating physician assessed each patient’s probability of having cancer with a 5-level scale (<10%, 10-39%, 40-60%, 61-85%, and >85%). Patients were followed until a diagnosis was established (either at the time of bronchoscopy or subsequently by another biopsy means) or until 12 months after bronchoscopy.
A total of 855 patients in AEGIS-1 and 502 patients in AEGIS-2 met enrollment criteria. After exclusions due to sample quality issues, loss to follow up, lack of final diagnosis, or non-primary lung cancer, 341 subjects were available in the validation set for AEGIS-2. For AEGIS-1, patients were randomly allocated to the development (described above) or validation (n=298) sets. Of the 639 patients in the validation study who underwent bronchoscopy, 272 (43%, 95% CI 39 to 46%) had a non-diagnostic examination. The prevalence of lung cancer was 74% and 78% in AEGIS-1 and AEGIS-2, respectively. The classifier improved prediction of cancer compared with bronchoscopy alone, but comparisons with a clinical predictor are not reported. For the subset of 272 patients with a non-diagnostic bronchoscopy, the classifier performance is presented by the pretest physician-predicted risk of cancer. For most of the subpopulations, there was a very high NPV. However, there were 13 false negatives, 10 of whom were considered at high (>60%) risk of cancer pre-bronchoscopy.
Vachani and colleagues reported on rates of invasive procedures from AEGIS-1 and -2 (Vachani, 2016). In 222 patients, 188 (85%) had an inconclusive bronchoscopy and follow-up procedure data available for analysis. Seventy-seven (41%) patients underwent an additional 99 invasive procedures, which included surgical lung biopsy in 40 (52%) patients. Benign and malignant diseases were ultimately diagnosed in 62 (81%) and 15 (19%) patients, respectively. Among those undergoing surgical biopsy, 20 (50%) were performed in patients with benign disease. If the classifier had been used to guide decision making, procedures could have been avoided in 21 (50%) of 42 patients who had additional invasive testing. Further, among 35 patients with an inconclusive index bronchoscopy who were diagnosed with lung cancer, the sensitivity of the classifier was 89%, with 4 (11%) patients having a false-negative classifier result. Invasive procedures after an inconclusive bronchoscopy occur frequently, and most are performed in patients ultimately diagnosed with benign disease.
Section Summary: Clinical Validity
Two multicenter prospective studies have provided evidence of the clinical validity for a bronchial genomic classifier in current or former cigarette smokers undergoing bronchoscopy for suspicion of lung cancer. For patients with intermediate risk of lung cancer with a non-diagnostic bronchoscopic examination, the NPV was 91%. However, there has been limited replication outside of a single trial group.
Clinical Utility
No evidence directly demonstrating improved outcomes in patients managed with the Percepta Bronchial Genomic Classifier (BGC) was identified. Therefore, a chain of indirect evidence was developed, which addresses 2 key questions: (1) does use of the Percepta BGC in individuals with indeterminate bronchoscopy results for suspected lung cancer change clinical management (in this case, reduction of invasive procedures); (2) do those management changes improve outcomes?
Changes in Management
The clinical setting in which Percepta BGC is meant to be used is not well-defined: individuals who are suspected to have cancer, but who have a non-diagnostic bronchoscopy. One decision impact study reporting on clinical management changes but not on outcomes after decisions for invasive procedures were made, have suggested that, in at least some cases, decisions for invasive procedures may be changed.
Ferguson and colleagues reported on the impact of the Percepta BGC on physician decision making for recommending invasive procedures among patients with an inconclusive bronchoscopy (Vachani, 2016). The results revealed that a negative (low risk) result may reduce invasive procedure recommendations in patients diagnosed with benign disease.
Improved Outcomes
Indirect evidence suggests that use of the Percepta BGC has the potential to reduce the number of unnecessary invasive procedures to definitively diagnose benign disease versus malignancy. Compared to the standard care plan, some patients without cancer will have avoided an unnecessary invasive procedure, which is weighed against the small increase in missed cancers in patients who had cancer but tested as negative (low risk) on the Percepta BGC.
