Individuals For Lung Cancer Screening Research Articles

The risk and benefit profiles of US-eligible lung cancer screening attendees vs nonattendees

Abstract Background The US Preventive Services Task Force (USPSTF) recommend lung cancer screening for individuals aged 50-80 years with at least 20 pack-years and no more than 15 quit-years, but uptake is low. The risk and benefit profiles of screening attendees are unknown; consequently, the impact and lost opportunity of ongoing lung cancer screening in the United States remains unclear. Methods We estimated lung cancer death risk (using the Lung Cancer Death Risk Assessment Tool) and life gained from screening (using the Life Years Gained From Screening-Computed Tomography model) for individuals aged 50-79 years who ever-smoked in the US representative 2022 Behavioral Risk Factor Surveillance System. We compared lung cancer death risk and life gained among USPSTF-eligible individuals by screening status (self-reported screened vs not screened in past year) and estimated the number of lung cancer deaths averted and life-years gained under current screening levels and if everyone eligible was screened. Results USPSTF eligibility was 33.7% (95% confidence interval [CI] = 33.1% to 34.4%), of whom 17.9% (95% CI = 17.0% to 18.8%) self-reported screening. Screening uptake increased with increasing lung cancer death risk quintile (Q1 = 5.2%, 95% CI = 3.0% to 8.8%; Q5 = 21.8%, 95% CI = 20.3% to 23.3%) and life-gain from screening quintile (Q1 = 6.2%, 95% CI = 3.8% to 9.9%; Q5 = 20.8%, 95% CI = 19.5% to 22.2%). Screened individuals had higher lung cancer death risk (risk ratio [RR] = 1.35, 95% CI = 1.26 to 1.46) and life-years gained (RR = 1.19, 95% CI = 1.12 to 1.25) than unscreened individuals. Currently, screening averts 19 306 lung cancer deaths and gains 237 564 life-years; screening everyone eligible would additionally avert 56 956 lung cancer deaths and gain 751 850 life-years. Two-thirds of USPSTF lung-eligible women were up to date with breast cancer screening, but only 17.3% attended lung screening in the past year. Conclusions Eligible screening attendees had higher lung cancer death risk and benefit from screening. Higher rates of screening could substantially increase the number of lung cancer deaths prevented.

The Benefits and Harms of Lung Cancer Screening in Individuals With Comorbidities

IntroductionIndividuals with a history of smoking and a high risk of lung cancer often have a high prevalence of smoking-related comorbidities. The presence of these comorbidities might alter the benefit-to-harm ratio of lung cancer screening by influencing the risk of complications, quality of life, and competing risks of death. Nevertheless, individuals with chronic diseases are underrepresented in screening clinical trials. In this study, we use microsimulation modeling to determine the impact of chronic diseases on lung cancer benefits and harms. MethodsWe extended a validated lung cancer screening microsimulation model that comprehensively recapitulates an individual’s lung cancer development, progression, detection, follow-up, treatment, and survival. We parameterized the model to reflect the impact of chronic diseases on complications from invasive testing, quality of life, and mortality in individuals in five-year age categories between the ages of 50 and 80 years. Outcomes included life-years (LY) gained per 100,000 in patients with chronic obstructive pulmonary disease, diabetes mellitus, heart disease, and history of stroke compared with screening-eligible individuals without comorbidities. ResultsAmong individuals between the ages of 50 and 54 years, we found that the presence of a comorbidity altered the LY gained from screening per 100,000 individuals depending on the comorbidity: 4296 LY with no comorbidities; 3462 LY, 3260 LY, 3031 LY, and 3257 LY with chronic obstructive pulmonary disease, heart disease, diabetes mellitus, and stroke, respectively. We observed greater reductions in LY gained in individuals with two comorbidities; we observed similar patterns for individuals between the ages of 55 and 59 years, 60 and 64 years, 65 and 69 years, 70 and 74 years, and 75 and 80 years. ConclusionsComorbidities reduce LY gained from screening per 100,000 compared with no comorbidities, and our results can be used by clinicians when discussing the benefits and harms of screening in their patients with comorbidities.

