Estimating sojourn time and sensitivity of screening for ovarian cancer using a Bayesian framework.

Background: Ovarian cancer is among the leading causes of gynecologic cancer-related death. Past ovarian cancer screening trials using combination of cancer antigen 125 testing and transvaginal ultrasound failed to yield statistically significant mortality reduction. Estimates of ovarian cancer sojourn time-that is, the period from when the cancer is first screen detectable until clinical detection-may inform future screening programs.

Recommendations to Improve Management of Incidental Pulmonary Nodules in Canada: Expert Panel Consensus.

Incidental pulmonary nodules (IPN) are common radiologic findings, yet management of IPNs is inconsistent across Canada. This study aims to improve IPN management based on multidisciplinary expert consensus and provides recommendations to overcome patient and system-level barriers. A modified Delphi consensus technique was conducted.

Risk-based lung cancer screening performance in a universal healthcare setting.

Globally, lung cancer is the leading cause of cancer death. Previous trials demonstrated that low-dose computed tomography lung cancer screening of high-risk individuals can reduce lung cancer mortality by 20% or more. Lung cancer screening has been approved by major guidelines in the United States, and over 4,000 sites offer screening.

Risk prediction models for lung cancer in people who have never smoked: a protocol of a systematic review.

Background: Lung cancer is one of the most commonly diagnosed cancers and the leading cause of cancer-related death worldwide. Although smoking is the primary cause of the cancer, lung cancer is also commonly diagnosed in people who have never smoked. Currently, the proportion of people who have never smoked diagnosed with lung cancer is increasing.

Radiomics analysis to predict pulmonary nodule malignancy using machine learning approaches.

Background: Low-dose CT screening can reduce lung cancer-related mortality. However, most screen-detected pulmonary abnormalities do not develop into cancer and it often remains challenging to identify malignant nodules, particularly among indeterminate nodules. We aimed to develop and assess prediction models based on radiological features to discriminate between benign and malignant pulmonary lesions detected on a baseline screen.

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.

Risk model-based management for second primary lung cancer among lung cancer survivors through a validated risk prediction model.

Background: Recent therapeutic advances and screening technologies have improved survival among patients with lung cancer, who are now at high risk of developing second primary lung cancer (SPLC). Recently, an SPLC risk-prediction model (called SPLC-RAT) was developed and validated using data from population-based epidemiological cohorts and clinical trials, but real-world validation has been lacking. The predictive performance of SPLC-RAT was evaluated in a hospital-based cohort of lung cancer survivors.

Sensitivity of US Preventive Services Task Force and PLCOm2012 lung cancer screening eligibility criteria in individuals with lung cancer in South Dakota self-reporting as Indigenous and non-Indigenous.

Background: Lung cancer is the leading cause of cancer deaths. Screening individuals who are at elevated risk using low-dose computed tomography reduces lung cancer mortality by ≥20%. Individuals who have community-based factors that contribute to an increased risk of developing lung cancer have high lung cancer rates and are diagnosed at younger ages.

Integrating Smoking Cessation Into Low-Dose Computed Tomography Lung Cancer Screening: Results of the Ontario, Canada Pilot.

Introduction: Low-dose computed tomography screening in high-risk individuals reduces lung cancer mortality. To inform the implementation of a provincial lung cancer screening program, Ontario Health undertook a Pilot study, which integrated smoking cessation (SC).

Methods: The impact of integrating SC into the Pilot was assessed by the following: rate of acceptance of a SC referral; proportion of individuals who were currently smoking cigarettes and attended a SC session; the quit rate at 1 year; change in the number of quit attempts; change in Heaviness of Smoking Index; and relapse rate in those who previously smoked.

Air Pollution and Lung Cancer: A Review by International Association for the Study of Lung Cancer Early Detection and Screening Committee.

Introduction: The second leading cause of lung cancer is air pollution. Air pollution and smoking are synergistic. Air pollution can worsen lung cancer survival.

Fifty-year forecasts of daily smoking prevalence: can Australia reach 5% by 2030?

Objective: To compare 50-year forecasts of Australian tobacco smoking rates in relation to trends in smoking initiation and cessation and in relation to a national target of ≤5% adult daily prevalence by 2030.

Methods: A compartmental model of Australian population daily smoking, calibrated to the observed smoking status of 229 523 participants aged 20-99 years in 26 surveys (1962-2016) by age, sex and birth year (1910-1996), estimated smoking prevalence to 2066 using Australian Bureau of Statistics 50-year population predictions. Prevalence forecasts were compared across scenarios in which smoking initiation and cessation trends from 2017 were continued, kept constant or reversed.

Evaluation of the accuracy of the PLCO 6-year lung cancer risk prediction model among smokers in the CARTaGENE population-based cohort.

Background: The PLCO prediction tool for risk of lung cancer has been proposed for a pilot program for lung cancer screening in Quebec, but has not been validated in this population. We sought to validate PLCO in a cohort of Quebec residents, and to determine the hypothetical performance of different screening strategies.

Methods: We included smokers without a history of lung cancer from the population-based CARTaGENE cohort.

