NCCN Guidelines as a Model of Extended Criteria for Lung Cancer Screening

ACR Appropriateness Criteria® Lung Cancer Screening: 2022 Update

Lung cancer remains the leading cause of cancer-related mortality for men and women in the United States. Screening for lung cancer with annual low-dose CT is saving lives, and the continued implementation of lung screening can save many more. In 2015, the CMS began covering annual lung screening for those who qualified based on the original United States Preventive Services Task Force (USPSTF) lung screening criteria, which included patients 55 to 77 year of age with a 30 pack-year history of smoking, who were either currently using tobacco or who had smoked within the previous 15 years. In 2021, the USPSTF issued new screening guidelines, decreasing the age of eligibility to 80 years of age and pack-years to 20. Lung screening remains controversial for those who do not meet the updated USPSTF criteria, but who have additional risk factors for the development of lung cancer. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Clinical Efficacy of Single-Port Thoracoscopic Lobectomy versus Three-Port Thoracoscopic Lobectomy for Lung Cancer

Objective

To evaluate the clinical efficacy of single-port thoracoscopic lobectomy versus three-port thoracoscopic lobectomy for lung cancer.

Methods

From February 2020 to February 2021, 200 lung cancer patients treated in our institution assessed for eligibility were enrolled and randomly assigned (1 : 1) to either the experimental group (single-port thoracoscopic lobectomy) or the control group (three-port thoracoscopic lobectomy). The outcomes were the eligible patients' surgical indices, pain stress indexes, and postoperative complications.

Results

The experimental group outperformed the control group in terms of incision length, postoperative drainage time, extubation time, time to get out of bed, time to analgesics administration, and postoperative pain score (P < 0.001). Compared with the control group, the experimental group reduced the intraoperative bleeding (161.98 ± 10.65 versus 179.65 ± 14.20, P < 0.001) and length of hospital stay (7.98 ± 0.56 versus 10.46 ± 1.23, P < 0.001). The operative time of the single-port thoracoscopic lobectomy was longer than that of the three-port thoracoscopic lobectomy (P < 0.001). There was no statistical difference between the two groups in the intraoperative conversion to thoracotomy and the number of lymph node dissections (P > 0.05). Postoperative pain stress indices and complication rates of the experimental group were significantly lower than those of the control group (P < 0.001).

Conclusion

Single-port thoracoscopic lobectomy can improve the perioperative indices of lung cancer patients, reduce their pain stress response, and accelerate postoperative recovery. However, its operation is difficult and time-consuming, requiring experienced surgeons for improved surgical outcomes in practice.

An Audit of Opportunistic Lung Cancer Screening in a Canadian Province

Objectives:

Lung cancer is a leading cause of cancer-related death in Canada. Early detection can improve outcomes and despite recommendations from the Canadian Task Force on Preventive Health Care to screen patients who are 55 to 74 years old and have a 30+ pack-year history, formal screening programs are rare in Canada. Our goal was to determine if screening is being performed in a representative Canadian population, if recommendations are being followed, and how screening impacts lung cancer stage at diagnosis and prognosis.

Methods:

A retrospective chart review was performed to identify patients either screened for lung cancer or imaged due to lung cancer symptoms in Eastern Newfoundland between 2015 and 2018. Age, smoking history, screening modality, diagnosis, cancer stage, and mortality were recorded.

Results:

Under 6.0% of the eligible population were screened for lung cancer with only 28.13% meeting age and smoking criteria and being screened appropriately with low-dose CT. However, 70% of patients that had lung cancers found by screening met age and smoking screening criteria. While lung cancer detection rates were similar, screening detected cancer in patients at an earlier stage (50% Stage 1) compared to patients who were not screened (20% Stage 1). Patients who were screened had an improved prognosis.

Conclusions:

Physicians are opportunistically screening for lung cancer, but not consistently following screening guidelines. As screening is sensitive, leads to earlier stage diagnosis, and has a mortality benefit, implementation of an organized screening program could increase quality assurance and prevent many lung-cancer related deaths.

Lung Screening Benefits and Challenges: A Review of The Data and Outline for Implementation

Lung cancer is the leading cause of cancer-related deaths worldwide, accounting for almost a fifth of all cancer-related deaths. Annual computed tomographic lung cancer screening (CTLS) detects lung cancer at earlier stages and reduces lung cancer-related mortality among high-risk individuals. Many medical organizations, including the U.S. Preventive Services Task Force, recommend annual CTLS in high-risk populations. However, fewer than 5% of individuals worldwide at high risk for lung cancer have undergone screening. In large part, this is owing to delayed implementation of CTLS in many countries throughout the world. Factors contributing to low uptake in countries with longstanding CTLS endorsement, such as the United States, include lack of patient and clinician awareness of current recommendations in favor of CTLS and clinician concerns about CTLS-related radiation exposure, false-positive results, overdiagnosis, and cost. This review of the literature serves to address these concerns by evaluating the potential risks and benefits of CTLS. Review of key components of a lung screening program, along with an updated shared decision aid, provides guidance for program development and optimization. Review of studies evaluating the population considered "high-risk" is included as this may affect future guidelines within the United States and other countries considering lung screening implementation.

