Two-Year Lung Cancer Incidence Among Patients Who Receive a Radiologist Recommendation for Chest CT in Neck CT and MRI Reports

颈部CT和MRI报告中放射科医生建议进行胸部CT检查的患者两年肺癌发病率

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Abstract

PURPOSE: The aim of this study was to estimate the 2-year incidence of lung cancer diagnosed as a result of radiologist recommendations for chest CT in neck CT and MRI reports. METHODS: A retrospective observational cohort study was conducted, including all patients without histories of lung cancer with recommendations for chest CT in neck CT and MRI reports from June 1, 2021, to May 31, 2022, in a multi-institution health care system. Outcome data were extracted up to December 31, 2024. Two-year lung cancer incidence was estimated using a person-time calculation to acknowledge censoring with confidence intervals based on quasi-likelihood. Odds of fulfillment of the recommended chest CT for pulmonary nodules relative to other pulmonary abnormalities were estimated using logistic regression. RESULTS: Two hundred seventy-six of 28,707 (1.0%) consecutive neck, brachial plexus, and parathyroid CT and MRI reports in 273 of 22,173 patients (1.2%) (mean age, 62.5 ± 1 years, 52% women) contained recommendations for chest CT in the absence of prior lung cancer diagnoses. The median follow-up time was 34 months (interquartile range, 24-40 months). One patient (estimated 2-year incidence rate, 0.40%; 95% confidence interval, 0.05%-3.55%) was diagnosed with an incidental indolent adenocarcinoma. Recommended CT was performed in 171 of 273 patients (62.6%) and was less likely to be performed for pulmonary nodules than other pulmonary abnormalities (odds ratio, 0.46; 95% confidence interval, 0.27-0.77). CONCLUSIONS: One year of recommendations for chest CT examinations in neck CT and MRI reports across a multi-institution health care system led to the identification of only a single incidental lung cancer, an indolent adenocarcinoma. These results suggest that the frequency of recommendations for chest CT should likely be substantially decreased, but analysis of larger datasets is needed to inform best practices.

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