PSA Doubling Time 4.65 months as an Optimal Cut-off of Japanese Nonmetastatic Castration-Resistant Prostate Cancer: Multi-institutional Study of Japanese Urological Oncology Group (JUOG)

PSA Doubling Time 4.65 months as an Optimal Cut-off of Japanese Nonmetastatic Castration-Resistant Prostate Cancer: Multi-institutional Study of Japanese Urological Oncology Group (JUOG) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article PSA Doubling Time 4.65 months as an Optimal Cut-off of Japanese Nonmetastatic Castration-Resistant Prostate Cancer: Multi-institutional Study of Japanese Urological Oncology Group (JUOG) Shinichi Sakamoto, Kodai Sato, Takahiro Kimura, Yoshiyuki Matsui, and 21 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4193962/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract A multicenter study of nonmetastatic castration-resistant prostate cancer (nmCRPC) was conducted to examine the prognostic to identify the optimal cut-off value of prostate-specific antigen (PSA) doubling time (PSADT) in Japanese nmCRPC. Of the 515 patients diagnosed and treated for nmCRPC at 25 participating Japanese Urological Oncology Group centers, 450 patients with complete clinical information were included. The prognostic values of clinical factors were evaluated with respect to prostate specific antigen progression-free (PFS), cancer-specific survival (CSS), and overall survival (OS). The optimal cutoff value of PSADT was identified using survival tree analysis by Python. The Median PSA and PSADT at diagnosis of nmCRPC were 3.3 ng/ml, and 5.2 months, respectively. Patients treated with novel hormonal therapy (NHT) showed significantly longer PFS (HR: Hazard Ratio 0.38, p < .0001) and PFS2 (HR 0.45, p < .0001) than those treated with vintage nonsteroidal antiandrogen agent (Vintage). The survival tree identified 4.65 months as the most prognostic PSADT cutoff point. Among the clinical and pathological factors PSADT of < 4.65 months remained an independent prognostic factor for OS (HR 2.96, p = .0003) and CSS (HR 3.66, p < .0001). Current data represented optimal cut-off of PSADT 4.65 months for a Japanese nmCRPC. Health sciences/Urology/Prostate Health sciences/Medical research/Outcomes research NHT nmCRPC Prostate cancer PSA doubling time Vintage Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Prostate cancer is the leading cause of male death in the United States 1 . The development of castration-resistant prostate cancer (CRPC) is a key factor affecting the prognosis of patients with prostate cancer. Among localized prostate cancers, treated by radical prostatectomy and radiation therapy eventually relapse and require adjuvant hormonal therapy. Despite the presence of predictive factors, approximately 20% of patients eventually develop castration resistance without radiographic progression and develop nonmetastatic castration-resistant prostate cancer (nmCRPC)(Baba et al., 2022; Suzuki et al., 2008; Takeuchi et al., 2018). Recent phase III clinical trials such as PROSPER, SPARTAN, and ARAMIS have indicated the prognostic advantage of novel hormonal therapy (NHT) in patients with high-risk nmCRPC 5 – 7 . The PSA doubling time (PSADT) is associated with the development of metastasis or death in nnCRPC 8 . Based on the entry criteria of these clinical trials, a PSADT of ≤ 10 months should be the cutoff point for patients with nmCRPC who are treated with NHT. Although recent novel imaging based on prostate-specific membrane antigen ligand positron emission tomography (PSMA-PET) has indicated the presence of distant metastasis in approximately 55% of nmCRPC patients 8 , the majority of clinical trials and daily practice are still based on conventional imaging. Thus, PSADT plays a key role in determining the treatment strategy for patients with nmCRPC. Previous phase III clinical trials have demonstrated the prognostic advantage of combined androgen deprivation therapy with bicalutamide and luteinizing hormone-releasing hormone (LH-RH) over LH-RH monotherapy in Japanese patients with locally advanced prostate cancer without metastasis 9 . Thus, Japanese patients with non-metastatic prostate cancer have traditionally