The effect of surgical treatment on survival from early lung cancer. Implications for screening

Increased Utilization of Low-Dose CT for Lung Cancer Screening at an Arkansas Community Oncology Clinic

BACKGROUND

Low-dose CT (LDCT) is underused in Arkansas for lung cancer screening, a rural state with a high incidence of lung cancer. The objective was to determine whether offering free LDCT increased the number of high-risk individuals screened in a rural catchment area.

METHODS

There were 5,402 patients enrolled in screening at Highlands Oncology, a community oncology clinic in Northwest Arkansas, from 2013 to 2020. Screenings were separated into time periods: period 1 (10 months for-fee), period 2 (10 months free with targeted advertisements and primary care outreach), and period 3 (62 months free with only primary care outreach). In all, 5,035 high-risk participants were eligible for analysis based on National Comprehensive Cancer Network Clinical Practice Guidelines in Oncology. Enrollment rates, incidence densities (IDs), Cox proportional hazard models, and Kaplan-Meier curves were performed to investigate differences between enrollment periods and high-risk groups.

RESULTS

Patient volume increased drastically once screenings were offered free of charge (period 1 = 4.6 versus period 2 = 66.0 and period 3 = 69.8 average patients per month). Incidence density per 1,000 person-years increased through each period (IDPeriod 1 = 17.2; IDPeriod 2 = 20.8; IDPeriod 3 = 25.5 cases). Cox models revealed significant differences in lung cancer risk between high-risk groups (P = .012) but not enrollment periods (P = .19). Kaplan-Meier lung cancer-free probabilities differed significantly between high-risk groups (log-rank P = .00068) but not enrollment periods (log-rank P = .18).

CONCLUSIONS

This study suggests that eligible patients are more receptive to free LDCT screening, despite most insurances not having a required copay for eligible patients.

A 20-year Follow-up of the International Early Lung Cancer Action Program (I-ELCAP)

Background The low-dose CT (≤3 mGy) screening report of 1000 Early Lung Cancer Action Program (ELCAP) participants in 1999 led to the International ELCAP (I-ELCAP) collaboration, which enrolled 31 567 participants in annual low-dose CT screening between 1992 and 2005. In 2006, I-ELCAP investigators reported the 10-year lung cancer-specific survival of 80% for 484 participants diagnosed with a first primary lung cancer through annual screening, with a high frequency of clinical stage I lung cancer (85%). Purpose To update the cure rate by determining the 20-year lung cancer-specific survival of participants diagnosed with first primary lung cancer through annual low-dose CT screening in the expanded I-ELCAP cohort. Materials and Methods For participants enrolled in the HIPAA-compliant prospective I-ELCAP cohort between 1992 and 2022 and observed until December 30, 2022, Kaplan-Meier survival analysis was used to determine the 10- and 20-year lung cancer-specific survival of participants diagnosed with first primary lung cancer through annual low-dose CT screening. Eligible participants were aged at least 40 years and had current or former cigarette use or had never smoked but had been exposed to secondhand tobacco smoke. Results Among 89 404 I-ELCAP participants, 1257 (1.4%) were diagnosed with a first primary lung cancer (684 male, 573 female; median age, 66 years; IQR, 61-72), with a median smoking history of 43.0 pack-years (IQR, 29.0-60.0). Median follow-up duration was 105 months (IQR, 41-182). The frequency of clinical stage I at pretreatment CT was 81% (1017 of 1257). The 10-year lung cancer-specific survival of 1257 participants was 81% (95% CI: 79, 84) and the 20-year lung cancer-specific survival was 81% (95% CI: 78, 83), and it was 95% (95% CI: 91, 98) for 181 participants with pathologic T1aN0M0 lung cancer. Conclusion The 10-year lung cancer-specific survival of 80% reported in 2006 for I-ELCAP participants enrolled in annual low-dose CT screening and diagnosed with a first primary lung cancer has persisted, as shown by the updated 20-year lung cancer-specific survival for the expanded I-ELCAP cohort. © RSNA, 2023 See also the editorials by Grenier and by Sequist and Olazagasti in this issue.

Automatic classification of pulmonary nodules in computed tomography images using pre-trained networks and bag of features

Lung cancer has the highest incidence in the world. The standard tests for its diagnostics are medical imaging exams, sputum cytology, and lung biopsy. Computed Tomography (CT) of the chest plays an essential role in the early detection of nodules since it can allow for more treatment options and increases patient survival. However, the analysis of these exams is a tiring and error-prone process. Thus, computational methods can help the specialist in this analysis. This work addresses the classification of pulmonary nodules as benign or malignant on CT images. Our approach uses the pre-trained VGG16, VGG19, Inception, Resnet50, and Xception, to extract features from each 2D slice of the 3D nodules. Then, we use Principal Component Analysis to reduce the dimensionality of the feature vectors and make them all the same length. Then, we use Bag of Features (BoF) to combine the feature vectors of the different 2D slices and generate only one signature representing the 3D nodule. The classification step uses Random Forest. We evaluated the proposed method with 1,405 segmented nodules from the LIDC-IDRI database and obtained an accuracy of 95.34%, F1-Score of 91.73, kappa of 0.88, sensitivity of 90.53%, specificity of 97.26% and AUC of 0.99. The main conclusion was that the combination by BoF of features extracted from 2D slices using pre-trained architectures produced better results than training 2D and 3D CNNs in the nodules. In addition, the use of BoF also makes the creation of the nodule signature independent of the number of slices.

Lung cancer in the emergency department

Background

Though decreasing in incidence and mortality in the USA, lung cancer remains the deadliest of all cancers. For a significant number of patients, the emergency department (ED) provides the first pivotal step in lung cancer prevention, diagnosis, and management. As screening recommendations and treatments advance, ED providers must stay up-to-date with the latest lung cancer recommendations. The purpose of this review is to identify the many ways that emergency providers may intersect with the disease spectrum of lung cancer and provide an updated array of knowledge regarding detection, management, complications, and interdisciplinary care.

Findings

Lung cancer, encompassing 10-12% of cancer-related emergency department visits and a 66% admission rate, is the most fatal malignancy in both men and women. Most patients presenting to the ED have not seen a primary care provider or undergone screening. Ultimately, half of those with a new lung cancer diagnosis in the ED die within 1 year. Incidental findings on computed tomography are mostly benign, but emergency staff must be aware of the factors that make them high risk. Radiologic presentations range from asymptomatic nodules to diffuse metastatic lesions with predominately pulmonary symptoms, and some may present with extra-thoracic manifestations including neurologic. The short-term prognosis for ED lung cancer patients is worse than that of other malignancies. Screening offers new hope through earlier diagnosis but is underutilized which may be due to racial and socioeconomic disparities. New treatments provide optimism but lead to new complications, some long-term. Multidisciplinary care is essential, and emergency medicine is responsible for the disposition of patients to the appropriate specialists at inpatient and outpatient centers.

