Authors
Hiroaki Iwamoto, Kouji Izumi, Kazuaki Machioka, Ren Toriumi, Takashi Shima, Masakazu Nozaki, Tomohiro Hori, Takahiro Inaba, Ryunosuke Nakagawa, Taiki Kamijima, Suguru Kadomoto, Tomoyuki Makino, Renato Naito, Hiroshi Yaegashi, Kazuyoshi Shigehara, Takahiro Nohara, Tohru Miyagi, Chikashi Seto, Yoshifumi Kadono, Atsushi Mizokami
Published in
International journal of urology : official journal of the Japanese Urological Association. Volume 33. Issue 10. Pages e70668.
Abstract
To evaluate treatment-effect heterogeneity associated with local therapy in nonmetastatic advanced prostate cancer and develop a simple hypothesis-generating framework to estimate the expected absolute survival benefit associated with local therapy.
This multicentre retrospective cohort study included 1198 patients with clinical T3-4N0M0 or cN1M0 prostate cancer from the Kaga Million Uro-Oncology Network (KAMU-ON). Multivariable Cox models evaluated the association between local therapy and overall survival. Treatment-effect heterogeneity was assessed using interaction analyses. Adjusted 5 year overall survival and absolute survival benefit were estimated by g-computation. A simple clinical framework based on clinicopathological variables was derived from the subgroup analyses.
Local therapy was independently associated with improved overall survival (adjusted hazard ratio 0.32, 95% confidence interval 0.21-0.48; p < 0.001). Significant treatment-effect heterogeneity was observed according to clinical T stage (p for interaction = 0.030). The greatest absolute survival benefits were observed in patients with clinical T3b/T4 disease (20.3 percentage points) and Grade Group 4-5 disease (17.2 percentage points). The framework stratified the estimated absolute survival benefit from 0.1 to 19.5 percentage points across score groups (p for interaction = 0.041; p for trend = 0.023).
The survival benefit associated with local therapy varied substantially across patients with nonmetastatic advanced prostate cancer. This hypothesis-generating framework may provide estimates of expected treatment benefit and support individualized treatment discussions.
PMID:
42844150
Bibliographic data and abstract were imported from PubMed on 08 Oct 2026.
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