been treated with vintage nonsteroidal antiandrogen agents (vintage) because of their relatively high sensitivity and low financial burden 4 . As the treatment landscape of Japanese patients with nmCRPC is unique, the aim of this study was to conduct a multi-institutional study to examine the prognostic difference between patients who received Vintage and NHT, and to identify the optimal cut-off for PSADT. Results Patient characteristics The demographic characteristics of the 450 patients at presentation are summarized in Table 1 . The median follow-up period in the entire cohort was 33 months, and the median age at diagnosis was 71 years. The median PSA level at the time of diagnosis of nmCRPC was 3.3 ng/ml. Lymph node metastasis was positive in 17.3% of the patients. The number of patients treated with primary radical prostatectomy, radiation therapy, and androgen deprivation therapy, including Vintage/LH-RH, were 97 (22.1%), 153 (34.9%), and 188 (42.9%), respectively. There were 180 and 270 patients in the vintage and NHT groups, respectively. In the NHT group, 121 (44.8%), 49 (18.1%), 47 (17.4%), and 47 (17.4%), respectively; and 6 patients received docetaxel. In the Vintage group, 173 (96.1%) patients received vintage drugs, and seven (1.6%) patients received LH-RH alone. There was a significant difference between the groups in terms of PSA value (p = 0.0121) and Gleason Score (GS) ≥ 8 (p = 0.0180), with no other significant difference observed. Prognostic outcomes in nmCRPC patients In the 450 nmCRPC patients, the median OS, PFS, and PFS2 were 94.8, 18.1, and 55.8 months, respectively, whereas CSS did not reach the median (Fig. 1 ). Survival was significantly longer in the NHT group than in the Vintage group for PFS(Hazard Ratio: HR 0.38, p <. 0001) and PFS2 (HR 0.45, p < .0001), but not for OS (HR 1.11, p = 0.6562) or CSS (HR 1.07, p = 0.7920) (Fig. 2 A-D). We conducted a propensity score-matched analysis to adjust for patient background between groups (Table S1 ). In the matched cohort, the prognostic trends for Vintage and NHT were similar, and significant differences were found for PFS and PFS2, but not for OS and CSS (Fig. 2 E-H). To enable a comparison with previous clinical trials that adopted the entry criteria of PSADT ≤ 10 months, we performed a sub-analysis of nmCRPC patients with PSADT ≤ 10 months. Our data indicated longer PSA-PFS and OS in the control arm than in previous clinical trials of nmCRPC 6 , 7 , 10 . The prognostic trends were similar between the Vintage and NHT groups, with significant differences in PFS and PFS2, but not in OS and CSS (Fig. S1 ). Optimal cut-off value of PSADT To further elucidate the prognostic significance of PSADT, a survival tree was used to identify the optimal cut-off values of PSADT to distinguish between good and poor prognoses. The overall median PSADT was 5.26 months (range, 0.32–82.25 months) (Fig. 3 A). A survival forest was adapted. The optimal cutoff for PSADT identified was 2.85 months for PFS and 4.65 months for OS and CSS. The proportion of patients with PSADT < 4.65 months was 43% and that with PSADT ≥ 4.65 months was 57% (Fig. 3 B). Time-dependent AUC demonstrated that PSADT 4.65 months derived by survival tree for OS and CSS, consistently showed better AUC at any time point compared to the AUC of the median PSADT of 5.26 months. Similarly, PSADT 2.85 months derived by survival tree for PFS demonstrated better AUC compared to the AUC of median PSADT 5.26 months after 30 months of CRPC treatment. Patients with PSADT < 4.65 months had significantly shorter survival than those with PSADT ≥ 4.65 months. For PFS and PFS2, patients with PSADT < 2.85 months had significantly shorter survival times than those with PSADT ≥ 2.85 months (Fig. 4 ). Based on proportional hazard analysis, PSADT < 4.65 months was independently associated with OS (HR 2.96, p = 0.0003) (Table 2 ) and CSS (HR 3.66, p < .0001) (Table 3 ), and PSADT < 2.85 months was an independent prognostic factor for PFS (HR 1.87, p < .0001) (Table 4 ). To assess the presence of prognostic differences between NHT and Vintage among high-risk cohorts, we also performed a sub-analysis of patients with PSADT < 