Conclusion

ED providers are intimately involved in all aspects of lung cancer care. Risk factor modification and referral for lung cancer screening are opportunities to further enhance patient care. In addition, with the advent of newer cancer therapies, ED providers must stay vigilant and up-to-date with all aspects of lung cancer including disparities, staging, symptoms of disease, prognosis, treatment, and therapy-related complications.

Cost-effectiveness of carbon-ion radiotherapy versus stereotactic body radiotherapy for non-small-cell lung cancer

Carbon-ion radiotherapy (CIRT) for clinical stage I non-small-cell lung cancer (NSCLC) is used as an advanced medical treatment regimen in Japan. Carbon-ion radiotherapy reportedly aids in achieving excellent treatment outcomes, despite its high medical cost. We aimed to compare CIRT with stereotactic body radiotherapy (SBRT) in terms of cost-effectiveness for treating clinical stage I NSCLC. Data of patients with clinical stage I NSCLC treated with CIRT or SBRT at Gunma University between 2010 and 2015 were analyzed. The CIRT and SBRT groups included 62 and 27 patients, respectively. After propensity-score matching, both groups comprised 15 patients. Life year (LY) was used as an indicator of outcome. The CIRT technical fee was 3 140 000 JPY. There was no technical fee for the second CIRT carried out on the same organ within 2 years. The incremental cost-effectiveness ratio (ICER) was calculated by dividing the incremental cost by the incremental LY for 5 years after treatment. Sensitivity analysis was applied to evaluate the impact of LY or costs of each group on ICER. The ICERs were 7 491 017 JPY/LY and 3 708 330 JPY/LY for all patients and matched patients, respectively. Hospitalization and examination costs were significantly higher in the CIRT group, and the impact of the CIRT technical costs was smaller than other costs and LY. Carbon-ion radiotherapy is a cost-effective treatment approach. However, our findings suggest that reducing excessive costs by considering the validity and necessity of examinations and hospitalizations would make CIRT a more cost-effective approach.

The Survival Advantage of Lobectomy over Wedge Resection Lessens as Health-Related Life Expectancy Decreases

Introduction

Patients with early-stage NSCLC typically must choose between a surgery with superior local control (lobectomy) or one that preserves lung parenchyma (wedge). Recognizing that many patients with cancer have competing mortality risks unrelated to cancer, we investigated whether an established model of predicting life expectancy could be used to identify patients with stage I NSCLC for whom survival after wedge is not different from lobectomy.

Methods

A retrospective cohort study using the National Cancer Institute's Surveillance Epidemiology and End Results-Medicare was performed to evaluate survival among treatment-naive patients, diagnosed 2005-2015, who underwent lobectomy or wedge for stage I (≤2 cm tumors) NSCLC. Comorbidity-related life expectancy (CR-LE) was estimated using a standard life-table approach based on comorbid conditions, sex, and age. Cox models and perioperative complications were stratified by 5-year CR-LE.

Results

A total of 4560 patients (median age 74, interquartile range 70-78) were identified. CR-LE was greater than or equal to 5 years for 4016 patients (wedge = 23%). CR-LE was less than 5 years for 544 patients (wedge = 41%). Among patients with CR-LE greater than or equal to 5, wedge resection was associated with higher risk of mortality than lobectomy (hazard ratio: 1.68, 95% confidence interval: 1.52-1.86, p < 0.001). For those with CR-LE less than 5, there was no significant difference in mortality risk between lobectomy and wedge (hazard ratio: 1.19, 95% confidence interval: 0.96-1.47; p = 0.11). CR-LE less than five patients who underwent a lobectomy had higher 90-day mortality compared with wedge (9% versus 4%, p = 0.04).

Conclusion

The survival advantage of lobectomy over wedge for stage I NSCLC seems to dissipate among patients with shorter life expectancy owing to age and comorbidities. Wedge resection may be a reasonable option for patients at high risk of dying from non-cancer-related causes.

Women have a higher resection rate for lung cancer and improved survival after surgery

OBJECTIVES

Surgery is the standard treatment in early-stage non-small-cell lung cancer and select cases of small-cell lung cancer, but gender differences in its use and outcome are poorly known. Gender differences in surgical resection rates and long-term survival after lung cancer surgery were therefore investigated.

METHODS

In Finland, 3524 patients underwent resection for primary lung cancer during 2004-2014. Surgical rate and mortality data were retrospectively retrieved from 3 nationwide compulsory registries. Survival was studied by comparing propensity-matched cohorts. Median follow-up was 8.6 years.

RESULTS

Surgery rate was higher in women (15.9% vs 12.3% in men, P < 0.0001). Overall survival was 85.3% 1 year, 51.4% 5 years, 33.4% 10 years and 24.2% at 14 years from surgery. In matched groups, survival after resection was better in women after 1 year (91.3% vs 83.3%), 5 years (60.2% vs 48.6%), 10 years (43.7% vs 27.9%) and 14 years (29.0% vs 21.1%) after surgery [hazard ratio (HR) 0.66; confidence interval (CI) 0.58-0.75; P < 0.0001]. Of all first-year survivors, 39.1% were alive 10 years and 28.3% 14 years after surgery. Among these matched first-year survivors, women had higher 14-year survival (36.9% vs 25.3%; HR 0.75; CI 0.65-0.87; P = 0.0002).

CONCLUSIONS

Surgery is performed for lung cancer more often in women. Women have more favourable short- and long-term outcome after lung cancer surgery. Gender discrepancy in survival continues to increase beyond the first year after surgery.

The Regimen of Computed Tomography Screening for Lung Cancer: Lessons Learned Over 25 Years From the International Early Lung Cancer Action Program

We learned many unanticipated and valuable lessons since we started planning our study of low-dose computed tomography (CT) screening for lung cancer in 1991. The publication of the baseline results of the Early Lung Cancer Action Project (ELCAP) in Lancet 1999 showed that CT screening could identify a high proportion of early, curable lung cancers. This stimulated large national screening studies to be quickly started. The ELCAP design, which provided evidence about screening in the context of a clinical program, was able to rapidly expand to a 12-institution study in New York State (NY-ELCAP) and to many international institutions (International-ELCAP), ultimately working with 82 institutions, all using the common I-ELCAP protocol. This expansion was possible because the investigators had developed the ELCAP Management System for screening, capturing data and CT images, and providing for quality assurance. This advanced registry and its rapid accumulation of data and images allowed continual assessment and updating of the regimen of screening as advances in knowledge and new technology emerged. For example, in the initial ELCAP study, introduction of helical CT scanners had allowed imaging of the entire lungs in a single breath, but the images were obtained in 10 mm increments resulting in about 30 images per person. Today, images are obtained in submillimeter slice thickness, resulting in around 700 images per person, which are viewed on high-resolution monitors. The regimen provides the imaging acquisition parameters, imaging interpretation, definition of positive result, and the recommendations for further workup, which now include identification of emphysema and coronary artery calcifications. Continual updating is critical to maximize the benefit of screening and to minimize potential harms. Insights were gained about the natural history of lung cancers, identification and management of nodule subtypes, increased understanding of nodule imaging and pathologic features, and measurement variability inherent in CT scanners. The registry also provides the foundation for assessment of new statistical techniques, including artificial intelligence, and integration of effective genomic and blood-based biomarkers, as they are developed.

