Costs of Diagnostic Assessment for Lung Cancer: A Medicare Claims Analysis

Pneumothorax risk reduction during CT-guided lung biopsy - Effect of fluid application to the pleura before lung puncture and the gravitational effect of pleural pressure

PURPOSE

This study investigated strategies to reduce pneumothorax risk in CT-guided lung biopsy. The approach involved administering 10 ml of 1 % lidocaine fluid in the subpleural or pleural space before lung puncture and utilizing the gravitational effect of pleural pressure with specific patient positioning.

METHOD

We retrospectively analyzed 72 percutaneous CT-guided lung biopsies performed at a single center between January 2020 and April 2023. These were grouped based on fluid administration during the biopsy and whether the biopsies were conducted in dependent or non-dependent lung regions. Confounding factors like patient demographics, lesion characteristics, and procedural details were assessed. Patient characteristics and the occurrence of pneumothoraces were compared using a Kurskal-Wallis test for continuous variables and a Fisher's exact test for categorical variables. Multivariable logistic regression was used to identify potential confounders.

RESULTS

Subpleural or pleural fluid administration and performing biopsies in dependent lung areas were significantly linked to lower peri-interventional pneumothorax incidence (n = 15; 65 % without fluid in non-dependent areas, n = 5; 42 % without fluid in dependent areas, n = 5; 36 % with fluid in non-dependent areas,n = 0; 0 % with fluid in dependent areas; p = .001). Even after adjusting for various factors, biopsy in dependent areas and fluid administration remained independently associated with reduced pneumothorax risk (OR 0.071, p<=.01 for lesions with fluid administration; OR 0.077, p = .016 for lesions in dependent areas).

CONCLUSIONS

Pre-puncture fluid administration to the pleura and consideration of gravitational effects during patient positioning can effectively decrease pneumothorax occurrences in CT-guided lung biopsy.

Minimally invasive biopsy-based diagnostics in support of precision cancer medicine

Precision cancer medicine (PCM) to support the treatment of solid tumors requires minimally invasive diagnostics. Here, we describe the development of fine-needle aspiration biopsy-based (FNA) molecular cytology which will be increasingly important in diagnostics and adaptive treatment. We provide support for FNA-based molecular cytology having a significant potential to replace core needle biopsy (CNB) as a patient-friendly potent technique for tumor sampling for various tumor types. This is not only because CNB is a more traumatic procedure and may be associated with more complications compared to FNA-based sampling, but also due to the recently developed molecular methods used with FNA. Recent studies show that image-guided FNA in combination with ultrasensitive molecular methods also offers opportunities for characterization of the tumor microenvironment which can aid therapeutic decisions. Here we provide arguments for an increased implementation of molecular FNA-based sampling as a patient-friendly diagnostic method, which may, due to its repeatability, facilitate regular sampling that is needed during different treatment lines, to provide tumor information, supporting treatment decisions, shortening lead times in healthcare, and benefit healthcare economics.

The Lung Cancer Prediction Model "Stress Test": Assessment of Models' Performance in a High-Risk Prospective Pulmonary Nodule Cohort

BACKGROUND

Pulmonary nodules represent a growing health care burden because of delayed diagnosis of malignant lesions and overtesting for benign processes. Clinical prediction models were developed to inform physician assessment of pretest probability of nodule malignancy but have not been validated in a high-risk cohort of nodules for which biopsy was ultimately performed.

RESEARCH QUESTION

Do guideline-recommended prediction models sufficiently discriminate between benign and malignant nodules when applied to cases referred for biopsy by navigational bronchoscopy?

STUDY DESIGN AND METHODS

We assembled a prospective cohort of 322 indeterminate pulmonary nodules in 282 patients referred to a tertiary medical center for diagnostic navigational bronchoscopy between 2017 and 2019. We calculated the probability of malignancy for each nodule using the Brock model, Mayo Clinic model, and Veterans Affairs (VA) model. On a subset of 168 patients who also had PET-CT scans before biopsy, we also calculated the probability of malignancy using the Herder model. The performance of the models was evaluated by calculating the area under the receiver operating characteristic curves (AUCs) for each model.

RESULTS

The study cohort contained 185 malignant and 137 benign nodules (57% prevalence of malignancy). The malignant and benign cohorts were similar in terms of size, with a median longest diameter for benign and malignant nodules of 15 and 16 mm, respectively. The Brock model, Mayo Clinic model, and VA model showed similar performance in the entire cohort (Brock AUC, 0.70; 95% CI, 0.64-0.76; Mayo Clinic AUC, 0.70; 95% CI, 0.64-0.76; VA AUC, 0.67; 95% CI, 0.62-0.74). For 168 nodules with available PET-CT scans, the Herder model had an AUC of 0.77 (95% CI, 0.68-0.85).

INTERPRETATION

Currently available clinical models provide insufficient discrimination between benign and malignant nodules in the common clinical scenario in which a patient is being referred for biopsy, especially when PET-CT scan information is not available.

Radiomics and artificial intelligence for risk stratification of pulmonary nodules: Ready for primetime?

Pulmonary nodules are ubiquitously found on computed tomography (CT) imaging either incidentally or via lung cancer screening and require careful diagnostic evaluation and management to both diagnose malignancy when present and avoid unnecessary biopsy of benign lesions. To engage in this complex decision-making, clinicians must first risk stratify pulmonary nodules to determine what the best course of action should be. Recent developments in imaging technology, computer processing power, and artificial intelligence algorithms have yielded radiomics-based computer-aided diagnosis tools that use CT imaging data including features invisible to the naked human eye to predict pulmonary nodule malignancy risk and are designed to be used as a supplement to routine clinical risk assessment. These tools vary widely in their algorithm construction, internal and external validation populations, intended-use populations, and commercial availability. While several clinical validation studies have been published, robust clinical utility and clinical effectiveness data are not yet currently available. However, there is reason for optimism as ongoing and future studies aim to target this knowledge gap, in the hopes of improving the diagnostic process for patients with pulmonary nodules.

Integration of liquid biopsy and immunotherapy: opening a new era in colorectal cancer treatment

Immunotherapy has revolutionized the conventional treatment approaches for colorectal cancer (CRC), offering new therapeutic prospects for patients. Liquid biopsy has shown significant potential in early screening, diagnosis, and postoperative monitoring by analyzing circulating tumor cells (CTC) and circulating tumor DNA (ctDNA). In the era of immunotherapy, liquid biopsy provides additional possibilities for guiding immune-based treatments. Emerging technologies such as mass spectrometry-based detection of neoantigens and flow cytometry-based T cell sorting offer new tools for liquid biopsy, aiming to optimize immune therapy strategies. The integration of liquid biopsy with immunotherapy holds promise for improving treatment outcomes in colorectal cancer patients, enabling breakthroughs in early diagnosis and treatment, and providing patients with more personalized, precise, and effective treatment strategies.

Update on Biomarkers for the Stratification of Indeterminate Pulmonary Nodules

Lung cancer is the leading cause of cancer-related deaths. Early detection and diagnosis are critical, as survival decreases with advanced stages. Approximately 1.6 million nodules are incidentally detected every year on chest CT scan images in the United States. This number of nodules identified is likely much larger after accounting for screening-detected nodules. Most of these nodules, whether incidentally or screening detected, are benign. Despite this, many patients undergo unnecessary invasive procedures to rule out cancer because our current stratification approaches are suboptimal, particularly for intermediate probability nodules. Thus, noninvasive strategies are urgently needed. Biomarkers have been developed to assist through the continuum of lung cancer care and include blood protein-based biomarkers, liquid biopsies, quantitative imaging analysis (radiomics), exhaled volatile organic compounds, and bronchial or nasal epithelium genomic classifiers, among others. Although many biomarkers have been developed, few have been integrated into clinical practice as they lack clinical utility studies showing improved patient-centered outcomes. Rapid technologic advances and large network collaborative efforts will continue to drive the discovery and validation of many novel biomarkers. Ultimately, however, randomized clinical utility studies showing improved patient outcomes will be required to bring biomarkers into clinical practice.

Multi-Omic Biomarkers Improve Indeterminate Pulmonary Nodule Malignancy Risk Assessment

The clinical management of patients with indeterminate pulmonary nodules is associated with unintended harm to patients and better methods are required to more precisely quantify lung cancer risk in this group. Here, we combine multiple noninvasive approaches to more accurately identify lung cancer in indeterminate pulmonary nodules. We analyzed 94 quantitative radiomic imaging features and 41 qualitative semantic imaging variables with molecular biomarkers from blood derived from an antibody-based microarray platform that determines protein, cancer-specific glycan, and autoantibody-antigen complex content with high sensitivity. From these datasets, we created a PSR (plasma, semantic, radiomic) risk prediction model comprising nine blood-based and imaging biomarkers with an area under the receiver operating curve (AUROC) of 0.964 that when tested in a second, independent cohort yielded an AUROC of 0.846. Incorporating known clinical risk factors (age, gender, and smoking pack years) for lung cancer into the PSR model improved the AUROC to 0.897 in the second cohort and was more accurate than a well-characterized clinical risk prediction model (AUROC = 0.802). Our findings support the use of a multi-omics approach to guide the clinical management of indeterminate pulmonary nodules.

The presence of circulating genetically abnormal cells in blood predicts risk of lung cancer in individuals with indeterminate pulmonary nodules

PURPOSE

Computed tomography is the standard method by which pulmonary nodules are detected. Greater than 40% of pulmonary biopsies are not lung cancer and therefore not necessary, suggesting that improved diagnostic tools are needed. The LungLB™ blood test was developed to aid the clinical assessment of indeterminate nodules suspicious for lung cancer. LungLB™ identifies circulating genetically abnormal cells (CGACs) that are present early in lung cancer pathogenesis.

