LDCT lung cancer screening in populations at different risk for lung cancer

Lung cancer screening provider recommendation and completion in black and White patients with a smoking history in two healthcare systems: a survey study

BACKGROUND

Annual lung cancer screening (LCS) with low dose CT reduces lung cancer mortality. LCS is underutilized. Black people who smoke tobacco have high risk of lung cancer but are less likely to be screened than are White people. This study reports provider recommendation and patient completion of LCS and colorectal cancer screening (CRCS) among patients by race to assess for utilization of LCS.

METHODS

3000 patients (oversampled for Black patients) across two healthcare systems (in Rhode Island and Minnesota) who had a chart documented age of 55 to 80 and a smoking history were invited to participate in a survey about cancer screening. Logistic regression analysis compared the rates of recommended and received cancer screenings.

RESULTS

1177 participants responded (42% response rate; 45% White, 39% Black). 24% of respondents were eligible for LCS based on USPSTF2013 criteria. One-third of patients eligible for LCS reported that a doctor had recommended screening, compared to 90% of patients reporting a doctor recommended CRCS. Of those recommended screening, 88% reported completing LCS vs. 83% who reported completion of a sigmoidoscopy/colonoscopy. Black patients were equally likely to receive LCS recommendations but less likely to complete LCS when referred compared to White patients. There was no difference in completion of CRCS between Black and White patients.

CONCLUSIONS

Primary care providers rarely recommend lung cancer screening to patients with a smoking history. Systemic changes are needed to improve provider referral for LCS and to facilitate eligible Black people to complete LCS.

Lung cancer screening in Brazil: recommendations from the Brazilian Society of Thoracic Surgery, Brazilian Thoracic Association, and Brazilian College of Radiology and Diagnostic Imaging

Although lung cancer (LC) is one of the most common and lethal tumors, only 15% of patients are diagnosed at an early stage. Smoking is still responsible for more than 85% of cases. Lung cancer screening (LCS) with low-dose CT (LDCT) reduces LC-related mortality by 20%, and that reduction reaches 38% when LCS by LDCT is combined with smoking cessation. In the last decade, a number of countries have adopted population-based LCS as a public health recommendation. Albeit still incipient, discussion on this topic in Brazil is becoming increasingly broad and necessary. With the aim of increasing knowledge and stimulating debate on LCS, the Brazilian Society of Thoracic Surgery, the Brazilian Thoracic Association, and the Brazilian College of Radiology and Diagnostic Imaging convened a panel of experts to prepare recommendations for LCS in Brazil. The recommendations presented here were based on a narrative review of the literature, with an emphasis on large population-based studies, systematic reviews, and the recommendations of international guidelines, and were developed after extensive discussion by the panel of experts. The following topics were reviewed: reasons for screening; general considerations about smoking; epidemiology of LC; eligibility criteria; incidental findings; granulomatous lesions; probabilistic models; minimum requirements for LDCT; volumetric acquisition; risks of screening; minimum structure and role of the multidisciplinary team; practice according to the Lung CT Screening Reporting and Data System; costs versus benefits of screening; and future perspectives for LCS.

Performance of Lung-RADS in different target populations: a systematic review and meta-analysis

OBJECTIVES

Multiple lung cancer screening studies reported the performance of Lung CT Screening Reporting and Data System (Lung-RADS), but none systematically evaluated its performance across different populations. This systematic review and meta-analysis aimed to evaluate the performance of Lung-RADS (versions 1.0 and 1.1) for detecting lung cancer in different populations.

METHODS

We performed literature searches in PubMed, Web of Science, Cochrane Library, and Embase databases on October 21, 2022, for studies that evaluated the accuracy of Lung-RADS in lung cancer screening. A bivariate random-effects model was used to estimate pooled sensitivity and specificity, and heterogeneity was explored in stratified and meta-regression analyses.