Machine learning analysis of DNA methylation profiles distinguishes primary lung squamous cell carcinomas from head and neck metastases

Head and neck squamous cell carcinoma (HNSC) patients are at risk of suffering from both pulmonary metastases or a second squamous cell carcinoma of the lung (LUSC). Differentiating pulmonary metastases from primary lung cancers is of high clinical importance, but not possible in most cases with current diagnostics. To address this, we performed DNA methylation profiling of primary tumors and trained three different machine learning methods to distinguish metastatic HNSC from primary LUSC. We developed an artificial neural network that correctly classified 96.4% of the cases in a validation cohort of 279 patients with HNSC and LUSC as well as normal lung controls, outperforming support vector machines (95.7%) and random forests (87.8%). Prediction accuracies of more than 99% were achieved for 92.1% (neural network), 90% (support vector machine), and 43% (random forest) of these cases by applying thresholds to the resulting probability scores and excluding samples with low confidence. As independent clinical validation of the approach, we analyzed a series of 51 patients with a history of HNSC and a second lung tumor, demonstrating the correct classifications based on clinicopathological properties. In summary, our approach may facilitate the reliable diagnostic differentiation of pulmonary metastases of HNSC from primary LUSC to guide therapeutic decisions.

Serum Platelet-Derived Growth Factor Is Significantly Lower in Patients with Lung Cancer and Continued to Decrease After Platinum-Based Chemotherapy

Objective

This study aimed to investigate the diagnosis and prediction of serum platelet-derived growth factor (PDGF) level in patients with lung cancer (LC).

Methods

Serum concentrations of PDGF-AA and PDGF-AB/BB were determined via Luminex assay in 210 patients with non-small cell lung cancer (NSCLC), 33 patients with small cell lung cancer (SCLC), and 168 healthy controls.

Results

The serum levels of PDGF-AA and PDGF-AB/BB were lower in patients with NSCLC (P < 0.05) and SCLC (P < 0.05), compared to healthy controls. The concentration of PDGF-AA or PDGF-AB/BB continued to markedly decrease in NSCLC after therapy with platinum-based chemotherapy (P < 0.05). The median survival times were 29 and 38 months in patients with NSCLC who received PDGF-AA < 30 ng/mL and PDGF-AA ≥ 30 ng/mL (P = 0.0078), and 26 and 38 months in patients with NSCLC who received PDGF-AB/BB < 42 ng/mL and PDGF-AB/BB ≥ 42 ng/mL (P = 0.0001), respectively. At the individual protein level, PDGF-AA and PDGF-AB/BB had better diagnostic values for NSCLC (AUC = 0.905, AUC = 0.922, respectively).

Conclusion

Serum PDGF may be a potential biomarker for diagnosis of patients with NSCLC and SCLC. However, the prognostic value of serum PDGF in patients with NSCLC harboring mutations and different therapies requires additional investigation.

Separation of bones from soft tissue in chest radiographs: Anatomy-specific orientation-frequency-specific deep neural network convolution

PURPOSE

Lung nodules that are missed by radiologists as well as by computer-aided detection (CAD) systems mostly overlap with ribs and clavicles. Removing the bony structures would result in better visualization of undetectable lesions. Our purpose in this study was to develop a virtual dual-energy imaging system to separate ribs and clavicles from soft tissue in chest radiographs.

METHODS

We developed a mixture of anatomy-specific, orientation-frequency-specific (ASOFS) deep neural network convolution (NNC) experts. Anatomy-specific (AS) NNC was designed to separate the bony structures from soft tissue in different lung segments. While an AS design was proposed previously under our massive-training artificial neural networks (MTANN) framework, in this work, we newly mathematically defined an AS experts model as well as its learning and inference strategies in a probabilistic deep-learning framework. In addition, in combination with our AS experts design, we newly proposed the orientation-frequency-specific (OFS) NNC models to decompose bone and soft-tissue structures into specific orientation-frequency components of different scales using a multi-resolution decomposition technique. We trained multiple NNC models, each of which is an expert for a specific orientation-frequency component in a particular anatomic segment. Perfect reconstruction discrete wavelet transform was used for OFS decomposition/reconstruction, while we introduced a soft-gating layer to merge the predictions of AS NNC experts. To train our model, we used the bone images obtained from a dual-energy system as the target (or teaching) images while the standard chest radiographs were used as the input to our model. The training, validation, and test were performed in a nested two-fold cross-validation manner.

RESULTS

We used a database of 118 chest radiographs with pulmonary nodules to evaluate our NNC scheme. In order to evaluate our scheme, we performed quantitative and qualitative evaluation of the predicted bone and soft-tissue images from our model as well as the ones of a state-of-the-art technique where the "gold-standard" dual-energy bone and soft-tissue images were used as the reference images. Both quantitative and qualitative evaluations demonstrated that our ASOFS NNC was superior to the state-of-the-art bone-suppression technique. Particularly, our scheme was better able to maintain the conspicuity of nodules and lung vessels, comparing to the reference technique, while it separated ribs and clavicles from soft tissue. Comparing to a state-of-the-art bone suppression technique, our bone images had substantially higher (t-test; P < 0.01) similarity, in terms of structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR), to the "gold-standard" dual-energy bone images.

CONCLUSIONS

Our deep ASOFS NNC scheme can decompose chest radiographs into their bone and soft-tissue images accurately, offering the improved conspicuity of lung nodules and vessels, and therefore would be useful for radiologists as well as CAD systems in detecting lung nodules in chest radiographs.

Economic burden of lung cancer: A retrospective cohort study in South Korea, 2002-2015

We evaluated the survival rates and medical expenditure in patients with lung cancer using a nationwide claims database in South Korea. A retrospective observational cohort study design was used, and 2,919 lung cancer patients and their matched controls were included. Medical expenditures were analyzed with the Kaplan-Meier sample average method, and patients were categorized into 4 groups by operation and primary treatment method (i.e. Patients with operation: OP = surgery, OP+CTx/RTx = surgery with anti-cancer drugs or radiotherapy; Patients without operation: CTx/RTx = anti-cancer drugs or radiotherapy, Supportive treatment). The 5-year medical expenditure per case was highest in the OP+CTx/RTx group ($36,013), followed by the CTx/RTx ($23,134), OP ($22,686), and supportive treatment group ($3,700). Lung cancer-related anti-cancer drug therapy was the major cost driver, with an average 53% share across all patients. Generalized linear regression revealed that monthly medical expenditure in lung cancer patients, after adjustment for follow-up month, was approximately 3.1–4.3 times higher than that in the control group (cost ratio for OP = 3.116, OP+CTx/RTx = 3.566, CTx/RTx = 4.340, supportive treatment = 4.157). The monthly medical expenditure at end of life was estimated at $2,139 for all decedents, and approximately a quarter of patients had received chemotherapy in the last 3 months. In conclusion, this study presented the quantified treatment costs of lung cancer on various aspects compared with matched controls according to the treatment of choice. In this study, patients with operation incurred lower lifetime treatment costs than patients with CTx/RTx or supportive treatment, indicating that the economic burden of lung cancer was affected by treatment method. Further studies including both cancer stage and treatment modality are needed to confirm these results and to provide more information on the economic burden according to disease severity.

