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Aim: Recent network meta-analyses (NMAs) in metastatic castration-sensitive prostate cancer have not adequately addressed potential treatment effect modifiers and population imbalances, which introduces bias. Although, individual-patient data (IPD) are seldom available across all trials, recent methodological advances allow adjustments using a combination of IPD and aggregate data. Materials & methods: IPD from the ARASENS trial (darolutamide + docetaxel + androgen-deprivation-therapy [ADT]) and aggregate data from a systematic review were analyzed. Two methods were used to adjust for population imbalances: multilevel network meta-regression (ML-NMR) using baseline characteristics, and network meta-interpolation (NMI) using subgroup data. Relative effects were estimated for an ARASENS-like population, with sensitivity analysis in an average trial population. Results: Twelve studies, including ARASENS, were included. All studies reported baseline characteristics for ML-NMR. Sufficient subgroup data for NMI were available in 8/12 studies for overall survival (OS) and 5/12 studies for progression-free survival (PFS). Darolutamide + docetaxel + ADT showed significant benefit over docetaxel + ADT, ADT and standard-nonsteroidal-antiandrogen + ADT in all analyses. ML-NMR showed improved OS for darolutamide + docetaxel + ADT compared with abiraterone + docetaxel + ADT, apalutamide + ADT, enzalutamide + ADT and abiraterone + ADT. ML-NMR also showed improved PFS for darolutamide + docetaxel + ADT compared with apalutamide + ADT and enzalutamide + ADT. Using NMI, darolutamide + docetaxel + ADT demonstrated OS benefit over abiraterone + ADT and PFS benefit relative to abiraterone + ADT and apalutamide + ADT. Findings were consistent in an average population, although ML-NMR did not show significant OS benefit of darolutamide + docetaxel + ADT over apalutamide + ADT. Conclusion: Improved outcomes were observed with darolutamide + docetaxel + ADT compared with other therapies. By incorporating effect modifiers and addressing population imbalances, we provide clinicians with a more accurate understanding of treatment efficacy for better-informed decision-making.
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Shore et al. (2026) studied this question.
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