MA19.05 Performance of Risk Prediction Models to Select Individuals for Lung Cancer Screening in the European Population

MA19.05 Performance of Risk Prediction Models to Select Individuals for Lung Cancer Screening in the European Population

Newly diagnosed lung cancer in hospitalized patients during the COVID-19 pandemic: How well are LDCTs utilized?

10624 Background: Medicare covers the cost of lung cancer screening in individuals aged 50-77 years with a high-risk smoking history. The COVID-19 pandemic caused a decrease in outpatient visits and cancer screenings. The objective of this study was to provide a comparison between the multitude of lung cancer diagnoses upon presentation to the hospital predating and during the COVID-19 pandemic in patients with varying insurance types. Methods: We retrospectively reviewed fifteen hospitals in West Florida with newly diagnosed lung cancer during the pre-pandemic period from March 2019-August 2020 and the pandemic period from March 2020- August 2021. These patients were split into subcategories based on insurance type: private medical insurance; Medicare; Medicaid; no insurance; and other. The chi-square test was used for statistical analysis. Results: A total of 1409 inpatients, 676 during the pre-pandemic and 733 during the pandemic, were identified with a new diagnosis of lung cancer upon presentation to the hospital. 74% of the pandemic population and 77% of the pre-pandemic population were patients insured with Medicare. Hospitals without LDCT screening programs were found to have 317 lung cancer diagnoses during the pre-pandemic period and 292 during the pandemic period. Hospitals with LDCT screening programs were found to have 359 lung cancer diagnoses during the pre-pandemic period and 441 during the pandemic period. Chi-square tests comparing pre-pandemic to pandemic did not show a p-value of statistical significance. Conclusions: A substantial number of patients with Medicare were newly diagnosed with lung cancer during the pre-pandemic and pandemic periods compared to patients with other insurance types. Although Medicare provides LDCT screening for lung cancer in high-risk populations at no out-of-pocket cost, about 75% of West Florida’s patients were diagnosed with lung-cancer upon presentation to the hospital. Hospitals with LDCT screening programs had an increase in cancer diagnoses during the pandemic, consistent with prior research data. Instead, the pandemic did not seem to affect hospitals without LDCT screening programs. We need to address the barriers in implementation of LDCT hospital-based screening programs to increase early diagnoses and decrease hospitalization diagnoses, leading to improved lung cancer mortality. [Table: see text]

Review of the future of lung cancer screening

: Lung cancer screening has progressed greatly in the last two decades since the initial publication of Early Lung Cancer Action Project (ELCAP) in 1999. Since then, large randomized trials, the National Lung Screening Trial (NLST) and NELSON studies, have also shown the benefit of lung cancer screening with CT, and it is now widely available. There are many areas for improving the benefit of screening by refining the eligibility criteria, continued optimization of the screening regimen, identifying other related diseases, and improved treatment. As artificial intelligence (AI) techniques continue to improve, an automated report of all diseases can be produced from the low-dose CT scan. New screening tests are being developed for lung cancer including blood-based tests. There is growing recognition that use of risk factor-based criteria which dichotomize age and pack-years of smoking to select eligible individuals for screening may not be the most efficient and may also lead to increased lung cancer disparity. Continued research will focus on optimal approaches for selecting high risk individuals for lung cancer screening and thus hopefully expand eligibility criteria beyond the current criteria which include only 20% of lung cancer patients. With the increase in early stage lung cancers identified from lung cancer screening, a key focus of ongoing research is the treatment of these cancers.

