Turning Gray: The Natural History of Lung Cancer Over Time

Observational Study of the Natural Growth History of Peripheral Small-Cell Lung Cancer on CT Imaging

BACKGROUND

This study aimed to investigate the natural growth history of peripheral small-cell lung cancer (SCLC) using CT imaging.

METHODS

A retrospective study was conducted on 27 patients with peripheral SCLC who underwent at least two CT scans. Two methods were used: Method 1 involved direct measurement of nodule dimensions using a calliper, while Method 2 involved tumour lesion segmentation and voxel volume calculation using the "py-radiomics" package in Python. Agreement between the two methods was assessed using the intraclass correlation coefficient (ICC). Volume doubling time (VDT) and growth rate (GR) were used as evaluation indices for SCLC growth, and growth distribution based on GR and volume measurements were depicted. We collected potential factors related to imaging VDT and performed a differential analysis. Patients were classified into slow-growing and fast-growing groups based on a VDT cut-off point of 60 days, and univariate analysis was used to identify factors influencing VDT.

RESULTS

Median VDT calculated by the two methods were 61 days and 71 days, respectively, with strong agreement. All patients had continuously growing tumours, and none had tumours that decreased in size or remained unchanged. Eight patients showed possible growth patterns, with six possibly exhibiting exponential growth and two possibly showing Gompertzian growth. Tumours deeper in the lung grew faster than those adjacent to the pleura.

CONCLUSIONS

Peripheral SCLC tumours grow rapidly and continuously without periods of nongrowth or regression. Tumours located deeper in the lung tend to grow faster, but further research is needed to confirm this finding.

The need for a comprehensive and integrated approach to lung cancer policy in Europe

Lung cancer is the leading cause of cancer-related deaths in Europe. Europe's Beating Cancer Plan calls for a comprehensive approach to the disease in general but not specifically to lung cancer. Such a comprehensive approach, integrating efforts to strengthen anti-tobacco policies, early detection and underlying models of care, is sorely needed for lung cancer - particularly considering disruptions to care during the COVID-19 pandemic. In a recently published think piece, a multidisciplinary group of experts proposed four key policy priority areas. First, to reduce stigma and improve awareness of potential symptoms, there is a need to foster a better understanding of lung cancer - among the public and healthcare professionals. Second, opportunities for early detection should be enhanced, and the implementation of targeted screening through low-dose computed tomography should be encouraged as a complement to smoking cessation services. This complementarity should be recognised and built into joint policy proposals, with development and better integration of screening and smoking cessation programmes on the ground. Third, the socioeconomic inequalities underpinning disparities in outcomes in people with lung cancer must be addressed, with targeted approaches to overcome barriers to access Finally, the overall quality of lung cancer care must be improved, making multidisciplinary care available to all and ensuring survivorship is given due attention.

Monitoring Circulating Tumor DNA in Untreated Non-Small-Cell Lung Cancer Patients

Circulating tumor DNA (ctDNA) has been utilized to monitor the clinical course of patients of non-small-cell lung cancer (NSCLC) who receive therapies targeting druggable mutations. However, despite providing valuable information on how NSCLC would naturally progress, the clinical utility of ctDNA for clinical-course monitoring and prediction of treatment-naïve NSCLC patients without druggable mutations remain unknown. We longitudinally followed a total of 12 treatment-naïve NSCLC patients, who did not harbor EGFR and ALK mutations, by collecting clinical information, radiological data, and plasma samples. Changes in ctDNA levels and tumor burden (TB) were compared with each other. New metastasis development, volume doubling time (VDT), and overall survival (OS) were analyzed regarding ctDNA detection at diagnosis. ctDNA was detected in the plasma of seven (58.3%) patients. Changes in ctDNA levels correlated with those in TB in a substantial fraction (57.1%) of patients and was also associated with brain metastasis, tumor necrosis, or pneumonia in other patients. All patients with ctDNA detection developed new metastasis during follow-ups in the organs that had been devoid of metastasis at diagnosis. The patients without ctDNA detection did not develop new metastasis (median duration of follow-ups: 9.8 months). In addition, patients with ctDNA detection had shorter VDT (p = 0.039) and worse OS (p = 0.019) than those without ctDNA detection. The natural course of NSCLC progression can be monitored by measuring ctDNA levels. Detection of ctDNA at diagnosis can predict development of new metastasis, rapid tumor growth and poor survival of NSCLC patients.

Interleukin-11: A Potential Biomarker and Molecular Therapeutic Target in Non-Small Cell Lung Cancer

Non-small cell lung cancer (NSCLC) accounts for 85% of lung cancer and is a fast progressive disease when left untreated. Identification of potential biomarkers in NSCLC is an ongoing area of research that aims to detect, diagnose, and prognosticate patients early to optimize treatment. We review the role of interleukin-11 (IL11), a stromal-cell derived pleiotropic cytokine with profibrotic and cellular remodeling properties, as a potential biomarker in NSCLC. This review identifies the need for biomarkers in NSCLC, the potential sources of IL11, and summarizes the available information leveraging upon published literature, publicly available datasets, and online tools. We identify accumulating evidence suggesting IL11 to be a potential biomarker in NSCLC patients. Further in-depth studies into the pathophysiological effects of IL11 on stromal-tumor interaction in NSCLC are warranted and current available literature highlights the potential value of IL11 detection as a diagnostic and prognostic biomarker in NSCLC.

Small (≤ 20 mm) ground-glass opacity pulmonary lesions: which factors influence the diagnostic accuracy of CT-guided percutaneous core needle biopsy?

Background

The diagnostic accuracy of computed tomography (CT)-guided percutaneous core needle biopsy (CNB) for small (≤ 20 mm) ground-glass opacity (GGO) lesions has not been reported in detail.

Objectives

To evaluate factors that affect the diagnostic accuracy of CT-guided percutaneous CNB for small (≤ 20 mm) GGO pulmonary lesions.

Methods

From January 2014 to February 2018, 156 patients with a small (≤ 20 mm) GGO pulmonary lesion who underwent CT-guided CNB were enrolled in this study. Factors affecting diagnostic accuracy were evaluated by analyzing patient and lesion characteristics and technical factors. Significant factors were identified by multivariate logistic regression.

Results

The diagnostic accuracy of CT-guided percutaneous CNB was 90.4% for small (≤ 20 mm) GGO pulmonary lesions. The diagnostic accuracy was higher for larger lesions (72.5% for lesions ≤ 10 mm, 96.6% for lesions between 11 and 20 mm [P < 0.001]). The diagnostic accuracy of CT-guided percutaneous CNB was 74.5% for lesions with > 90% GGO components and 97.2% for lesions with 50–90% GGO components (P < 0.001). In multivariate analysis, the significant factors influencing diagnostic accuracy were lesion size (P = 0.022; odds ratio [OR] for a lesion between 11 and 20 mm in size was approximately 5 times higher than that for a lesion ≤ 10 mm; 95% confidence interval [CI], 1.3 to 18.5), and GGO component (P = 0.015; OR for a lesion with 50–90% GGO components was approximately 6 times higher than that for a lesion with > 90% GGO components; 95% CI: 1.4 to 25.7).

Conclusions

Lesion size and GGO component are factors affecting diagnostic accuracy. The diagnostic accuracy was higher for larger lesions and lesions with 50–90% GGO components.

