Prediction and diagnosis of interval metastasis after neoadjuvant chemoradiotherapy for oesophageal cancer using 18F-FDG PET/CT
Year: 2018
Type: article
Study design: Observational Study
Abstract: During neoadjuvant chemoradiotherapy for oesophageal cancer, or in the interval prior to surgery, some patients develop systemic metastasis. This study aimed to evaluate the diagnostic performance of 18 F-FDG PET/CT for the detection of interval metastasis and to identify predictors of interval metastases in a large cohort of oesophageal cancer patients. In total, 783 consecutive patients with potentially resectable oesophageal cancer who underwent chemoradiotherapy and pre- and post-treatment 18 F-FDG PET/CT between 2006 and 2015 were analyzed from a prospectively maintained database. Diagnostic accuracy measures were calculated on a per-patient basis using histological verification or clinical follow-up as a reference standard. Multivariable logistic regression analysis was performed to determine pre-treatment predictors of interval metastasis. A prediction score was developed to predict the probability of interval metastasis. Of 783 patients that underwent 18 F-FDG PET/CT restaging, 65 (8.3%) were found to have interval metastasis and 44 (5.6%) were deemed to have false positive lesions. The resulting sensitivity and specificity was 74.7% (95% CI: 64.3–83.4%) and 93.7% (95% CI: 91.6–95.4%), respectively. Multivariable analysis revealed that tumor length, cN status, squamous cell tumor histology, and baseline SUV max were associated with interval metastasis. Based on these criteria, a prediction score was developed with an optimism adjusted C-index of 0.67 that demonstrated accurate calibration. 18 F-FDG PET/CT restaging detects distant interval metastases in 8.3% of patients after chemoradiotherapy for oesophageal cancer. The provided prediction score may stratify risk of developing interval metastasis, and could be used to prioritize additional restaging modalities for patients most likely to benefit.
Authors: Lucas Goense, Jelle P. Ruurda, Brett W. Carter, Penny Fang, Linus Ho, Gert J. Meijer, Richard van Hillegersberg, Wayne L. Hofstetter, Steven H. Lin
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,490
Funder: René Vogels Stichting
OpenAlex ID: W2802567097
