Quantitative imaging in medicine and surgery · 2026
Prognostic value of pretherapy CT-based Node-RADS for overall survival in extensive-stage small cell lung cancer treated with chemoimmunotherapy: a comparison with clinical N staging.
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Sun Yan, Zhang Yi, Yu Sanqiang, Wen Lu, Yang Yanhui, Fu Yi, Tang Genyan, Jiang Sishi, Wang Ruoxi, Yu Xiaoping
Аннотация
BACKGROUND: The Node Reporting and Data System (Node-RADS) provides a standardized and effective assessment of lymph nodes, but its relationship with the prognosis of small cell lung cancer (SCLC) remains unknown. This study aimed to assess the value of Node-RADS for predicting overall survival (OS) in extensive-stage SCLC patients treated with chemoimmunotherapy.
METHODS: The clinical data including OS of 297 patients with extensive-stage SCLC who underwent chemoimmunotherapy were collected retrospectively. On the pretherapeutic chest computed tomography (CT) scans, we evaluated the maximum Node-RADS score per patient and the number of positive nodal stations, defined using two thresholds: LNM-Station3 (score ≥3) and LNM-Station4 (score ≥4). The Clinical-NR3 model, incorporating pretreatment clinical variables, the maximum Node-RADS score, and LNM-Station3, was developed using Cox regression analyses to predict OS. Similarly, the Clinical-NR4 model was constructed using clinical variables, the Maximum Node-RADS score, and LNM-Station4, whereas the Clinical-cN model was created as a control based on the clinical variables and cN stage.
RESULTS: LNM-Station3 and LNM-Station4 acted as independent predictors for OS in the Clinical-NR3 and Clinical-NR4 models, respectively. The cN stage was not significantly associated with OS in the Clinical-cN model (P>0.05). The Clinical-NR4 model demonstrated a higher concordance index (C-index) than the Clinical-cN model (0.759 vs. 0.726, P=0.009). The C-index (0.748) of the Clinical-NR3 model did not show a statistically significant difference from that of the Clinical-NR4 (P=0.093) and Clinical-cN (P=0.059) models. The Clinical-NR4 model exhibited more favorable area under the curve (AUC) values of the time-dependent receiver operating characteristic (ROC) curves than the Clinical-cN model.
CONCLUSIONS: The baseline LNM-Station based on Node-RADS is an effective prognostic indicator for extensive-stage SCLC. The pretherapeutic CT-based Node-RADS models provide incremental prognostic value beyond conventional clinical N (cN) staging in patients with SCLC.
METHODS: The clinical data including OS of 297 patients with extensive-stage SCLC who underwent chemoimmunotherapy were collected retrospectively. On the pretherapeutic chest computed tomography (CT) scans, we evaluated the maximum Node-RADS score per patient and the number of positive nodal stations, defined using two thresholds: LNM-Station3 (score ≥3) and LNM-Station4 (score ≥4). The Clinical-NR3 model, incorporating pretreatment clinical variables, the maximum Node-RADS score, and LNM-Station3, was developed using Cox regression analyses to predict OS. Similarly, the Clinical-NR4 model was constructed using clinical variables, the Maximum Node-RADS score, and LNM-Station4, whereas the Clinical-cN model was created as a control based on the clinical variables and cN stage.
RESULTS: LNM-Station3 and LNM-Station4 acted as independent predictors for OS in the Clinical-NR3 and Clinical-NR4 models, respectively. The cN stage was not significantly associated with OS in the Clinical-cN model (P>0.05). The Clinical-NR4 model demonstrated a higher concordance index (C-index) than the Clinical-cN model (0.759 vs. 0.726, P=0.009). The C-index (0.748) of the Clinical-NR3 model did not show a statistically significant difference from that of the Clinical-NR4 (P=0.093) and Clinical-cN (P=0.059) models. The Clinical-NR4 model exhibited more favorable area under the curve (AUC) values of the time-dependent receiver operating characteristic (ROC) curves than the Clinical-cN model.
CONCLUSIONS: The baseline LNM-Station based on Node-RADS is an effective prognostic indicator for extensive-stage SCLC. The pretherapeutic CT-based Node-RADS models provide incremental prognostic value beyond conventional clinical N (cN) staging in patients with SCLC.