Lung Cancer Screening in Individuals With and Without Lung-Related Comorbidities

Comorbidities characterize the underlying health status of individuals. In the context of lung cancer screening (LCS), lung-related comorbidities may influence the observed benefits and harms. To compare the characteristics of individuals undergoing LCS, the LCS examination result, the cancer detection rate (CDR), and the false-positive rate (FPR) in those with and without lung-related comorbidities. A prospective cohort study was conducted in 5 academic and community screening sites across North Carolina from January 1, 2014, to November 7, 2020. Participants included 611 individuals screened for lung cancer who completed a 1-page health history questionnaire. Presence of at least 1 self-reported lung-related comorbidity, including chronic obstructive pulmonary disease, chronic bronchitis, emphysema, asthma, bronchiectasis, pulmonary fibrosis, silicosis, asbestosis, sarcoidosis, and tuberculosis. The LCS examination result was determined from the radiologist's Lung Imaging Reporting and Data System assessment (negative, 1 or 2; positive, 3 or 4). The age-adjusted CDR and FPR were calculated per 100 LCS examinations, using binary logistic regression. Among the 611 individuals screened for lung cancer (308 men [50.4%]; mean [SD] age, 64 [6.2] years), 335 (54.8%) had at least 1 lung-related comorbidity. Individuals with vs without lung-related comorbidities were more likely to be female than male (180 of 335 [53.7%] vs 123 of 276 [44.6%]; P = .02), White vs non-White race (275 of 326 [84.4%] vs 193 of 272 [71.0%]; P < .001), and have high school or less education vs greater than a high school education (108 of 231 [46.7%] vs 64 of 208 [30.8%]; P = .001). There were no significant differences in the proportion of positive LCS examinations in those with vs without a lung-related comorbidity at baseline (37 [16.0%] vs 22 [11.1%]; P = .14) or subsequent (40 [12.3%] vs 23 [10.6%]; P = .54) LCS examination. Comparing individuals with vs without lung-related comorbidities, there was no statistically significant difference in the CDR (1.6 vs 1.9 per 100; P = .73) or FPR (13.0 vs 9.3 per 100; P = .16). Of the 17 individuals with lung cancer, 13 patients (76.5%) were diagnosed with stage I lung cancer. The findings of this study suggest that individuals with self-reported lung-related comorbidities undergoing LCS were more likely to be female, of White race, and have less education than those without lung-related comorbidity. Although no statistically significant differences in the proportion of positive examinations, CDR, or FPR by self-reported lung comorbidities were noted, additional studies with larger numbers of individuals undergoing screening are needed to understand LCS outcomes in those with lung-related comorbidities.

EP01.04-002 The Impact of Enforcing a Structure in Lung Cancer Screening Strategy on the Effectiveness and Efficiency of the Screening Program

In 2021, the US Preventive Services Task Force (USPSTF) recommended annual lung cancer screening for individuals aged 50-80 years, who have at least 20 pack-year smoking history and currently smoke or have quit smoking within 15 years. The USPSTF strategy is practical and easy to implement, but suboptimal in terms of effectiveness and efficiency. Recently, the ENGAGE decision-analytic screening framework has been developed offering dynamic personalized lung cancer screening schedules that maximize individuals’ expected quality-adjusted life years (QALY).

Referring high-risk individuals for lung cancer screening: A systematic review of interventions with healthcare professionals.

This systematic review described the effect of interventions aimed at helping Healthcare Professionals refer high-risk individuals for lung cancer screening. Primary outcomes included: lung cancer detection, screening for lung cancer, lung cancer treatments received and lung cancer mortality. Healthcare professionals' knowledge and awareness of lung cancer screening served as secondary outcomes. Experimental studies published between January 2016 and 2021 were included. The search was conducted in MEDLINE, CINAHL, ERIC, PsycARTICLES, PsycInfo and Psychology and Behavioral Sciences Collection. The quality of the included studies was assessed using the Mixed Methods Appraisal Tool and the level of evidence was assessed using the Scottish Intercollegiate Guidelines Network grading system. Nine studies were included. Nurse navigation, electronic prompts for lung cancer screening and shared decision-making helped improve patient outcomes. Specialist screenings yielded more significant incidental findings and a higher percentage of Lung-RADS 1 results (i.e. no nodules/definitely benign nodules), while Primary Care Physician screenings were associated with higher numbers of Lung-RADS 2 results (i.e. benign nodules with a very low likelihood to becoming malignant). An increase in Healthcare Professionals' knowledge and awareness of lung cancer screening was achieved using group-based learning compared to lecture-based education delivery. The effectiveness of Nurse navigation is evident, as are the benefits of adequate training, shared decision-making, as well as a structured, clear and well-understood referral processes supported by the use of electronic system-incorporated prompts.