RESULTS

A total of 31 studies with 104,224 participants were included. For version 1.0 (27 studies, 95,413 individuals), pooled sensitivity was 0.96 (95% confidence interval [CI]: 0.90-0.99) and pooled specificity was 0.90 (95% CI: 0.87-0.92). Studies in high-risk populations showed higher sensitivity (0.98 [95% CI: 0.92-0.99] vs. 0.84 [95% CI: 0.50-0.96]) and lower specificity (0.87 [95% CI: 0.85-0.88] vs. 0.95 (95% CI: 0.92-0.97]) than studies in general populations. Non-Asian studies tended toward higher sensitivity (0.97 [95% CI: 0.91-0.99] vs. 0.91 [95% CI: 0.67-0.98]) and lower specificity (0.88 [95% CI: 0.85-0.90] vs. 0.93 [95% CI: 0.88-0.96]) than Asian studies. For version 1.1 (4 studies, 8811 individuals), pooled sensitivity was 0.91 (95% CI: 0.83-0.96) and specificity was 0.81 (95% CI: 0.67-0.90).

CONCLUSION

Among studies using Lung-RADS version 1.0, considerable heterogeneity in sensitivity and specificity was noted, explained by population type (high risk vs. general), population area (Asia vs. non-Asia), and cancer prevalence.

CLINICAL RELEVANCE STATEMENT

Meta-regression of lung cancer screening studies using Lung-RADS version 1.0 showed considerable heterogeneity in sensitivity and specificity, explained by the different target populations, including high-risk versus general populations, Asian versus non-Asian populations, and populations with different lung cancer prevalence.

KEY POINTS

• High-risk population studies showed higher sensitivity and lower specificity compared with studies performed in general populations by using Lung-RADS version 1.0. • In non-Asian studies, the diagnostic performance of Lung-RADS version 1.0 tended to be better than in Asian studies. • There are limited studies on the performance of Lung-RADS version 1.1, and evidence is lacking for Asian populations.

Risk Model-Based Lung Cancer Screening and Racial and Ethnic Disparities in the US

Importance

The revised 2021 US Preventive Services Task Force (USPSTF) guidelines for lung cancer screening have been shown to reduce disparities in screening eligibility and performance between African American and White individuals vs the 2013 guidelines. However, potential disparities across other racial and ethnic groups in the US remain unknown. Risk model-based screening may reduce racial and ethnic disparities and improve screening performance, but neither validation of key risk prediction models nor their screening performance has been examined by race and ethnicity.

Objective

To validate and recalibrate the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial 2012 (PLCOm2012) model-a well-established risk prediction model based on a predominantly White population-across races and ethnicities in the US and evaluate racial and ethnic disparities and screening performance through risk-based screening using PLCOm2012 vs the USPSTF 2021 criteria.

Design, Setting, and Participants

In a population-based cohort design, the Multiethnic Cohort Study enrolled participants in 1993-1996, followed up through December 31, 2018. Data analysis was conducted from April 1, 2022, to May 19. 2023. A total of 105 261 adults with a smoking history were included.

Exposures

The 6-year lung cancer risk was calculated through recalibrated PLCOm2012 (ie, PLCOm2012-Update) and screening eligibility based on a 6-year risk threshold greater than or equal to 1.3%, yielding similar eligibility as the USPSTF 2021 guidelines.

Outcomes

Predictive accuracy, screening eligibility-incidence (E-I) ratio (ie, ratio of the number of eligible to incident cases), and screening performance (sensitivity, specificity, and number needed to screen to detect 1 lung cancer).

