Guiding induction chemotherapy of locoregionally advanced nasopharyngeal carcinoma with ternary classification of predicted individual treatment effect

Background and purpose

Induction chemotherapy (IC) before concurrent chemoradiotherapy does not universally improve long-term overall survival (OS) in locoregionally advanced nasopharyngeal carcinoma (LANPC). Conventional risk stratification often yields suboptimal IC decisions. Our study introduces a ternary classification of predicted individual treatment effect (PITE) to guide personalized IC decisions.

Materials and methods

A two-center retrospective analysis of 1,213 patients with LANPC was conducted to develop and validate prognostic models integrating magnetic resonance imaging and clinical data to estimate individual 5-year OS probabilities for IC and non-IC treatments. Differences in these probabilities defined PITE, facilitating patient stratification into three IC recommendation categories. Model effectiveness was validated using Kaplan–Meier estimators, decision curve-like analysis, and evaluations of variable importance and distribution.

Results

The models exhibited strong predictive performance in both treatments across training and cross-validation sets, enabling accurate PITE calculations and patient classification. Compared with non-IC treatment, IC markedly improved OS in the IC-preferred group (HR = 0.62, p = 0.02), had no effect in the IC-neutral group (HR = 1.00, p = 0.70), and worsened OS in the IC-opposed group (HR = 2.00, p = 0.03). The ternary PITE classification effectively identified 41.7 % of high-risk patients not benefiting from IC, and yielded a 2.68 % higher mean 5-year OS probability over risk-based decisions. Significantly increasing distributions of key prognostic indicators, such as metastatic lymph node number and plasma Epstein–Barr virus DNA level from IC-opposed to IC-preferred groups, further validated the clinical relevance of PITE classification.

Conclusion

The ternary PITE classification offers an accurate and clinically advantageous approach to guide personalized IC decision-making in patients with LANPC.