METHODS

LungLB™ is a 4-color fluorescence in-situ hybridization assay for detecting CGACs from peripheral blood. A prospective correlational study was performed on 151 participants scheduled for a pulmonary nodule biopsy. Mann-Whitney, Fisher's Exact and Chi-Square tests were used to assess participant demographics and correlation of LungLB™ with biopsy results, and sensitivity and specificity were also evaluated.

RESULTS

Participants from Mount Sinai Hospital (n = 83) and MD Anderson (n = 68), scheduled for a pulmonary biopsy were enrolled to have a LungLB™ test. Additional clinical variables including smoking history, previous cancer, lesion size, and nodule appearance were also collected. LungLB™ achieved 77% sensitivity and 72% specificity with an AUC of 0.78 for predicting lung cancer in the associated needle biopsy. Multivariate analysis found that clinical and radiological factors commonly used in malignancy prediction models did not impact the test performance. High test performance was observed across all participant characteristics, including clinical categories where other tests perform poorly (Mayo Clinic Model, AUC = 0.52).

CONCLUSION

Early clinical performance of the LungLB™ test supports a role in the discrimination of benign from malignant pulmonary nodules. Extended studies are underway.

Canine Scent Detection in Lung Cancer Screening

Canines historically have been proven to have great benefits in human medicine. They have a unique ability to detect volatile organic compounds, or VOCs, in several different diseases, which allows them to work efficiently as a medical alert dog or detect the presence of certain diseases in human samples. Early studies have shown efficiency in the ability of canines to detect malignant cells from primary lung tumors in the fluid and breath samples of patients. Lung cancer is the third most common cancer and is the number one cause of cancer-related deaths in the United States. Because of its commonality, The U.S. Preventive Services Task Force developed guidelines for screening high-risk individuals, which includes low-dose CT with proven efficacy. Although effective, it comes with limitations, including increased cost, concern for radiation exposure, and low compliance amongst those who are eligible for screening. Other screening methods have been studied to overcome these deficiencies, including the use of canines trained in medical scent detection. Medical scent canines may prove to be an efficient alternative form of screening to the traditional use of low-dose CT and may be a viable non-imaging screening alternative.

Longitudinal lung cancer prediction convolutional neural network model improves the classification of indeterminate pulmonary nodules

A deep learning model (LCP CNN) for the stratification of indeterminate pulmonary nodules (IPNs) demonstrated better discrimination than commonly used clinical prediction models. However, the LCP CNN score is based on a single timepoint that ignores longitudinal information when prior imaging studies are available. Clinically, IPNs are often followed over time and temporal trends in nodule size or morphology inform management. In this study we investigated whether the change in LCP CNN scores over time was different between benign and malignant nodules. This study used a prospective-specimen collection, retrospective-blinded-evaluation (PRoBE) design. Subjects with incidentally or screening detected IPNs 6-30 mm in diameter with at least 3 consecutive CT scans prior to diagnosis (slice thickness ≤ 1.5 mm) with the same nodule present were included. Disease outcome was adjudicated by biopsy-proven malignancy, biopsy-proven benign disease and absence of growth on at least 2-year imaging follow-up. Lung nodules were analyzed using the Optellum LCP CNN model. Investigators performing image analysis were blinded to all clinical data. The LCP CNN score was determined for 48 benign and 32 malignant nodules. There was no significant difference in the initial LCP CNN score between benign and malignant nodules. Overall, the LCP CNN scores of benign nodules remained relatively stable over time while that of malignant nodules continued to increase over time. The difference in these two trends was statistically significant. We also developed a joint model that incorporates longitudinal LCP CNN scores to predict future probability of cancer. Malignant and benign nodules appear to have distinctive trends in LCP CNN score over time. This suggests that longitudinal modeling may improve radiomic prediction of lung cancer over current models. Additional studies are needed to validate these early findings.

Prediction of Complication Risk in Computed Tomography-guided Thoracic Biopsy: A Prescription for Improving Procedure Safety

PURPOSE

Computed tomography-guided transthoracic biopsy (CTTB) is a minimally invasive procedure with a high diagnostic yield for a variety of thoracic diseases. We comprehensively assessed a large CTTB cohort to predict procedural and patient factors associated with the risk of complications.

MATERIALS AND METHODS

The medical record and computed tomography images of 1430 patients who underwent CTTB were reviewed individually to obtain clinical information and technical procedure factors. Statistical analyses included descriptive and summary statistics, univariate analysis with the Fisher test, and multivariate logistic regression.

RESULTS

The most common type of complication was pneumothorax (17.4%), followed by bleeding (5.9%). Only 26 patients (1.8%) developed a major complication. Lung lesions carried a higher risk of complications than nonlung lesions. For lung lesions, the nondependent position of the lesion, vertical needle approach, trespassing aerated lung, and involvement of a trainee increased the risk of complication, whereas the use of the coaxial technique was a protective factor. The time with the needle in the lung, the number of biopsy samples, and the distance crossing the aerated lung were identified as additional risk factors in multivariate analysis. For nonlung lesions, trespassing the pleural space was the single best predictor of complications. A logistic regression-based model achieved an area under the receiver operating characteristic curve of 0.975, 0.699, and 0.722 for the prediction of major, minor, and no complications, respectively.

CONCLUSIONS

Technical procedural factors that can be modified by the operator are highly predictive of the risk of complications in CTTB.

Radiologic and histopathologic features of hydrogel sealant after lung resection in participants of a prospective randomized clinical trial

PURPOSE

To summarize imaging and histopathologic characteristics of hydrogel sealant (plug) in lung parenchyma and assess their correlation with time since deployment of sealant.

MATERIALS AND METHODS

Among a total of 208 participants randomized to the hydrogel sealant arm of a lung biopsy prospective randomized clinical trial, 51 underwent resection of the biopsied lesion. In 34 participants sealant material was present on histopathologic sections (n = 22), or they had cross-sectional imaging of chest between biopsy and resection (n = 23) or they had both imaging and histopathology (n = 11). Histopathologic and imaging findings were described. The association of these findings with time since sealant deployment was evaluated using the Wilcoxon rank sum test.

RESULTS

The mean time since sealant deployment for histopathology was 45.7 days (median 36, range 14-181) and for imaging studies was 99 days (median 32, range 4-527). The sealant was infiltrated by inflammatory cells in 20 (91%) participants. The main general histopathologic pattern of sealant was foamy in 12 (57%) and mesh in 8 (38%) participants. Imaging appearance of sealant was serpiginous in 18 (60%), linear in 10 (33%) or lobulated in 2 (6.7%) participants. In 2 participants the sealant was hypermetabolic with no histopathologic evidence of tumor. No correlation was found between time since sealant deployment and imaging or histopathologic appearances.

CONCLUSION

Hydrogel sealant appears as a serpiginous, linear, or lobulated opacity on cross-sectional imaging which can be metabolically active. It is associated with an inflammatory reaction with a foamy or mesh general pattern on histopathological assessment. No correlation was found between time since sealant deployment and imaging or histopathologic appearances.

Clinical Impact and Generalizability of a Computer-Assisted Diagnostic Tool to Risk-Stratify Lung Nodules With CT

OBJECTIVE

To evaluate whether an imaging classifier for radiology practice can improve lung nodule classification and follow-up.

METHODS

A machine learning classifier was developed and trained using imaging data from the National Lung Screening Trial (NSLT) to produce a malignancy risk score (malignancy Similarity Index [mSI]) for individual lung nodules. In addition to NLST cohorts, external cohorts were developed from a tertiary referral lung cancer screening program data set and an external nonscreening data set of all nodules detected on CT. Performance of the mSI combined with Lung-RADS was compared with Lung-RADS alone and the Mayo and Brock risk calculators.

RESULTS

We analyzed 963 subjects and 1,331 nodules across these cohorts. The mSI was comparable in accuracy (area under the curve = 0.89) to existing clinical risk models (area under the curve = 0.86-0.88) and independently predictive in the NLST cohort of 704 nodules. When compared with Lung-RADS, the mSI significantly increased sensitivity across all cohorts (25%-117%), with significant increases in specificity in the screening cohorts (17%-33%). When used in conjunction with Lung-RADS, use of mSI would result in earlier diagnoses and reduced follow-up across cohorts, including the potential for early diagnosis in 42% of malignant NLST nodules from prior-year CT scans.

CONCLUSION

A computer-assisted diagnosis software improved risk classification from chest CTs of screening and incidentally detected lung nodules compared with Lung-RADS. mSI added predictive value independent of existing radiological and clinical variables. These results suggest the generalizability and potential clinical impact of a tool that is straightforward to implement in practice.

Comparing modalities for risk assessment in patients with pulmonary lesions and nondiagnostic bronchoscopy for suspected lung cancer

BACKGROUND

Bronchoscopy is commonly utilized for non-surgical sampling of indeterminant pulmonary lesions, but nondiagnostic procedures are common. Accurate assessment of the risk of malignancy is essential for decision making in these patients, yet we lack tools that perform well across this heterogeneous group of patients. We sought to evaluate the accuracy of three previously validated risk models and physician-assessed risk (PAR) in patients with a newly identified lung lesion undergoing bronchoscopy for suspected lung cancer where the result is nondiagnostic.

