Prognostic nomogram to predict the distant metastasis after intensity-modulated radiation therapy for patients with nasopharyngeal carcinoma

Enhancing Nasopharyngeal Carcinoma Survival Prediction: Integrating Pre- and Post-Treatment MRI Radiomics with Clinical Data

Recurrences are frequent in nasopharyngeal carcinoma (NPC) despite high remission rates with treatment, leading to considerable morbidity. This study aimed to develop a prediction model for NPC survival by harnessing both pre- and post-treatment magnetic resonance imaging (MRI) radiomics in conjunction with clinical data, focusing on 3-year progression-free survival (PFS) as the primary outcome. Our comprehensive approach involved retrospective clinical and MRI data collection of 276 eligible NPC patients from three independent hospitals (180 in the training cohort, 46 in the validation cohort, and 50 in the external cohort) who underwent MRI scans twice, once within 2 months prior to treatment and once within 10 months after treatment. From the contrast-enhanced T1-weighted images before and after treatment, 3404 radiomics features were extracted. These features were not only derived from the primary lesion but also from the adjacent lymph nodes surrounding the tumor. We conducted appropriate feature selection pipelines, followed by Cox proportional hazards models for survival analysis. Model evaluation was performed using receiver operating characteristic (ROC) analysis, the Kaplan-Meier method, and nomogram construction. Our study unveiled several crucial predictors of NPC survival, notably highlighting the synergistic combination of pre- and post-treatment data in both clinical and radiomics assessments. Our prediction model demonstrated robust performance, with an accuracy of AUCs of 0.66 (95% CI: 0.536-0.779) in the training cohort, 0.717 (95% CI: 0.536-0.883) in the testing cohort, and 0.827 (95% CI: 0.684-0.948) in validation cohort in prognosticating patient outcomes. Our study presented a novel and effective prediction model for NPC survival, leveraging both pre- and post-treatment clinical data in conjunction with MRI features. Its constructed nomogram provides potentially significant implications for NPC research, offering clinicians a valuable tool for individualized treatment planning and patient counseling.

Recommendation for imaging follow-up strategy based on time-specific disease failure for nasopharyngeal carcinoma

BACKGROUND

To develop a common follow-up strategy for appropriate imaging examination at an appropriate time for nasopharyngeal carcinoma (NPC).

METHODS

Independent prognostic factors were identified by Cox regression analysis, and a nomogram model was developed. Random survival forest (RSF) model was constructed to depict probability of disease failure during a 5-year follow-up and establish a reasonable risk-based follow-up strategy.

RESULTS

The nomogram model finally categorized the patients into three risk groups. RSF model demonstrated distribution trends for local and regional recurrences, bone metastasis, liver metastasis, and lung metastasis of NPC. Adequate imaging at follow-up should be considered between 10 and 21 months for patients at moderate-risk of recurrence or metastasis and 7-36 months for those at high-risk.

CONCLUSIONS

The temporal distribution of incidence rates of recurrence or metastasis varied among different risk groups. We recommend implementing a focused and targeted imaging surveillance intervention at appropriate times to improve its efficiency and reduce costs.