4.65 months. No significant differences in OS and CSS were observed between the NHT and Vintage groups (Fig. S2). A comparison between recent nmCRPC clinical trials and current data is summarized in Table 5 . Among PSADT ≤ 10 months, our cohorts in the control arm showed longer overall survival (approximately 20 months) compared to the survival in the control arm of global clinical trials. Discussion The present results show a significant association between PSADT and prognosis in Japanese patients with nmCRPC. The survival tree identified an optimal PSADT cutoff value of 2.85 months for PFS and 4.65 months for OS and CSS. Furthermore, patients with nmCRPC treated with NHT showed prolonged PFS and PFS2 compared to those treated with Vintage. In contrast, no significant difference was observed between the two groups in terms of OS or CSS. The current data indicate the prognostic value of PSADT and the prognostic advantage of NHT over Vintage for PFS and PFS2 among Japanese patients with nmCRPC. Previous evidence has indicated that PSA kinetics are associated with the risk of disease progression and mortality among patients with nmCRPC. Higher baseline PSA and shorter PSADT were associated with shorter time to bone metastasis-free survival (BMFS) and mortality among 201 nmCRPC patients 11 . Among 331 patients with nmCRPC, higher baseline PSA and higher PSA velocity were associated with shorter OS and shorter BMFS 12 . In the denosumab study, analysis of the placebo arm demonstrated that a PSADT of < 8 months was associated with BMFS and OS. PSADT ≤ 10 months and PSADT ≤ 6 months were associated with shortening of BMFS and OS by 3 and 7 months, respectively; however, baseline PSA was not associated with BMFS 8 , 13 . In agreement with these results, the current study demonstrated that PSADT remained an independent prognostic factor for PFS, OS, and CSS, whereas PSA level did not. PSADT appears to be a key predictor of prognosis in Japanese patients with nmCRPC. Japan has a relatively unique history of hormonal treatment of prostate cancer. Patients were prescribed 80 mg bicalutamide, which is higher than the 50 mg prescribed in Western countries. The prognosis of prostate cancer patients treated with Vintage androgen deprivation therapy is longer than that of patients in Western countries; thus, revision of high-risk and high-volume criteria may be argued 13 . Previous phase 3, double-blind, randomized trials have demonstrated that combined androgen blockade of bicalutamide 80 mg plus an LH-RH agonist prolonged treatment failure, time to progression, and OS compared to LH-RH monotherapy in patients with locally advanced prostate cancer without metastasis 9 , 14 . However, no survival advantage has been observed for combined androgen blockade over LH-RH monotherapy in metastatic hormone-sensitive prostate cancer 9 , 14 . Therefore, the non-metastatic stage of prostate cancer has been regarded as the main target of vintage. Recent sub-analyses of global clinical trials and real-world data of Japanese nmCRPC patients have also demonstrated the prognostic significance of NHT in terms of PFS and metastasis-free survival 10 , 15 , but its effect on overall survival has not been documented. The present study demonstrated the outcomes of OS and CSS for the first time in a large Japanese population with nmCRPC. Our data indicate the advantages of NHT over Vintage for PFS and PFS2, but not for OS and CSS. In the present study, the median PFS and OS in the non-NHT group (Vintage) were 6.0 and 76.7 months, respectively, among patients with PSADT ≤ 10 months. When compared with previous global clinical trials, the current data show an increase of 2 months in PFS and 20 months in OS 5 – 7 . As the median follow-up period in our study was only 33 months, further follow-up is required to objectively assess the long-term outcomes in patients with nmCRPC. Survival tree has been applied to the treatment of various cancers 16 – 18 . Compared with conventional statistical analysis, a survival tree can handle greater amounts of data and comprehend the rules and patterns behind the data 17 , 18 . In the field of prostate cancer, radiographic images and