A guide for managing patients with stage I NSCLC: deciding between lobectomy, segmentectomy, wedge, SBRT and ablation-part 3: systematic review of evidence regarding surgery in compromised patients or specific tumors

Background

Clinical decision-making for patients with stage I lung cancer is complex. It involves multiple options [lobectomy, segmentectomy, wedge, stereotactic body radiotherapy (SBRT), thermal ablation], weighing multiple outcomes (e.g., short-, intermediate-, long-term) and multiple aspects of each (e.g., magnitude of a difference, the degree of confidence in the evidence, and the applicability to the patient and setting at hand). A structure is needed to summarize the relevant evidence for an individual patient and to identify which outcomes have the greatest impact on the decision-making.

Methods

A PubMed systematic review from 2000-2021 of outcomes after lobectomy, segmentectomy and wedge resection in older patients, patients with limited pulmonary reserve and favorable tumors is the focus of this paper. Evidence was abstracted from randomized trials and non-randomized comparisons (NRCs) with adjustment for confounders. The analysis involved careful assessment, including characteristics of patients, settings, residual confounding etc. to expose degrees of uncertainty and applicability to individual patients. Evidence is summarized that provides an at-a-glance overall impression as well as the ability to delve into layers of details of the patients, settings and treatments involved.

Results

In older patients, perioperative mortality is minimally altered by resection extent and only slightly affected by increasing age; sublobar resection may slightly decrease morbidity. Long-term outcomes are worse after lesser resection; the difference is slightly attenuated with increasing age. Reported short-term outcomes are quite acceptable in (selected) patients with severely limited pulmonary reserve, not clearly altered by resection extent but substantially improved by a minimally invasive approach. Quality-of-life (QOL) and impact on pulmonary function hasn't been well studied, but there appears to be little difference by resection extent in older or compromised patients. Patient selection is paramount but not well defined. Ground-glass and screen-detected tumors exhibit favorable long-term outcomes regardless of resection extent; however solid tumors <1 cm are not a reliably favorable group.

Conclusions

A systematic, comprehensive summary of evidence regarding resection extent in compromised patients and favorable tumors with attention to aspects of applicability, uncertainty and effect modifiers provides a foundation for a framework for individualized decision-making.

Community-based lung cancer screening by low-dose computed tomography in China: First round results and a meta-analysis

OBJECTIVE

To evaluate the efficiency of low-dose computed tomography (LDCT) screening for lung cancer in China by analyzing the baseline results of a community-based screening study accompanied with a meta-analysis.

METHODS

A first round of community-based lung cancer screening with LDCT was conducted in Tianjin, China, and a systematic literature search was performed to identify LDCT screening and registry-based clinical studies for lung cancer in China. Baseline results in the community-based screening study were described by participant risk level and the lung cancer detection rate was compared with the pooled rate among the screening studies. The percentage of patients per stage was compared between the community-based study and screening and clinical studies.

RESULTS

In the community-based study, 5523 participants (43.6% men) underwent LDCT. The lung cancer detection rate was 0.5% (high-risk, 1.2%; low-risk, 0.4%), with stage I disease present in 70.0% (high-risk, 50.0%; low-risk, 83.3%), and the adenocarcinoma present in 84.4% (high-risk, 61.5%; low-risk, 100%). Among all screen-detected lung cancer, women accounted for 8.3% and 66.7% in the high- and low-risk group, respectively. In the screening studies from mainland China, the lung cancer detection rate 0.6% (95 %CI: 0.3%-0.9%) for high-risk populations. The proportions with carcinoma in situ and stage I disease in the screening and clinical studies were 76.4% (95 %CI: 66.3%-85.3%) and 15.2% (95 %CI: 11.8%-18.9%), respectively.

CONCLUSIONS

The stage shift of lung cancer due to screening suggests a potential effectiveness of LDCT screening in China. Nearly 70% of screen-detected lung cancers in low-risk populations are identified in women.

A Propensity-Matched Analysis of Survival of Clinically Diagnosed Early-Stage Lung Cancer and Biopsy-Proven Early-Stage Non-Small Cell Lung Cancer Following Stereotactic Ablative Radiotherapy

Purpose

Stereotactic body radiotherapy (SBRT) has been increasingly regarded as a reasonable option for early-stage lung cancer patients without pretreatment pathologic results, but the efficacy and safety in a Chinese population remains unclear. The aim of this study was to compare survival outcomes and toxicities between patients with clinically diagnosed early-stage lung cancer or biopsy-proven early-stage non-small cell lung cancer and to demonstrate the rationality of this treatment.

Material and Methods

From May 2012 to December 2018, 56 patients with clinically diagnosed early-stage lung cancer and 60 patients with early-stage biopsy-proven were selected into non-pathological group and pathological group, respectively. Propensity score matching (PSM) was performed to reduce patient selection bias. Survival analysis with log-rank test was used to assess the differences of treatment outcomes, which included local control (LC), progression-free survival (PFS), and overall survival (OS).

Results

The median age was 76 (range 47–93) years, and the median follow-up time was 58.3 (range 4.3–95.1) months in the cohort without pathologic results. The median age was 74 (range 57–88) years, and the median follow-up time was 56.3 (range 2.6–94) months in the cohort with pathologic results. 45 matched-pair were analyzed. The 5-year LC, PFS, and OS rates in matched-pair patients with or without pathologic biopsy were 85.5% and 89.8%, 40.6% and 70.9%, and 63.2% and 76.1%, respectively. On Kaplan-Meier survival analysis after PSM analysis, there was no significant difference between patients with pathologic results versus patients with no pathologic results in terms of LC (P= 0.498) and OS (P=0.141). Of the matched-pair patients treated with SBRT, only 1 patient experienced grade 3 or above radiation pneumonitis.

Conclusion

For early-stage lung cancer patients with medically inoperable or not suitable for invasive diagnosis, SBRT may be a good local treatment.

Use and Outcomes of SBRT for Early Stage NSCLC Without Pathologic Confirmation in the Veterans Health Care Administration

Purpose

Stereotactic body radiation therapy (SBRT) use has increased among patients without pathologic confirmation (PC) of lung cancer. Empirical SBRT without PC raises concerns about variation in workup and patient selection, but national trends have not been well described. In this study, we assessed patterns of empirical SBRT use, workup, and causes of death among a large national non-small cell lung cancer (NSCLC) cohort.

Methods and Materials

We identified 2221 patients treated with SBRT for cT1-T2aN0M0 NSCLC in the Veterans Affairs health care system from 2008 to 2015. We reviewed their pretreatment workup and assessed associations between absence of PC and clinical and demographic factors. We compared causes of death between PC and non-PC groups and used Cox proportional hazards modeling to compare overall survival and lung cancer specific survival (LCSS) between these groups.

Results

Treatment without PC varied from 0% to 61% among Veterans Affairs medical centers, with at least 5 cases of stage I NSCLC. Overall, 14.9% of patients were treated without PC and 8.8% did not have a biopsy attempt. Ten percent of facilities were responsible for almost two-thirds (62%) of cases of treatment without PC. Of non-PC patients, 95.5% had positron emission tomography scans, 40.6% had biopsy procedures attempted, and 12.7% underwent endobronchial ultrasound. Non-PC patients were more likely to have cT1 tumors and live outside the histoplasmosis belt. Age, sex, smoking status, and Charlson comorbidity index were similar between groups. Lung cancer was the most common cause of death in both groups. Overall survival was similar between groups, whereas non-PC patients had better LCSS (hazard ratio = 0.77, P = .031).

Conclusions

Empirical SBRT use varied widely among institutions and appropriate radiographic workup was consistently used in this national cohort. Future studies should investigate determinants of variation and reasons for higher LCSS among non-PC patients.

