Development and validation of tumor-to-blood based nomograms for preoperative prediction of lymph node metastasis in lung cancer.

backgroundTo develop and validate tumor-to-blood based nomograms for preoperative prediction of lymph node (LN) metastasis in patients with lung cancer (LC).

methodsA prediction model was developed in a primary cohort comprising 330 LN stations from patients with pathologically confirmed LC, these data having been gathered from January 2016 to June 2019. Tumor-to-blood variables of LNs were calculated from positron emission tomography-computed tomography (PET-CT) images of LC and the short axis diameters of LNs were measured on CT images. Tumor-to-blood variables, number of stations suspected of harboring LN metastasis according to PET, and independent clinicopathological risk factors were included in the final nomograms. After being internally validated, the nomograms were used to assess an independent validation cohort containing 101 consecutive LN stations accumulated from July 2019 to March 2020.

resultsFour tumor-to-blood variables (left atrium, inferior vena cava, liver, and aortic arch) and the maximum standardized uptake value (SUVmax) for LNs were found to be significantly associated with LN status (p < 0.001 for both primary and validation cohorts). Five predictive nomograms were built. Of these, one with LN SUVmax/left atrium SUVmax was found to be optimal for predicting LN status with AUC 0.830 (95% confidence interval [CI]: 0.774-0.886) in the primary cohort and AUC 0.865 (95% CI: 0.782-0.948) in the validation cohort. All models showed good discrimination, with a modest C-index, and good calibration in both primary and validation cohorts.

conclusionsWe have developed tumor-to-blood based nomograms that incorporate identified clinicopathological risk factors and facilitate preoperative prediction of LN metastasis in LC patients.