Risk-based lung cancer screening eligibility criteria: towards implementation.

Retrospective studies have consistently shown that risk-prediction models are superior at identifying individuals eligible for lung cancer screening compared with criteria based on combinations of age accumulated pack-years and years since smoking cessation (ie, pack-year criteria). 1 ten Haaf K Jeon J Tammemägi MC et al. Risk prediction models for selection of lung cancer screening candidates: a retrospective validation study. PLOS Med. 2017; 14e1002277 Crossref Scopus (149) Google Scholar Although some studies advocate the use of risk-prediction models in existing and future screening programmes, others have been reserved in advocating their use because of the absence of evidence from prospective studies. 2 Force USPSTScreening for lung cancer: US Preventive Services Task Force recommendation statement. JAMA. 2021; 325: 962-970 Crossref PubMed Scopus (228) Google Scholar , 3 Tammemägi MC Darling GE Schmidt H et al. Selection of individuals for lung cancer screening based on risk prediction model performance and economic factors—the Ontario experience. Lung Cancer. 2021; 156: 31-40 Summary Full Text Full Text PDF PubMed Scopus (3) Google Scholar In The Lancet Oncology, Martin Tammemägi and colleagues 4 Tammemägi MC Ruparel M Tremblay A et al. USPSTF2013 versus PLCOm2012 lung cancer screening eligibility criteria (International Lung Screening Trial): interim analysis of a prospective cohort study. Lancet Oncol. 2021; (published online Dec 10.)https://doi.org/10.1016/S1470-2045(21)00590-8 Summary Full Text Full Text PDF PubMed Google Scholar report an interim analysis of the International Lung Screening Trial (ILST), a large prospective multinational trial that compares a risk-prediction model with pack-year criteria. The ILST compared the sensitivity of the US Preventive Services Task Force (USPSTF) 2013 eligibility criteria (aged 55–80 years, ≥30 pack-years smoking history, and ≤15 years since smoking cessation) with the PLCOm2012 risk model when selecting a similar number of eligible individuals (aged 55–80 years with a PLCOm2012 risk threshold ≥1·7%). The sensitivity of the PLCOm2012 model to identify individuals who develop lung cancer was 15·8 percentage points higher than that of the USPSTF2013 criteria (162 [94·7%; 95% CI 90·2–97·6] of 171 individuals vs 135 [78·9%; 72·1–84·8] of 171 individuals; p=0·0001). Analyses that included individuals not meeting either the PLCOm2012 risk threshold of at least 1·7% or USPSTF2013-positive criteria also showed superior sensitivity (162 [85·3%; 79·4–90·0] of 190 individuals vs 135 [71·1%; 64·0–77·4] of 190 individuals; p=0·0001) and both criteria had similar specificities (8357 [65·6%; 64·7–66·4] of 12 735 vs 8330 [65·4%; 64·5–66·2] of 12 735 individuals; p=0·72). Thus, the ILST demonstrated that the superiority of risk-prediction models over pack-year criteria is maintained in a prospective analysis. USPSTF2013 versus PLCOm2012 lung cancer screening eligibility criteria (International Lung Screening Trial): interim analysis of a prospective cohort studyPLCOm2012 appears to be more efficient than the USPSTF2013 criteria for selecting individuals to enrol into lung cancer screening programmes and should be used for identifying high-risk individuals who benefit from the inclusion in these programmes. Full-Text PDF Open Access

A risk prediction model for selecting high-risk population for computed tomography lung cancer screening in China