diagnostic accuracy have been examined using machine learning and Python 19 , 20 ; however, the prognostic factors of localized and metastatic prostate cancer, especially during androgen deprivation therapy, have not been well studied. To optimize the prognostic cutoff value of PSADT, we used a survival tree by Python. We identified a PSADT of 2.35 months for PFS and 4.65 months for OS/CSS. Among all clinical factors, including baseline PSA level, the cutoff value of PSADT was the only independent prognostic factor. Although PSADT < 4.65 months was identified as an unfavorable prognostic factor for nmCRPC, no significant difference in OS/CSS was observed between NHT and Vintage, even within this group. A recent study reported that PSMA-PET identified nearly 55% of metastases among patients with nmCRPC who were diagnosed using conventional imaging 8 . Metastatic-directed therapy may have a further prognostic advantage among high-risk nmCRPC patients 21 . The present study has several limitations. First, we conducted a retrospective analysis and included only a limited number of patients. Second, metastasis-free survival could not be assessed due to heterogeneity and a lack of consensus in identifying radiographic progression in a real-world setting. Third, the median follow-up was 32.7 months, which limits the precise assessment of long-term outcomes in patients with prostate cancer. Further follow-up analysis of currently registered patients is in progress. In conclusion, PSADT is significantly associated with the prognosis of Japanese patients with nmCRPC. In particular, a PSADT cut-off of 4.65 months may be used to identify the poor prognosis group and personalize treatment strategies. Further follow-up will elucidate the long-term outcomes of Japanese nmCRPC. Methods Patients and clinical variables This retrospective study analyzed the data of 450 of 515 patients who were treated for nmCRPC collected from 25 hospitals in collaboration with the Japanese Urological Oncology Group (JUOG). Sixty-five cases were excluded from the analysis due to duplicate data, missing treatment information, or missing recurrence information. The primary endpoint was overall survival (OS), and the secondary endpoints were cancer-specific survival (CSS), PSA level, progression-free survival (PFS), and time to second progression or death (PFS2) 5 . Patients were subdivided into Vintage and NHT groups. The Vintage group included patients who received bicalutamide, flutamide, LH-RH therapy, and surgical castration. The NHT group included patients who received abiraterone, apalutamide, enzalutamide, or darolutamide. Seven patients treated with docetaxel were included in the NHT group. Progression was determined on the basis of PSA progression, radiographic progression, or death. PSA progression was determined based on the definition of PCWG3 22,23 . Statistical analysis Univariate and multivariate Cox proportional models and the Kaplan–Meier method were used for predictive analyses. The log-rank test was used for the statistical comparison of groups using the Kaplan–Meier method. Fisher’s exact test was used to analyze the association between Vintage and NHT groups. P-values were set at significance levels of ≤ 0.05 and marginal significance levels of ≤ 0.10. Statistical computations were performed using the JMP Pro 15 software (SAS Institute, Cary, NC, USA). Propensity score-matched analysis was performed based on factors including age, PSA, and Gleason Score. Determination of optimal PSADT using Survival Tree The optimal cutoff value for PSADT was identified using a survival tree, as described previously 23 . Briefly, a survival tree predicts the cumulative hazard function after considering survival time and censoring data. It calculates the case hazard function by majority voting over decision trees that predict survival. The threshold value of each node feature amount was calculated to maximize the difference in hazard between cases. We adopted the value of PSADT calculated in this manner as the threshold. The time-dependent area under the curve (AUC) was compared between median cut-off and the identified cut-off of PSADT. Abbreviations AR: androgen receptor NHT: novel hormonal therapy CRPC: castration-resistant prostate cancer nmCRPC: nonmetastatic castration-resistant prostate cancer PSA: prostate-specific antigen PSADT: PSA doubling time PS match: propensity score match Vintage: vintage nonsteroidal antiandrogen agent OS: Overall survival PFS: Progression-free survival CSS: Cancer-specific survival LH-RH: Luteinizing hormone-releasing hormone Declarations Ethical approval This study was approved by the Institutional Review Board of Chiba University Hospital (approval No. 4221) and the regional medical research review boards of all 24 hospitals participating in JUOG. The present study was conducted in accordance with ethical standards that promote and ensure respect and integrity for all human subjects and the Declaration of Helsinki. All experiments were performed in accordance with relevant named guidelines and regulations. Conflict of interest Shinichi Sakamoto received honoraria from Janssen Pharmaceutical, K.K.. Shintaro Narita received honoraria from Janssen Pharmaceutical, and AstraZeneca K.K.. Masaki Shiota received honoraria from Janssen, AstraZeneca, Astellas, Sanofi, and Bayer K.K. and research funding support from Daiichi Sankyo. Ethics Statement The research protocol was approved by the Institutional Review Board of Chiba University Hospital (approval No. 4221) and regional medical research review boards of all 24 hospitals. Funding information The present study was supported by grants from the Grant-in-Aid for Scientific Research (KAKENHI) (20H03813 to TI, and 20K09555 to SS). Author Contribution KS, TK, YM, YS, KH, HM, SN, JM, RM, TK, TS, RT, MS, JA, NT, SS, TK, ST, YY, YT and TK contributed to the design and implementation of the research, EK, KS, and SS to the analysis of the results and to the writing of the manuscript. HK, and TI conceived the original and supervised the project. KS and EK performed a survival tree analysis. Acknowledgement We wish to thank the members of the Japanese Urological Oncology Group (JUOG) for supporting the data collection and coordinating ethical approval. The rest of the authors who contributed to the study are listed in the Appendix. We also thank Akira Kurozumi from the department of Urology, Asahi General Hospital, Akinori Takei and Satoshi Fukasawa from the Department of Urology, Funabashi Municipal Medical Center, Koichiro Akakura, Hiroki Kito from the Department of Urology, Japan Community Health Care Organization, Hiroki Watanabe, Takahiro Shimizu, Satoshi Yamamoto and Kazuyoshi Nakamura from the Department of Urology, Kimitsu Chuo Hospital for supporting data collection and coordinating ethical approval. We extend special thanks to the Department of Urology, Chiba University School of Medicine, for their technical assistance. We also thank Lim Jasmine from the Department of Surgery, Faculty of Medicine, University of Malaya, for scientific advice. Data Availability The data that support the findings of this study are available from the Japanese Urological Oncology Group (JUOG), but restrictions apply to the availability of these data, which were used under license for the current study and so are not publicly available. The data are, however, available from the authors upon reasonable request and with the permission of the Japanese Urological Oncology Group (JUOG). The contact should be made to a corresponding author: Shinichi Sakamoto, E-mail: [email protected] , Chiba University Graduate School of Medicine, 1-8-1 Inohana, Chuou-ku, Chiba, Japan. References Siegel, R. L., Miller, K. D., Fuchs, H. E. & Jemal, A. Cancer statistics, 2022. CA Cancer J Clin 72, 7–33 (2022). Baba, H. et al. Tumor Location and a Tumor Volume over 2.8 cc Predict the Prognosis for Japanese Localized Prostate Cancer. 