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ImportanceLow-dose computed tomography (LDCT) lung screening has been shown to reduce lung cancer mortality. Significant incidental findings (SIFs) have been widely reported in patients undergoing LDCT lung screening. However, the exact nature of these SIF findings has not been described.ObjectiveTo describe SIFs reported in the LDCT arm of the National Lung Screening Trial and classify SIFs as reportable or not reportable to the referring clinician (RC) using the American College of Radiology’s white papers on incidental findings.Design, Setting, and ParticipantsThis was a retrospective case series study of 26 455 participants in the National Lung Screening Trial who underwent at least 1 screening examination with LDCT. The trial was conducted from 2002 to 2009, and data were collected at 33 US academic medical centers.Main Outcomes and MeasuresSignificant incident findings were defined as a final diagnosis of a negative screen result with significant abnormalities that were not suspicious for lung cancer or a positive screen result with emphysema, significant cardiovascular abnormality, or significant abnormality above or below the diaphragm.ResultsOf 26 455 participants, 10 833 (41.0%) were women, the mean (SD) age was 61.4 (5.0) years, and there were 1179 (4.5%) Black, 470 (1.8%) Hispanic/Latino, and 24 123 (91.2%) White individuals. Participants were scheduled to undergo 3 screenings during the course of the trial; the present study included 75 126 LDCT screening examinations performed for 26 455 participants. A SIF was reported for 8954 (33.8%) of 26 455 participants who were screened with LDCT. Of screening tests with a SIF detected, 12 228 (89.1%) had a SIF considered reportable to the RC, with a higher proportion of reportable SIFs among those with a positive screen result for lung cancer (7632 [94.1%]) compared with those with a negative screen result (4596 [81.8%]). The most common SIFs reported included emphysema (8677 [43.0%] of 20 156 SIFs reported), coronary artery calcium (2432 [12.1%]), and masses or suspicious lesions (1493 [7.4%]). Masses included kidney (647 [3.2%]), liver (420 [2.1%]), adrenal (265 [1.3%]), and breast (161 [0.8%]) abnormalities. Classification was based on free-text comments; 2205 of 13 299 comments (16.6%) could not be classified. The hierarchical reporting of final diagnosis in NLST may have been associated with an overestimate of severe emphysema in participants with a positive screen result for lung cancer.Conclusions and RelevanceThis case series study found that SIFs were commonly reported in the LDCT arm of the National Lung Screening Trial, and most of these SIFs were considered reportable to the RC and likely to require follow-up. Future screening trials should standardize SIF reporting.

To our knowledge, no prior multicenter clinical trial has reported interobserver agreement of (18)F-FDG PET/CT scans for staging of clinical N0 neck in head and neck cancer. Methods: A total of 287 participants were recruited. For visual analysis, positive nodal uptake of (18)F-FDG was defined as uptake visually greater than activity seen in the blood pool. Results: The negative predictive value of the (18)F-FDG PET/CT for N0 clinical neck was 86% or above for visual assessment (95% CI, 86%–88%) for the 2 central readers and above 90% (95% CI, 90%–95%) for SUV(max) for central reads and site reads dichotomized at the optimal cutoff value of 1.8 and the prespecified cutoff value of 3.5, respectively. The κ coefficients between the 2 expert readers and between central reads and site reads varied between 0.53 and 0.78. Conclusion: The NPV of the (18)F-FDG PET/CT for N0 clinical neck was 86% or above for visual assessment and above 90% for SUV(max) cut points of 1.8 and 3.5 with moderate to substantial agreements.

6597 Background: We prospectively assessed financial burden (FB) due to treatment costs among patients with colorectal cancer (CRC) recruited by NCI Community Oncology Research Program (NCORP) sites. Methods: Patients with newly diagnosed CRC treated with curative intent enrolled through NCORP sites and completed the FACIT Comprehensive Score for Financial Toxicity (COST) instrument at 0-, 3, 6, and 12 months. Higher COST score (range 0-44) indicates greater financial well-being. Effects of demographic, clinical, self-efficacy and safety net affiliation on FB were assessed using linear mixed modeling with compound symmetry covariance structure to account for measurement correlation from the same subject. Results: In 450 patients (mean age 61, 47% female, 84% white, 64% colon, 31% rectal) attrition was comparable across demographics, clinical variables and baseline FB. Higher COST score was linearly correlated with time. Increasing age, income less than $60,000 (vs. less than $29,999), higher self-efficacy, and higher neighborhood socioeconomic status (nSES) predicted a higher COST score; these effects were not moderated by time. Chemotherapy receipt, insurance type, and treatment at a safety net hospital did not predict COST score. Conclusions: Among those with CRC treated with curative intent in community settings, FB improves over the 12 months post diagnosis. Individual and neighborhood level social determinants of health are protective from financial fragility.[Table: see text]

Purpose Optimization of the clinical management of screen-detected lung nodules is needed to avoid unnecessary diagnostic interventions. Herein we demonstrate the potential value of a novel radiomics-based approach for the classification of screen-detected indeterminate nodules. Material and methods Independent quantitative variables assessing various radiologic nodule features such as sphericity, flatness, elongation, spiculation, lobulation and curvature were developed from the NLST dataset using 726 indeterminate nodules (all ≥ 7 mm, benign, n = 318 and malignant, n = 408). Multivariate analysis was performed using least absolute shrinkage and selection operator (LASSO) method for variable selection and regularization in order to enhance the prediction accuracy and interpretability of the multivariate model. The bootstrapping method was then applied for the internal validation and the optimism-corrected AUC was reported for the final model. Results Eight of the originally considered 57 quantitative radiologic features were selected by LASSO multivariate modeling. These 8 features include variables capturing Location: vertical location (Offset carina centroid z), Size: volume estimate (Minimum enclosing brick), Shape: flatness, Density: texture analysis (Score Indicative of Lesion/Lung Aggression/Abnormality (SILA) texture), and surface characteristics: surface complexity (Maximum shape index and Average shape index), and estimates of surface curvature (Average positive mean curvature and Minimum mean curvature), all with P