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. In this study of lung cancer in South Dakota, the authors compared the sensitivity of screening eligibility criteria for self-reported Indigenous race and evaluated the need for screening at younger ages. METHODS: US Preventive Services Task Force (USPSTF) 2013 and 2021 (USPSTF2013 and USPSTF2021) criteria and two versions of the PLCOm2012 risk-prediction model (based on the 2012 Prostate, Lung, Colorectal, and Ovarian [PLCO] Cancer Screening Trial), one with a predictor for race and one without, were applied at USPSTF-equivalent thresholds of ≥1.7% in 6 years and ≥1.0% in 6 years to 1565 individuals who were sequentially diagnosed with lung cancer (of whom 12.7% self-reported as Indigenous) at the Monument Health Cancer Care Institute in South Dakota (2010-2019). RESULTS: Eligibility sensitivities of USPSTF criteria did not differ significantly between individuals who self-reported their race as Indigenous and those who did not (p > .05). Sensitivities of both PLCOm2012 models were significantly higher than comparable USPSTF criteria. The sensitivity of USPSTF2021 criteria was 66.1% and, for comparable PLCOm2012 models with and without race, sensitivity was 90.7% and 89.6%, respectively (both p < .001); 1.4% of individuals were younger than 50 years, and proportions did not differ by Indigenous classification (p = .518). CONCLUSIONS: Disparities in screening eligibility were not observed for individuals who self-reported their race as Indigenous. USPSTF criteria had lower sensitivities for lung cancer eligibility. Both PLCOm2012 models had high sensitivities, with higher sensitivity for the model that included race. The PLCOm2012noRace model selected effectively in this population, and screening individuals younger than 50 years did not appear to be justified. PLAIN LANGUAGE SUMMARY: Lung cancer is the leading cause of cancer deaths. Studies show that using low-dose computed tomography scans to screen people who smoke or who used to smoke and are at elevated risk for lung cancer reduces lung cancer deaths. This study of 1565 individuals with lung cancer in South Dakota compared screening eligibility using US Preventive Services Task Force (USPSTF) criteria and a lung cancer risk-prediction model (PLCOm2012; from the 2012 Prostate, Lung, Colorectal, and Ovarian [PLCO] Cancer Screening Trial). The model had higher sensitivity and picked more people with lung cancer to screen compared with USPSTF criteria. Eligibility sensitivities were similar for individuals who self-reported as Indigenous versus those who did not between USPSTF criteria and the model.

Prediction of true positive lung cancers in individuals with abnormal suspicious chest radiographs: a prostate, lung, colorectal, and ovarian cancer screening trial study.

INTRODUCTION: Chest radiographs are routinely employed in clinical practice. Radiographic findings that are abnormal suspicious (AS) for lung cancer occur commonly. The majority of AS radiographic abnormalities are not cancer. This study identifies predictors of true positive (TP) AS and presents models for estimating the probability of lung cancer. METHODS: This is a prospective cohort study nested in the randomized National Cancer Institute's Prostate Lung Colorectal Ovarian Cancer Screening Trial (PLCO). First-time AS screens in the screening arm of the PLCO were studied. Associations between nonradiographic and radiographic factors, and TP AS were evaluated by multiple logistic regression. RESULTS: The PLCO intervention arm had 77,465 individuals, of whom 12,314 were AS and of these 232 (1.9%) had lung cancer (were TP). Important independent predictors of TP were older age, lower education, greater pack years and duration smoking history, body mass index <30, family history of lung cancer, lung nodule, lung mass, unilateral mediastinal or hilar lymphadenopathy, lung infiltrate, and upper/middle chest AS location. The model including these variables had a receiver operator characteristic area under the curve (ROC AUC) of 86.4%. This model excluding the smoking variables had an ROC AUC of 77.1% and excluding all nonradiographic variables had an ROC AUC of 73.3% (p < 0.0001 for all these model differences). Smoking and nonsmoking nonradiographic variables significantly added to prediction. CONCLUSION: This study identifies important nonradiographic and radiographic predictors of lung cancer, and presents an accurate model for estimating the probability of lung cancer in individuals with suspicious radiographs. These findings may be of value for screening, research, and patient and clinician decision-making.