METHODS

We performed an analysis of prospective data collected for the Percepta Bronchial Genomic Classifier Multicenter Registry. PAR and three previously validated risk models (Mayo Clinic, Veteran's Affairs, and Brock) were used to determine the probability of lung cancer (low, intermediate, or high) in 375 patients with pulmonary lesions who underwent bronchoscopy for possible lung cancer with nondiagnostic pathology. Results were compared to the actual adjudicated prevalence of malignancy in each pre-test risk group, determined with a minimum of 12 months follow up after bronchoscopy.

RESULTS

PAR and the risk models performed poorly overall in the assessment of risk in this patient population. PAR most closely matched the observed prevalence of malignancy in patients at 12 months after bronchoscopy, but all modalities had a low area under the curve, and in all clinical models more than half of all the lesions labeled as high risk were truly or likely benign. The studied risk model calculators overestimate the risk of malignancy compared to PAR, particularly in the subset in older patients, irregularly bordered nodules, and masses > 3 cm. Overall, the risk models perform only slightly better when confined to lung nodules < 3 cm in this population.

CONCLUSION

The currently available tools for the assessment of risk of malignancy perform suboptimally in patients with nondiagnostic findings following a bronchoscopic evaluation for lung cancer. More accurate and objective tools for risk assessment are needed.

TRIAL REGISTRATION

not applicable.

A handheld electronic device with the potential to detect lung cancer biomarkers from exhaled breath

Lung cancer is the leading cause of cancer death in the United States. It has the lowest 5-year survival rate among the most common cancers and therefore, early diagnosis is critical to improve the survival rate. In this paper, a new handheld electronic device is proposed to detect nine lung cancer biomarkers in the exhaled breath. An electrochemical gas sensor was produced through deposition of a thin layer of graphene and Prussian blue on a chromium-modified silicon substrate. Selective binding of the analyte was formed by molecular imprinting polymer (MIP). Subsequent polymerization and removal of the analyte yielded a layer of a conductive polymer on top of the sensor containing molecularly imprinted cavities selective for the target molecule. The sensors were tested over 1-20 parts per trillion (ppt) level of concentration while the sensor resistance has been monitored as the sensors react to the analyte by resistance change. Pentane sensor was also tested for selectivity. A printed circuit board was designed to measure the resistance of each sensor and send the data to a developed application in smartphone through Bluetooth. This handheld device has the potential to be used as a diagnostic method in the near future.

Artificial Intelligence Tool for Assessment of Indeterminate Pulmonary Nodules Detected with CT

Background Limited data are available regarding whether computer-aided diagnosis (CAD) improves assessment of malignancy risk in indeterminate pulmonary nodules (IPNs). Purpose To evaluate the effect of an artificial intelligence-based CAD tool on clinician IPN diagnostic performance and agreement for both malignancy risk categories and management recommendations. Materials and Methods This was a retrospective multireader multicase study performed in June and July 2020 on chest CT studies of IPNs. Readers used only CT imaging data and provided an estimate of malignancy risk and a management recommendation for each case without and with CAD. The effect of CAD on average reader diagnostic performance was assessed using the Obuchowski-Rockette and Dorfman-Berbaum-Metz method to calculate estimates of area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. Multirater Fleiss κ statistics were used to measure interobserver agreement for malignancy risk and management recommendations. Results A total of 300 chest CT scans of IPNs with maximal diameters of 5-30 mm (50.0% malignant) were reviewed by 12 readers (six radiologists, six pulmonologists) (patient median age, 65 years; IQR, 59-71 years; 164 [55%] men). Readers' average AUC improved from 0.82 to 0.89 with CAD (P < .001). At malignancy risk thresholds of 5% and 65%, use of CAD improved average sensitivity from 94.1% to 97.9% (P = .01) and from 52.6% to 63.1% (P < .001), respectively. Average reader specificity improved from 37.4% to 42.3% (P = .03) and from 87.3% to 89.9% (P = .05), respectively. Reader interobserver agreement improved with CAD for both the less than 5% (Fleiss κ, 0.50 vs 0.71; P < .001) and more than 65% (Fleiss κ, 0.54 vs 0.71; P < .001) malignancy risk categories. Overall reader interobserver agreement for management recommendation categories (no action, CT surveillance, diagnostic procedure) also improved with CAD (Fleiss κ, 0.44 vs 0.52; P = .001). Conclusion Use of computer-aided diagnosis improved estimation of indeterminate pulmonary nodule malignancy risk on chest CT scans and improved interobserver agreement for both risk stratification and management recommendations. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Yanagawa in this issue.

Introduction of Nanomaterials to Biosensors for Exosome Detection: Case Study for Cancer Analysis

Exosomes have been gaining attention for early cancer diagnosis owing to their biological functions in cells. Several studies have reported the relevance of exosomes in various diseases, including pancreatic cancer, retroperitoneal fibrosis, obesity, neurodegenerative diseases, and atherosclerosis. Particularly, exosomes are regarded as biomarkers for cancer diagnosis and can be detected in biofluids, such as saliva, urine, peritoneal fluid, and blood. Thus, exosomes are advantageous for cancer liquid biopsies as they overcome the current limitations of cancer tissue biopsies. Several studies have reported methods for exosome isolation, and analysis for cancer diagnosis. However, further clinical trials are still required to determine accurate exosome concentration quantification methods. Recently, various biosensors have been developed to detect exosomal biomarkers, including tumor-derived exosomes, nucleic acids, and proteins. Among these, the exact quantification of tumor-derived exosomes is a serious obstacle to the clinical use of liquid biopsies. Precise detection of exosome concentration is difficult because it requires clinical sample pretreatment. To solve this problem, the use of the nanobiohybrid material-based biosensor provides improved sensitivity and selectivity. The present review will discuss recent progress in exosome biosensors consisting of nanomaterials and biomaterial hybrids for electrochemical, electrical, and optical-based biosensors.

Economic Analysis of Tissue-First, Plasma-First, and Complementary NGS Approaches for Treatment-Naïve Metastatic Lung Adenocarcinoma

Background

To compare the testing costs and testing turnaround times of tissue-first, plasma-first, and complementary next-generation sequencing (NGS) approaches in patients with treatment-naïve metastatic lung adenocarcinoma.

Materials and Methods

We developed a decision tree model to compare three different approaches. Patients were entered into the model upon cancer diagnosis and those with both insufficient tissue specimens and negative liquid-based NGS were subjected to tissue re-biopsy. Actionable gene alterations with the U.S. Food and Drug Administration (FDA)-approved therapies included epidermal growth factor receptor (EGFR) mutation, anaplastic lymphoma kinase (ALK) gene rearrangement, ROS proto-oncogene 1 (ROS1) rearrangement, B-Raf proto-oncogene (BRAF) V600E mutation, rearranged during transfection (RET) gene rearrangement, mesenchymal-epithelial transition factor (MET) mutation, neurotrophic tyrosine receptor kinase (NTRK) gene rearrangement, K-Ras proto-oncogene (KRAS) G12C mutation, and human epidermal growth factor receptor 2 (HER2) mutation. Model outcomes were testing costs, testing turnaround times, and monetary losses taking both cost and time into consideration. We presented base-case results using probabilistic analysis. Stacked one-way and three-way sensitivity analyses were also performed.

Results

In terms of testing costs, tissue-first approach incurred US$2,354($1,963-$2,779) and was the most cost-efficient strategy. Complementary approach testing turnaround time (days) of 12.7 (10.8 to 14.9) was found as the least time-consuming strategy. Tissue-first, complementary, and plasma-first approaches resulted in monetary losses in USD of $4,745 ($4,010-$5,480), $6,778 ($5,923-$7,600), and $7,006 ($6,047-$7,964) respectively, and identified the same percentage of patients with appropriate FDA-approved therapies. Costs for liquid-based NGS, EGFR mutation rates, and quantity of tissue specimens were the major determinants in minimizing monetary loss. Plasma-first approach would be the preferable strategy if its testing price was reduced in USD to $818, $1,343, and $1,869 for populations with EGFR mutation rates of 30%, 45%, and 60% respectively.

Conclusion

The tissue-first approach is currently the best strategy in minimizing monetary loss. The complementary approach is an alternative for populations with a low EGFR mutation rate. The plasma-first approach becomes increasingly preferable as EGFR mutation rates gradually increase.

18F-FSPG PET imaging for the evaluation of indeterminate pulmonary nodules

Background

¹⁸F-fluorodeoxyglucose (FDG) PET/CT is recommended for evaluation of intermediate-risk indeterminate pulmonary nodules (IPNs). While highly sensitive, the specificity of FDG remains suboptimal for differentiating malignant from benign nodules, particularly in areas where fungal lung diseases are prevalent. Thus, a cancer-specific imaging probe is greatly needed. In this study, we tested the hypothesis that a PET radiotracer (S)-4-(3-[¹⁸F]-fluoropropyl)-L-glutamic acid (FSPG) improves the diagnostic accuracy of IPNs compared to ¹⁸F-FDG PET/CT.

Methods

This study was conducted at a major academic medical center and an affiliated VA medical center. Twenty-six patients with newly discovered IPNs 7-30mm diameter or newly diagnosed lung cancer completed serial PET/CT scans utilizing ¹⁸F-FDG and ¹⁸F-FSPG, without intervening treatment of the lesion. The scans were independently reviewed by two dual-trained diagnostic radiology and nuclear medicine physicians. Characteristics evaluated included quantitative SUVmax values of the pulmonary nodules and metastases.