Results

Of 105 261 participants (60 011 [57.0%] men; mean [SD] age, 59.8 [8.7] years), consisting of 19 258 (18.3%) African American, 27 227 (25.9%) Japanese American, 21 383 (20.3%) Latino, 8368 (7.9%) Native Hawaiian/Other Pacific Islander, and 29 025 (27.6%) White individuals, 1464 (1.4%) developed lung cancer within 6 years from enrollment. The PLCOm2012-Update showed good predictive accuracy across races and ethnicities (area under the curve, 0.72-0.82). The USPSTF 2021 criteria yielded a large disparity among African American individuals, whose E-I ratio was 53% lower vs White individuals (E-I ratio: 9.5 vs 20.3; P < .001). Under the risk-based screening (PLCOm2012-Update 6-year risk ≥1.3%), the disparity between African American and White individuals was substantially reduced (E-I ratio: 15.9 vs 18.4; P < .001), with minimal disparities observed in persons of other minoritized groups, including Japanese American, Latino, and Native Hawaiian/Other Pacific Islander. Risk-based screening yielded superior overall and race and ethnicity-specific performance to the USPSTF 2021 criteria, with higher overall sensitivity (67.2% vs 57.7%) and lower number needed to screen (26 vs 30) at similar specificity (76.6%).

Conclusions

The findings of this cohort study suggest that risk-based lung cancer screening can reduce racial and ethnic disparities and improve screening performance across races and ethnicities vs the USPSTF 2021 criteria.

Recalibrating Risk Prediction Models by Synthesizing Data Sources: Adapting the Lung Cancer PLCO Model for Taiwan

BACKGROUND

Methods synthesizing multiple data sources without prospective datasets have been proposed for absolute risk model development. This study proposed methods for adapting risk models for another population without prospective cohorts, which would help alleviate the health disparities caused by advances in absolute risk models. To exemplify, we adapted the lung cancer risk model PLCOM2012, well studied in the west, for Taiwan.

METHODS

Using Taiwanese multiple data sources, we formed an age-matched case-control study of ever-smokers (AMCCSE), estimated the number of ever-smoking lung cancer patients in 2011-2016 (NESLP2011), and synthesized a dataset resembling the population of cancer-free ever-smokers in 2010 regarding the PLCOM2012 risk factors (SPES2010). The AMCCSE was used to estimate the overall calibration slope, and the requirement that NESLP2011 equals the estimated total risk of individuals in SPES2010 was used to handle the calibration-in-the-large problem.

RESULTS

The adapted model PLCOT-1 (PLCOT-2) had an AUC of 0.78 (0.75). They had high performance in calibration and clinical usefulness on subgroups of SPES2010 defined by age and smoking experience. Selecting the same number of individuals for low-dose computed tomography screening using PLCOT-1 (PLCOT-2) would have identified approximately 6% (8%) more lung cancers than the US Preventive Services Task Forces 2021 criteria. Smokers having 40+ pack-years had an average PLCOT-1 (PLCOT-2) risk of 3.8% (2.6%).

CONCLUSIONS

The adapted PLCOT models had high predictive performance.

IMPACT

The PLCOT models could be used to design lung cancer screening programs in Taiwan. The methods could be applicable to other cancer models.

Implementation of an Integrated Lung Cancer Prevention and Screening Program Using a Mobile Computed Tomography (CT) Unit in Brazil

INTRODUCTION

Lung cancer is the deadliest cancer worldwide and in Brazil. Despite strong evidence, lung cancer screening by low-dose computed tomography (LDCT) in high-risk individuals is far from a reality in many countries, particularly in Brazil. Brazil has a universal public health system marked with important inequalities. One affordable strategy to increase the coverage of resources is to use mobile units.

OBJECTIVES

To describe the implementation and results of an innovative lung cancer prevention program that integrates tobacco cessation and lung cancer screening using a mobile CT unit.

METHODOLOGY

From May 2019 to Dec 2020, health professionals from 18 public primary health care units in Barretos, Brazil, were trained to offer smoking cessation counseling and treatment. Eligible high-risk participants of this program were also invited to perform lung cancer screening in a mobile LDCT unit that was specially conceived to be dispatched to the community. A detailed epidemiological questionnaire was administered to the LDCT participants.