Oligometastatic Lung Cancer Defined by Biology, Science, and Secondary Growths

Breast cancer was the first malignant tumor for which TNM classification was proposed by the International Union Against Cancer. Volume and distribution of tumor burden were considered clinically important in this cancer. Lung cancer is caused by excessive cigarette smoking. Prognosis is worst in small cell lung cancer and in non-small cell lung cancer measuring over 3 cm in size and having regional lymphatic spread. Metastatic spread from lung cancer is favored by lymphatic spread to the locoregional lymph nodes and blood-borne spread to 5 sites-lung, brain, bone, liver, and adrenal-all of which are unfavorable prognostic indicators.

Can Biologic Aggressiveness and Metastatic Potential of Primary Lung Cancer Be Predicted from Clinical Staging Alone?

The future biologic aggressiveness and metastatic potential of lung cancer, as in other cancers, cannot be predetermined from the current clinical information, imaging studies, and pathologic examination whose purpose is to provide diagnosis and mutation studies and molecular drivers only in making decision for treatment. There is a need for better understanding of the biologic characteristics and aggressiveness of lung cancer. The most that is achieved from clinical staging and pathologic staging is in the planning of treatment of lung cancer and predicting prognosis. Aggressive biologic behavior to come is not within the domain of clinical staging or pathologic staging.

Guiding Principles in the Management of Synchronous and Metachronous Primary Non-Small Cell Lung Cancer

Multiple lung cancers can be found simultaneously, with incidence ranging from 1% to 8%. Documentation of more than 1 pulmonary lesion can be challenging, because these solid, ground-glass, or mixed-density tumors may represent multicentric malignant disease or intrapulmonary metastases. If mediastinal nodal and distant deposits are excluded, surgery should be contemplated. After surgical treatment of lung cancer, patients should be followed closely for an undetermined period of time. Good clinical judgment is of outmost importance in deciding which individuals will benefit from those surgical interventions and which are candidates for alternate therapies. Every case should be discussed in a multidisciplinary meeting.

Combination of the G-8 Screening Tool and Hand-Grip Strength to Predict Long-Term Overall Survival in Non-Small Cell Lung Cancer Patients Undergoing Stereotactic Body Radiotherapy

The Geriatric 8 (G-8) is a known predictor of overall survival (OS) in older cancer patients, but is mainly based on nutritional aspects. This study aimed to assess if the G-8 combined with a hand-grip strength test (HGST) in patients with NSCLC treated with stereotactic body radiotherapy can predict long-term OS better than the G-8 alone. A total of 46 SBRT-treated patients with NSCLC of stage T1-T2N0M0 were included. Patients were divided into three groups: fit (normal G-8 and HGST), vulnerable (abnormal G-8 or HGST), or frail (abnormal G-8 and HGST). Statistically significant differences were found in 4-year OS between the fit, vulnerable, and frail groups (70% vs. 46% vs. 25%, p = 0.04), as well as between the normal and abnormal G-8 groups (69% vs. 39%, p = 0.02). In a multivariable analysis of OS, being vulnerable with a hazard ratio (HR) of 2.03 or frail with an HR of 3.80 indicated poorer OS, but this did not reach statistical significance. This study suggests that there might be a benefit of adding a physical test to the G-8 for more precisely predicting overall survival in SBRT-treated patients with localized NSCLC. However, this should be confirmed in a larger study population.

Chest X-ray sensitivity and lung cancer outcomes: a retrospective observational study

Background

Chest X-ray (CXR) is the first-line investigation for lung cancer in many healthcare systems. An understanding of the consequences of false-negative CXRs on time to diagnosis, stage, and survival is limited.

Aim

To determine the sensitivity of CXR for lung cancer and to compare stage at diagnosis, time to diagnosis, and survival between those with CXR that detected, or did not detect, lung cancer.

Design and setting

Retrospective observational study using routinely collected healthcare data.

Method

All patients diagnosed with lung cancer in Leeds Teaching Hospitals NHS Trust during 2008–2015 who had a GP-requested CXR in the year before diagnosis were categorised based on the result of the earliest CXR performed in that period. The sensitivity of CXR was calculated and analyses were performed with respect to time to diagnosis, survival, and stage at diagnosis.

Results

CXR was negative for 17.7% of patients (n = 376/2129). Median time from initial CXR to diagnosis was 43 days for those with a positive CXR and 204 days for those with a negative CXR. Of those with a positive CXR, 29.8% (95% confidence interval [CI] = 27.9% to 31.8%) were diagnosed at stage I or II, compared with 33.5% (95% CI = 28.8% to 38.6%) with a negative CXR.

Conclusion

GPs should consider lung cancer in patients with persistent symptoms even when CXR is negative. Despite longer duration to diagnosis for those with false-negative CXRs, there was no evidence of an adverse impact on stage at diagnosis or survival; however, this comparison is likely to be affected by confounding variables.

Estimating lung cancer risk from chest X-ray and symptoms: a prospective cohort study

Background

Chest X-ray (CXR) is the first-line investigation for lung cancer in many countries but previous research has suggested that the disease is not detected by CXR in approximately 20% of patients. The risk of lung cancer, with particular symptoms, following a negative CXR is not known.

Aim

To establish the sensitivity and specificity of CXR requested by patients who are symptomatic; determine the positive predictive values (PPVs) of each presenting symptom of lung cancer following a negative CXR; and determine whether symptoms associated with lung cancer are different in those who had a positive CXR result compared with those who had a negative CXR result.

Design and setting

A prospective cohort study was conducted in Leeds, UK, based on routinely collected data from a service that allowed patients with symptoms of lung cancer to request CXR.

Method

Symptom data were combined with a diagnostic category (positive or negative) for each CXR, and the sensitivity and specificity of CXR for lung cancer were calculated. The PPV of lung cancer associated with each symptom or combination of symptoms was estimated for those patients with a negative CXR.

Results

In total, 114 (1.3%) of 8996 patients who requested a CXR were diagnosed with lung cancer within 1 year. Sensitivity was 75.4% and specificity was 90.2%. The PPV of all symptoms for a diagnosis of lung cancer within 1 year of CXR was <1% for all individual symptoms except for haemoptysis, which had a PPV of 2.9%. PPVs for a diagnosis of lung cancer within 2 years of CXR was <1.5% for all single symptoms except for haemoptysis, which had a PPV of 3.9%.

Conclusion

CXR has limited sensitivity; however, in a population with a low prevalence of lung cancer, its high specificity and negative predictive value means that lung cancer is very unlikely to be present following a negative result. Findings also support guidance that unexplained haemoptysis warrants urgent referral, regardless of CXR result.

Time from presentation to pre-diagnostic chest X-ray in patients with symptomatic lung cancer: a cohort study using electronic patient records from English primary care

BACKGROUND

National guidelines in England recommend prompt chest X-ray (within 14 days) in patients presenting in general practice with unexplained symptoms of possible lung cancer, including persistent cough, shortness of breath, or weight loss.

AIM

To examine time to chest X-ray in symptomatic patients in English general practice before lung cancer diagnosis, and explore demographical variation.

DESIGN AND SETTING

Retrospective cohort study using routinely collected general practice, cancer registry, and imaging data from England.

METHOD

Patients with lung cancer who presented symptomatically in general practice in the year pre-diagnosis and who had a pre-diagnostic chest X-ray were included. Time from presentation to chest X-ray (presentation-test interval) was determined and intervals classified based on national guideline recommendations as concordant (≤14 days) or non-concordant (>14 days). Variation in intervals was examined by age, sex, smoking status, and deprivation.

