OBJECTIVE: To report the long-term follow-up of subsolid nodules (SSNs) detected in participants of a prospective low-dose CT lung cancer screening cohort, and to investigate the utility of the PanCan model in stratifying risk in baseline SSNs. METHODS: Participants underwent a baseline scan, two annual incidence scans and further follow-up scans for the detected nodules. All SSNs underwent a minimum of 2 years of follow-up (unless resolved or resected). Risk of malignancy was estimated using the PanCan model; discrimination [area under the receiver-operating characteristic curve (AUC)] and calibration (Hosmer-Lemeshow goodness-of-fit test) were assessed. The Mann-Whitney U-Wilcoxon test was used to compare estimated risk between groups. RESULTS: 70 SSNs were detected in 41 (16.0%) out of 256 total participants. Median follow-up period was 25.5 months (range 2.0-74.0 months). 29 (41.4%) SSNs were transient. Five (7.1%) SSNs were resected, all found to be Stage I lung adenocarcinoma, including one SSN stable in size for 3.0 years before growth was detected. The PanCan model had good discrimination for the 52 baseline SSNs (AUC = 0.89; 95% confidence interval 0.76-1); the Hosmer-Lemeshow goodness-of-fit test was non-significant (p = 0.27). Estimated risk was significantly higher in the baseline SSNs found to be cancer vs those not found to be cancer after 2-6 years of follow-up (p < 0.01). CONCLUSION: Our findings support a long-term follow-up approach for screen-detected SSNs for 3 years or longer. The PanCan model appeared discriminatory and well calibrated in this cohort. ADVANCES IN KNOWLEDGE: The PanCan model may have utility in identifying low-risk SSNs which could be followed with less frequent CT scans.
OBJECTIVE: To report the long-term follow-up of subsolid nodules (SSNs) detected in participants of a prospective low-dose CT lung cancer screening cohort, and to investigate the utility of the PanCan model in stratifying risk in baseline SSNs. METHODS:Participants underwent a baseline scan, two annual incidence scans and further follow-up scans for the detected nodules. All SSNs underwent a minimum of 2 years of follow-up (unless resolved or resected). Risk of malignancy was estimated using the PanCan model; discrimination [area under the receiver-operating characteristic curve (AUC)] and calibration (Hosmer-Lemeshow goodness-of-fit test) were assessed. The Mann-Whitney U-Wilcoxon test was used to compare estimated risk between groups. RESULTS: 70 SSNs were detected in 41 (16.0%) out of 256 total participants. Median follow-up period was 25.5 months (range 2.0-74.0 months). 29 (41.4%) SSNs were transient. Five (7.1%) SSNs were resected, all found to be Stage I lung adenocarcinoma, including one SSN stable in size for 3.0 years before growth was detected. The PanCan model had good discrimination for the 52 baseline SSNs (AUC = 0.89; 95% confidence interval 0.76-1); the Hosmer-Lemeshow goodness-of-fit test was non-significant (p = 0.27). Estimated risk was significantly higher in the baseline SSNs found to be cancer vs those not found to be cancer after 2-6 years of follow-up (p < 0.01). CONCLUSION: Our findings support a long-term follow-up approach for screen-detected SSNs for 3 years or longer. The PanCan model appeared discriminatory and well calibrated in this cohort. ADVANCES IN KNOWLEDGE: The PanCan model may have utility in identifying low-risk SSNs which could be followed with less frequent CT scans.
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