Whether the tradeoff between avoiding unneeded surgeries and the potential for missed cancer is worthwhile depends, in part, on patient and physician preferences. Missed malignancies would likely be continued to be followed by active surveillance by low-dose CT imaging. In the context of lung cancers, overall survival is dependent on detection of lung cancer at early, more treatable stages. Avoiding invasive procedures in situations where patients are at very low likelihood of having lung cancer is likely beneficial, given the known complications of invasive procedures (e.g., pneumothorax). However, reductions in unnecessary invasive procedures must be weighed against outcomes and harms associated with a missed diagnosis of lung cancer at earlier, more treatable stages.
Section Summary: Clinical Utility
Direct evidence of the clinical utility for gene expression profiling of bronchial brushings is lacking. Indirect evidence suggests that Percepta BGC has the potential to reduce the number of unnecessary invasive procedures to definitively diagnose benign disease versus malignancy. However, long-term follow-up data is required to determine the survival outcomes in patients with a missed diagnosis of lung cancer at earlier, more treatable stages.
Summary of Evidence
For individuals with undiagnosed pulmonary nodules detected by computed tomography (CT) who receive plasma-based proteomic screening, the evidence includes an analytic validity study as well as prospective cohort and prospective-retrospective studies. Relevant outcomes are overall survival, disease-specific survival, test accuracy and validity, morbid events, hospitalizations, and resource utilization. The commercially available tests have been designed to have a high negative predictive value (NPV) of 90%, although studies have reported on slightly different versions. A single multicenter prospective-retrospective study revealed that 32% of surgeries and 31.8% of invasive procedures could have been avoided; however, 24.0% of patients with malignancy would have been triaged to CT surveillance (false-negative). Studies have not reported how it reclassifies patients relative to clinical classifiers in terms of risk. Indirect evidence has suggested that a proteomic classifier with high NPV has the potential to reduce the number of unnecessary invasive procedures to definitively diagnose benign disease versus malignancy. The evidence is insufficient to determine the effects of the technology on health outcomes.
For individuals with undiagnosed pulmonary nodules pulmonary nodules following indeterminate bronchoscopy results for suspected lung cancer who receive gene expression profiling of bronchial brushings, the evidence includes an analytic study and multicenter prospective studies. Relevant outcomes are overall survival, disease-specific survival, test accuracy and validity, morbid events, hospitalizations, and resource utilization. Reported receiver operating characteristic curve values ranged from 0.74 to 0.81, with a NPV of 91%. Among patients with low and intermediate pretest probability of cancer with an inconclusive bronchoscopy, 77 (85%) patients underwent invasive diagnostic procedures. However, there were a relatively high number of missed cancers. No validation of the test in other populations was identified. In addition, where the test would fall in the clinical pathway (i.e. other than indeterminate bronchoscopy) is uncertain. The evidence is insufficient to determine the effects of the technology on health outcomes.
Ongoing and Unpublished Clinical Trials
A search of ClinicalTrials.gov in April 2017 did not identify any ongoing or unpublished trials that would likely influence this review.
2018 Update
A literature search conducted using the MEDLINE database did not reveal any new information that would prompt a change in the coverage statement.
2019 Update
Annual policy review completed with a literature search using the MEDLINE database through May 2019. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
Plasma-Based Proteomic Screening of Pulmonary Nodules
Kearney et al conducted an exploratory study that combined the 11-protein plasma classifier (Xpresys Lung) with clinical risk factors using 222 samples associated with a lung nodule of 8 to 20 mm in diameter from the reclassification study by Vachani et al (2015) described above (Kearney, 2017; Vachani, 2015; Mazzone, 2017). The study determined that the ratio of LG3BP to a normalizer protein C163A was the diagnostic and normalizer protein pair with the highest area under the curve (60%). At sensitivity of 90% and specificity of 33%, the ratio of the proteomic marker was more accurate than clinical risk factors, and the combination of the clinical risk factors with the proteomic markers was more accurate than either alone. This study led to the development of the Xpresys Lung version 2, which includes LG3BP, C163A, and clinical risk factors.