Results

A total of 17 out of 26 patients had cancer and 9 had benign lesions. ¹⁸F-FSPG was negative in 6 of 9 benign lesions compared to 7 of 9 with ¹⁸F-FDG. ¹⁸F-FSPG and ¹⁸F-FDG were positive in 14 of 17 and 12 of 17 malignant lesions, respectively. ¹⁸F-FSPG detected brain and intracardiac metastases missed by ¹⁸F-FDG PET in one case, while ¹⁸F-FDG detected a metastasis to the kidney missed by ¹⁸F-FSPG.

Conclusion

In this pilot study, there was no significant difference in overall diagnostic accuracy between ¹⁸F-FSPG and ¹⁸F-FDG for the evaluation of IPNs and staging of lung cancer. Additional studies will be needed to determine the clinical utility of this tracer in the management of IPNs and lung cancer.

Circulating Tumor-Macrophage Fusion Cells and Circulating Tumor Cells Complement Non-Small-Cell Lung Cancer Screening in Patients With Suspicious Lung-RADS 4 Nodules

PURPOSE

Low-dose computed tomography (LDCT) screening of high-risk patients decreases lung cancer-related mortality. However, high false-positive rates associated with LDCT result in unnecessary interventions. To distinguish non-small-cell lung cancer (NSCLC) from benign nodules, in the present study, we integrated cellular liquid biomarkers in patients with suspicious lung nodules (lung cancer screening reporting and data system [Lung-RADS] 4).

METHODS

Prospectively, 7.5 mL of blood was collected from 221 individuals (training set: 90 nonscreened NSCLC patients, 74 high-risk screening patients with no/benign nodules [Lung-RADS 1-3], and 20 never smokers; validation set: 37 patients with suspicious nodules [Lung-RADS 4]). Circulating tumor cells (CTCs), CTC clusters, and tumor-macrophage fusion (TMF) cells were identified by blinded analyses. Screening patients underwent a median of two LDCTs (range, 1-4) with a median surveillance time of 30 (range, 11-50) months.

RESULTS

In the validation set of 37 Lung-RADS 4 patients, all circulating cellular biomarker counts (P < .005; Wilcoxon test) and positivity rates were significantly higher in 23 biopsy-proven NSCLC patients (CTCs: 23 of 23 [100%], CTC clusters: 6 of 23 [26.1%], and TMF cells: 15 of 23 [65.2%]) than in 14 patients with biopsy-proven benign nodules (6 of 14 [42.9%], 0 of 14 [0%], and 2 of 14 [14.3%]). On the basis of cutoff values from the training set, logistic regression with receiver operating characteristic and area under the curve analyses demonstrated that CTCs (sensitivity: 0.870, specificity: 1.0, and area under the curve: 0.989) and TMF cells (0.652; 0.880; 0.790) complement LDCT in diagnosing NSCLC in Lung-RADS 4 patients.

CONCLUSION

Cellular liquid biomarkers have a potential to complement LDCT interpretation of suspicious Lung-RADS 4 nodules to distinguish NSCLC from benign lung nodules. A future prospective, large-scale, multicenter clinical trial should validate the role of cellular liquid biomarkers in improving diagnostic accuracy in high-risk patients with Lung-RADS 4 nodules.

Continuous Positive Airway Pressure Adherence and Treatment Cost in Patients With Obstructive Sleep Apnea and Cardiovascular Disease

Objective

To determine whether continuous positive airway pressure (CPAP) adherence reduces health care–related costs or use in patients with obstructive sleep apnea (OSA) and comorbid cardiovascular disease (CVD).

Patients

A total of 23 million patients with CVD were identified in the Medicare fee-for-service database. Of the 65,198 who completed a sleep study between January 2016 and September 2018, 55,125 were diagnosed as having OSA and 1758 were identified in the 5% Medicare durable medical equipment (DME) database.

Methods

Patients with DME claims were categorized as adherent (AD, treatment evidenced ≥91 days after CPAP initiation; n=614) or nonadherent (nAD, n=242) to CPAP therapy. In addition, 9881 individuals with CVD who were not diagnosed as having OSA after sleep testing and without CPAP initiation were included as control patients. Propensity score matching balanced the groups for age, sex, and comorbidities (eg, diabetes mellitus), resulting in 241 participants per cohort. Dependent variables included total episode-of-care, inpatient, outpatient, skilled nursing, home health, and DME costs across 12 months.

Results

Total episode-of-care costs of AD participants ($6825) were lower than those of nAD ($11,312; P<.05) and control ($8102) participants. This difference (Δ) was attributable to fewer outpatient expenses (Δ$2290; P<.05) relative to the nAD group and fewer inpatient expenses (Δ$745) relative to the control group because skilled nursing costs were comparable between groups (P=.73).

Conclusion

Adherence to CPAP treatment reduces annual health care–related expenses by 40% in Medicare patients with CVD and OSA.

Predictive Efficacy of Blood-Based Tumor Mutation Burden Assay for Immune Checkpoint Inhibitors Therapy in Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis

Background

In non-small cell lung cancer (NSCLC) patients treated by immune checkpoint inhibitors (ICIs), tumor mutation burden (TMB) has been found to have predictive potential for survival. When compared to TMB detection in tissue (tTMB), detecting TMB in the blood (bTMB) has practical advantages; yet, the results of various studies are conflicting. The question of whether bTMB can be utilized as a predictive biomarker is becoming increasingly contentious. To confirm the predictive efficacy of bTMB, researchers did a systematic review and meta-analysis to look into the relationship between ICIs and bTMB.

Method

From the inception to March 2021, Cochrane Library, PubMed, EMBASE and other databases were systematically searched. The predictive value of bTMB in ICIs, or the efficacy of ICIs against chemotherapy, was studied. The results were presented as pooled ratio rate (RR) and hazard ratio (HR) with 95% confidence intervals for the Objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). Subgroup analysis, heterogeneity analyses, and sensitivity analysis were also performed.

Results

A total of 2,610 NSCLC patients were studied in seven trials. There were no significant differences in OS (HR = 1.09; 95% CI: 0.62–1.91, P = 0.774) or PFS (HR = 0.73; 95% CI: 0.20–2.65, P = 0.629) between high and low bTMB groups in the ICIs cohort. When ICIs were compared to chemotherapy, ICIs were found to enhance OS (HR = 0.74; 95% CI: 0.59–0.92, P = 0.006), but the improvement in PFS and ORR was only a numerical trend (PFS: HR = 0.83; 95% CI: 0.63–1.09, P = 0.173; ORR: RR = 0.92, 95% CI: 0.77–1.10, P = 0.372). NSCLC patients treated with ICIs in the high bTMB group had better survival benefits than chemotherapy patients in terms of OS (HR = 0.63; 95% CI: 0.51–0.76, P <0.001), PFS (HR = 0.63; 95% CI: 0.52–0.76, P <0.001), and ORR (RR = 1.86; 95% CI: 1.32–2.62, P <0.001), while in the low TMB group, the results were no different or even reversed (OS: HR = 0.89; 95% CI: 0.64–1.24, P = 0.485; PFS: HR = 1.21, 95% CI: 0.93–1.58, P = 0.154; ORR: RR = 0.68, 95% CI: 0.54–0.85, P = 0.001).

Conclusions

TMB could predict the enhanced survival benefit of NSCLC patients treated with ICIs; however the role of bTMB is limited at this stage. For NSCLC patients with high TMB, ICIc may be a better option than chemotherapy.

Transparent Machine Learning Models to Diagnose Suspicious Thoracic Lesions Leveraging CT Guided Biopsy Data

RATIONALE AND OBJECTIVES

To train and validate machine learning models capable of classifying suspicious thoracic lesions as benign or malignant and to further classify malignant lesions by pathologic subtype while quantifying feature importance for each classification.

MATERIALS AND METHODS

796 patients who had undergone CT guided thoracic biopsy for a concerning thoracic lesion (79.3% lung, 11.4% mediastinum, 6.5% pleura, 2.7% chest wall) were retrospectively enrolled. Lesions were classified as malignant or benign based on ground-truth pathology result, and malignant lesions were classified as primary or secondary cancer. Clinical variables were extracted from EMR and radiology reports. Supervised binary and multiclass classification models were trained to classify lesions based on the input features and evaluated on a held-out test set. Model specific feature analyses were performed to identify variables most predictive of each class, as well as to assess the independent importance of clinical, and imaging features.

RESULTS

Binary classification models achieved a top accuracy of 80.6%, with predictive features included smoking history, age, lesion size, and lesion location. Multiclass classification models achieved a top weighted average f1-score of 0.73. Features predictive of primary cancer included smoking history, race, and age, while features predictive of secondary cancer included lesion location, and a history of cancer.

CONCLUSION

Machine learning models enable classification of suspicious thoracic lesions based on clinical and imaging variables, achieving clinically useful performance while identifying importance of individual input features on a pathology-proven dataset. We believe models such as these are more likely to be trusted and adopted by clinicians.

Evaluation of exosomal non-coding RNAs in cancer using high-throughput sequencing

Clinical oncologists need more reliable and non-invasive diagnostic and prognostic biomarkers to follow-up cancer patients. However, the existing biomarkers are often invasive and costly, emphasizing the need for the development of biomarkers to provide convenient and precise detection. Extracellular vesicles especially exosomes have recently been the focus of translational research to develop non-invasive and reliable biomarkers for several diseases such as cancers, suggesting as a valuable source of tumor markers. Exosomes are nano-sized extracellular vesicles secreted by various living cells that can be found in all body fluids including serum, urine, saliva, cerebrospinal fluid, and ascites. Different molecular and genetic contents of their origin such as nucleic acids, proteins, lipids, and glycans in a stable form make exosomes a promising approach for various cancers' diagnoses, prediction, and follow-up in a minimally invasive manner. Since exosomes are used by cancer cells for intercellular communication, they play a critical role in the disease process, highlighting the importance of their use as clinically relevant biomarkers. However, regardless of the advantages that exosome-based diagnostics have, they suffer from problems regarding their isolation, detection, and characterization of their contents. This study reviews the history and biogenesis of exosomes and discusses non-coding RNAs (ncRNAs) and their potential as tumor markers in different types of cancer, with a focus on next generation sequencing (NGS) as a detection method. Moreover, the advantages and challenges associated with exosome-based diagnostics are also presented.