Mitochondrial NDUFA4L2 protein promotes the vitality of lung cancer cells by repressing oxidative stress

BACKGROUND

Non-small cell lung cancer (NSCLC) accounts for a significant proportion of cancer-related deaths and lacks an effective treatment strategy. NSCLC tissues are generally found in a low oxygen environment. The NDUFA4L2 protein, located in the mitochondria, is encoded by the nucleus genome and is considered a crucial mediator that regulates cell survival. A better understanding of the mechanism of NDUFA4L2 in NSCLC survival in hypoxic environments is essential to design new therapeutic methods.

METHODS

Twenty NSCLC and corresponding paired non-tumorous lung tissue samples were collected. NSCLC cell lines were cultured in hypoxic conditions to investigate the mechanism of NDUFA4L2 in NSCLC. The role of NDUFA4L2 was confirmed by using Western blotting, reactive oxygen species measurement, flow cytometry, immunofluorescence analysis, and wound healing and colony formation assays.

RESULTS

The expression of HIF-1α and mitochondrial NDUFA4L2 increased in NSCLC cell lines cultured in hypoxic conditions (1% O₂ ). NDUFA4L2 was drastically overexpressed in human NSCLC tissues and cell lines cultured in hypoxic conditions. HIF-1α regulated the expression of NDUFA4L2. Knockdown of NDUFA4L2 notably increased mitochondrial reactive oxygen species production, which suppressed the viability of NSCLC.

CONCLUSION

In conclusion, overexpression of NDUFA4L2 is a key factor for maintaining NSCLC growth, suggesting that mitochondrial NDUFA4L2 may be a potential target for the treatment of lung cancer.

Multimodal chemometric approach for the analysis of human exhaled breath in lung cancer patients by TD-GC × GC-TOFMS

Lung cancer is the deadliest cancer in developed countries. To reduce its mortality rate, it is important to enhance our capability to detect it at earlier stages by developing early diagnostic methods. In that context, the analysis of exhaled breath is an interesting approach because of the simplicity of the medical act and its non-invasiveness. Thermal desorption comprehensive two-dimensional gas chromatography time of flight mass spectrometry (TD-GC × GC-TOFMS) has been used to characterize and compare the volatile content of human breath of lung cancer patients and healthy volunteers. On the sampling side, the contaminations induced by the bags membrane and further environmental migration of VOCs during and after the sampling have also been investigated. Over a realistic period of 6 h, the concentration of contaminants inside the bag can increase from 2 to 3 folds based on simulated breath samples. On the data processing side, Fisher ratio (FR) and random forest (RF) approaches were applied and compared in regards to their ability to reduce the data dimensionality and to extract the significant information. Both approaches allow to efficiently smooth the background signal and extract significant features (27 for FR and 17 for RF). Principal component analysis (PCA) was used to evaluate the clustering capacity of the different models. For both approaches, a separation along PC-1 was obtained with a variance score around 35%. The combined model provides a partial separation with a PC-1 score of 52%. This proof-of-concept study further confirms the potential of breath analysis for cancer detection but also underlines the importance of quality control over the full analytical procedure, including the processing of the data.

Effects of postoperative non-steroidal anti-inflammatory drugs on long-term survival and recurrence of patients with non-small cell lung cancer

Non-steroidal anti-inflammatory drugs (NSAIDs) are widely used to relieve postoperative fever, surgery pain, and inflammation. In addition, NSAIDs have anticancer activity and may reduce the risk and mortality of several cancers. However, the association between postoperative NSAIDs and the clinical outcome of non-small cell lung cancer (NSCLC) patients with fever after surgery is not fully understood. We performed a retrospective study of NSCLC patients who underwent surgery between July 2011 and June 2012, aiming to evaluate the effect of postoperative NSAIDs on overall survival (OS) and progression-free survival (PFS). Differences in clinical data between the postoperative NSAIDs group and non-NSAIDs groups were analyzed by Chi-square tests. Kaplan-Meier curves method and Cox regression analysis were conducted for survival analysis. The primary and secondary endpoints were OS and PFS, respectively. This retrospective study included 347 NSCLC patients. There were no significant differences in the clinical characteristics between the NSAIDs group and non-NSAIDs group except for age (P = .024) and differential degree (P = .040). Administration of postoperative NSAIDs was related to longer OS (hazards ratio [HR] 0.528, 95% confidence interval [CI] 0.278-0.884, P = .006) and longer PFS (HR 0.557, 95% CI 0.317-0.841, P = .002) in the multivariate Cox regression model. Subgroup analysis showed statistically significant differences in elderly individuals, male subjects, low smoking index, poor differentiation, and non-adenocarcinoma subgroups, respectively. In conclusion, the administration of postoperative NSAIDs was related to longer OS and PFS in NSCLC patients with postoperative fever.

Stereotactic body radiation therapy (SBRT) for early stage non-small cell lung cancer (NSCLC): contemporary insights and advances

The standard-of-care treatment for early-stage non-small cell lung cancer (NSCLC) continues to be surgery in the form of lobectomy or pneumonectomy. Stereotactic body radiation therapy (SBRT) has evolved as a viable alternative to surgery for medically inoperable patients, achieving excellent local control (LC) with relatively minimal toxicity in standard-risk patients. Nevertheless, the maturation of SBRT has fostered debate regarding its use, technique, dose, and fractionation, particularly in the context of patient- and disease-specific characteristics such as tumor size and location. This review will cover the recent trends and future directions of SBRT as it becomes an increasingly individualized modality in the treatment of early-stage NSCLC.

Vasculature surrounding a nodule: A novel lung cancer biomarker

PURPOSE

To investigate whether the vessels surrounding a nodule depicted on non-contrast, low-dose computed tomography (LDCT) can discriminate benign and malignant screen detected nodules.

MATERIALS AND METHODS

We collected a dataset consisting of LDCT scans acquired on 100 subjects from the Pittsburgh Lung Screening study (PLuSS). Fifty subjects were diagnosed with lung cancer and 50 subjects had suspicious nodules later proven benign. For the lung cancer cases, the location of the malignant nodule in the LDCT scans was known; while for the benign cases, the largest nodule in the LDCT scan was used in the analysis. A computer algorithm was developed to identify surrounding vessels and quantify the number and volume of vessels that were connected or near the nodule. A nonparametric receiver operating characteristic (ROC) analysis was performed based on a single nodule per subject to assess the discriminability of the surrounding vessels to provide a lung cancer diagnosis. Odds ratio (OR) were computed to determine the probability of a nodule being lung cancer based on the vessel features.