Performance of Risk Factor-Based Guidelines and Model-Based Chest CT Lung Cancer Screening in World Trade Center-Exposed Fire Department Rescue/Recovery Workers

BACKGROUND

Lung cancer is a leading cause of cancer incidence and death in the United States. Risk factor-based guidelines and risk model-based strategies are used to identify patients who could benefit from low-dose chest CT (LDCT) screening. Few studies compare guidelines or models within the same cohort. We evaluate lung cancer screening performance of two risk factor-based guidelines (US Preventive Services Task Force 2014 recommendations [USPSTF-2014] and National Comprehensive Cancer Network Group 2 [NCCN-2]) and two risk model-based strategies, Prostate Lung Colorectal and Ovarian Cancer Screening (PLCOm2012) and the Bach model) in the same occupational cohort.

RESEARCH QUESTION

Which risk factor-based guideline or model-based strategy is most accurate in detecting lung cancers in a highly exposed occupational cohort?

STUDY DESIGN AND METHODS

Fire Department of City of New York (FDNY) rescue/recovery workers exposed to the September 11, 2001 attacks underwent LDCT lung cancer screening based on smoking history and age. The USPSTF-2014, NCCN-2, PLCOm2012 model, and Bach model were retrospectively applied to determine how many lung cancers were diagnosed using each approach.

RESULTS

Among the study population (N = 3,953), 930 underwent a baseline scan that met at least one risk factor or model-based LDCT screening strategy; 73% received annual follow-up scans. Among the 3,953, 63 lung cancers were diagnosed, of which 50 were detected by at least one LDCT screening strategy. The NCCN-2 guideline was the most sensitive (79.4%; 50/63). When compared with NCCN-2, stricter age and smoking criteria reduced sensitivity of the other guidelines/models (USPSTF-2014 [44%], PLCOm2012 [51%], and Bach[46%]). The 13 missed lung cancers were mainly attributable to smoking less and quitting longer than guideline/model eligibility criteria. False-positive rates were similar across all four guidelines/models.

INTERPRETATION

In this cohort, our findings support expanding eligibility for LDCT lung cancer screening by lowering smoking history from ≥30 to ≥20 pack-years and age from 55 years to 50 years old. Additional studies are needed to determine its generalizability to other occupational/environmental exposed cohorts.

Surgery and invasive diagnostic procedures for benign disease are rare in a large low-dose computed tomography lung cancer screening program

OBJECTIVE

Lung cancer screening with low-dose chest computed tomography improves survival. However, concerns about overdiagnosis and unnecessary interventions persist. We reviewed our lung cancer screening program to determine the rate of surgery and invasive procedures for nonmalignant disease.

METHODS

We reviewed all patients undergoing lung cancer screening from January 2012 to June 2017 with follow-up through January 2019. Patients with suspicious findings (Lung CT Screening Reporting and Data System 4) were referred for further evaluation.

RESULTS

Of 3280 patients screened, 345 (10.5%) had Lung CT Screening Reporting and Data System 4 findings. A total of 311 patients had complete follow-up, of whom 93 (29.9%) were diagnosed with lung cancer. Eighty-three patients underwent lung surgery (2.5% of screened patients). Forty patients underwent lobectomy (48.2%), 3 patients (3.6%) underwent bilobectomy, and 40 patients (48.2%) underwent sublobar resection. Fourteen patients underwent surgery for benign disease (0.43% of screened patients). Fifty-four patients, 5 with benign disease, had at least 1 invasive diagnostic procedure but never underwent surgery. The incidence of any invasive intervention for nonmalignant disease was 0.95% (31/3280 patients). There were no postprocedural deaths within 60 days. Twenty-five patients (0.76%) underwent stereotactic body radiation therapy; 19 patients (76%) had presumed lung cancer without pretreatment pathologic confirmation.

CONCLUSIONS

Surgical resection for benign disease occurred in 0.43% of patients undergoing lung cancer screening. The combined incidence of any invasive diagnostic or therapeutic intervention, including surgical resection, for benign disease was only 0.95%. Periprocedural complications were rare. These results indicate that concern over unnecessary interventions is overstated and should not hinder adoption of lung cancer screening. A multidisciplinary team approach, including thoracic surgeons, is critical to maintain an appropriate rate of interventions in lung cancer screening.

ERS International Congress, Madrid, 2019: highlights from the Thoracic Oncology Assembly

Lung cancer is a devastating disease affecting hundreds of thousands of patients in Europe. Despite recent advances in treatment, its prognosis remains poor. This is mainly attributed to the late stages that diagnoses are usually established at, consequently excluding curative treatment options. During the 2019 European Respiratory Society International Congress in Madrid, Spain, lung cancer experts presented the most recent aspects of lung cancer early detection with low-dose computed tomography.