Percepta Genomic Sequencing Classifier and decision-making in patients with high-risk lung nodules: a decision impact study

BACKGROUND

Incidental and screening-identified lung nodules are common, and a bronchoscopic evaluation is frequently nondiagnostic. The Percepta Genomic Sequencing Classifier (GSC) is a genomic classifier developed in current and former smokers which can be used for further risk stratification in these patients. Percepta GSC has the capability of up-classifying patients with a pre-bronchoscopy risk that is high (> 60%) to "very high risk" with a positive predictive value of 91.5%. This prospective, randomized decision impact survey was designed to test the hypothesis that an up-classification of risk of malignancy from high to very high will increase the rate of referral for surgical or ablative therapy without additional intervening procedures while increasing physician confidence.

METHODS

Data were collected from 37 cases from the Percepta GSC validation cohort in which the pre-bronchoscopy risk of malignancy was high (> 60%), the bronchoscopy was nondiagnostic, and the patient was up-classified to very high risk by Percepta GSC. The cases were randomly presented to U.S pulmonologists in three formats: a pre-post cohort where each case is presented initially without and then with a GSG result, and two independent cohorts where each case is presented either with or without with a GSC result. Physicians were surveyed with respect to subsequent management steps and confidence in that decision.

RESULTS

One hundred and one survey takers provided a total of 1341 evaluations of the 37 patient cases across the three different cohorts. The rate of recommendation for surgical resection was significantly higher in the independent cohort with a GSC result compared to the independent cohort without a GSC result (45% vs. 17%, p < 0.001) In the pre-post cross-over cohort, the rate increased from 17 to 56% (p < 0.001) following the review of the GSC result. A GSC up-classification from high to very high risk of malignancy increased Pulmonologists' confidence in decision-making following a nondiagnostic bronchoscopy.

CONCLUSIONS

Use of the Percepta GSC classifier will allow more patients with early lung cancer to proceed more rapidly to potentially curative therapy while decreasing unnecessary intervening diagnostic procedures following a nondiagnostic bronchoscopy.

Blood-based liquid biopsy: Insights into early detection and clinical management of lung cancer

Currently, early detection of lung cancer relies on the characterisation of images generated from computed tomography (CT). However, lung tissue biopsy, a highly invasive surgical procedure, is required to confirm CT-derived diagnostic results with very high false-positive rates. Hence, a non-invasive or minimally invasive biomarkers is essential to complement the existing low-dose CT (LDCT) for early detection, improve responses to a certain treatment, predict cancer recurrence, and to evaluate prognosis. In the past decade, liquid biopsies (e.g., blood) have been demonstrated to be highly effective for lung cancer biomarker discovery. In this review, the roles of emerging liquid biopsy-derived biomarkers such as circulating nucleic acids, circulating tumour cells (CTCs), long non-coding RNA (lncRNA), and microRNA (miRNA), as well as exosomes, have been highlighted. The advantages and limitations of these blood-based minimally invasive biomarkers have been discussed. Furthermore, the current progress of the identified biomarkers for clinical management of lung cancer has been summarised. Finally, a potential strategy for the early detection of lung cancer, using a combination of LDCT scans and well-validated biomarkers, has been discussed.

Integrated Biomarkers for the Management of Indeterminate Pulmonary Nodules

Rationale: Patients with indeterminate pulmonary nodules (IPNs) at risk of cancer undergo high rates of invasive, costly, and morbid procedures. Objectives: To train and externally validate a risk prediction model that combined clinical, blood, and imaging biomarkers to improve the noninvasive management of IPNs. Methods: In this prospectively collected, retrospective blinded evaluation study, probability of cancer was calculated for 456 patient nodules using the Mayo Clinic model, and patients were categorized into low-, intermediate-, and high-risk groups. A combined biomarker model (CBM) including clinical variables, serum high sensitivity CYFRA 21-1 level, and a radiomic signature was trained in cohort 1 (n = 170) and validated in cohorts 2-4 (total n = 286). All patients were pooled to recalibrate the model for clinical implementation. The clinical utility of the CBM compared with current clinical care was evaluated in 2 cohorts. Measurements and Main Results: The CBM provided improved diagnostic accuracy over the Mayo Clinic model with an improvement in area under the curve of 0.124 (95% bootstrap confidence interval, 0.091-0.156; P < 2 × 10-16). Applying 10% and 70% risk thresholds resulted in a bias-corrected clinical reclassification index for cases and control subjects of 0.15 and 0.12, respectively. A clinical utility analysis of patient medical records estimated that a CBM-guided strategy would have reduced invasive procedures from 62.9% to 50.6% in the intermediate-risk benign population and shortened the median time to diagnosis of cancer from 60 to 21 days in intermediate-risk cancers. Conclusions: Integration of clinical, blood, and image biomarkers improves noninvasive diagnosis of patients with IPNs, potentially reducing the rate of unnecessary invasive procedures while shortening the time to diagnosis.

A Low-Dose CT-Based Radiomic Model to Improve Characterization and Screening Recall Intervals of Indeterminate Prevalent Pulmonary Nodules

Lung cancer (LC) is currently one of the main causes of cancer-related deaths worldwide. Low-dose computed tomography (LDCT) of the chest has been proven effective in secondary prevention (i.e., early detection) of LC by several trials. In this work, we investigated the potential impact of radiomics on indeterminate prevalent pulmonary nodule (PN) characterization and risk stratification in subjects undergoing LDCT-based LC screening. As a proof-of-concept for radiomic analyses, the first aim of our study was to assess whether indeterminate PNs could be automatically classified by an LDCT radiomic classifier as solid or sub-solid (first-level classification), and in particular for sub-solid lesions, as non-solid versus part-solid (second-level classification). The second aim of the study was to assess whether an LCDT radiomic classifier could automatically predict PN risk of malignancy, and thus optimize LDCT recall timing in screening programs. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, positive predictive value, negative predictive value, sensitivity, and specificity. The experimental results showed that an LDCT radiomic machine learning classifier can achieve excellent performance for characterization of screen-detected PNs (mean AUC of 0.89 ± 0.02 and 0.80 ± 0.18 on the blinded test dataset for the first-level and second-level classifiers, respectively), providing quantitative information to support clinical management. Our study showed that a radiomic classifier could be used to optimize LDCT recall for indeterminate PNs. According to the performance of such a classifier on the blinded test dataset, within the first 6 months, 46% of the malignant PNs and 38% of the benign ones were identified, improving early detection of LC by doubling the current detection rate of malignant nodules from 23% to 46% at a low cost of false positives. In conclusion, we showed the high potential of LDCT-based radiomics for improving the characterization and optimizing screening recall intervals of indeterminate PNs.

Flexible Bronchoscopy Biopsy Tools and Techniques to Optimize Diagnostic Yield: A Contemporary Review

Background:

Flexible bronchoscopy is essential in diagnosing many pathologic conditions, and tools such as lavage and biopsies using brushes, forceps, and needles are paramount to success.

Introduction:

Bronchoscopists worldwide are routinely confronted with questions about such tools regarding the type, size, utility, costs, safety, anticipated yield, and others. Does the underlying suspected condition matter to the choice of instruments used? What is the anticipated outcome for benign versus malignant diseases? These and other questions are raised daily by bronchoscopists.

Methods:

Pubmed was reviewed for research in the English language pertaining to diagnostic bronchoscopy. The literature is conflicting on the benefits of the types of tools available. The success of brush biopsies, forceps, and transbronchial needle aspiration is only partially dependent on the size of the instrument used or its other characteristics. Multiple biopsies are needed, and different approaches may be complementary in some circumstances.

Results:

By understanding the factors that involve in a biopsy, the bronchoscopist is more likely to be successful when a crucial diagnosis is mandatory.

Conclusion:

This review aims to be a reference to bronchoscopists everywhere as they contemplate their approach to flexible diagnostic bronchoscopy.

Percutaneous Lung Biopsy with Pleural and Parenchymal Blood Patching: Results and Complications from 1,112 Core Biopsies

PURPOSE

To evaluate the outcomes of computed tomography (CT) fluoroscopy-guided core lung biopsies with emphasis on diagnostic yield, complications, and efficacy of parenchymal and pleural blood patching to avoid chest tube placement.

METHODS

This is a single-center retrospective analysis of CT fluoroscopy-guided percutaneous core lung biopsies between 2006 and 2020. Parenchymal blood patching during introducer needle withdrawal was performed in 74% of cases as a preventive measure, and pleural blood patching was the primary salvage maneuver for symptomatic or growing pneumothorax in 60 of 83 (72.2%) applicable cases.