RESULTS

The areas under the ROC curves (AUCs) for vessel count and vessel volume were 0.722 (95% CI=0.616-0.811, p<0.01) and 0.676 (95% CI=0.565-0.772), respectively. The number of vessels attached to a nodule was significantly higher in the lung cancer group 9.7 (±9.6) compared to the non-lung cancer group 4.0 (±4.3) CONCLUSION: Our preliminary results showed that malignant nodules are often surrounded by more vessels compared to benign nodules, suggesting that the surrounding vessel characteristics could serve as lung cancer biomarker for indeterminate nodules detected during LDCT lung cancer screening using only the information collected during the initial visit.

[Lung cancer screening with thoracic X‑ray and CT : Current situation]

CLINICAL/METHODICAL ISSUE

Attempts at the early detection of lung cancer using imaging methods began as far back as the 1950s.

STANDARD RADIOLOGICAL METHODS

Several studies attempted to demonstrate a reduction of lung cancer mortality by chest radiography screening but all were unsuccessful.

METHODICAL INNOVATIONS

Even the first small screening studies using computed tomography (CT) could not demonstrate a reduction in lung cancer-specific mortality until in 2011 the results of the largest randomized controlled low-dose CT screening study in the USA (NLST) were published. The NLST results could show a significant 20 % reduction of lung cancer mortality in elderly and heavy smokers using CT.

PERFORMANCE

Confirmation of the NLST results are urgently needed so that the data of the largest European study (NELSON) are eagerly awaited.

ACHIEVEMENTS

Pooled with the data from several smaller European studies these results will provide important information and evidence for the establishment of future CT screening programs in Europe.

PRACTICAL RECOMMENDATIONS

Randomized controlled trials are the basis of evidence-based medicine; therefore, the positive results of the methodologically very good NLST study cannot be ignored, even if it is the only such study completed so far with highly convincing conclusions. The NLST results clearly demonstrate that positive effects for the health of the population can only be expected if the processes are clearly defined and the quality is assured.

Navigation bronchoscopy for diagnosis and small nodule location

Lung cancer continues to be the most common cause of cancer death. Screening programs for high risk patients with the use of low-dose computed tomography (CT) has led to the identification of small lung lesions that were difficult to identify using previous imaging modalities. Electromagnetic navigational bronchoscopy (ENB) is a novel technique that has shown to be of great utility during the evaluation of small, peripheral lesions, that would otherwise be challenging to evaluate with conventional bronchoscopy. The diagnostic yield of navigational bronchoscopy however is highly variable, with reports ranging from 59% to 94%. This variability suggests that well-defined selection criteria and standardized protocols for the use of ENB are lacking. Despite this variability, we believe that this technique is a useful tool evaluating small peripheral lung lesions when patients are properly selected.

Tyrosine Kinase Receptor Landscape in Lung Cancer: Therapeutical Implications

Lung cancer is a heterogeneous disease responsible for the most cases of cancer-related deaths. The majority of patients are clinically diagnosed at advanced stages, with a poor survival rate. For this reason, the identification of oncodrivers and novel biomarkers is decisive for the future clinical management of this pathology. The rise of high throughput technologies popularly referred to as “omics” has accelerated the discovery of new biomarkers and drivers for this pathology. Within them, tyrosine kinase receptors (TKRs) have proven to be of importance as diagnostic, prognostic, and predictive tools and, due to their molecular nature, as therapeutic targets. Along this review, the role of TKRs in the different lung cancer histologies, research on improvement of anti-TKR therapy, and the current approaches to manage anti-TKR resistance will be discussed.

Optimizing the Detection of Circulating Markers to Aid in Early Lung Cancer Detection

Improving early detection of lung cancer is critical to improving lung cancer survival. Studies have shown that computerized tomography (CT) screening can reduce mortality from lung cancer, but this involves risks of radiation exposure and can identify non-cancer lung nodules that lead to unnecessary interventions for some. There is a critical need to develop alternative, less invasive methods to identify patients who have early-stage lung cancer. The detection of circulating tumor cells (CTCs) are a promising area of research, but current technology is limited by a low yield of CTCs. Alternate studies are investigating circulating nucleic acids and proteins as possible tumor markers. It is critical to develop innovative methods for early lung cancer detection that may include CTCs or other markers that are low-risk and low-cost, yet specific and sensitive, to facilitate improved survival by diagnosing the disease when it is surgically curable.

Pulmonary nodules and CT screening: the past, present and future

Lung cancer screening has come a long way since the early studies with chest X-ray. Advancing technology and progress in the processing of images have enabled low dose CT to be tried and tested, and evidence suggests its use can result in a significant mortality benefit. There are several issues that need refining in order to successfully implement screening in the UK and elsewhere. Some countries have started patchy implementation of screening and there is increased recognition that the appropriate management of pulmonary nodules is crucial to optimise benefits of early detection, while reducing harm caused by inappropriate medical intervention. This review summarises and differentiates the many recent guidelines on pulmonary nodule management, discusses screening activity in other countries and exposes the present barriers to implementation in the UK.

After Detection: The Improved Accuracy of Lung Cancer Assessment Using Radiologic Computer-aided Diagnosis

RATIONALE AND OBJECTIVES

The aim of this study was to evaluate the improved accuracy of radiologic assessment of lung cancer afforded by computer-aided diagnosis (CADx).

MATERIALS AND METHODS

Inclusion/exclusion criteria were formulated, and a systematic inquiry of research databases was conducted. Following title and abstract review, an in-depth review of 149 surviving articles was performed with accepted articles undergoing a Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-based quality review and data abstraction.

RESULTS

A total of 14 articles, representing 1868 scans, passed the review. Increases in the receiver operating characteristic (ROC) area under the curve of .8 or higher were seen in all nine studies that reported it, except for one that employed subspecialized radiologists.

CONCLUSIONS

This systematic review demonstrated improved accuracy of lung cancer assessment using CADx over manual review, in eight high-quality observer-performance studies. The improved accuracy afforded by radiologic lung-CADx suggests the need to explore its use in screening and regular clinical workflow.

Unsupervised segmentation of lung fields in chest radiographs using multiresolution fractal feature vector and deformable models

Segmenting lung fields in a chest radiograph is essential for automatically analyzing an image. We present an unsupervised method based on multiresolution fractal feature vector. The feature vector characterizes the lung field region effectively. A fuzzy c-means clustering algorithm is then applied to obtain a satisfactory initial contour. The final contour is obtained by deformable models. The results show the feasibility and high performance of the proposed method. Furthermore, based on the segmentation of lung fields, the cardiothoracic ratio (CTR) can be measured. The CTR is a simple index for evaluating cardiac hypertrophy. After identifying a suspicious symptom based on the estimated CTR, a physician can suggest that the patient undergoes additional extensive tests before a treatment plan is finalized.