RESULTS

In a cohort of 2102 patients with lung cancer, the median presentation-test interval was 49 (interquartile range [IQR] 5-172) days. Of these, 727 (35%) patients had presentation-test intervals of ≤14 days (median 1 [IQR 0-6] day) and 1375 (65%) had presentation-test intervals of >14 days (median 128 [IQR 52-231] days). Intervals were longer among patients who smoke (equivalent to 63% longer than non-smokers; P<0.001), older patients (equivalent to 7% longer for every 10 years from age 27; P = 0.013), and females (equivalent to 12% longer than males; P = 0.016).

CONCLUSION

In symptomatic primary care patients who underwent chest X-ray before lung cancer diagnosis, only 35% were tested within the timeframe recommended by national guidelines. Patients who smoke, older patients, and females experienced longer intervals. These findings could help guide initiatives aimed at improving timely lung cancer diagnosis.

Duration of lead time in screening for lung cancer

BACKGROUND

Screening for lung cancer has used chest radiography (CR), low dose computed tomography (LDCT) and sputum cytology (SC). Estimates of the lead time (LT), i.e., the time interval from detection of lung cancer by screening to the development of symptoms, have been derived from longitudinal studies of populations at risk, tumor doubling time (DT), the ratio between its prevalence at the first round of screening and its annual incidence during follow-up, and by probability modeling derived from the results of screening trials.

OBJECTIVE

To review and update the estimates of LT of lung cancer.

METHODS

A non-systematic search of the literature for estimates of LT and screening trials. Search of the reference sections of the retrieved papers for additional relevant studies. Calculation of LTs derived from these studies.

RESULTS

LT since detection by CR was 0.8-1.1 years if derived from longitudinal studies; 0.6-2.1 years if derived from prevalence / incidence ratios; 0.2 years if derived from the average tumor DT; and 0.2-1.0 if derived from probability modeling. LT since detection by LDCT was 1.1-3.5 if derived from prevalence / incidence ratios; 3.9 if derived from DT; and 0.9 if derived from probability modeling. LT since detection of squamous cell cancer by SC in persons with normal CR was 1.3-1.5 if derived from prevalence/incidence ratios; and 2.1 years if derived from the DT of squamous cell cancer.

CONCLUSIONS

Most estimates of the LT yield values of 0.2-1.5 years for detection by CR; of 0.9-3.5 years for detection by LDCT; and about 2 years or less for detection of squamous cell cancer by SC in persons with normal CR. The heterogeneity of the screening trials and methods of derivation may account for the variability of LT estimates.

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.

Natural history of pathologically confirmed pulmonary subsolid nodules with deep learning-assisted nodule segmentation

OBJECTIVE

To explore the natural history of pulmonary subsolid nodules (SSNs) with different pathological types by deep learning-assisted nodule segmentation.

METHODS

Between June 2012 and June 2019, 95 resected SSNs with preoperative long-term follow-up were enrolled in this retrospective study. SSN detection and segmentation were performed on preoperative follow-up CTs using the deep learning-based Dr. Wise system. SSNs were categorized into invasive adenocarcinoma (IAC, n = 47) and non-IAC (n = 48) groups; according to the interval change during the preoperative follow-up, SSNs were divided into growth (n = 68), nongrowth (n = 22), and new emergence (n = 5) groups. We analyzed the cumulative percentages and pattern of SSN growth and identified significant factors for IAC diagnosis and SSN growth.

RESULTS

The mean preoperative follow-up was 42.1 ± 17.0 months. More SSNs showed growth or new emergence in the IAC than in the non-IAC group (89.4% vs. 64.6%, p = 0.009). Volume doubling time was non-significantly shorter for IACs than for non-IACs (1436.0 ± 1188.2 vs. 2087.5 ± 1799.7 days, p = 0.077). Median mass doubling time was significantly shorter for IACs than for non-IACs (821.7 vs. 1944.1 days, p = 0.001). Lobulated sign (p = 0.002) and SSN mass (p = 0.004) were significant factors for differentiating IACs. IACs showed significantly higher cumulative growth percentages than non-IACs in the first 70 months of follow-up. The growth pattern of SSNs may conform to the exponential model. The initial volume (p = 0.042) was a predictor for SSN growth.

CONCLUSIONS

IACs appearing as SSNs showed an indolent course. The mean growth rate was larger for IACs than for non-IACs. SSNs with larger initial volume are more likely to grow.

KEY POINTS

• Invasive adenocarcinomas (IACs) appearing as subsolid nodules (SSNs), with a mean volume doubling time (VDT) of 1436.0 ± 1188.2 days and median mass doubling time (MDT) of 821.7 days, showed an indolent course. • The VDT was shorter for IACs than for non-IACs (1436.0 ± 1188.2 vs. 2087.5 ± 1799.7 days), but the difference was not significant (p = 0.077). The median MDT was significantly shorter for IACs than for non-IACs (821.7 vs. 1944.1 days, p = 0.001). • SSNs with lobulated sign and larger mass (> 390.5 mg) may very likely be IACs. SSNs with larger initial volume are more likely to grow.

Approach to the Subsolid Nodule

Most focal persistent ground glass nodules (GGNs) do not progress over 10 years. Research suggests that GGNs that do not progress, those that do, and solid lung cancers are fundamentally different diseases, although histologically they seem similar. Surveillance of GGNs to identify those that gradually progress is safe and does not risk losing a window. GGNs with 5 mm solid component or less than 10 mm consolidation (mediastinal and lung windows, respectively, on thin slice CT) are highly curable with resection. The optimal type of resection is unclear; sublobar resection is reasonable but an adequate margin is critically important.

Analyzing the Time From Discovery to Definitive Surgical Therapy for Lung Cancer Based on Referral Patterns

OBJECTIVE

Surgery for early stage non-small cell lung cancer can be curative. A delay from diagnosis to surgery can lead to increased mortality. Our objective was to determine if referring patients to specialists before a thoracic surgeon caused a delay in definitive treatment.

MATERIALS AND METHODS

A retrospective review was conducted of patients who had surgery for non-small cell lung cancer by a single surgeon at our institution from 2013 to 2016. Patients were divided into 2 groups: those who saw a specialist before a thoracic surgeon and patients who were referred directly to a surgeon once the pulmonary nodule was identified on computed tomography (CT). The time from initial CT to resection was compared. Secondary analysis compared private insurance versus Medicare/Medicaid. Percentage of patients upstaged was compared.

RESULTS

There was no significant difference between groups when comparing time from CT to surgery (79.88 vs. 79.90 d; P=0.58). There was a significant decrease in time from CT to surgery for patients with private insurance compared with Medicare/Medicaid patients (66.05 vs. 86.99 d; P=0.03) and fewer private insurance patients were upstaged (22.9% vs. 31.8%; P=0.32). More patients who saw a different specialist first were upstaged compared with patients sent directly to thoracic surgery (32.6% vs. 22.2%; P=0.22).

CONCLUSIONS

When comparing time from CT detection of a lung nodule to surgery, no significant difference was found between patients sent to nonthoracic specialists first and those referred directly to a thoracic surgeon. There was a significant decrease in time from CT to surgery for patients with private insurance compared with Medicare/Medicaid.