RESULTS

A total of 1,029 patients underwent 1,112 biopsies (532 men; mean age, 66 years; 38.6%, history of emphysema; lesion size, 16.7 mm). The diagnostic yield was 93.6% (1,032/1,103). Fewer complications requiring intervention were observed in patients who underwent parenchymal blood patching (5.7% vs 14.2%, P < .001). Further intervention was required in 83 of 182 pneumothorax cases, which included the following: (a) pleural blood patch (5.4%, 60/1,112), (b) chest tube placement without a pleural blood patch attempt (1.5%, 17/1,112), and (c) simple aspiration (0.5%, 6/1,112). Pleural blood patch as monotherapy was successful in 83.3% (50/60) of cases without need for further intervention. The overall chest tube rate was 2.6% (29/1,112). Emphysema was the only significant risk factor for complications requiring intervention (P ≤ .001).

CONCLUSIONS

Parenchymal blood patching during introducer needle withdrawal decreased complications requiring intervention. Salvage pleural blood patching reduced the frequency of chest tube placement for pneumothorax.

Risk stratification of indeterminate pulmonary nodules

PURPOSE OF REVIEW

Lung cancer remains the leading cause of cancer-related death in the United States, with poor overall 5-year survival. Early detection and diagnosis are key to survival as demonstrated in lung cancer screening trials. However, with increasing implementation of screening guidelines and use of computed tomography, there has been a sharp rise in the incidence of indeterminate pulmonary nodules (IPNs). Risk stratification of IPNs, particularly those in the intermediate-risk category, remains challenging in clinical practice. Individual risk factors, imaging characteristics, biomarkers, and prediction models are currently used to assist in risk stratifying patients, but such strategies remain suboptimal. This review focuses on established risk stratification methods, current areas of research, and future directions.

RECENT FINDINGS

The multitude of yearly incidental and screening-detected IPNs, its management-related healthcare costs, and risk of invasive procedures provides a strong rationale for risk stratification efforts. The development of new molecular and imaging biomarkers to discriminate benign from malignant lung nodules shows great promise. Yet, risk stratification methods need integration into the diagnostic workflow and await validation in prospective, biomarker-driven clinical trials.

SUMMARY

Novel biomarkers and new imaging analysis, including radiomics and deep-learning methods, have been developed to optimize the risk stratification of IPNs. While promising, additional validation and clinical studies are needed before they can be part of routine clinical practice.

A circulating tumor cell-based digital assay for the detection of EGFR T790M mutation in advanced non-small cell lung cancer

Determining the status of epidermal growth factor receptor (EGFR) T790M mutation is crucial for guiding further treatment intervention in advanced non-small cell lung cancer (NSCLC) patients who develop acquired resistance to initial EGFR tyrosine kinase inhibitor (TKI) treatment. Circulating tumor cells (CTCs) which contain plentiful copies of well-preserved RNA offer an ideal source for noninvasive detection of T790M mutation in NSCLC. We developed a CTC-based digital assay which synergistically integrates NanoVelcro Chips for enriching NSCLC CTCs and reverse-transcription droplet digital PCR (RT-ddPCR) for quantifying T790M transcripts in the enriched CTCs. We collected 46 peripheral arterial and venous blood samples from 27 advanced NSCLC patients for testing this CTC-based digital assay. The results showed that the T790M mutational status observed by the CTC-based digital assay matched with those observed by tissue-based diagnostic methods. Furthermore, higher copy numbers of T790M transcripts were observed in peripheral arterial blood than those detected in the matched peripheral venous blood. In short, our results demonstrated the potential of the NanoVelcro CTC-digital assay for noninvasive detection of the T790M mutation in NSCLC, and suggested that peripheral arterial blood sampling may offer a more abundant CTC source than peripheral venous blood in advanced NSCLC patients.

Exosome-based liquid biopsies in cancer: opportunities and challenges

Liquid biopsy in cancer has gained momentum in clinical research and is experiencing a boom for a variety of applications. There are significant efforts to utilize liquid biopsies in cancer for early detection and treatment stratification, as well as residual disease and recurrence monitoring. Although most efforts have used circulating tumor cells and circulating tumor DNA for this purpose, exosomes and other extracellular vesicles have emerged as a platform with potentially broader and complementary applications. Exosomes/extracellular vesicles are small vesicles released by cells, including cancer cells, into the surrounding biofluids. These exosomes contain tumor-derived materials such as DNA, RNA, protein, lipid, sugar structures, and metabolites. In addition, exosomes carry molecules on their surface that provides clues regarding their origin, making it possible to sort vesicle types and enrich signatures from tissue-specific origins. Exosomes are part of the intercellular communication system and cancer cells frequently use them as biological messengers to benefit their growth. Since exosomes are part of the disease process, they have become of tremendous interest in biomarker research. Exosomes are remarkably stable in biofluids, such as plasma and urine, and can be isolated for clinical evaluation even in the early stages of the disease. Exosome-based biomarkers have quickly become adopted in the clinical arena and the first exosome RNA-based prostate cancer test has already helped >50 000 patients in their decision process and is now included in the National Comprehensive Cancer Network guidelines for early prostate cancer detection. This review will discuss the advantages and challenges of exosome-based liquid biopsies for tumor biomarkers and clinical implementation in the context of circulating tumor DNA and circulating tumor cells.

Costs of Biopsy and Complications in Patients with Lung Cancer

Purpose

To describe the distribution of diagnostic procedures, rates of complications, and total cost of biopsies for patients with lung cancer.

Patients and Methods

Observational study using data from IBM Marketscan^® Databases for continuously insured adult patients with a primary lung cancer diagnosis and treatment between July 2013 and June 2017. Costs of lung cancer diagnosis covered 6 months prior to index biopsy through treatment. Costs of chest CT scans, biopsy, and post-procedural complications were estimated from total payments. Costs of biopsies incidental to inpatient admissions were estimated by comparable outpatient biopsies.

Results

The database included 22,870 patients who had a total of 37,160 biopsies, of which 16,009 (43.1%) were percutaneous, 14,997 (40.4%) bronchoscopic, 4072 (11.0%) surgical and 2082 (5.6%) mediastinoscopic. Multiple biopsies were performed on 41.9% of patients. The most common complications among patients receiving only one type of biopsy were pneumothorax (1304 patients, 8.4%), bleeding (744 patients, 4.8%) and intubation (400 patients, 2.6%). However, most complications did not require interventions that would add to costs. Median total costs were highest for inpatient surgical biopsies ($29,988) and lowest for outpatient percutaneous biopsies ($1028). Repeat biopsies of the same type increased costs by 40–80%. Complications account for 13% of total costs.

Conclusion

Costs of biopsies to confirm lung cancer diagnosis vary substantially by type of biopsy and setting. Multiple biopsies, inpatient procedures and complications result in higher costs.

Efficacy of Tract Embolization After Percutaneous Pulmonary Radiofrequency Ablation

PURPOSE

To evaluate the efficacy of tract embolization technique using gelatin sponge slurry with iodinated contrast medium (GSSI) to reduce the incidence of pneumothorax and chest tube placement after computed tomography-guided lung radiofrequency ablation (RFA).

MATERIALS AND METHODS

In this single-institute retrospective study, we examined all patients with metastatic cancer treated from January 2016 to December 2019 by interventional radiologists with computed tomography-guided lung RFA. Since 2017 in our institution, we have applied a tract embolization technique using GSSI for all RFA. Patients were included into those who underwent lung RFA performed either with GSSI (Group A) or without GSSI (Group B). Univariate and multivariate analyses were performed between the two groups to identify risk factors for pneumothorax and chest tube placement, including patient demographics and lesion characteristics.

RESULTS

This study included 116 patients (54 men, 62 women; mean age, 65 ± 11 years) who underwent RFA. Group A comprised 71 patients and Group B comprised 45 patients. Patients who underwent tract embolization had a significantly lower incidence of pneumothorax (Group A, 34% vs. Group B, 62%; p < 0.001) and chest tube insertion (Group A, 10% vs. Group B, 29%; p < 0.01). No embolic complications occurred. The hospitalization stay was significantly shorter in patients who underwent tract embolization (mean, 1.04 ± 0.2 days; p = 0.02).

CONCLUSION

Tract embolization after percutaneous lung RFA significantly reduced the rate of post-RFA pneumothorax and chest tube placement and was safer than the standard lung RFA technique.

Patient out-of-pocket costs for suspicious pulmonary nodule biopsy in lung cancer patients

AIMS

Dynamic changes in the payer landscape have resulted in increasing out-of-pocket costs (OOPCs). Little is known about OOPC for patients undergoing biopsy for suspicious pulmonary nodules in the United States. This study seeks to describe the spectrum of OOPC for diagnostic tissue sampling for suspicious pulmonary nodule with an ultimate diagnosis of lung cancer.

METHODS

Retrospective cohort study of adult patients with a primary lung cancer diagnosis and treatment who underwent diagnostic biopsy for suspicious pulmonary nodule utilizing IBM Marketscan Databases (2013-2017). Claims data included both total hospital and physician billed costs, insurer reimbursement and OOPC. OOPCs were further stratified by type of biopsy, whether the patient underwent a single or multiple biopsies, and year of biopsy.

RESULTS

A total of 22,870 patients aged 18-95 who underwent diagnostic lung biopsy were identified. The gender ratio was 49:51 for female:male and 50% of patients were aged 65 or above. 78% of patients had a co-morbidity. The median OOPC for a patient receiving a single biopsy (any type) was $600, two biopsies: $706, three biopsies: $811, and four biopsies: $1,177. By biopsy type, the median OOPC for a patient requiring a single biopsy was $604 for percutaneous biopsy, $316 for surgical biopsy, $674 for bronchoscopic biopsy, and $545 for mediastinoscopic biopsy.