ObjectiveTwo large randomized controlled trials (RCTs) have demonstrated that low dose computed tomography (LDCT) screening reduces lung cancer mortality. Risk-prediction models have been proved to select individuals for lung cancer screening effectively. With the focus on established risk factors for lung cancer routinely available in general cancer screening settings, we aimed to develop and internally validated a risk prediction model for lung cancer. Materials and methodsUsing data from the Cancer Screening Program in Urban China (CanSPUC) in Henan province, China between 2013 and 2019, we conducted a prospective cohort study consisting of 282,254 participants including 126,445 males and 155,809 females. Detailed questionnaire, physical assessment and follow-up were completed for all participants. Using Cox proportional risk regression analysis, we developed the Henan Lung Cancer Risk Models based on simplified questionnaire. Model discrimination was evaluated by concordance statistics (C-statistics), and model calibration was evaluated by the bootstrap sampling, respectively. ResultsBy 2020, a total of 589 lung cancer cases occurred in the follow-up yielding an incident density of 64.91/100,000 person-years (pyrs). Age, gender, smoking, history of tuberculosis and history of emphysema were included into the model. The C-index of the model for 1-year lung cancer risk was 0.766 and 0.741 in the training set and validation set, respectively. In stratified analysis, the model showed better predictive power in males, younger participants, and former or current smoking participants. The model calibrated well across the deciles of predicted risk in both the overall population and all subgroups. ConclusionsWe developed and internally validated a simple risk prediction model for lung cancer, which may be useful to identify high-risk individuals for more intensive screening for cancer prevention.

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

IntroductionRandomized 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. MethodsIn 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). ResultsThe 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. ConclusionsThe 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.

ES12.02 Defining High Risk

ES12.02 Defining High Risk

Perspectives of family physicians towards access to lung cancer screening for individuals living with low income \u2013 a qualitative study

BackgroundIndividuals living with low income are less likely to participate in lung cancer screening (LCS) with low-dose computed tomography. Family physicians (FPs) are typically responsible for referring eligible patients to LCS; therefore, we sought to understand their perspectives on access to lung cancer screening for individuals living with low income in order to improve equity in access to LCS.MethodsA theory-informed thematic analysis was conducted using data collected from 11 semi-structured interviews with FPs recruited from three primary care sites in downtown Toronto. Data was coded using the Systems Model of Clinical Preventative Care as a framework and interpretation was guided by the synergies of oppression analytical lens.ResultsFour overarching themes describe FP perspectives on access to LCS for individuals living with low income: the degree of social disadvantage that influences lung cancer risk and opportunities to access care; the clinical encounter, where there is often a mismatch between the complex health needs of low income individuals and structure of health care appointments; the need for equity-oriented health care, illustrated by the neglect of structural origins of health risk and the benefits of a trauma-informed approach; and finally, the multiprong strategies that will be needed in order to improve equity in health outcomes.ConclusionAn equity-oriented and interdisciplinary team based approach to care will be needed in order to improve access to LCS, and attention must be given to the upstream determinants of lung cancer in order to reduce lung cancer risk.

Assessing risk-based LDCT screening strategies versus the current USPSTF lung cancer screening recommendations at an institutional setting.

e13572 Background: Lung cancer is the leading cause of cancer related deaths in men and women with 1.76 million deaths worldwide in 2018 [1]. Given its high prevalence and mortality, trials were developed to improve screening strategies. National-Lung-Screening-Trial showed a 20% relative-risk-reduction in mortality in people screened with annual low-dose-CT-scan [2] leading to the implementation of current USPSTF guidelines. We used USPSTF screening criteria to estimate the proportion of non-small cell lung cancer (NSCLC) patients that would have been screening-eligible at our institution.Upon chart review 33% of overall lung cancer patients at our institution did not meet the screening guidelines. We decided to investigate the need to modify the current screening guidelines of our institution based on individual risk assessment. Methods: We conducted a retrospective observational cohort study of the new diagnoses at Louisiana-State-University-Shreveport from 2011-2015. Patients were categorized into high-risk (groups 1 and 2), moderate risk, and low risk according to 2018 NCCN Lung Cancer Screening Guidelines Version 1.2020 [3]. To differentiate between high-risk group 2 and moderate risk, the Tammemagi lung cancer risk calculator was employed, considering 1.3% threshold of lung cancer risk over 6-year time frame [4]. According to NCCN, high-risk group 1 and 2 are eligible for annual low-dose-CT-scan. Results: 33% of overall lung cancer patients at our institution did not meet the screening guidelines criteria, among the 33% ineligible for screening, only 12.5% fell under the high-risk category based on the Tammemagi calculator. Conclusions: Despite using individual risk assessment based on Tammemagi calculator, 87.5% of lung cancer patients ineligible to current USPSTF guidelines are still missing the eligibility for screening at our institution. We believe more efficient risk prediction models have to be developed to improve selection of individuals for lung cancer screening.