Mathematical model predicts response to chemotherapy in advanced non-resectable non-small cell lung cancer patients treated with platinum-based doublet

We developed a computational platform including machine learning and a mechanistic mathematical model to find the optimal protocol for administration of platinum-doublet chemotherapy in a palliative setting. The platform has been applied to advanced metastatic non-small cell lung cancer (NSCLC). The 42 NSCLC patients treated with palliative intent at Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, were collected from a retrospective cohort of patients diagnosed in 2004–2014. Patients were followed-up, for three years. Clinical data collected include complete information about the clinical course of the patients including treatment schedule, response according to RECIST classification, and survival. The core of the platform is the mathematical model, in the form of a system of ordinary differential equations, describing dynamics of platinum-sensitive and platinum-resistant cancer cells and interactions reflecting competition for space and resources. The model is simulated stochastically by sampling the parameter values from a joint probability distribution function. The machine learning model is applied to calibrate the mathematical model and to fit it to the overall survival curve. The model simulations faithfully reproduce the clinical cohort at three levels long-term response (OS), the initial response (according to RECIST criteria), and the relationship between the number of chemotherapy cycles and time between two consecutive chemotherapy cycles. In addition, we investigated the relationship between initial and long-term response. We showed that those two variables do not correlate which means that we cannot predict patient survival solely based on the initial response. We also tested several chemotherapy schedules to find the best one for patients treated with palliative intent. We found that the optimal treatment schedule depends, among others, on the strength of competition among various subclones in a tumor. The computational platform developed allows optimizing chemotherapy protocols, within admissible limits of toxicity, for palliative treatment of metastatic NSCLC. The simplicity of the method allows its application to chemotherapy optimization in different cancers.

Lung cancer is usually diagnosed at an advanced stage because of non-specific symptoms. The most common subtype of lung cancer is non-small cell lung cancer, which constitutes 80% of lung cancer cases. Here, we developed the methodology for finding the optimal treatment schedule for patients treated with palliative intent. The goal is not to cure the patients who are at an advanced stage but to prolong their survival by the administration of platinum-based chemotherapy. The method is based on the mathematical model describing the growth of tumors and its response to chemotherapy which is calibrated using real clinical data.

Treatment modality and outcomes among early-stage non-small cell lung cancer patients with COPD: a cohort study

Background

While there is an increasing number of early-stage non-small cell lung cancer (NSCLC) patients with chronic obstructive pulmonary disease (COPD), there are no specific clinical guidelines for treating them. This study aims to evaluate different treatment modalities and corresponding clinical outcomes among early-stage NSCLC patients with COPD.

Methods

We retrospectively reviewed 692 patients with stage I and II NSCLC and COPD from January 2012 to June 2014. Patients were categorized into four groups according to primary treatment modality: surgery only group (n=442), surgery with adjuvant treatment group (n=157), radiotherapy (RT) group (n=48), and supportive care (SC)-only group (n=45).

Results

Overall, mortality rate was the highest in the SC-only group (35.7 deaths per 100 person-years), followed by RT group (21.5 deaths per 100 person-years), surgery with adjuvant treatment group (8.9 deaths per 100 person-years) and surgery only group (7.2 deaths per 100 person-years). The adjusted hazard ratios (HR) for all-cause mortality compared to the surgery only group were 1.18 (95% CI, 0.84–1.67) in surgery with adjuvant treatment group, 1.61 (95% CI, 1.01–2.57) in RT group and 3.23 (95% CI, 1.99–5.23) in SC-only group.

Conclusions

Surgical resection should be considered as the first choice for early-stage NSCLC with COPD. Despite poor lung function or general patient condition, RT rather than SC can be an alternative option if surgery is not feasible. A multi-disciplinary approach and active communication between patients and physicians might be helpful for adequate decision-making regarding treatment for patients with early-stage NSCLC and COPD.

Peritumoral and intratumoral radiomic features predict survival outcomes among patients diagnosed in lung cancer screening

The National Lung Screening Trial (NLST) demonstrated that screening with low-dose computed tomography (LDCT) is associated with a 20% reduction in lung cancer mortality. One potential limitation of LDCT screening is overdiagnosis of slow growing and indolent cancers. In this study, peritumoral and intratumoral radiomics was used to identify a vulnerable subset of lung patients associated with poor survival outcomes. Incident lung cancer patients from the NLST were split into training and test cohorts and an external cohort of non-screen detected adenocarcinomas was used for further validation. After removing redundant and non-reproducible radiomics features, backward elimination analyses identified a single model which was subjected to Classification and Regression Tree to stratify patients into three risk-groups based on two radiomics features (NGTDM Busyness and Statistical Root Mean Square [RMS]). The final model was validated in the test cohort and the cohort of non-screen detected adenocarcinomas. Using a radio-genomics dataset, Statistical RMS was significantly associated with FOXF2 gene by both correlation and two-group analyses. Our rigorous approach generated a novel radiomics model that identified a vulnerable high-risk group of early stage patients associated with poor outcomes. These patients may require aggressive follow-up and/or adjuvant therapy to mitigate their poor outcomes.

Oncologic Outcomes of Surgery Versus SBRT for Non-Small-Cell Lung Carcinoma: A Systematic Review and Meta-analysis

BACKGROUND

The optimal treatment of stage I non-small-cell lung carcinoma is subject to debate. The aim of this study was to compare overall survival and oncologic outcomes of lobar resection (LR), sublobar resection (SR), and stereotactic body radiotherapy (SBRT).

METHODS

A systematic review and meta-analysis of oncologic outcomes of propensity matched comparative and noncomparative cohort studies was performed. Outcomes of interest were overall survival and disease-free survival. The inverse variance method and the random-effects method for meta-analysis were utilized to assess the pooled estimates.

RESULTS

A total of 100 studies with patients treated for clinical stage I non-small-cell lung carcinoma were included. Long-term overall and disease-free survival after LR was superior over SBRT in all comparisons, and for most comparisons, SR was superior to SBRT. Noncomparative studies showed superior long-term overall and disease-free survival for both LR and SR over SBRT. Although the papers were heterogeneous and of low quality, results remained essentially the same throughout a large number of stratifications and sensitivity analyses.

CONCLUSION

Results of this systematic review and meta-analysis showed that LR has superior outcomes compared to SBRT for cI non-small-cell lung carcinoma. New trials are underway evaluating long-term results of SBRT in potentially operable patients.

Stereotactic Image Guided Lung Radiation Therapy for Clinical Early Stage Non-Small Cell Lung Cancer: A Long-Term Report From a Multi-Institutional Database of Patients Treated With or Without a Pathologic Diagnosis

PURPOSE

Early stage lung cancer is treated with stereotactic body radiation therapy (SBRT) in patients who are unable or unwilling to undergo surgical resection. Some patients' comorbidities are so severe that they are unable to even undergo a biopsy. A clinical diagnosis without biopsy before SBRT has been used, but there are limited data on its efficacy.

METHODS AND MATERIALS

Data on patients treated with SBRT for non-small cell lung cancer, with and without tissue confirmation, were collected from multiple institutions across Europe, Canada, and the United States. Patients with a minimum of 2 years of comprehensive follow up were selected for analysis. Treatment and patient characteristics were compared. Overall survival (OS), disease-free survival (DFS), cause-specific survival (CSS), and rates of local recurrence (LR), regional recurrence (RR), and distant metastasis (DM) were calculated and analyzed.

RESULTS

A total of 701 patients were identified, of which 67% had tissue confirmation of their tumors. The 3- and 5-year outcomes for OS, CSS, and DFS were 83.8%, 93.1%, 69%, and 60.6%, 86.7%, 45.5%, respectively. The rates for LR, RR, and DM at 3 and 5 years were 6.4%, 9.3%, 14.3%, and 10.5%, 14.3%, 19.7%, respectively. There were no statistically significant differences in survival outcomes or recurrences between the biopsy and no-biopsy cohorts.