Silvestri et al reported the validation of the Xpresys Lung version 2 (BDX-XL2) in a prospective multicenter observational study (Pulmonary Nodule Plasma Proteomic Classifier [PANOPTIC])that enrolled 685 patients with lung nodules of 8 to 30 mm and a low pretest probability of malignancy < 50% (Silvestri, 2018). After exclusions for missing clinical data or a pretest probability of > 50%, 178 patients remained in the intended use population. Of these, 66 were classified as likely benign, 65 of which had a benign nodule, while 1 of 29 malignant nodules (3%) was misclassified as likely benign. Of the 149 benign nodules in the study, 44% were correctly classified as likely benign. For the 71 patients who had invasive procedures, 42 had benign nodules. Use of the integrated proteomic classifier would have reduced the number of patients undergoing an invasive procedure to 27, a 36% relative risk reduction, with 1 malignant nodule misclassified as benign.
The primary limitation of the study by Vachani et al is that the technology is very different from the current marketed version. The primary limitation of the study by Silvestri et al is that a high number of patients were excluded from the study due to incomplete clinical data or because they were subsequently determined to be outside of the intended use population. It is unclear if the intended use population was determined a priori.
Practice Guidelines and Position Statements
American Thoracic Society
The American Thoracic Society published a position statement on the evaluation of molecular biomarkers for the early detection of lung cancer. The Society states that "a clinically useful molecular biomarker applied to the evaluation of lung nodules may lead to expedited therapy for early lung cancer and/or fewer aggressive interventions in patients with benign lung nodules." To be considered clinically useful, a molecular diagnosis "must lead to earlier diagnosis of malignant nodules without substantially increasing the number of procedures performed on patients with benign nodules" or "fewer procedures for patients with benign nodules without substantially delaying the diagnosis of cancer in patients with malignant nodules."
2020 Update
A literature search was conducted through May 2020. There was no new information identified that would prompt a change in the coverage statement.
2021 Update
Annual policy review completed with a literature search using the MEDLINE database through May 2021. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
In an extended analysis and 2 year follow-up of the PANOPTIC trial, Tanner et al found that all nodules designated as benign at year 1 remained benign by imaging at year 2 with no change in pathologic diagnoses or nodule size by CT (Tanner, 2021). Additionally, the area under the curve of the integrated classifier was 0.76 (95% CI, 0.69-0.82), which outperformed the physician pretest probability for malignancy (0.69; 95% CI, 0.62-0.76) and the Mayo (0.69; 95% CI, 0.62-0.76), Veterans Administration (0.6; 95% CI, 0.53-0.67), and Brock (0.71; 95% CI, 0.63-0.77) models in the lower risk pretest probability (≤50%) cohort.
2022 Update
Annual policy review completed with a literature search using the MEDLINE database through May 2022. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
Lee et al provided additional data on the effect of Percepta BCG on clinical management decisions among patients (N=283) with low or intermediate-risk lung nodules who had at least 1 year of follow-up (Lee, 2021). The availability of Percepta results led to 34.3% of patients having their risk of malignancy downgraded. Two-thirds of these patients switched from a planned invasive procedure to surveillance.
2023 Update
Annual policy review completed with a literature search using the MEDLINE database through May 2023. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
Mazzone et al conducted a prospective, multicenter, blinded, clinical validation study on individuals (N=412) who currently or formerly were smokers and were undergoing bronchoscopy for suspected lung cancer from the AEGIS-1/AEGIS-2 cohorts and the Percepta Registry (Mazzone, 2022). The sensitivity, specificity, and predictive values were calculated using predefined thresholds. Investigators noted that Percepta GSC performance was similar between the AEGIS-1 and -2 cohorts and the Percepta Registry with an overall area under the curve of 0.73 (95% CI, 68.3 to 78.4), demonstrating the robustness of the classifier performance across different patient cohorts. Investigators also estimated the potential utility of Percepta GSC in decreasing invasive procedure utilization, had the classifier result been available to manage these lesions. It was determined that, if the classifier results were used in nodule management, 50% of patients with benign lesions and 29% of patients with malignant lesions undergoing additional invasive procedures could have avoided these procedures.