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Saito, S. et al. Machine-learning predicts time-series prognosis factors in metastatic prostate cancer patients treated with androgen deprivation therapy. Sci Rep 13, 6325 (2023). Tables Table 1. Patient characteristics Variable Overall Vintage NHT P Number 450 180 270 Age (years) 71 73 71 0.1734 PSA at biopsy (ng/mL) 23 20.4 24.9 0.1806 PSA (ng/mL) 3.3 2.9 3.9 0.0121* PSADT (M) 5.26 5.09 5.32 0.7717 Hb (g/dL) 13.1 13 13.1 0.4625 Performance status PS≥1 98 (23.4%) 40 (24.2%) 58 (22.8%) 0.7398 PS<1 321 (76.6%) 125 (75.8%) 196 (77.2%) unknown 31 15 16 Biopsy Gleason score GS≥8 272 (70.3%) 95 (63.3%) 177 (74.7%) 0.0180* GS<8 115 (29.7%) 55 (36.7%) 60 (25.3%) unknown 63 30 33 cT stage at biopsy cT≥３ 232 98 (60.9%) 134 (58.3%) 0.605 cT<３ 159 63 (39.1%) 96 (41.7%) unknown 59 19 4 cN stage cN1 72 (17.3%) 25 (15.8%) 47 (18.3%） 0.5176 cN0 343 (82.7%) 133 (84.2%) 210 (81.7%) unknown 35 22 13 Primary Treatment Prostatectomy 97 (22.1%) 35 (20.1%） 62 (23.5%) 0.4417 Radiation Therapy 153 (34.9%) 58 (33.3%) 95 (36.0%) Vintage・ADT 188 (42.9%) 81 (46.6%) 107 (40.5%) unknown 12 6 6 Treatment for nmCRPC Enzalutamide 121 (26.9%) 121 (44.8%) Abiraterone 49 (10.9%) 49 (18.1%) Apalutamide 47 (10.4%) 47 (17.4%) Darolutamide 47 (10.4%) 47 (17.4%) Docetaxel 6 (1.3%) 6 (2.2%) Vintage 173 (38.4%) 173 (96.1%) LH-RH 7 (1.6%) 7 (3.9%) NHT; novel hormonal therapy, cN1; clinical positive pelvic lymph node metastasis, cT stage; clinical T stage, Hb; hemoglobin, HR; hazard ratio, nmCRPC; nonmetastatic CRPC, PS; performance status, PSA; prostate-specific antigen, PSADT; PSA doubling time, Vintage; Vintage androgen receptor antagonist, * P <0.05 Table 2. Univariate and multivariate Cox proportional hazard models for OS Univariate Analysis Multivariate Analysis Variable HR P-value HR P-value PS ≥１ 1.91 (1.17–3.12) 0.0055* 1.10 (0.56–2.13) 0.7835 Age ≥ 71 (years) 2.60 (1.61–4.15) <.0001* 2.83 (1.57–5.08) 0.0005* cT ≥ 3 1.57 (0.95–2.57) 0.0700 cN1 (+) 2.52 (1.54–4.12) 0.0002* 2.47 (1.25–4.88) 0.0089* Hb ≥ 13.1 (g/dL) 0.59 (0.36–0.95) 0.0229* 0.56 (0.32–0.98) 0.0422* PSADT < 4.65 (months) 3.16 (1.94–5.14) <.0001* 2.96 (1.65–5.32) 0.0003* PSA ≥ 3.3 (ng/dL) 1.76 (1.12–2.74) 0.0132* 0.84 (0.47–1.51) 0.5625 NHT vs. Vintage 1.10 (0.71–1.72) 0.6562 NHT; novel hormonal therapy, cN1; clinical positive pelvic lymph nodes metastasis, cT stage; clinical T stage, Hb; Hemoglobin, HR; hazard ratio, OS; overall survival, PS; Performance status, PSA; Prostate specific antigen, PSADT; PSA doubling time, Vintage; Vintage androgen receptor antagonist, * P <0.05 Table 3. Univariate and multivariate Cox proportional hazard models for CSS Univariate Analysis Multivariate Analysis Variable HR P-value HR P-value PS ≥１ 1.96 (1.16–3.32) 0.0124* 1.49 (0.78–2.86) 0.2278 Age ≥ 71 (years) 2.60 (1.57–4.13) 0.0002* 3.11 (1.71–5.64) 0.0002* cT ≥ 3 1.53 (0.91–2.58) 0.11 cN1(+) 2.70 (1.61–4.55) 0.0002* 2.47 (1.29–4.71) 0.0062* Hb ≥ 13.1 (g/dL) 0.64 (0.38–1.08) 0.0946 PSADT < 4.65 (months) 3.72 (2.18–6.37) <.0001* 3.66 (2.01–6.68) <.0001* PSA ≥ 3.3 (ng/dL) 1.80 (1.11–2.91) 0.0167* 1.52 (0.85–2.72) 0.1627* NHT vs. Vintage 1.07 (0.66–1.71) 0.7920 NHT; novel hormonal therapy, cN1; clinical positive pelvic lymph node metastasis, cT stage; clinical T stage, Hb; hemoglobin, PS; performance status, HR; hazard ratio, PSA; prostate-specific antigen, PSADT; PSA doubling time, Vintage; Vintage androgen receptor antagonist, *P <0.05 Table 4. Univariate and multivariate Cox proportional hazard models for PFS Univariate Analysis Multivariate Analysis Variable HR P-value HR P-value PS ≥ 1 1.27 (0.95–1.70) 0.1074 Age ≥ 71 (years) 1.37 (1.07–1.76) 0.0139* 1.16 (0.89–1.52) 0.2616 cT ≥ 3 1.18 (0.91–1.54) 0.2100 cN1(+) 1.38 (1.00–1.91) 0.0498 Hb ≥ 13.1 (g/dL) 0.86 (0.66–1.12) 0.2566 PSADT < 2.85 (months) 2.06 (1.47–2.89) <.0001* 2.07 (1.47–2.91) <.0001* PSA ≥ 3.3 (ng/dL) 0.99 (0.78–1.26) 0.9483 NHT vs. Vintage 0.39 (0.30–0.49) <.0001* 0.38 (0.29–0.49) <.0001* NHT; novel hormonal therapy, cN1; clinical positive pelvic lymph node metastasis, cT stage; clinical T stage, Hb; hemoglobin, HR; hazard ratio, PS; performance status, PFS; progression-free survival, PSA; prostate-specific antigen, PSADT; PSA doubling time, Vintage; Vintage androgen receptor antagonist, *P <0.05 Table 5. Summary of clinical trials and the current study SPARTAN (apalutamide) PROSPER (enzalutamide) ARAMIS (darolutamide) JUOG Study Entry PSADT ≦ 10 months PSADT ≦ 10 months PSADT ≦ 10 months PSADT ≦ 10 months Whole cohort Median PSADT (months) 4.4 4.5 4.5 4.3 5.3 PSA (ng/mL) 7.8 9.2 9.2 3.1 3.3 F/U periods 52 