Improving Lung Cancer Screening Access for Individuals With Serious Mental Illness

Lung cancer continues to be the leading cause of cancer mortality in the United States across all races and ethnicities, but it does not affect everyone equally. Individuals with serious mental illness (SMI), including schizophrenia and bipolar disorder, experience two to four times greater lung cancer mortality in part due to high rates of smoking, delays in cancer diagnosis, and inequities in cancer treatment. Additionally, adults with SMI experience patient, clinician, and health care system–level barriers to accessing cancer screening, such as cognitive deficits that impact understanding of cancer risk, higher rates of poverty and social isolation, patient-provider communication challenges, decreased access to tobacco cessation, and the fragmentation of primary care and mental health care. Despite the proven benefits and mandated coverage by public and private payers, lung cancer screening participation rates remain low among eligible patients, below 4% a year. Given disparities in other cancer screening modalities, these rates are likely to be even lower among individuals with SMI. This article provides a brief overview of current challenges in lung cancer screening and describes a pilot collaboration between radiology and psychiatry that has potential to improve access to lung cancer screening for individuals with serious mental illness.

Identifying high-risk individuals for lung cancer screening: Going beyond NLST criteria.

BackgroundThere are two main types of strategies to identify target population for lung cancer screening: 1) strategies based on age and cumulative smoking criteria, 2) risk prediction models allowing the calculation of an individual risk. The objective of this study was to compare different strategies to identify the proportion of the Spanish population at high risk of developing lung cancer, susceptible to be included in a lung cancer screening programme.MethodsCross-sectional study. We used the data of the Spanish National Interview Health Survey (ENSE) of 2011–2012 (21,006 individuals) to estimate the proportion of participants at high risk of developing lung cancer. This estimation was performed using the U.S. national lung screening trial (NLST) criteria and a 6-year prediction model (PLCOm2012), both independently and in combination.ResultsThe prevalence of individuals at high risk of developing lung cancer according to the NLST criteria was 4.9% (7.9% for men, 2.4% for women). Among the 1,034 subjects who met the NLST criteria, 533 (427 men and 106 women) had a 6-year lung cancer risk ≥2.0%. The combination of these two selection strategies showed that 2.5% of the Spanish population had a high risk of developing lung cancer. However, this selection process did not take into account different groups of subjects <75 years old having an individual risk of lung cancer ≥2%, such as heavy smokers <55 years old who were long-time former smokers, and ever-smokers having smoked <30 pack-years with other risk factors.ConclusionsFurther research is needed to determine which selection strategy achieves a higher benefit/harm ratio and to assess other prevention strategies for individuals with elevated risk for lung cancer but who do not meet the screening eligibility criteria.

Selecting high-risk individuals for lung cancer screening; the use of risk prediction models vs. simplified eligibility criteria

In 2011 the US National Lung Cancer Screening Trial (NLST) showed a 20% reduction in lung-cancer mortality among long-term heavy smokers screened by low-dose spiral computed tomography (LDCT) compared to standard X-ray diagnostics (1), and the US Prevention Services Task Force (USPSTF) recommends lung cancer screening for all individuals who meet the original NLST eligibility criteria of being 55 to 80 years of age, having smoked 30 or more pack years, and not having quit smoking more than 15 years ago.