The National Comprehensive Cancer Network (NCCN) guidelines for non-small cell lung cancer, small cell lung cancer, or lung cancer screening do not mention plasma-based proteomic screening testing or gene expression profiling as a potential diagnostic or screening tool (NCCN, 2023; NCCN, 2023; NCCN, 2023).
Some plans will provide limited coverage for the BDX-XL2 test (Biodesix) for the management of a lung nodule between 8 and 30 mm in diameter, in patients at least 40 years of age and with a pre-test cancer risk of 50% or less, as assessed by the Mayo Clinic Model for Solitary Pulmonary Nodules. Per Biodesix, both the Nodify XL2 and Nodify CDT tests are $0 out of pocket for covered Medicare beneficiaries (Biodesix, 2023).
Some plans will provide limited coverage for the PERCEPTA Bronchial Genomic Classifier (Veracyte) to identify patients with clinical low- or intermediate-risk of malignancy, after a non-diagnostic bronchoscopy, who may be followed with CT surveillance in lieu of further invasive biopsies or surgery. A patient’s clinical risk of malignancy may be ascertained by the McWilliams or Gould risk assessment models. Coverage does not include clinical high risk patients or patients with known lung cancer. Per Veracyte, the PERCEPTA Genomic Sequencing Classifier test is covered by Medicare (Veracyte, 2023).
Lam et al reported on a study on the sensitivity of the EarlyCDT-Lung test which evaluated 574 subjects from four separate cohorts (Lam, 2011). Group 1 (n=122) included subjects with small cell lung cancer (SCLC); Group 2 (n=249) was composed of 97% of subjects with non-small cell lung cancer (NSCLC); Group 3 (n=122) only included subjects with NSCLC; and in Group 4 (n=81) 62% of subjects were diagnosed with NSCLC. For Group 1, the results indicated a sensitivity of 57% for SCLC (specificity data not calculated). The sensitivity and specificity for Group 2 was 34% and 87% for NSCLC. For Group 3, sensitivity and specificity was 31% and 84% for NSCLC. Finally, in Group 4, sensitivity and specificity was 35% and 89% for NSCLC and 43% and 89% for SCLC. No significant difference in positivity was reported for the EarlyCDT-Lung test with regard to different lung cancer stages.
Chapman published the results of a case-control study involving 235 subjects with newly diagnosed lung cancer (Chapman, 2012). 235 healthy controls were used to evaluate both 6- and 7-antigen versions of the test. In addition, two prospective consecutive series of 776 and 836 individuals at an increased risk of developing lung cancer were also evaluated with both versions of the EarlyCDT-Lung test. The 6-antigen panel gave a sensitivity of 39% and a specificity of 89%, while the 7-antigen panel resulted in a sensitivity of 41% and a specificity of 91%. Once adjusted for occult cancers in the population, this resulted in a specificity of 93%.
González Maldonado et al reported on a study evaluating the early detection accuracy, in terms of sensitivity and specificity, of EarlyCDT®-Lung test in which the EarlyCDT Lung test was performed on individuals with lung cancer detected by low-dose computed tomography (CT) and for 180 retrospectively selected cancer-free participants (Gonzalez Maldonado, 2021). 90 of the cancer-free participants were randomly selected from all cancer-free participants (baseline control) and 90 were randomly selected from the cancer-free participants with suspicious imaging findings (suspicious nodules controls). The EarlyCDT lung test resulted in a sensitivity of 13.0% (95% [CI, 4.9 to 26.3%) in the baseline group. They found that the EarlyCDT test had a specificity of 88.9% (95% CI, 80.5 to 94.5%) in the baseline control group and 91.1% (95% CI, 83.2 to 96.1%) in the suspicious nodule control group.