Autofluorescence (safe) bronchoscopy and p21/ki-67 immunostaining related to carcinogenesis

Archival biopsy materials from 20 randomly selected asymptomatic volunteers from the Czech uranium miners (CZ UM) risk group (n=98) were examined for p21 and ki-67 immunostatning. There were 16 areas with normal respiratory epithelium and 22 areas with bronchial intra-epithelial neoplasia (IEN). Normal and IEN areas were identified by autofluorescence (System Autofluorescence Endoscopy, SAFE-1000) and monitored during 1998-2002. The majority of specimens from areas with normal autofluorescence intensity with ciliated columnar bronchial epithelium showed strong predominantly cytoplasmic p21 positivity. The SAFE monitoring divided areas of decreased autofluorescence intensity with early stage IEN lesions into two groups. Persistent lesions (P)-showing a spectrum of p21 cytoplasmic staining ranging from negative or isolated negativity to weak or moderate positivity combined with higher proliferative capacity proved by ki-67 nuclear staining. Disappearing lesions (D)-showing strong cytoplasmic p21 positivity and negative ki-67 staining. The IEN lesions were classified into three groups based on p21/ki-67 immunostaining: proliferative lesions at risk (R) with low or without p21 plasma immunostaining combined with high ki-67 nuclear reactivity; ambiguous lesions (A) including cases combining strong p21 cytoplasmic positivity with high ki-67 nuclear reactivity or p21 cytoplasmic negativity with ki-67 negativity staining patterns; the quiescent lesion group (Q) was characterized by strong p21 cytoplasmic positivity and negative ki-67 immunostaining.

Adaptive Statistical Iterative Reconstruction-Applied Ultra-Low-Dose CT with Radiography-Comparable Radiation Dose: Usefulness for Lung Nodule Detection

Objective

To assess the performance of adaptive statistical iterative reconstruction (ASIR)-applied ultra-low-dose CT (ULDCT) in detecting small lung nodules.

Materials and Methods

Thirty patients underwent both ULDCT and standard dose CT (SCT). After determining the reference standard nodules, five observers, blinded to the reference standard reading results, independently evaluated SCT and both subsets of ASIR- and filtered back projection (FBP)-driven ULDCT images. Data assessed by observers were compared statistically.

Results

Converted effective doses in SCT and ULDCT were 2.81 ± 0.92 and 0.17 ± 0.02 mSv, respectively. A total of 114 lung nodules were detected on SCT as a standard reference. There was no statistically significant difference in sensitivity between ASIR-driven ULDCT and SCT for three out of the five observers (p = 0.678, 0.735, < 0.01, 0.038, and < 0.868 for observers 1, 2, 3, 4, and 5, respectively). The sensitivity of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT in three out of the five observers (p < 0.01 for three observers, and p = 0.064 and 0.146 for two observers). In jackknife alternative free-response receiver operating characteristic analysis, the mean values of figure-of-merit (FOM) for FBP, ASIR-driven ULDCT, and SCT were 0.682, 0.772, and 0.821, respectively, and there were no significant differences in FOM values between ASIR-driven ULDCT and SCT (p = 0.11), but the FOM value of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT and SCT (p = 0.01 and 0.00).

Conclusion

Adaptive statistical iterative reconstruction-driven ULDCT delivering a radiation dose of only 0.17 mSv offers acceptable sensitivity in nodule detection compared with SCT and has better performance than FBP-driven ULDCT.

Effect of mu Agonists on Long-Term Survival and Recurrence in Nonsmall Cell Lung Cancer Patients

Opioids are widely used for postoperative analgesia. Morphine may have an effect on cell replication, migration, and cancer recurrence. However, the association of postoperative mu agonists with outcome of nonsmall cell lung cancer (NSCLC) patients has not been fully investigated.We retrospectively evaluated the impact of postoperative mu agonists on overall survival (OS) and disease-free survival (DFS) in early stage NSCLC patients. Patients and relevant medical information were selected from the Bio-Bank of Shandong Provincial Hospital. Difference of clinicopathologic information in postoperative mu agonists group and no mu agonists group was analyzed by χ test. Univariate and multivariate Cox regression analysis were conducted and represented as hazards ratio and 95% confidence interval form. The primary endpoint was OS and secondary endpoint was DFS.This retrospective study included 984 consecutive NSCLC patients who underwent surgery between January 2006 and December 2011. No significant difference existed between postoperative mu agonists usage group and no mu agonists usage group in clinicopathologic information except operation type (P = 0.041). Postoperative mu agonists usage was related to shorter OS (HR 1.514, 95% CI 1.197-1.916, P = 0.001) and shorter DFS (HR 1.415, 95% CI 1.123-1.781, P = 0.003) in the multivariate Cox regression model. For the patients who received postoperative chemotherapy or radiotherapy postoperative mu agonists also predict shorter survival (HR 1.437, 95% CI 1.041-1.982, P = 0.027). Subgroup analysis showed that administration of postoperative mu agonists was related to shorter OS, especially in males, more smoking, poor differential degree, bilobectomy or pneumonectomy, and stage III subgroup, respectively.Administration of postoperative mu agonists was related to shorter OS and DFS for the NSCLC patients who underwent surgery.

Serum LAMC2 enhances the prognostic value of a multi-parametric panel in non-small cell lung cancer

Background:

Non-small cell lung cancer (NSCLC) lacks reliable serological biomarkers for predicting patients' survival and response to treatment. The present study examined the capability of serum LAMC2 and four known tumour markers for disease prognosis and patients' risk stratification.

Methods:

LAMC2, CA 125, CEA, CYFRA 21-1 and SCC levels were retrospectively measured in sera obtained from 127 patients diagnosed with NSCLC by commercial immunoassays. Prognostic performance of the markers was compared with established clinical parameters and multivariate models were constructed to assess the prognostic complementarity of variables.

Results:

LAMC2 showed significant prognostic ability for overall survival (hazards ratio: 1.607, 95% confidence interval: 1.268–2.037, P<0.0001) in the full cohort. LAMC2 and CYFRA 21-1 combination enhanced prognostic models based on common clinical parameters (c-index: 0.81 vs 0.72, P=0.00018), further enabling stratification of patients into clear risk groups. A bootstrap-based cross-validation analysis was supportive of our findings. Combination of LAMC2 and CA 125 showed similar performance.

Conclusions:

Our preliminary study proposes LAMC2 as a novel NSCLC prognostic factor. LAMC2 combined with CA 125 and CYFRA 21-1 could aid in clinical prediction of NSCLC patients' overall survival and inform clinical practice. Larger studies are necessary to unravel LAMC2's full potential as a new NSCLC biomarker.