48 29 33 33 PSA-PFS (months) ARAT/cont NR/3.7 (HR 0.06) 37.2/3.9 (HR 0.07) NR/NR (HR 0.71) 29.4/6.0 (HR 0.34) 29.7/8.2 (HR 0.38) OS (months) ARAT/cont 73.9/59.9 (HR 0.78) 67.0/56.3 (HR 0.73) NR/NR (HR 0.69) NR/76.7 months (HR 1.04) NR/94.8 months (HR 1.11) NHT; novel hormonal therapy, Cont; control, F/U periods; follow-up periods, HR; hazard ratio, NR; not reached, OS; overall survival, PSA; prostate specific antigen, PSADT; PSA doubling time, PFS; progression-free survival Additional Declarations No competing interests reported. Supplementary Files SuppleTableandfigure.docx Supporting Information Fig. S1. Prognostic comparison of nmCRPC patients with PSADT ≤ 10 months treated by NHT and Vintage. (A) Overall survival (OS), (B) cancer-specific survival (CSS), (C) progression-free survival (PFS), and (D) time to second progression or death (PFS2) of nmCRPC patients with PSADT ≤ 10 months treated by NHT and Vintage were analyzed by Kaplan–Meier method. Statistical significances were evaluated by log-rank test. Hazard risk (HR) was evaluated by proportional hazard model. Fig. S2. Prognostic comparison of nmCRPC patients treated by NHT and Vintage with PSADT < 4.65 months. (A) Overall survival (OS) and (B) cancer-specific survival (CSS) of nmCRPC patients treated by NHT and Vintage with PSADT ≤ 4.65 months were analyzed by Kaplan–Meier method. Statistical significances were evaluated by log-rank test. Hazard risk (HR) was evaluated by proportional hazard model. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 15 May, 2024 Reviews received at journal 14 May, 2024 Reviews received at journal 28 Apr, 2024 Reviewers agreed at journal 24 Apr, 2024 Reviewers agreed at journal 22 Apr, 2024 Reviewers invited by journal 22 Apr, 2024 Editor assigned by journal 17 Apr, 2024 Editor invited by journal 14 Apr, 2024 Submission checks completed at journal 14 Apr, 2024 First submitted to journal 30 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4193962","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":290927106,"identity":"e2c826a4-402e-41fb-846a-66afd384f4c3","order_by":0,"name":"Shinichi Sakamoto","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIie3QsQrCMBCA4ROh00nXiNVnuBLQRfBV6uQiUncHIdAuomulL+EjVAJ1ic4Obg7OIjiJGnUUjN1E8i8JgY9LAmCz/WIMoKwXdAFBvo4yIykJAPKq46KkTRk+x5lrpeKwD0cX5Kv1UoYj6I5L689jvF3uiyQnbKpBIJNcE9gEn+/FAl+go8kWSaJz00SRgfSOAq+EPHmQK3xD+r6oRITENKlE3xBPDdP5lCNTfZLzKfDI+JZavDiF50bHjRXXG6jPmOHH3nOYKigA3ElhYrPZbP/dHc9ARa7xQfqaAAAAAElFTkSuQmCC","orcid":"","institution":"Chiba University Graduate School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Shinichi","middleName":"","lastName":"Sakamoto","suffix":""},{"id":290927107,"identity":"8ba7d82f-4ce1-4635-8877-df14f5bbb08c","order_by":1,"name":"Kodai Sato","email":"","orcid":"","institution":"Chiba University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Kodai","middleName":"","lastName":"Sato","suffix":""},{"id":290927108,"identity":"59bfda67-06c4-463e-95e6-cf78b6926778","order_by":2,"name":"Takahiro Kimura","email":"","orcid":"","institution":"Jikei University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Takahiro","middleName":"","lastName":"Kimura","suffix":""},{"id":290927109,"identity":"3a054ce6-a036-4fc7-bd98-127f9c7a8e37","order_by":3,"name":"Yoshiyuki Matsui","email":"","orcid":"","institution":"National Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"Yoshiyuki","middleName":"","lastName":"Matsui","suffix":""},{"id":290927110,"identity":"ee5b2ef0-bdba-4a23-93ba-adb7dd0ae3a7","order_by":4,"name":"Yusuke Shiraishi","email":"","orcid":"","institution":"Shizuoka General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yusuke","middleName":"","lastName":"Shiraishi","suffix":""},{"id":290927111,"identity":"2555208f-b336-478a-b156-09f152899c83","order_by":5,"name":"Kohei Hashimoto","email":"","orcid":"","institution":"Sapporo Medical University","correspondingAuthor":false,"prefix":"","firstName":"Kohei","middleName":"","lastName":"Hashimoto","suffix":""},{"id":290927112,"identity":"c6eed636-e647-48e5-ba6f-1522c6c0315e","order_by":6,"name":"Hideaki Miyake","email":"","orcid":"","institution":"Hamamatsu