Hierarchical dynamic model for risk‑stratified screening of nasopharyngeal carcinoma

Cancer research · Nasopharyngeal carcinoma

These findings demonstrate that hierarchical dynamic models significantly enhance current serological screening strategies for nasopharyngeal carcinoma, though further prospective validation is warranted.

Early detection of nasopharyngeal carcinoma through Epstein‑Barr virus serology is hampered by a low positive predictive value. This study aims to develop a hierarchical dynamic model to refine risk stratification among individuals initially identified as medium‑ or high‑risk by Epstein‑Barr virus serology. By integrating longitudinal Epstein‑Barr virus antibody data with age, sex, and family history, the model is trained using data from the PRO‑NPC‑001 program. In the validation cohort, the high‑risk model using one‑year data achieves a positive predictive value of 18.2 % (about a fourfold increase over serology screening), with a negative predictive value of 97.7 % and an area under the curve of 0.783. With two‑year data, the positive predictive values for the high‑risk and medium‑risk models are 8.8 % and 1.1 %, respectively, with area under the curve values of 0.859 and 0.687. Compared with serology‑only screening, the hierarchical dynamic models reduce the need for follow‑up examinations by 74.2 % in high‑risk individuals, yielding cost savings of up to 65.6 %. These findings demonstrate that hierarchical dynamic models significantly enhance current serological screening strategies for nasopharyngeal carcinoma, though further prospective validation is warranted.

Early detection of nasopharyngeal carcinoma improves long‑term survival, yet current serological screening has a low predictive value, so improved risk stratification could save lives and reduce unnecessary procedures.

Evidence level: Állatkísérletes. Állatmodellben vizsgálták.

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