Key thoracic oncology highlights from #ERSCongress Madrid 2019https://bit.ly/3dQZtv7

The diagnostic accuracy of artificial intelligence in thoracic diseases: A protocol for systematic review and meta-analysis

INTRODUCTION

Thoracic diseases include a variety of common human primary malignant tumors, among which lung cancer and esophageal cancer are among the top 10 in cancer incidence and mortality. Early diagnosis is an important part of cancer treatment, so artificial intelligence (AI) systems have been developed for the accurate and automated detection and diagnosis of thoracic tumors. However, the complicated AI structure and image processing made the diagnosis result of AI-based system unstable. The purpose of this study is to systematically review published evidence to explore the accuracy of AI systems in diagnosing thoracic cancers.

METHODS AND ANALYSIS

We will conduct a systematic review and meta-analysis of the diagnostic accuracy of AI systems for the prediction of thoracic diseases. The primary objective is to assess the diagnostic accuracy of thoracic cancers, including assessing potential biases and calculating combined estimates of sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). The secondary objective is to evaluate the factors associated with different models, classifiers, and radiomics information. We will search databases such as PubMed/MEDLINE, Embase (via OVID), and the Cochrane Library. Two reviewers will independently screen titles and abstracts, perform full article reviews and extract study data. We will report study characteristics and assess methodological quality using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. RevMan 5.3 and Meta-disc 1.4 software will be used for data synthesis. If pooling is appropriate, we will produce summary receiver operating characteristic (SROC) curves, summary operating points (pooled sensitivity and specificity), and 95% confidence intervals around the summary operating points. Methodological subgroup and sensitivity analyses will be performed to explore heterogeneity.

PROSPERO REGISTRATION NUMBER

CRD42019135247.

The Patient Perspective on Lung Cancer Screening and Health Disparities

Lung cancer screening is just starting to be implemented across the United States. Challenges to screening include access to care, awareness of the option for screening, stigma and implicit bias that are due to stigmatization of smoking, stigma of race, nihilism with lung cancer diagnosis viewed as a "death sentence," shared decision making, and underestimation of lung cancer risk. African Americans (AA) have the highest lung cancer mortality rate in the United States despite similar smoking rates as whites. AAs are diagnosed at a later stage, and there is a greater likelihood they will refuse treatment options when diagnosed. Additionally, fewer AAs were found to meet lung cancer screening eligibility criteria compared with whites because of lower tobacco exposure and younger age at time of diagnosis. Outreach and access for lung cancer screening in the AA community and other subpopulations at risk are critical to avoid further increasing disparities in lung cancer morbidity and mortality as lung cancer screening is implemented across the United States. The path forward requires implementing outreach programs and providing lung cancer screening in underserved communities at high risk for lung cancer; consideration of using National Comprehensive Cancer Network guidelines for screening selection criteria, including risk model screening selection; and developing interventions to address stigma, clinician implicit bias, and nihilism.

Serum miR-223: A Validated Biomarker for Detection of Early-Stage Non-Small Cell Lung Cancer

BACKGROUND

The published circulating miRNA signatures proposed for early-stage non-small cell lung cancer (NSCLC) detection are inconsistent and difficult to replicate. Reproducibility and validation of an miRNA simple signature of NSCLC are prerequisites for translation to clinical application.

METHODS

The serum level of miR-223 and miR-29c, emerging from published studies, respectively, as a highly sensitive and a highly specific biomarker of early-stage NSCLC, was measured with droplet digital PCR (ddPCR) technique in an Italian cohort of 75 patients with stage I-II NSCLC and 111 tumor-free controls. By ROC curve analysis we evaluated the miR-223 and miR-29c performance in discerning NSCLC cases from healthy controls.

RESULTS

Reproducibility and robust measurability of the two miRNAs using ddPCR were documented. In a training set (40 stage I-II NSCLCs and 56 controls), miR-223 and miR-29c, respectively, showed an AUC of 0.753 [95% confidence interval (CI), 0.655-0.836] and 0.632 (95% CI, 0.527-0.729) in identifying NSCLC. Combination of miR-223 with miR-29c yielded an AUC of 0.750, not improved over that of miR-223 alone. Furthermore, in an independent blind set (35 stage I-II NSCLCs and 55 controls), we validated serum miR-223 as an effective biomarker of stage I-II NSCLC (AUC = 0.808; 95% CI, 0.712-0.884), confirming the miR-223 diagnostic performance reported by others in Chinese cohorts.

CONCLUSIONS

Using ddPCR technology, miR-223 was externally validated as a reproducible, effective serum biomarker of early-stage NSCLC in ethnically different subjects. Combination with miR-29c did not improve the miR-223 diagnostic performance.

IMPACT

Serum miR-223 determination may be proposed as a tool for refining NSCLC risk stratification, independent of smoking habit and age.

Artificial intelligence in cancer imaging: Clinical challenges and applications

Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care.