RESULTS

Among the 233 screened participants, the majority were women (54.9%), and the average age was 62 years old. A total of 52.8% of participants showed high or very high nicotine dependence. After 1 year, 27.8% of participants who were involved in smoking cessation groups had quit smoking. The first LDCT round revealed that the majority of participants (83.7%) exhibited lung-Rads 1 or 2; 7.3% exhibited lung-Rads 3; 7.7% exhibited lung-Rads 4a; and 3% exhibited lung-Rads 4b or 4x. The three participants with lung-Rads 4b were further confirmed, and their surgery led to the diagnosis of early-stage cancer (1 case of adenocarcinoma and two cases of squamous cell carcinoma), leading to a cancer diagnosis rate of 12.8/1000.

CONCLUSION

Our results indicate promising outcomes for an onsite integrative program enrolling high-risk individuals in a middle-income country. Evidence barriers and challenges remain to be overcome.

A modeling analysis to compare eligibility strategies for lung cancer screening in Brazil

BACKGROUND

Country-specific evidence is needed to guide decisions regarding whether and how to implement lung cancer screening in different settings. For this study, we estimated the potential numbers of individuals screened and lung cancer deaths prevented in Brazil after applying different strategies to define screening eligibility.

METHODS

We applied the Lung Cancer Death Risk Assessment Tool (LCDRAT) to survey data on current and former smokers (ever-smokers) in 15 Brazilian state capital cities that comprise 18% of the Brazilian population. We evaluated three strategies to define eligibility for screening: (1) pack-years and cessation time (≥30 pack-years and <15 years since cessation); (2) the LCDRAT risk model with a fixed risk threshold; and (3) LCDRAT with age-specific risk thresholds.

FINDINGS

Among 2.3 million Brazilian ever-smokers aged 55-79 years, 21,459 (95%CI 20,532-22,387) lung cancer deaths were predicted over 5 years without screening. Applying the fixed risk-based eligibility definition would prevent more lung cancer deaths than the pack-years definition [2,939 (95%CI 2751-3127) vs. 2,500 (95%CI 2318-2681) lung cancer deaths], and with higher screening efficiency [NNS=177 (95%CI 170-183) vs. 205 (95%CI 194-216)], but would tend to screen older individuals [mean age 67.8 (95%CI 67.5-68.2) vs. 63.4 (95%CI 63.0-63.9) years]. Applying age-specific risk thresholds would allow younger ever-smokers to be screened, although these individuals would be at lower risk. The age-specific thresholds strategy would avert three-fifths (60.1%) of preventable lung cancer deaths [N = 2629 (95%CI 2448-2810)] by screening 21.9% of ever-smokers.

INTERPRETATION

The definition of eligibility impacts the efficiency of lung cancer screening and the mean age of the eligible population. As implementation of lung screening proceeds in different countries, our analytical framework can be used to guide similar analyses in other contexts. Due to limitations of our models, more research would be needed.

Contemporary Lung Cancer Screening and the Promise of Blood-Based Biomarkers

In this issue, the study by Dagnino and colleagues represents an important addition to the maturing field of blood-based biomarkers for lung cancer screening. Their comprehensive approach to analyzing circulating inflammatory proteins identified CDCP1 as a potential biomarker for distinguishing patients with or without lung cancer, a finding that was confirmed in a validation cohort. CDCP1 blood levels, when combined with smoking history, gave an AUC receiver operator characteristic of 0.75. Analysis of transcripts in peripheral blood cells suggested a Wnt/β-catenin signaling-based mechanism for CDCP1 in tumorigenesis providing biologic plausibility. CDCP1 now joins the ranks of other potential blood-based lung cancer screening biomarkers (including epithelial tumor marker proteins, tumor-associated miRNA, antitumor antibodies, and tumor-specific DNA methylation) that need validation in future clinical trials. Further exploration of how CDCP1 levels might be integrated into current lung cancer screening programs, including both detection of lung cancer, and evaluation of the need for invasive biopsies, as well as how CDCP1 performs in different racial populations, is warranted.See related article by Dagnino et al., p. 3738.