CONCLUSIONS

SBRT for clinically diagnosed lung cancers is efficacious in appropriately selected patients, with similar outcomes as those with a pathologic diagnosis. Thorough clinical and radiographic evaluations in a multidisciplinary setting are critical to the management of these patients.

Sensitivity of chest X-ray for detecting lung cancer in people presenting with symptoms: a systematic review

BACKGROUND

Despite increasing use of computed tomography (CT), chest X-ray remains the first-line investigation for suspected lung cancer in primary care in the UK. No systematic review evidence exists as to the sensitivity of chest X-ray for detecting lung cancer in people presenting with symptoms.

AIM

To estimate the sensitivity of chest X-ray for detecting lung cancer in symptomatic people.

DESIGN AND SETTING

A systematic review was conducted to determine the sensitivity of chest X-ray for the detection of lung cancer.

METHOD

Databases including MEDLINE, EMBASE, and the Cochrane Library were searched; a grey literature search was also performed.

RESULTS

A total of 21 studies met the eligibility criteria. Almost all were of poor quality. Only one study had the diagnostic accuracy of chest X-ray as its primary objective. Most articles were case studies with a high risk of bias. Several were drawn from non-representative groups, for example, specific presentations, histological subtypes, or comorbidities. Only three studies had a low risk of bias. Two primary care studies reported sensitivities of 76.8% (95% confidence interval [CI] = 64.5 to 84.2%) and 79.3% (95% CI = 67.6 to 91.0%). One secondary care study reported a sensitivity of 79.7% (95% CI = 72.7 to 86.8%).

CONCLUSION

Though there is a paucity of evidence, the highest-quality studies suggest that the sensitivity of chest X-ray for symptomatic lung cancer is only 77% to 80%. GPs should consider if further investigation is necessary in high-risk patients who have had a negative chest X-ray.

Cancer recurrence times from a branching process model

As cancer advances, cells often spread from the primary tumor to other parts of the body and form metastases. This is the main cause of cancer related mortality. Here we investigate a conceptually simple model of metastasis formation where metastatic lesions are initiated at a rate which depends on the size of the primary tumor. The evolution of each metastasis is described as an independent branching process. We assume that the primary tumor is resected at a given size and study the earliest time at which any metastasis reaches a minimal detectable size. The parameters of our model are estimated independently for breast, colorectal, headneck, lung and prostate cancers. We use these estimates to compare predictions from our model with values reported in clinical literature. For some cancer types, we find a remarkably wide range of resection sizes such that metastases are very likely to be present, but none of them are detectable. Our model predicts that only very early resections can prevent recurrence, and that small delays in the time of surgery can significantly increase the recurrence probability.

Quantitative mathematical modeling of clinical brain metastasis dynamics in non-small cell lung cancer

Brain metastases (BMs) are associated with poor prognosis in non-small cell lung cancer (NSCLC), but are only visible when large enough. Therapeutic decisions such as whole brain radiation therapy would benefit from patient-specific predictions of radiologically undetectable BMs. Here, we propose a mathematical modeling approach and use it to analyze clinical data of BM from NSCLC. Primary tumor growth was best described by a gompertzian model for the pre-diagnosis history, followed by a tumor growth inhibition model during treatment. Growth parameters were estimated only from the size at diagnosis and histology, but predicted plausible individual estimates of the tumor age (2.1-5.3 years). Multiple metastatic models were further assessed from fitting either literature data of BM probability (n = 183 patients) or longitudinal measurements of visible BMs in two patients. Among the tested models, the one featuring dormancy was best able to describe the data. It predicted latency phases of 4.4-5.7 months and onset of BMs 14-19 months before diagnosis. This quantitative model paves the way for a computational tool of potential help during therapeutic management.

Long-term follow-up of persistent pulmonary pure ground-glass nodules with deep learning-assisted nodule segmentation

OBJECTIVE

To investigate the natural history of persistent pulmonary pure ground-glass nodules (pGGNs) with deep learning-assisted nodule segmentation.

METHODS

Between January 2007 and October 2018, 110 pGGNs from 110 patients with 573 follow-up CT scans were included in this retrospective study. pGGN automatic segmentation was performed on initial and all follow-up CT scans using the Dr. Wise system based on convolution neural networks. Subsequently, pGGN diameter, density, volume, mass, volume doubling time (VDT), and mass doubling time (MDT) were calculated automatically. Enrolled pGGNs were categorized into growth, 52 (47.3%), and non-growth, 58 (52.7%), groups according to volume growth. Kaplan-Meier analyses with the log-rank test and Cox proportional hazards regression analysis were conducted to analyze the cumulative percentages of pGGN growth and identify risk factors for growth.

RESULTS

The mean follow-up period of the enrolled pGGNs was 48.7 ± 23.8 months. The median VDT of the 52 pGGNs having grown was 1448 (range, 339-8640) days, and their median MDT was 1332 (range, 290-38,912) days. The 12-month, 24.7-month, and 60.8-month cumulative percentages of pGGN growth were 10%, 25.5%, and 51.1%, respectively, and they significantly differed among the initial diameter, volume, and mass subgroups (all p < 0.001). The growth pattern of pGGNs may conform to the exponential model. Lobulated sign (p = 0.044), initial mean diameter (p < 0.001), volume (p = 0.003), and mass (p = 0.023) predicted pGGN growth.

CONCLUSIONS

Persistent pGGNs showed an indolent course. Deep learning can assist in accurately elucidating the natural history of pGGNs. pGGNs with lobulated sign and larger initial diameter, volume, and mass are more likely to grow.

KEY POINTS

• The pure ground-glass nodule (pGGN) segmentation accuracy of the Dr. Wise system based on convolution neural networks (CNNs) was 96.5% (573/594). • The median volume doubling time (VDT) of 52 pure ground-glass nodules (pGGNs) having grown was 1448 days (range, 339-8640 days), and their median mass doubling time (MDT) was 1332 days (range, 290-38,912 days). The mean time to growth in volume was 854 ± 675 days (range, 116-2856 days). • The 12-month, 24.7-month, and 60.8-month cumulative percentages of pGGN growth were 10%, 25.5%, and 51.1%, respectively, and they significantly differed among the initial diameter, volume, and mass subgroups (all p values < 0.001). The growth pattern of pure ground-glass nodules may conform to exponential model.

Pragmatic methods for reviewing exceptionally large bodies of evidence: systematic mapping review and overview of systematic reviews using lung cancer survival as an exemplar

INTRODUCTION

Lung cancer (LC) is the most common cause of cancer death in the world and associated with significant economic burden. We conducted a review of published literature to identify prognostic factors associated with LC survival and determine which may be modifiable and could be targeted to improve outcomes.

METHODS

The exceptionally large volume of LC prognostic research required a new staged approach to reviewing the literature. This comprised an initial mapping review of existing reviews or meta-analyses, based on titles and abstracts, followed by an overview of systematic reviews evaluating factors that independently contribute to lung cancer survival. The overview of reviews was based on full text papers and incorporated a more in-depth assessment of reviews evaluating modifiable factors.

RESULTS

A large volume of published systematic reviews and meta-analyses were identified, but very few focused on modifiable factors for LC survival. Several modifiable factors were identified, which are potential candidates for targeted interventions aiming to improve cancer outcomes. The mapping review included 398 reviews, of which 207 investigated the independent effect of prognostic factors on lung cancer survival. The most frequently evaluated factors were novel biomarkers (86 biomarkers in 138 reviews). Only 15 modifiable factors were investigated in 20 reviews. Those associated with significant survival improvement included normal BMI/less weight loss, good performance status, not smoking/quitting after diagnosis, good pre-treatment quality of life, small gross volume tumour, early-stage tumour, lung resection undertaken by a thoracic/cardiothoracic surgeon, care being discussed by a multidisciplinary team, and timeliness of care.