Economic impact of using risk models for eligibility selection to the International lung screening Trial.

Objectives: Using risk models as eligibility criteria for lung screening can reduce race and sex-based disparities. We used data from the International Lung Screening Trial(ILST; NCT02871856) to compare the economic impact of using the PLCOm2012 risk model or the US Preventative Services' categorical age-smoking history-based criteria (USPSTF-2013).

Materials And Methods: The cost-effectiveness of using PLCOm2012 versus USPSTF-2013 was evaluated with a decision analytic model based on the ILST and other screening trials.

Updated cost-effectiveness analysis of lung cancer screening for Australia, capturing differences in the health economic impact of NELSON and NLST outcomes.

Background: A national, lung cancer screening programme is under consideration in Australia, and we assessed cost-effectiveness using updated data and assumptions.

Methods: We estimated the cost-effectiveness of lung screening by applying screening parameters and outcomes from either the National Lung Screening Trial (NLST) or the NEderlands-Leuvens Longkanker Screenings ONderzoek (NELSON) to Australian data on lung cancer risk, mortality, health-system costs, and smoking trends using a deterministic, multi-cohort model. Incremental cost-effectiveness ratios (ICERs) were calculated for a lifetime horizon.

Lung Cancer Absolute Risk Models for Mortality in an Asian Population using the China Kadoorie Biobank.

Background: Lung cancer is the leading cause of cancer mortality globally. Early detection through risk-based screening can markedly improve prognosis. However, most risk models were developed in North American cohorts of smokers, whereas less is known about risk profiles for never-smokers, which represent a growing proportion of lung cancers, particularly in Asian populations.

Race & sex disparities related to low-dose computed tomography lung cancer screening eligibility criteria: A lung cancer cases review.

Introduction: The United States Preventive Services Task Force (USPSTF) recommendations do not account for race and sex differences in lung cancer risk. We compared the sensitivity for finding lung cancer cases eligible for lung cancer screening (LCS) by USPSTF 2013 recommendations versus the PLCOm2012 model at an equivalent threshold.

Methods: Using Georgetown University Hospital tumor registry, we identified lung cancer cases (≥55 years old) between 2014 and 2018.

Racial and Ethnic Disparities in Lung Cancer Screening by the 2021 USPSTF Guidelines Versus Risk-Based Criteria: The Multiethnic Cohort Study.

Background: In 2021, the US Preventive Services Task Force (USPSTF) revised its lung cancer screening guidelines to expand screening eligibility. We evaluated screening sensitivities and racial and ethnic disparities under the 2021 USPSTF criteria vs alternative risk-based criteria in a racially and ethnically diverse population.

Methods: In the Multiethnic Cohort, we evaluated the proportion of ever-smoking lung cancer cases eligible for screening (ie, screening sensitivity) under the 2021 USPSTF criteria and under risk-based criteria through the PLCOm2012 model (6-year risk ≥1.

Delivery of Cancer Care in Ontario, Canada, During the First Year of the COVID-19 Pandemic.

Importance: The COVID-19 pandemic has impacted cancer systems worldwide. Quantifying the changes is critical to informing the delivery of care while the pandemic continues, as well as for system recovery and future pandemic planning.

Objective: To quantify change in the delivery of cancer services across the continuum of care during the COVID-19 pandemic.

Lung cancer screening use and implications of varying eligibility criteria by race and ethnicity: 2019 Behavioral Risk Factor Surveillance System data.

Background: In 2021, the US Preventive Services Task Force (USPSTF) expanded the eligibility criteria for low-dose computed tomographic lung cancer screening (LCS) to reduce racial disparities that resulted from the 2013 USPSTF criteria. The annual LCS rate has risen slowly since the 2013 USPSTF screening recommendations. Using the 2019 Behavioral Risk Factor Surveillance System (BRFSS), this study 1) describes LCS use in 2019, 2) compares the percent eligible for LCS using the 2013 versus 2021 USPSTF criteria, and 3) determines the percent eligible using the more detailed PLCOm2012 risk-prediction model.

Blood-Based Biomarker Panel for Personalized Lung Cancer Risk Assessment.

Purpose: To investigate whether a panel of circulating protein biomarkers would improve risk assessment for lung cancer screening in combination with a risk model on the basis of participant characteristics.

Methods: A blinded validation study was performed using prostate lung colorectal ovarian (PLCO) Cancer Screening Trial data and biospecimens to evaluate the performance of a four-marker protein panel (4MP) consisting of the precursor form of surfactant protein B, cancer antigen 125, carcinoembryonic antigen, and cytokeratin-19 fragment in combination with a lung cancer risk prediction model (PLCO) compared with current US Preventive Services Task Force (USPSTF) screening criteria. The 4MP was assayed in 1,299 sera collected preceding lung cancer diagnosis and 8,709 noncase sera.

USPSTF2013 versus PLCOm2012 lung cancer screening eligibility criteria (International Lung Screening Trial): interim analysis of a prospective cohort study.

Background: Lung cancer is a major health problem. CT lung screening can reduce lung cancer mortality through early diagnosis by at least 20%. Screening high-risk individuals is most effective.