Meta-analysis of the diagnostic yield and safety of electromagnetic navigation bronchoscopy for lung nodules

OBJECTIVE

This meta-analysis is to evaluate the overall diagnostic yield and accuracy of electromagnetic navigation bronchoscopy (ENB)-based targeted biopsies in detecting peripheral lesions.

METHODS

A systematic search in PubMed was performed using "electromagnetic navigation bronchoscopy" crossed with "peripheral lesions" and "lung nodules". Test performance characteristics with the use of forest plots, summary receiver operating characteristic curves (SROCs) and bivariate random effects were summarized using Meta-Disc software. Adverse events and complications were recorded if reported.

RESULTS

A total of 17 studies (1,106 patients with peripheral lung lesions) were included in this analysis. The pooled sensitivity, specificity, positive likelihood ratios (PLRs), negative likelihood ratios (NLRs), and diagnostic odds ratios (DORs) of ENB was 82%, 100%, 19.36, 0.23, and 97.62, respectively. The area under the curve (AUC) for the SROC was 0.9786. No procedure-related complication was found.

CONCLUSIONS

ENB is an effective and safe procedure in diagnosing peripheral lung lesions.

Comparative effectiveness issues in lung cancer

Lung cancer accounts for more cancer deaths than breast, prostate, colorectal and pancreatic cancer combined. With an aging population, greater intensity of cancer care, and the need for care of the growing number of cancer survivors, comparative effectiveness research opportunities will continue to emerge for this disease. In this chapter, we focus on CER opportunities in lung cancer surgery from the vantage point of those factors directly influenced by the surgeon, patient and the healthcare system.

Tailoring polymersome bilayer permeability improves enhanced permeability and retention effect for bioimaging

Self-assembled nanoparticles conjugated with various imaging contrast agents have been used for the detection and imaging of pathologic tissues. Inadvertently, these nanoparticles undergo fast, dilution-induced disintegration in circulation and quickly lose their capability to associate with and image the site of interest. To resolve this challenge, we hypothesize that decreasing the bilayer permeability of polymersomes can stabilize their structure, extend their lifetime in circulation, and hence improve the quality of bioimaging when the polymersome is coupled with an imaging probe. This hypothesis is examined by using poly(2-hydroxyethyl-co-octadecyl aspartamide), sequentially modified with methacrylate groups, to build model polymersomes. The bilayer permeability of the polymersome is decreased by increasing the packing density of the bilayer with methacrylate groups and is further decreased by inducing chemical cross-linking reactions between the methacrylate groups. The polymersome with decreased bilayer permeability demonstrates greater particle stability in physiological media and ultimately can better highlight tumors in mice over 2 days compared to those with higher bilayer permeability after labeling with a near-infrared (NIR) fluorescent probe. We envisage that the resulting nanoparticles will not only improve diagnosis but also further image-guided therapies.

TFIIB-related factor 2 is associated with poor prognosis of nonsmall cell lung cancer patients through promoting tumor epithelial-mesenchymal transition

In this study, we found that increased BRF2 protein expression was prevalent in NSCLC. Overexpression of BRF2 correlated with abnormal expression of E-cadherin, N-cadherin, and snail. Additionally, expression of BRF2 was found to be an independent prognostic factor in NSCLC patients. Furthermore, we showed that targeted knockdown of BRF2 expression could inhibit the migratory and invasive abilities of NSCLC cells and induced loss of the epithelial-mesenchymal transition of NSCLC cells. These results suggested that BRF2 overexpression in tumor tissues is significantly associated with the poor prognosis of NSCLC patients through promoting epithelial-mesenchymal transition (EMT) program.

TFIIB-related factor 2 over expression is a prognosis marker for early-stage non-small cell lung cancer correlated with tumor angiogenesis

Background

The aim of this study was to examine BRF2 expression in patients with non-small cell lung cancer (NSCLC) and explore the relationship of BRF2 protein with clinicopathologic factors, tumor angiogenesis and prognosis.

Methods

Both BRF2 protein and intratumoral microvessels were examined by immunohistochemical staining in 107 non-small cell lung cancer patients. Intratumoral m icrovessel density (MVD) was measured by counting CD-34 positive immunostained endothelial cells. Western blot and RT-PCR analyses were utilized to investigate the BRF2 expression status in tissues

Results

A notably higher level of BRF2 expression was found in NSCLC tissues at protein levels. In addition, univariate and multivariate analysis demonstrated that BRF2 protein over-expression and high MVD were significantly associated with tumor relapse. Although BRF2 overexpression and high MVD indicated poor 5-year overall survival (p = 0.004 and p = 0.019, respectively), multivariate analysis demonstrated that only BRF2 overexpression was an independent prognostic factor for unfavorable overall survival (P = 0.021).

Conclusions

BRF2 is a promising biomarker to identify individuals with poor prognostic potential and a possible target for anti-angiogenic therapy for patients with early-stage NSCLC.

Separation of bones from chest radiographs by means of anatomically specific multiple massive-training ANNs combined with total variation minimization smoothing

Most lung nodules that are missed by radiologists as well as computer-aided detection (CADe) schemes overlap with ribs or clavicles in chest radiographs (CXRs). The purpose of this study was to separate bony structures such as ribs and clavicles from soft tissue in CXRs. To achieve this, we developed anatomically specific multiple massive-training artificial neural networks (MTANNs) combined with total variation (TV) minimization smoothing and a histogram-matching-based consistency improvement method. The anatomically specific multiple MTANNs were designed to separate bones from soft tissue in different anatomic segments of the lungs. Each of the MTANNs was trained with the corresponding anatomic segment in the teaching bone images. The output segmental images from the multiple MTANNs were merged to produce an entire bone image. TV minimization smoothing was applied to the bone image for reduction of noise while preserving edges. This bone image was then subtracted from the original CXR to produce a soft-tissue image where bones were separated out. This new method was compared with conventional MTANNs with a database of 110 CXRs with nodules. Our new anatomically specific MTANNs separated rib edges, ribs close to the lung wall, and the clavicles from soft tissue in CXRs to a substantially higher level than did the conventional MTANNs, while the conspicuity of lung nodules and vessels was maintained. Thus, our technique for bone-soft-tissue separation by means of our new MTANNs would be potentially useful for radiologists as well as CADe schemes in detection of lung nodules on CXRs.

Bone suppressed images improve radiologists' detection performance for pulmonary nodules in chest radiographs

OBJECTIVES

To assess the effect of bone suppression imaging on observer performance in detecting lung nodules in chest radiographs.

MATERIALS AND METHODS

Posteroanterior (PA) and lateral digital chest radiographs of 111 (average age 65) patients with a CT proven solitary nodule (median diameter 15 mm), and 189 (average age 63) controls were read by 5 radiologists and 3 residents. Conspicuity of nodules on the radiographs was classified in obvious (n = 32), moderate (n = 32), subtle (n = 29) and very subtle (n = 18). Observers read the PA and lateral chest radiographs without and with an additional PA bone suppressed image (BSI) (ClearRead Bone Suppression 2.4, Riverain Technologies, Ohio) within one reading session. Multi reader multi case (MRMC) receiver operating characteristics (ROC) were used for statistical analysis.

