Positron Emission Tomography in Segmentectomy for cT1N0M0 Nonsmall Cell Lung Cancer
Background This study was aimed to examine the significance of fluorodeoxyglucose positron emission tomography in predicting prognosis after segmentectomy in lung cancer.
Methods This was a retrospective cohort study, including 227 patients with cT1N0M0 nonsmall cell lung cancer who underwent positron emission tomography followed by segmentectomy between 2012 and 2019. Significance of tumor histology, T-stage, tumor size, and standardized uptake value on positron emission tomography in relation to recurrence-free survival were examined using Cox's proportional hazard analysis. Median follow-up period was 56 months (range: 1–95 months).
Results Tumor stages were Tis in 25 patients, T1mi/T1a in 51, T1b in 98, and T1c in 53. Twenty-six patients (11%) experienced recurrences, including local (n = 8) and distant (n = 18). Multivariate analysis showed that the significant variables for recurrence-free survival were T-stage and standardized uptake value (p = 0.002 and 0.015, respectively), whereas tumor histology and tumor size were not significant (p = 0.28 and 0.44, respectively). When tumor size was divided into ≤2 cm and >2 cm for analysis, it was not significant again (p = 0.49), whereas standardized uptake value remained significant (p = 0.008). While standardized uptake value of tumors with recurrences was significantly higher than those without (4.9–2.8 and 2.6–2.5, respectively, p < 0.001), there was no significant difference between local and distant recurrences (p = 0.32). Cut-off value of standardized uptake value for recurrences was 3.2. Five-year recurrence-free survival rates in tumors with standardized uptake value <3.2 and ≥3.2 were 86 and 65%, respectively (p < 0.001).
Conclusion Positron emission tomography could predict the prognosis after segmentectomy better than tumor size.
Date and number of Institutional Review Board approval: February in 2014 (approval number: 14–003).
Received: 13 August 2020
Accepted: 26 October 2020
12 February 2021 (online)
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