Selection of individuals for lung cancer screening based on risk prediction model performance and economic factors - The Ontario experience

INTRODUCTION

Randomized controlled trials have shown that screening with computed tomography reduces lung cancer mortality but is most effective when applied to high-risk individuals. Accurate lung cancer risk prediction models effectively select individuals for screening. Few pilots or programs have implemented risk models for enrolling individuals for screening in real-world, population-based settings. This report describes implementation of the PLCOm2012 risk prediction model in the Ontario Health (Cancer Care Ontario) lung cancer screening Pilot.

METHODS

In the Pilot's Health Technology Assessment, 576 categorical age/pack-years/quit-years scenarios were evaluated using MISCAN microsimulation modeling and cost-effectiveness analyses. A preferred model was selected which provided the most life-years gained per cost. The PLCOm2012 was compared to the preferred MISCAN scenario at a threshold that yielded the same number eligible (risk ≥2.0 %/6-years).

RESULTS

The PLCOm2012 had significantly higher sensitivity and predictive value (68.1 % vs 59.6 %, p < 0.0001; 4.90 % vs 4.29 %, p = 0.044), and an Expert Panel selected it for use in the Pilot. The Pilot cancer detection rate was significantly higher than in the NLST (p = 0.009) or NELSON (p = 0.003) and there was a significant shift to early stage compared to historical Ontario Cancer Registry statistics (p < 0.0001). Pre- and post-Pilot evaluations found that conducting quality risk assessments were not excessively time consuming or difficult, and participants' satisfaction was high.

CONCLUSIONS

The PLCOm2012 was efficiently implemented in the Pilot in a real-world setting and is being used to transition into a provincial program. Compared to categorical age/pack-years/quit-years criteria, risk assessment using the PLCOm2012 can lead to effective and efficient screening.

Risk Prediction Model Versus United States Preventive Services Task Force Lung Cancer Screening Eligibility Criteria: Reducing Race Disparities

INTRODUCTION

Disparities exist in lung cancer outcomes between African American and white people. The current United States Preventive Services Task Force (USPSTF) lung cancer screening eligibility criteria, which is based solely on age and smoking history, may exacerbate racial disparities. We evaluated whether the PLCOm2012 risk prediction model more effectively selects African American ever-smokers for screening.

METHODS

Lung cancer cases diagnosed between 2010 and 2019 at an urban medical center serving a racially and ethnically diverse population were retrospectively reviewed for lung cancer screening eligibility based on the USPSTF criteria versus the PLCOm2012 model.

RESULTS

This cohort of 883 ever-smokers comprised the following racial and ethnic makeup: 258 white (29.2%), 497 African American (56.3%), 69 Hispanic (7.8%), 24 Asian (2.7%), and 35 other (4.0%). Compared with the USPSTF criteria, the PLCOm2012 model increased the sensitivity for the African American cohort at lung cancer risk thresholds of 1.51%, 1.70%, and 2.00% per 6 years (p < 0.0001). For example, at the 1.70% risk threshold, the PLCOm2012 model identified 71.3% African American cases, whereas the USPSTF criteria only identified 50.3% (p < 0.0001). In contrast, in case of whites there was no difference (66.0% versus 62.4%, respectively [p = 0.203]). Of the African American ever-smokers who were PLCO1.7%-positive and USPSTF-negative, the criteria missed from the USPSTF were those with pack-years less than 30 (67.7%), quit time of greater than 15 years (22.5%), and age less than 55 years (13.0%).

CONCLUSIONS

The PLCOm2012 model was found to be preferable over the USPSTF criteria at identifying African American ever-smokers for lung cancer screening. The broader use of this model in racially diverse populations may help overcome disparities in lung cancer screening and outcomes.