The current study aimed to develop and validate a prediction model to estimate the independent risk factors for lateral cervical lymph node metastasis (LLNM) in papillary thyroid carcinoma (PTC) patients based on dual-energy computed tomography (DECT). Method: This study retrospectively conducted 406 consecutive patients from July 2015 to June 2019 to form the derivation cohorts and performed internal validation. 101 consecutive patients from July 2019 to June 2020 were included to create the external validation cohort. Univariable and multivariable logistic regression analyses were used to evaluate independent risk factors for LLNM. A prediction model based on DECT parameters was built and presented on a nomogram. The internal and external validations were performed. Results: Iodine concentration (IC) in the arterial phase (OR 2.761, 95% CI 1.028-7.415, P 0.044), IC in venous phase (OR 3.820, 95% CI 1.430-10.209, P 0.008), located in the superior pole (OR 4.181, 95% CI 2.645-6.609, P 0.000), and extrathyroidal extension (OR 4.392, 95% CI 2.142-9.004, P 0.000) were independently associated with LLNM in the derivation cohort. These four predictors were incorporated into the nomogram. The model showed good discrimination in the derivation (AUC, 0.899), internal (AUC, 0.905), and external validation (AUC, 0.912) cohorts. The decision curve revealed that more advantages would be added using the nomogram to estimate LLNM, which implied that the lateral lymph node dissection was recommended. Conclusions: DECT parameters could provide independent indicators of LLNM in PTC patients, and the nomogram based on them may be helpful in treatment decision-making.
This study demonstrated MRC and CTC as potential diagnostic approaches for colorectal cancer. CTC had a higher diagnostic value of PLR and area under the ROC for colorectal cancer.
Objectives To establish and validate a predictive model integrating with clinical and dual-energy CT (DECT) variables for individual recurrence-free survival (RFS) prediction in early-stage glottic laryngeal cancer (EGLC) after larynx-preserving surgery. Methods This retrospective study included 212 consecutive patients with EGLC who underwent DECT before larynxpreserving surgery between January 2015 and December 2018. Using Cox proportional hazard regression model to determine independent predictors for RFS and presented on a nomogram. The model's performance was assessed using Harrell's concordance index (C-index), time-dependent area under curve (TD-AUC) plot, and calibration curve. A risk stratification system was established using the nomogram with median scores of all cases to divide all patients into two prognostic groups. Results Recurrence occurred in 39/212 (18.4%) cases. Normalized iodine concentration in arterial (NICAP) and venous phases (NICVP) were verified as significant predictors of RFS in multivariate Cox regression (hazard ratio [HR], 4.2; 95% confidence interval [CI]: 2.3, 7.7, p < .001 and HR, 3.0; 95% CI: 1.5, 5.9, p = .002, respectively). Nomogram based on clinical and DECT variables was better than did only clinical variables. The prediction model proved well-calibrated and had good discriminative ability in the training and validation samples. A risk stratification system was built that could effectively classify EGLC patients into two risk groups. Conclusions DECT could provide independent RFS indicators in patients with EGLC, and the nomogram based on DECT and clinical variables was useful in predicting RFS at several time points. Key Points • Dual-energy CT(DECT) variables can predict recurrence-free survival (RFS) after larynx-preserving surgery in patients with early-stage glottic laryngeal cancer (EGLC). • The model that integrates clinical and DECT variables predicted RFS better than did only clinical variables.• A risk stratification system based on the nomogram could effectively classify EGLC patients into two risk groups.Huanlei Zhang and Ying Zou contributed equally as co-first authors.
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