Abstract

This paper presents a methodological framework for evaluating individualized cancer treatments within the context of precision oncology. The framework integrates N-of-1 trials with matched cohort analysis. N-of-1 trials optimize drug selection and dosing based on individual patient characteristics, while matched cohort analysis, using propensity score matching, enables robust evaluation of treatment effects at both the individual and population levels. This reduces selection bias and facilitates meaningful comparisons between treatment cohorts. This integrated strategy bridges personalized care and population-level evidence, offering a scalable, real-world model for advancing individualized cancer therapies. While this approach is rooted in Western medical research methodology, it shares fundamental similarities with the Traditional Chinese Medicine (TCM) principle of “syndrome differentiation and treatment.” This alignment makes it particularly suitable for evaluating both Western and TCM approaches, either independently or in combination. The framework allows for the integration of personalized approaches within a rigorous research methodology, bridging individual patient care with population-level evidence (Figure 1).

Figure 1:Bridging individual patient care with population-level evidence.

Keywords:Individualized treatment; N-of-1 trials; Precision oncology; Propensity score matching; Observational study; Personalized medicine; Cancer treatment; Traditional Chinese Medicine (TCM)