RESULTS

ROC analysis showed improved detection with use of BSI compared to chest radiographs alone (AUC = 0.883 versus 0.855; p = 0.004). Performance also increased at high specificities exceeding 80% (pAUC = 0.136 versus 0.124; p = 0.0007). Operating at a specificity of 90%, sensitivity increased with BSI from 66% to 71% (p = 0.0004). Increase of detection performance was highest for nodules with moderate and subtle conspicuity (p = 0.02; p = 0.03).

CONCLUSION

Bone suppressed images improve radiologists' detection performance for pulmonary nodules, especially for those of moderate and subtle conspicuity.

microRNA detection in feces, sputum, pleural effusion and urine: novel tools for cancer screening (Review)

microRNAs (miRNAs) are short non-coding RNA sequences that play important roles in the regulation of gene expression. They have significant regulatory functions in basic cellular processes, including differentiation, proliferation and apoptosis. miRNAs are differentially expressed in tumors, compared with normal tissues. Importantly, miRNAs are also stable and abundantly present in body fluids and feces. The high reproducibility, sensitivity and specificity of miRNAs in body fluids and feces enable miRNAs to be used as potential molecular markers for cancer screening. An increasingly large number of research studies have reported the role of miRNAs in this field. In the present review, we focused mainly on the application of detecting miRNAs in stool, sputum, pleural effusion and urine, to detect colon, lung and urological cancers, highlighting the role of miRNAs in early diagnosis and prognosis.

Molecular classification of non-small-cell lung cancer: diagnosis, individualized treatment, and prognosis

Non-small-cell lung cancer (NSCLC) is the most common cause of premature death among the malignant diseases worldwide. The current staging criteria do not fully capture the complexity of this disease. Molecular biology techniques, particularly gene expression microarrays, proteomics, and next-generation sequencing, have recently been developed to facilitate effectively its molecular classification. The underlying etiology, pathogenesis, therapeutics, and prognosis of NSCLC based on an improved molecular classification scheme may promote individualized treatment and improve clinical outcomes. This review focuses on the molecular classification of NSCLC based on gene expression microarray technology reported during the past decade, as well as their applications for improving the diagnosis, staging and treatment of NSCLC, including the discovery of prognostic markers or potential therapeutic targets. We highlight some of the recent studies that may refine the identification of NSCLC subtypes using novel techniques such as epigenetics, proteomics, or deep sequencing.

Effect of insurance status on the surgical treatment of early-stage non-small cell lung cancer

BACKGROUND

Social disparities permeate non-small cell lung cancer (NSCLC) treatment, yet little is known about the effect of insurance status on the delivery of guideline surgical treatment for early-stage (I or II) NSCLC.

METHODS

We used the California Cancer Registry (1996 through 2008) to identify patients 50 to 94 years old with early-stage NSCLC. We used logistic regression models to assess whether or not insurance status (private insurance, Medicare, Medicaid, no insurance, and unknown) had an effect on whether or not a lobectomy (or bilobectomy) is performed.

RESULTS

A total of 10,854 patients met our inclusion criteria. Compared with patients with private insurance, we found that patients with Medicare (adjusted odds ratio [aOR] 0.87; 95% confidence interval [CI]: 0.79 to 0.95), Medicaid (aOR 0.45; 95% CI: 0.36 to 0.57), or no insurance (aOR 0.45; 95% CI: 0.29 to 0.70) were significantly less likely to undergo lobectomy, even after adjusting for patient factors (age, race, and gender) and tumor characteristics (histology and tumor size). Increasing age, African American race, squamous cell carcinoma, and increasing tumor size were significant independent negative predictors of whether or not a lobectomy was performed.

CONCLUSIONS

Patients without private insurance were significantly less likely than patients with private insurance to undergo a lobectomy for early-stage NSCLC. The variables(s) contributing to this disparity have yet to be elucidated.

Intensity-modulated stereotactic radiotherapy for the treatment of medically inoperable patients with NSCLC stage I

The standard treatment for stage I non-small cell lung cancer (NSCLC) is lobectomy. However, a considerable number of patients are not eligible for standard lung surgery due to poor pulmonary function or comorbidities. We evaluated the efficacy and tolerability of intensity-modulated stereotactic radiotherapy (IMSRT) with moderate hypofractionation for these patients. Twelve patients were selected for IMSRT. 4D-CT planning was performed by gating CT-scanning positioning. The applied doses ranged between 10x4.5 Gy (80% ID) (N=1), 12x4.5 Gy (95% ID) (N=1) and 10x5.5 Gy (95% ID) (N=10). Long-term follow-up was performed including spirometry and CT for evaluation of local, locoregional and distant control. Even in patients with poor pulmonary function IMRST was safe and well tolerated. No severe acute adverse effects were observed. Estimated local control at 2 years was 90%. Moreover, IMSRT does not induce a significant deterioration of pulmonary function. IMRST is safe and feasible even for patients with very poor pulmonary function. The applied dose provides a high local control rate, although the biological equivalent dose (BED) is lower compared to the average of other SRT regimens. Therefore, IMRST may be an efficient alternative for all NSCLC stage I patients with contraindications to standard lobectomy especially in patients with small tumors in high-risk localisations.

Computer-aided nodule detection and volumetry to reduce variability between radiologists in the interpretation of lung nodules at low-dose screening computed tomography

OBJECTIVE

The aim of this study was to evaluate whether a computer-aided diagnosis (CAD) system improves interobserver agreement in the interpretation of lung nodules at low-dose computed tomography (CT) screening for lung cancer.

MATERIALS AND METHODS

Baseline low-dose screening CT examinations from 134 participants enrolled in the National Lung Screening Trial were reviewed by 7 chest radiologists. All participants consented to the use of their deidentified images for research purposes. Screening results were classified as positive when noncalcified nodules larger than 4 mm in diameter were present. Follow-up evaluation was recommended according to the nodule diameter: 4 mm or smaller, more than 4 to 8 mm, and larger than 8 mm. When multiple nodules were present, recommendations were based on the largest nodule. Readers initially assessed the nodule presence visually and measured the average nodule diameter manually. Revision of their decisions after reviewing the CAD marks and size measurement was allowed. Interobserver agreement evaluated using multirater κ statistics was compared between initial assessment and that with CAD.

RESULTS

Multirater κ values for the positivity of the screening results and follow-up recommendations were improved from moderate (κ = 0.53-0.54) at initial assessment to good (κ = 0.66-0.67) after reviewing CAD results. The average percentage of agreement between reader pairs on the positivity of screening results and follow-up recommendations per case was also increased from 77% and 72% at initial assessment to 84% and 80% with CAD, respectively.

CONCLUSION

Computer-aided diagnosis may improve the reader agreement on the positivity of screening results and follow-up recommendations in the assessment of low-dose screening CT.