The treatment and prognosis of de novo metastatic hormone-sensitive prostate cancer (mHSPC) vary. We established and validated a novel prognostic model for predicting cancer-specific survival (CSS) in patients with mHSPC using retrospective data from a contemporary cohort.
1092 Japanese patients diagnosed with de novo mHSPC between 2014 and 2020 were registered. The patients treated with androgen deprivation therapy and first-generation anti-androgens (ADT/CAB) were assigned to the Discovery (N = 467) or Validation (N = 328) cohorts. Those treated with ADT and androgen-receptor signaling inhibitors (ARSIs) were assigned to the ARSI cohort (N = 81).
Using the Discovery cohort, independent prognostic factors of CSS, the extent of disease score ≥ 2 or the presence of liver metastasis; lactate dehydrogenase levels > 250U/L; a primary Gleason pattern of 5, and serum albumin levels ≤ 3.7 g/dl, were identified. The prognostic model incorporating these factors showed high predictability and reproducibility in the Validation cohort. The 5-year CSS of the low-risk group was 86% and that of the high-risk group was 22%. Approximately 26.4%, 62.7%, and 10.9% of the patients in the Validation cohort defined as high-risk by the LATITUDE criteria were further grouped into high-, intermediate-, and low-risk groups by the new model with significant differences in CSS. In the ARSIs cohort, high-risk group had a significantly shorter time to castration resistance than the intermediate-risk group.
The novel model based on prognostic factors can predict patient outcomes with high accuracy and reproducibility. The model may be used to optimize the treatment intensity of de novo mHSPC.
International journal of clinical oncology. 2024 Jul 19 [Epub ahead of print]
Hiroshi Fujiwara, Masashi Kubota, Yu Hidaka, Kaoru Ito, Takashi Kawahara, Ryoma Kurahashi, Yuto Hattori, Yusuke Shiraishi, Yusuke Hama, Noriyuki Makita, Yu Tashiro, Shotaro Hatano, Ryosuke Ikeuchi, Masakazu Nakashima, Noriaki Utsunomiya, Yasushi Takashima, Shinya Somiya, Kanji Nagahama, Takeru Fujimoto, Kosuke Shimizu, Kazuto Imai, Takehiro Takahashi, Takayuki Sumiyoshi, Takayuki Goto, Satoshi Morita, Takashi Kobayashi, Shusuke Akamatsu
Shizuoka City Shizuoka Hospital, Shizuoka, Japan., Department of Urology, Kyoto University Graduate School of Medicine, Kyoto, Japan., Department of Biomedical Statistics and Bioinformatics, Kyoto University Graduate School of Medicine, Kyoto, Japan., Department of Urology, Miyazaki University Graduate School of Medicine, Miyazaki, Japan., Department of Urology, Tsukuba University Graduate School of Medicine, Tsukuba, Japan., Department of Urology, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan., Department of Urology, Kobe City Medical Center General Hospital, Kobe, Japan., Department of Urology, Shizuoka General Hospital, Shizuoka, Japan., Department of Urology, Kurashiki Central Hospital, Kurashiki, Japan., Department of Urology, Kyoto City Hospital, Kyoto, Japan., Department of Urology, Red Cross Otsu Hospital, Otsu, Japan., Department of Urology, Shimada General Medical Center, Shimada, Japan., Department of Urology, Medical Research Institute Kitano Hospital, Osaka, Japan., Department of Urology, Japanese Red Cross Wakayama Medical Center, Wakayama, Japan., Department of Urology, Kobe City Nishi-Kobe Medical Center, Kobe, Japan., Department of Urology, Tenri Hospital, Tenri, Japan., Department of Urology, Rakuwakai Otowa Hospital, Kyoto, Japan., Department of Urology, National Hospital Organization Himeji Medical Center, Himeji, Japan., Department of Urology, Hamamatsu Rosai Hospital, Hamamatsu, Japan., Department of Urology, Kansai Electric Power Hospital, Osaka, Japan., Department of Urology, Osaka Red Cross Hospital, Osaka, Japan., Department of Urology, Kyoto University Graduate School of Medicine, Kyoto, Japan. .