LIMITATIONS

Under-estimation of OOP expenses from costs of transportation, job loss, and loss of productivity. Over-estimation of OOPC from lack of individual claims adjudication.

CONCLUSIONS

The median OOPC for lung cancer patient requiring a single diagnostic lung biopsy is $600. Prior research indicates that almost 50% of the lung cancer patient population undergoes multiple biopsies increasing costs anywhere between 20% and 100% resulting in further patient financial burden for each episodic biopsy attempt. Further cost-effectiveness research is needed to differentiate various diagnostic technologies for lung biopsy.

A Blood-based Assay for Assessment of Tumor Mutational Burden in First-line Metastatic NSCLC Treatment: Results from the MYSTIC Study

PURPOSE

Tumor mutational burden (TMB) has been shown to be predictive of survival benefit in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors. Measuring TMB in the blood (bTMB) using circulating cell-free tumor DNA (ctDNA) offers practical advantages compared with TMB measurement in tissue (tTMB); however, there is a need for validated assays and identification of optimal cutoffs. We describe the analytic validation of a new bTMB algorithm and its clinical utility using data from the phase III MYSTIC trial.

PATIENTS AND METHODS

The dataset used for the clinical validation was from MYSTIC, which evaluated first-line durvalumab (anti-PD-L1 antibody) ± tremelimumab (anticytotoxic T-lymphocyte-associated antigen-4 antibody) or chemotherapy for metastatic NSCLC. bTMB and tTMB were evaluated using the GuardantOMNI and FoundationOne CDx assays, respectively. A Cox proportional hazards model and minimal P value cross-validation approach were used to identify the optimal bTMB cutoff.

RESULTS

In MYSTIC, somatic mutations could be detected in ctDNA extracted from plasma samples in a majority of patients, allowing subsequent calculation of bTMB. The success rate for obtaining valid TMB scores was higher for bTMB (809/1,001; 81%) than for tTMB (460/735; 63%). Minimal P value cross-validation analysis confirmed the selection of bTMB ≥20 mutations per megabase (mut/Mb) as the optimal cutoff for clinical benefit with durvalumab + tremelimumab.

CONCLUSIONS

Our study demonstrates the feasibility, accuracy, and reproducibility of the GuardantOMNI ctDNA platform for quantifying bTMB from plasma samples. Using the new bTMB algorithm and an optimal bTMB cutoff of ≥20 mut/Mb, high bTMB was predictive of clinical benefit with durvalumab + tremelimumab versus chemotherapy.

Implementing ctDNA Analysis in the Clinic: Challenges and Opportunities in Non-Small Cell Lung Cancer

Tumor genomic profiling has a dramatic impact on the selection of targeted treatment and for the identification of resistance mechanisms at the time of progression. Solid tissue biopsies are sometimes challenging, and liquid biopsies are used as a non-invasive alternative when tissue is limiting. The clinical relevance of tumor genotyping through analysis of ctDNA is now widely recognized at all steps of the clinical evaluation process in metastatic non-small cell lung cancer (NSCLC) patients. ctDNA analysis through liquid biopsy has recently gained increasing attention as well in the management of early and locally advanced, not oncogene-addicted, NSCLC. Its potential applications in early disease detection and the response evaluation to radical treatments are promising. The aim of this review is to summarize the landscape of liquid biopsies in clinical practice and also to provide an overview of the potential perspectives of development focusing on early detection and screening, the assessment of minimal residual disease, and its potential role in predicting response to immunotherapy. In addition to available studies demonstrating the clinical relevance of liquid biopsies, there is a need for standardization and well-designed clinical trials to demonstrate its clinical utility.

Generic Protocols for the Analytical Validation of Next-Generation Sequencing-Based ctDNA Assays: A Joint Consensus Recommendation of the BloodPAC's Analytical Variables Working Group

Liquid biopsy, particularly the analysis of circulating tumor DNA (ctDNA), has demonstrated considerable promise for numerous clinical intended uses. Successful validation and commercialization of novel ctDNA tests have the potential to improve the outcomes of patients with cancer. The goal of the Blood Profiling Atlas Consortium (BloodPAC) is to accelerate the development and validation of liquid biopsy assays that will be introduced into the clinic. To accomplish this goal, the BloodPAC conducts research in the following areas: Data Collection and Analysis within the BloodPAC Data Commons; Preanalytical Variables; Analytical Variables; Patient Context Variables; and Reimbursement. In this document, the BloodPAC's Analytical Variables Working Group (AV WG) attempts to define a set of generic analytical validation protocols tailored for ctDNA-based Next-Generation Sequencing (NGS) assays. Analytical validation of ctDNA assays poses several unique challenges that primarily arise from the fact that very few tumor-derived DNA molecules may be present in circulation relative to the amount of nontumor-derived cell-free DNA (cfDNA). These challenges include the exquisite level of sensitivity and specificity needed to detect ctDNA, the potential for false negatives in detecting these rare molecules, and the increased reliance on contrived samples to attain sufficient ctDNA for analytical validation. By addressing these unique challenges, the BloodPAC hopes to expedite sponsors' presubmission discussions with the Food and Drug Administration (FDA) with the protocols presented herein. By sharing best practices with the broader community, this work may also save the time and capacity of FDA reviewers through increased efficiency.

Identification of circulating tumor cells using 4-color fluorescence in situ hybridization: Validation of a noninvasive aid for ruling out lung cancer in patients with low-dose computed tomography-detected lung nodules

BACKGROUND

Approximately one third of needle biopsies that are performed to rule out malignancy of indeterminate pulmonary nodules detected radiologically during lung cancer screening are negative, thus exposing cancer-free patients to risks of pneumothorax, bleeding, and infection. A noninvasive confirmatory tool (eg, liquid biopsy) is urgently needed in the lung cancer diagnosis setting to stratify patients who should receive biopsy versus those who should be monitored.

METHODS

A novel antigen-independent, 4-color fluorescence in situ hybridization (FISH)-based method was developed to detect circulating tumor cells (CTCs) with abnormalities in gene copy numbers in mononuclear cell-enriched peripheral blood samples from patients with (n = 107) and without (n = 100) lung cancer.

RESULTS

Identification of CTCs using FISH probes at 10q22.3/CEP10 and 3p22.1/3q29 detected lung cancer cases with 94.2% accuracy, 89% sensitivity, and 100% specificity compared with biopsy.

CONCLUSION

The high accuracy of this liquid biopsy method suggests that it may be used as a noninvasive decision tool to reduce the frequency of unnecessary needle biopsy in patients with benign pulmonary lesions.

Noninvasive biomarkers for lung cancer diagnosis, where do we stand?

The 2010's saw demonstration of the power of lung cancer screening to reduce mortality. However, with implementation of lung cancer screening comes the challenge of diagnosing millions of lung nodules every year. When compared to other cancers with widespread screening strategies (breast, colorectal, cervical, prostate, and skin), obtaining a lung nodule tissue biopsy to confirm a positive screening test remains associated with higher morbidity and cost. Therefore, non-invasive diagnostic biomarkers may have a unique opportunity in lung cancer to greatly improve the management of patients at risk. This review covers recent advances in the field of liquid biomarkers and computed tomographic imaging features, with special attention to new methods for combination of biomarkers as well as the use of artificial intelligence for the discrimination of benign from malignant nodules.

Efficacy of the tract embolization technique with gelatin sponge slurry to reduce pneumothorax and chest tube placement after percutaneous CT-guided lung biopsy

PURPOSE

To assess the efficacy of the tract embolization technique using gelatin sponge slurry after CT-guided lung biopsy to reduce pneumothorax and chest tube placement rates.

MATERIALS AND METHODS

We retrospectively compared 231 CT-guided lung biopsies performed with the tract embolization technique using gelatin sponge slurry (treated group) with 213 biopsies performed without embolization (control group). All procedures were performed at our institution between January 2014 and September 2018 by one of three experienced interventional radiologists using a 19-gauge coaxial needle. Multivariate analysis was performed between groups for risk factors for pneumothorax and chest tube placement, including patient demographics and lesion characteristics.

RESULTS

When comparing the two groups, there was no significant difference concerning age, gender, emphysema, lesion size, lesion location, lesion morphology, needle tract depth and biopsy-side down patient positioning. Compared to the control group, patients with gelatin sponge slurry tract embolization had statistically lower rates of pneumothorax (10% vs. 25.8%; p < 0.0001) and chest tube placement (3.5% vs. 12.2%; p = 0.0005). Using multiple logistic regression analysis, the only variable that had an influence on the pneumothorax rate was the group (OR 0.32, 95% CI 0.18-0.56, p < 0.0001), and the variables that had an influence on the chest tube insertion rates were the group (OR 0.21, 95% CI 0.08-0.51, p = 0.0006) and presence of emphysema (OR 3.50, 95% CI 1.53-8.03, p = 0.0031).

CONCLUSIONS

Tract embolization technique using gelatin sponge slurry after percutaneous CT-guided lung biopsy significantly reduces pneumothorax and chest tube placement rates.

LEVEL OF EVIDENCE

Level 3a.

Blood-Based Next-Generation Sequencing Analysis of Appendiceal Cancers

BACKGROUND

Appendiceal cancers (ACs) are rare. The genomic landscape of ACs has not been well studied. The aim of this study was to confirm the feasibility of next-generation sequencing (NGS) using circulating tumor DNA (ctDNA) in ACs and characterize common genomic alterations.

MATERIALS AND METHODS

Molecular alterations in 372 plasma samples from 303 patients with AC using clinical-grade NGS of ctDNA (Guardant360) across multiple institutions were evaluated. Test detects single nucleotide variants in 54-73 genes, copy number amplifications, fusions, and indels in selected genes.