CONCLUSIONS

The study utilised a novel approach for reviewing an extensive and complicated body of research evidence. It enabled us to address a broad research question and focus on a specific area of priority. The staged approach ensured the review remained relevant to the stakeholders throughout, whilst maintaining the use of objective and transparent methods. It also provided important information on the needs of future research. However, it required extensive planning, management, and ongoing reviewer training.

Prognostic value of two geriatric screening tools in a cohort of older patients with early stage Non-Small Cell Lung Cancer treated with hypofractionated stereotactic radiotherapy

OBJECTIVES

To investigate whether assessment with two geriatric screening tools shows a correlation with clinical outcomes of patients aged 65 years or more, with early-stage Non-Small Cell Lung Cancer (es-NSCLC) treated with hypofractionated stereotactic radiotherapy.

METHODS

From March 2014 to June 2018 we retrospectively evaluated 42 patients with stage I and II lung tumors. Patients were assessed with Charlson Comorbidity Index (CCI) and G8 screening tool. Median age was 74 years (range, 65-91). Stereotactic radiotherapy was performed with Helical Tomotherapy delivering 50-70 Gray (Gy) in 8-10 fractions. Toxicity was evaluated using Common Terminology Criteria for Adverse Events v4.0 criteria.

RESULTS

Median CCI and G8 scores were 6 (4-11) and 14 (12-17), respectively. With a median follow-up of 14 months (3-37), we observed: 3 cases of acute Grade 2 (G2) radiation pneumonitis, 1 late G2 non-cardiac chest pain, 1 late G2 dysphagia and 1 case of late G2 radiation pneumonitis. At statistical analysis, G8 scores ≤14 were significantly associated with late toxicity rates (p = .0073). Local failure was predictive of disease free survival and Overall Survival (p < .001 and p = .001). Death occurred in 12 patients, 6 for non-cancer related causes, with 1- and 2-yrs cancer specific survival rates of 94.8% and 90%, 1- and 2-yrs OS rates of 93% and 80%, respectively.

CONCLUSIONS

Our experience shows a correlation between G8 scores and late toxicity in older patients treated with stereotactic radiotherapy for lung cancer, suggesting the need for prospective studies evaluating its use for the identification of patients at higher risk of adverse events.

Computed Tomography-Based Score Indicative of Lung Cancer Aggression (SILA) Predicts the Degree of Histologic Tissue Invasion and Patient Survival in Lung Adenocarcinoma Spectrum

OBJECTIVE

Most computed tomography (CT)-detected lung cancers are adenocarcinomas (ACs), representing lesions with variable tissue invasion, aggressiveness, and clinical outcome. Visual radiologic characterization of AC pulmonary nodules is both inconsistent and inadequate to confidently predict histopathologic classification or prognosis. Comprehensive pathologic interpretation requires full nodule resection. We have described a computerized scoring system for AC detected on CT scans that can noninvasively estimate the degree of histologic invasion and simultaneously predict patient survival.

METHODS

The Computer-Aided Nodule Assessment and Risk Yield has been validated to characterize CT-detected nodules across the spectrum of AC. With the use of unsupervised clustering, nine natural exemplars were identified as basic radiographic features of AC nodules. We now introduce the Score Indicative of Lung Cancer Aggression (SILA), which is a cumulative aggregate of normalized distributions of ordered Computer-Aided Nodule Assessment and Risk Yield exemplars. The SILA values for each of 237 unique nodules in AC were compared with the histopathologically defined maximum linear extent of tumor invasion. With use of the SILA, Kaplan-Meier survival and Cox proportionality analysis were performed on patients with stage I AC, who comprised a subset of our cohort.

RESULTS

The SILA discriminated between indolent and invasive AC (p < 0.0001). In addition, prediction of linear extent of histopathologic tumor invasion was possible. In stage I AC, three separate SILA prognosis groups were identified: indolent, intermediate, and poor, with 5-year survival rates of 100%, 79%, 58%, respectively. Cox proportionality hazard modeling predicted a 50% increase in mortality, for a 0.1 unit increase in the SILA over a median follow-up time of 3.6 years (p < 0.0002).

CONCLUSIONS

The SILA is a computer-based analytic measure allowing noninvasive approximation of histologic invasion and prediction of patient survival in CT-detected AC nodules.

Quantitative radiomic model for predicting malignancy of small solid pulmonary nodules detected by low-dose CT screening

Background

It is a permanent challenge to differentiate small solid lung nodules. Massive data, extracted from medical image through radiomics analysis, may help early diagnosis of lung cancer. The aim of this study was to assess the usefulness of a quantitative radiomic model developed from baseline low-dose computed tomography (LDCT) screening for the purpose of predicting malignancy in small solid pulmonary nodules (SSPNs).

Methods

This retrospective study included malignant and benign SSPNs (6 to 15 mm) detected in baseline low-dose CT screening. The malignancy was confirmed pathologically, and benignity was confirmed by long term follow-up or pathological diagnosis. The non-contrast CT images were reconstructed with a lung kernel of a slice thickness of 1 mm and were processed to extract 385 quantitative radiomic features using Analysis-Kinetic software. A predictive model was established with the training set of 156 benign and 40 malignant nodules, and was tested with the validation set of 77 benign and 21 malignant nodules through the analysis of R square. The performance of the radiomic model in predicting malignancy was compared with that of the ACR Lung Imaging Reporting and Data System (ACR lung-RADS).

Results

In 294 cases of SSPNs, 61 lung cancers and 24 benign nodules were confirmed pathologically and the remaining 209 nodules were stable with long-term follow-up (4.1±0.9 years). Eleven non-redundant features, including 8 high-order texture features, were extracted from the training data set. The sensitivity and specificity of the prediction model in malignancy differentiation were 81.0% and 92.2% respectively. The accuracy was superior to ACR-lung RADS (89.8% vs. 76.5%).

Conclusions

A radiomic model based on baseline low-dose CT screening for lung cancer can improve the accuracy in predicting malignancy of SSPNs.

Synchronous multiple non-small cell lung cancers in an allograft lung recipient

We described a case report of synchronous non-small cell lung cancers arising in lung transplants after allograft. Immunosuppressive therapy of the recipient induced an accelerated growth rate of primary tumour and metastases as was been observed in orthotopic liver allograft for hepatocellular carcinoma.

Cost-utility analysis of a potential lung cancer screening program for a high-risk population in Germany: A modelling approach

BACKGROUND

Lung cancer is the leading cause of cancer death in Germany. Although several randomized trials in Europe have evaluated the effectiveness of lung cancer screening programs, evidence on the cost-effectiveness of lung cancer screening is scarce.

OBJECTIVE

To evaluate the cost-effectiveness of a population-based lung cancer screening program from the perspective of a German payer.

METHODS

We conducted a cost-effectiveness analysis from the public payer perspective for a high-risk population defined as heavy former and current smokers (≥20 cigarettes per day) between 55 and 75 years of age. The underlying model consisted of two Markov models. We differentiated between a population-based annual screening program and standard clinical care. Depending on stage at diagnosis, simulated patients were assigned to one of five treatment paths according to the German clinical guideline for the diagnosis and treatment of lung cancer. Costs, life years saved, and quality adjusted life years (QALYs) were used as outcomes. Values for input parameters were taken from the literature. The model was run for 60 cycles with a cycle length of three months. Deterministic and probabilistic sensitivity analyses were conducted.