Borg et al reported on a study evaluating the EarlyCDT lung test in 246 individuals with suspected lung cancer (Borg, 2021). After completing a diagnostic work-up, 75 of 246 individuals (30%) were found to have lung cancer, 12 of 246 individuals (5%) had lung metastases originating from primary tumors in other locations, and 159 of 246 (65%) had no cancer detected. The sensitivity of the EarlyCDT lung test for detecting lung cancer was 33% (25 of 75 individuals were identified by the test). The sensitivity for detecting any lung malignancy (including lung metastases from tumors in other locations) was 31% (27 of 87 individuals were identified by the test). Test sensitivity was higher in older individuals; sensitivities were 11%, 31% and 55% in those age 60 or younger, 61-75 years and over 75 years, respectively. The test also had a higher sensitivity in heavier smokers. Sensitivity was 33% in individuals with at least 10 tobacco pack years and 44% in those with at least 50 pack years. The authors concluded that the test did not have sufficient sensitivity for use in a low-dose CT lung cancer detection program.
Silvestri et al reported on a prospective, multicenter observational trial of individuals with 8 to 30 mm lung nodules (Silvestri, 2018). This study was a retrospective evaluation of the performance of the Nodify XL2 test. A total of 392 subjects 40 years of age or older with lung nodules between 8 and 30 mm detected by CT were included in the study, but the report focused on 178 subjects who had a pre-test probability of the nodule being cancerous of ≤ 50%. The authors reported sensitivity of 97% and a specificity of 44%. The posttest probability of distinguishing benign from cancerous nodules was 98%. In a subset of subjects who were determined to be “likely benign” according to the Nodify XL2 test, 44% were identified correctly as being likely benign and 3% with cancerous nodes were incorrectly identified as being benign. The authors concluded that when used for lung nodules with a ≤ 50% probability of a node being cancerous, the Nodify XL2 test accurately identifies benign lung nodules with good performance characteristics and that invasive procedures could be reduced by diverting benign nodules to surveillance. However, the findings of this study must be considered to be preliminary before the test in used in clinical practice. Additional study is needed to fully understand the true health outcome benefits of this test.
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PMID 28960111 National Comprehensive Cancer Network (NCCN).(2023) NCCN Guidelines Version 1.2023: Lung Cancer Screening. 2023; https://www.nccn.org/professionals/physician_gls/pdf/lung_screening.pdf. Accessed March 11, 2023. National Comprehensive Cancer Network (NCCN).(2023) NCCN Guidelines Version 2.2023: Non-Small Cell Lung Cancer. 2023; https://www.nccn.org/professionals/physician_gls/pdf/nscl.pdf. Accessed March 13, 2023 National Comprehensive Cancer Network (NCCN).(2023) NCCN Guidelines Version 3.2023: Small Cell Lung Cancer. 2023; https://www.nccn.org/professionals/physician_gls/pdf/sclc.pdf. Accessed March 12, 2023. Oncimmune.(2023) Early Cancer Detection Test EarlyCDT. 2023. https://www.oncimmune.com/healthcare/early-cancer-detection/. Accessed August 3, 2023. Pecot CV, Li M, Zhang XJ, et al.(2012) Added value of a serum proteomic signature in the diagnostic evaluation of lung nodules. Cancer Epidemiol Biomarkers Prev. May 2012;21(5):786-792. 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PMID 29496499 Tanner NT, Springmeyer SC, Porter A, et al.(2021) Assessment of Integrated Classifier's Ability to Distinguish Benign From Malignant Lung Nodules: Extended Analyses and 2-Year Follow-Up Results of the PANOPTIC (Pulmonary Nodule Plasma Proteomic Classifier) Trial. Chest. Mar 2021; 159(3): 1283-1287. PMID 33171158 Vachani A, Hammoud Z, Springmeyer S, et al.(2015) Clinical utility of a plasma protein classifier for indeterminate lung nodules. Lung. Dec 2015;193(6):1023-1027. PMID 26376647 Vachani A, Pass HI, Rom WN, et al.(2015) Validation of a multiprotein plasma classifier to identify benign lung nodules. J Thorac Oncol. Apr 2015;10(4):629-637. PMID 25590604 Vachani A, Whitney DH, Parsons EC, et al.(2016) Clinical utility of a bronchial genomic classifier in patients with suspected lung cancer. Chest. Jul 2016;150(1):210-218. 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Group specific policy will supersede this policy when applicable. This policy does not apply to the Wal-Mart Associates Group Health Plan participants or to the Tyson Group Health Plan participants.
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