RESULTS

A total of 303 patients with AC were evaluated, of which 169 (56%) were female. Median age was 56.8 (25-83) years. ctDNA NGS testing was performed on 372 plasma samples; 48 patients had testing performed twice, 9 patients had testing performed three times, and 1 patient had testing performed four times. Genomic alterations were defined in 207 (n = 207/372, 55.6%) samples, and 288 alterations were identified excluding variants of uncertain significance and synonymous mutations. Alterations were identified in at least one sample from 184 patients; TP53-associated genes (n = 71, 38.6%), KRAS (n = 33, 17.9%), APC (n = 14, 7.6%), EGFR (n = 12, 6.5%), BRAF (n = 11, 5.9%), NF1 (n = 10, 5.4%), MYC (n = 9, 4.9%), GNAS (n = 8, 4.3%), MET (n = 6, 3.3%), PIK3CA (n = 5, 2.7%), and ATM (n = 5, 2.7%). Other low-frequency but clinically relevant genomic alterations were as follows: AR (n = 4, 2.2%), TERT (n = 4, 2.2%), ERBB2 (n = 4, 2.2%), SMAD4 (n = 3, 1.6%), CDK4 (n = 2, 1.1%), NRAS (n = 2, 1.1%), FGFR1 (n = 2, 1.1%), FGFR2 (n = 2, 1.1%), PTEN (n = 2, 1.1%), RB1 (n = 2, 1.1%), and CDK6, CDKN2A, BRCA1, BRCA2, JAK2, IDH2, MAPK, NTRK1, CDH1, ARID1A, and PDGFRA (n = 1, 0.5%).

CONCLUSION

Evaluation of ctDNA is feasible among patients with AC. The frequency of genomic alterations is similar to that previously reported in tissue NGS. Liquid biopsies are not invasive and can provide personalized options for targeted therapies in patients with AC.

IMPLICATIONS FOR PRACTICE

The complexity of appendiceal cancer and its unique genomic characteristics suggest that customized combination therapy may be required for many patients. Theoretically, as more oncogenic pathways are discovered and more targeted therapies are approved, customized treatment based on the patient's unique molecular profile will lead to personalized care and improve patient outcomes. Liquid biopsies are noninvasive, cost-effective, and promising methods that provide patients with access to personalized treatment.

Healthcare resource utilization and associated cost analysis of the PROCLAIM study in patients with stage III non-small-cell lung cancer

Objective: To analyze patient-reported swallowing difficulties, healthcare resource utilization and associated costs during the PROCLAIM study. Methods: Patients with stage III non-squamous non-small cell lung cancer received pemetrexed-cisplatin (PemCis) combined with concurrent thoracic radiotherapy followed by consolidation pemetrexed, or concurrent chemoradiotherapy with etoposide-cisplatin (EtoCis) followed by standard consolidation chemotherapy. Patient - reported swallowing function was measured using diaries. Resource utilization (hospitalizations, transfusions, concomitant medications) was compared between treatment arms using Fisher's exact test and independent t-test. Medical resource use costs were analyzed using nonparametric Wilcoxon rank sum test. Results: Patient-reported difficulty in swallowing function (diary score ≥4) was 33.8% in the PemCis arm and 29% in the EtoCis arm. Overall resource use, including hospitalizations, was similar between treatment arms; however, fewer patients in the PemCis arm received transfusions and selected concomitant medications. Concurrent phase analyses were consistent with the overall study. A significantly lower percentage of patients (31.1% vs. 40.8%) were hospitalized in the PemCis arm. Total costs were significantly higher in the PemCis arm. Other medical costs (excluding study treatment costs) during the concurrent phase were lower for patients in the PemCis arm, due to significantly lower hospitalization costs and lower use of concomitant medications. Subgroup analysis yielded similar results. Conclusions: Patient-reported difficulty in swallowing post-baseline and resource utilization were consistent with previously reported safety outcomes. In the overall study, higher total costs for PemCis were driven by study drug cost. When adjusting for treatment duration, other monthly medical costs were favorable to PemCis. Patients on pemetrexed remained longer on therapy, suggesting better tolerability. ClinicalTrials.gov identifier: NCT00686959.

Complications and Economic Burden Associated With Obtaining Tissue for Diagnosis and Molecular Analysis in Patients With Non-Small-Cell Lung Cancer in the United States

PURPOSE

With an increase in biomarker-directed therapies, tissue biopsy to identify targetable genomic and immunologic alterations has become the mainstay of managing patients with non-small-cell lung cancer (NSCLC); however, little is known about the associated economic impact and complication rate. This study assesses the frequency, complications, and costs of diagnostic and postprogression biopsy.

METHODS

This retrospective, observational study was conducted using administrative claims data from more than 30 million commercially insured individuals in the United States (2006 to 2014). Data were analyzed for the overall population and by time of biopsy (diagnostic or postprogression biopsy).

RESULTS

Of 20,013 eligible patients, 13,411 (67%) received a diagnostic biopsy, whereas only 2,056 (10%) received a postprogression biopsy (mean cost, $9,977 and $16,806, respectively). Complication rates were similar at diagnosis and after progression, on the day of biopsy (10% v 7%, respectively) and within 30 days (63% v 61%, respectively). Mean costs were higher among patients with a complication compared with those without a complication on the day of biopsy (diagnostic biopsy, $12,030 v $6,508, respectively; postprogression biopsy, $22,593 v $7,812, respectively), within 7 days of biopsy (diagnostic biopsy, $13,657 v $7,765, respectively; postprogression biopsy, $23,969 v $8,932, respectively), and within 30 days of biopsy (diagnostic biopsy, $24,968 v $15,988, respectively; postprogression biopsy, $30,293 v $12,494, respectively; P < .001 for all comparisons).

CONCLUSION

From 2006 to 2014, postprogression biopsies were not common practice in NSCLC. Complication rates were similar at diagnosis and after progression, with mean costs higher among patients with a complication than those without a complication. With increasing demands for effective novel targeted therapies and safe testing methods, these data may be valuable in determining the budget impact and comparing complication rates with newer, less invasive molecular testing methods, including plasma circulating tumor DNA testing.

Molecular testing strategies in non-small cell lung cancer: optimizing the diagnostic journey

Molecular testing identifies patients with advanced non-small cell lung cancer (NSCLC) who may benefit from targeted therapy or immunotherapy (i.e., immune checkpoint inhibitor treatment for patients with high tumor mutational burden (TMB), microsatellite instability-high or mismatch repair-deficient tumors). Current guidelines state that molecular testing should be conducted at the time of initial diagnosis and tumor progression on targeted therapy. In real-world clinical practice in the United States (US), molecular testing is often not conducted or happens late in the diagnostic journey, resulting in delayed or inappropriate treatment. Herein, we review the rationale for molecular testing in advanced NSCLC, along with best-practice guidelines based on published recommendations and our own clinical experience, including a case study. We propose three strategies to optimize molecular testing in newly diagnosed patients with advanced NSCLC: (I) pulmonologists, interventional radiologists, or thoracic surgeons order molecular tests as soon as advanced NSCLC with an adenocarcinoma component is suspected; (II) liquid biopsies conducted early in the diagnostic pathway; and (III) pathologist-directed reflex testing, as conducted in other areas of oncology. To help facilitate these strategies, we outline our recommendations for optimal sample collection techniques and stewardship. In summary, we believe that implementation of these individual strategies will allow clinicians to effectively leverage available treatment options for advanced NSCLC, reducing the time to optimal treatment and improving patient outcomes.

Prospective Clinical Validation of the InVisionFirst-Lung Circulating Tumor DNA Assay for Molecular Profiling of Patients With Advanced Nonsquamous Non-Small-Cell Lung Cancer

PURPOSE

Guidelines advocate molecular profiling in the evaluation of advanced non-small-cell lung cancer (NSCLC) and support the use of plasma circulating tumor DNA (ctDNA)-based profiling for patients with insufficient tissue. Thorough prospective clinical validation studies of next-generation sequencing (NGS)-based ctDNA assays are lacking. We report the multicentered prospective clinical validation of the InVision ctDNA assay in patients with advanced untreated NSCLC.

METHODS

A total of 264 patients with untreated advanced NSCLC were prospectively recruited, and their plasma was analyzed using a ctDNA NGS assay for detection of genomic alterations in 36 commonly mutated genes. Tumor tissue was available in 178 patients for molecular profiling for comparison with plasma profiling. The remaining 86 patients were included to compare ctDNA profiles in patients with and without tissue for profiling.

RESULTS

Concordance of InVisionFirst with matched tissue profiling was 97.8%, with 82.9% positive predictive value, 98.5% negative predictive value, 70.6% sensitivity, and 99.2% specificity. Considering specific alterations in eight genes that most influence patient management, the positive predictive value was 97.8%, with 97.1% negative predictive value, 73.9% sensitivity, and 99.8% specificity. Across the entire study, 48 patients with actionable alterations were identified by ctDNA testing compared with only 38 by tissue testing. ctDNA NGS reported either an actionable alteration or an alteration generally considered mutually exclusive for such actionable changes in 53% of patients.

CONCLUSION

The liquid biopsy NGS assay demonstrated excellent concordance with tissue profiling in this multicenter, prospective, clinical validation study, with sensitivity and specificity equivalent to Food and Drug Administration-approved single-gene ctDNA assays. The use of plasma-based molecular profiling using NGS led to the detection of 26% more actionable alterations compared with standard-of-care tissue testing in this study.