Abstract IA17: Risk prediction modeling in lung cancer: How can we improve?

Abstract IA17: Risk prediction modeling in lung cancer: How can we improve?

Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study.

BackgroundSelection of candidates for lung cancer screening based on individual risk has been proposed as an alternative to criteria based on age and cumulative smoking exposure (pack-years). Nine previously established risk models were assessed for their ability to identify those most likely to develop or die from lung cancer. All models considered age and various aspects of smoking exposure (smoking status, smoking duration, cigarettes per day, pack-years smoked, time since smoking cessation) as risk predictors. In addition, some models considered factors such as gender, race, ethnicity, education, body mass index, chronic obstructive pulmonary disease, emphysema, personal history of cancer, personal history of pneumonia, and family history of lung cancer.Methods and findingsRetrospective analyses were performed on 53,452 National Lung Screening Trial (NLST) participants (1,925 lung cancer cases and 884 lung cancer deaths) and 80,672 Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO) ever-smoking participants (1,463 lung cancer cases and 915 lung cancer deaths). Six-year lung cancer incidence and mortality risk predictions were assessed for (1) calibration (graphically) by comparing the agreement between the predicted and the observed risks, (2) discrimination (area under the receiver operating characteristic curve [AUC]) between individuals with and without lung cancer (death), and (3) clinical usefulness (net benefit in decision curve analysis) by identifying risk thresholds at which applying risk-based eligibility would improve lung cancer screening efficacy. To further assess performance, risk model sensitivities and specificities in the PLCO were compared to those based on the NLST eligibility criteria. Calibration was satisfactory, but discrimination ranged widely (AUCs from 0.61 to 0.81). The models outperformed the NLST eligibility criteria over a substantial range of risk thresholds in decision curve analysis, with a higher sensitivity for all models and a slightly higher specificity for some models. The PLCOm2012, Bach, and Two-Stage Clonal Expansion incidence models had the best overall performance, with AUCs >0.68 in the NLST and >0.77 in the PLCO. These three models had the highest sensitivity and specificity for predicting 6-y lung cancer incidence in the PLCO chest radiography arm, with sensitivities >79.8% and specificities >62.3%. In contrast, the NLST eligibility criteria yielded a sensitivity of 71.4% and a specificity of 62.2%. Limitations of this study include the lack of identification of optimal risk thresholds, as this requires additional information on the long-term benefits (e.g., life-years gained and mortality reduction) and harms (e.g., overdiagnosis) of risk-based screening strategies using these models. In addition, information on some predictor variables included in the risk prediction models was not available.ConclusionsSelection of individuals for lung cancer screening using individual risk is superior to selection criteria based on age and pack-years alone. The benefits, harms, and feasibility of implementing lung cancer screening policies based on risk prediction models should be assessed and compared with those of current recommendations.

Pilot study on use of home telephoning to identify and recruit high-risk individuals for lung cancer screening

Widespread lung cancer screening with low-dose computed tomography is urgently needed in Europe to identify lung cancers early and reduce lung cancer deaths. The most effective method of identifying high-risk individuals and recruiting them for screening has not been determined. In the present pilot study we investigated direct telephoning to families as a way of identifying high risk individuals and recruiting them to a screening/smoking cessation program, that avoided the selection bias of voluntary screening. Families in the province of Milan, Italy, were contacted by telephone at their homes and asked about family members over 50 years who were heavy smokers (30 or more pack-years). Persons meeting these criteria were contacted and asked to participate in the program. Those who agreed were given an appointment to undergo screening and receive smoking cessation counseling. Among the 1000 contacted families, involving 2300 persons, 44 (1.9%) were eligible for LDCT screening, and 12 (27%) of these participated in the program. The cost of this recruitment strategy pilot study was around 150 euro per screened subject. We obtained useful information on the proportion of the general population eligible for lung cancer screening and the proportion of those who responded. However the cost of home telephone calling is probably too high to be practicable as a method of recruiting high risk persons for screening. Alternative recruitment methods, possibly involving family physicians practitioners, need to be investigated.