RESULTS

In the base case, annual lung cancer screening led to an increase in incremental costs (€ 1,153 per person) compared to standard clinical care. However, the screening approach was associated with an incremental gain in life years (0.06 per person) and QALYs (0.04 per person). Thus, the incremental cost-effectiveness ratio (ICER) was € 19,302 per life year saved and € 30,291 per QALY. A probabilistic sensitivity analysis with 10,000 draws resulted in average ICERs of € 22,118 per life year and € 34,841 per QALY.

CONCLUSION

We provide evidence that lung cancer screening for a high-risk population may be more effective, but also more costly, than standard clinical care from the perspective of a German payer.

Clinicopathological characteristics and prognosis of pulmonary pleomorphic carcinoma: a population-based retrospective study using SEER data

Background

Pulmonary pleomorphic carcinoma (PPC) is a rare malignancy; unique clinicopathological characteristics and prognosis have not been described.

Methods

PPC patient information collected in the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2014 were extracted, evaluated, and compared with NSCLC patient data. Overall survival (OS) was evaluated by the Kaplan-Meier method. Univariate analysis (UVA) and multivariate analysis (MVA) by the Cox proportional hazards regression identified risk factors that predicted OS and the results were used to construct a nomogram to predict 1-, 3-, and 5-year OS in PPC patients.

Results

A total of 309 patients diagnosed with PPC were identified among the records of 320,510 NSCLC patients. The median age was 66 (IQR, 57-75) years, 59.2% were men, 79.3% were White, 63.9% had upper lobe tumors, 77.0% were poorly differentiated, and 38.0% were AJCC stage IV. Median OS was 9 (95% CI: 6.69-11.31) months and 5-year OS was 25.1% (95% CI: 23.6-26.6%). PPC patients had significantly larger and less differentiated tumors, a higher rate of radical surgical resection, less N+ disease, and fewer distant metastases (P<0.001) than NSCLC patients. UVA and MVA identified age, T stage, M stage, surgery, and chemotherapy as independent risk factors. The nomogram had a calibration index of 0.798.

Conclusions

PPC had distinct clinicopathological characteristics. Age, T stage, M stage, surgery and chemotherapy were independently associated with OS. The nomogram accurately predicted 1-, 3- and 5-year OS.

Computer Aided Nodule Analysis and Risk Yield (CANARY) characterization of adenocarcinoma: radiologic biopsy, risk stratification and future directions

The majority of incidentally and screen-detected lung cancers are adenocarcinomas. Optimal management of these tumors is clinically challenging due to variability in tumor histopathology and behavior. Invasive adenocarcinoma (IA) is generally aggressive while adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) may be extremely indolent. Computer Aided Nodule Analysis and Risk Yield (CANARY) is a quantitative computed tomography (CT) analysis tool that allows non-invasive assessment of tumor characteristics. This analysis may obviate the need for tissue biopsy and facilitate the risk stratification of adenocarcinoma of the lung. CANARY was developed by unsupervised machine learning techniques using CT data of histopathologically-characterized adenocarcinomas of the lung. This technique identified 9 distinct exemplars that constitute the spectrum of CT features found in adenocarcinoma of the lung. The distributions of these features in a nodule correlate with histopathology. Further automated clustering of CANARY nodules defined three distinct groups that have distinctly different post-resection disease free survival (DFS). CANARY has been validated within the NLST cohort and multiple other cohorts. Using semi-automated segmentation as input to CANARY, there is excellent repeatability and interoperator correlation of results. Confirmation and longitudinal tracking of indolent adenocarcinoma with CANARY may ultimately add decision support in nuanced cases where surgery may not be in the best interest of the patient due to competing comorbidity. Currently under investigation is CANARY's role in detecting differing driver mutations and tumor response to targeted chemotherapeutics. Combining the results from CANARY analysis with clinical information and other quantitative techniques such as analysis of the tumor-free surrounding lung may aid in building more powerful predictive models. The next step in CANARY investigation will be its prospective application, both in selecting low-risk stage 1 adenocarcinoma for active surveillance and investigation in selecting high-risk early stage adenocarcinoma for adjuvant therapy.

Cost-effectiveness of an autoantibody test (EarlyCDT-Lung) as an aid to early diagnosis of lung cancer in patients with incidentally detected pulmonary nodules

OBJECTIVE

Patients who have incidentally detected pulmonary nodules and an estimated intermediate risk (5-60%) of lung cancer frequently are followed via computed tomography (CT) surveillance to detect nodule growth, despite guidelines for a more aggressive diagnostic strategy. We examined the cost-effectiveness of an autoantibody test (AABT)-Early Cancer Detection Test-Lung (EarlyCDT-LungTM)-as an aid to early diagnosis of lung cancer among such patients.

METHODS

We developed a decision-analytic model to evaluate use of the AABT versus CT surveillance alone. In the model, patients with a positive AABT-because they are at substantially enhanced risk of lung cancer-are assumed to go directly to biopsy, resulting in diagnosis of lung cancer in earlier stages than under current guidelines (a beneficial stage shift). Patients with a negative AABT, and those scheduled for CT surveillance alone, are assumed to have periodic CT screenings to detect rapid growth and thus to have their lung cancers diagnosed-on average-at more advanced stages.

RESULTS

Among 1,000 patients who have incidentally detected nodules 8-30 mm, have an intermediate-risk of lung cancer, and are evaluated by CT surveillance alone, 95 (9.5%) are assumed to have lung cancer (local, 73.6%; regional, 22.0%; distant, 4.4%). With use of the AABT set at a sensitivity/specificity of 41%/93% (stage shift = 10.8%), although expected costs would be higher by $949,442 ($949 per person), life years would be higher by 53 (0.05 per person), resulting in a cost per life-year gained of $18,029 and a cost per quality-adjusted life year (QALY) gained of $24,330. With use of the AABT set at a sensitivity/specificity of 28%/98% (stage shift = 7.4%), corresponding cost-effectiveness ratios would be $18,454 and $24,833.

CONCLUSIONS

Under our base-case assumptions, and reasonable variations thereof, using AABT as an aid in the early diagnosis of lung cancer in patients with incidentally detected pulmonary nodules who are estimated to be at intermediate risk of lung cancer and are scheduled for CT surveillance alone is likely to be a cost-effective use of healthcare resources.

The potential for increased tumor control probability in non-small cell lung cancer with a hypofractionated integrated boost to the gross tumor volume

Treatment outcomes in locally advanced non-small cell lung cancer (NSCLC) to date have been poor, with normal tissue toxicity often limiting the dose that can be delivered to the tumor. Treatment intensification in NSCLC via targeted dose escalation with modern delivery techniques may offer the potential for a significant increase in tumor control probability (TCP) without a clinically significant increase in organ-at-risk (OAR) toxicity. In this planning study, 20 patients were re-planned with a volumetric modulated arc therapy (VMAT) and an inhomogeneous dose distribution with iteratively escalated doses to the gross tumor volume (iGTV) (composite GTV across multiple 4-dimensional computed tomography [4DCT] phases) in a series of 20 fraction regimes. For each plan OAR doses, target coverage and predicted TCPs were collected and compared with homogenous 3-dimensional (3D) and VMAT plans, as well as with each other. In 70% of patients, it was possible to escalate to 75 Gy in 20 fractions within OAR tolerances, opening the possibility of treating these patients to a biological effective dose (BED) of 103.1 Gy₁₀. This planning study forms the basis of a clinical trial INTENSE (Inhomogeneous Targeted Dose Escalation in Non-Small CEll Lung Cancer), CTRIAL 15-47.