University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hideaki","middleName":"","lastName":"Miyake","suffix":""},{"id":290927113,"identity":"65a38bc0-61c1-450b-a22c-a8fb355a2995","order_by":7,"name":"Shintaro Narita","email":"","orcid":"","institution":"Akita 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University","correspondingAuthor":false,"prefix":"","firstName":"Takuma","middleName":"","lastName":"Kato","suffix":""},{"id":290927117,"identity":"59879634-6c22-467f-a9dc-87880106210f","order_by":11,"name":"Toshihiro Saito","email":"","orcid":"","institution":"Niigata Cancer Center Hospital","correspondingAuthor":false,"prefix":"","firstName":"Toshihiro","middleName":"","lastName":"Saito","suffix":""},{"id":290927118,"identity":"47b41a01-2cf7-4c96-87be-bec5f20b34dc","order_by":12,"name":"Ryotaro Tomida","email":"","orcid":"","institution":"Shikoku Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"Ryotaro","middleName":"","lastName":"Tomida","suffix":""},{"id":290927119,"identity":"62a022a1-4f79-47b8-a4ae-199faa87632a","order_by":13,"name":"Masaki Shiota","email":"","orcid":"","institution":"Kyushu University","correspondingAuthor":false,"prefix":"","firstName":"Masaki","middleName":"","lastName":"Shiota","suffix":""},{"id":290927120,"identity":"833c8386-5234-400a-9d87-7d464ad778ce","order_by":14,"name":"Joraku Akira","email":"","orcid":"","institution":"Ibaraki Prefectural Hospital, Ibaraki Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"Joraku","middleName":"","lastName":"Akira","suffix":""},{"id":290927121,"identity":"6cc650c0-f718-4bb0-ae7f-3785b6b5ee9d","order_by":15,"name":"Naoki Terada","email":"","orcid":"","institution":"University of Fukui","correspondingAuthor":false,"prefix":"","firstName":"Naoki","middleName":"","lastName":"Terada","suffix":""},{"id":290927122,"identity":"05e03e1d-1436-409a-81cf-c955446e5fd5","order_by":16,"name":"Suekane Shigetaka","email":"","orcid":"","institution":"Kurume University","correspondingAuthor":false,"prefix":"","firstName":"Suekane","middleName":"","lastName":"Shigetaka","suffix":""},{"id":290927123,"identity":"d2a9e743-3587-46ab-95d4-9e3829719e65","order_by":17,"name":"Tomoyuki Kaneko","email":"","orcid":"","institution":"Teikyo University","correspondingAuthor":false,"prefix":"","firstName":"Tomoyuki","middleName":"","lastName":"Kaneko","suffix":""},{"id":290927124,"identity":"9d99c47f-2cd5-4ee3-a234-31b62f7deb68","order_by":18,"name":"Shuichi Tatarano","email":"","orcid":"","institution":"Kagoshima University","correspondingAuthor":false,"prefix":"","firstName":"Shuichi","middleName":"","lastName":"Tatarano","suffix":""},{"id":290927125,"identity":"55cef25e-be21-4f45-96ef-33aaf77bfc22","order_by":19,"name":"Naotaka Nishiyama","email":"","orcid":"","institution":"University of Toyama","correspondingAuthor":false,"prefix":"","firstName":"Naotaka","middleName":"","lastName":"Nishiyama","suffix":""},{"id":290927126,"identity":"e0b558be-94d9-4bd5-9562-9bd3522729a7","order_by":20,"name":"Eiryo Kawakami","email":"","orcid":"","institution":"Chiba University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Eiryo","middleName":"","lastName":"Kawakami","suffix":""},{"id":290927127,"identity":"9baa2d9e-2388-4b6c-bf5a-82a7920ee8af","order_by":21,"name":"Tomohiko Ichikawa","email":"","orcid":"","institution":"Chiba University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Tomohiko","middleName":"","lastName":"Ichikawa","suffix":""},{"id":290927128,"identity":"2e40e962-f030-4478-a5ef-fc4f9b1b26d3","order_by":22,"name":"Hiroshi Kitamura","email":"","orcid":"","institution":"University of Toyama","correspondingAuthor":false,"prefix":"","firstName":"Hiroshi","middleName":"","lastName":"Kitamura","suffix":""},{"id":290927129,"identity":"aaa971c0-4e70-45d2-9678-55e9530cde4b","order_by":23,"name":"Yuko Yoshio","email":"","orcid":"","institution":"Mie University","correspondingAuthor":false,"prefix":"","firstName":"Yuko","middleName":"","lastName":"Yoshio","suffix":""},{"id":290927130,"identity":"6d50d7c0-a7a6-4396-b21b-5ee36c14051b","order_by":24,"name":"Takayuki Yoshino","email":"","orcid":"","institution":"University of Tsukuba","correspondingAuthor":false,"prefix":"","firstName":"Takayuki","middleName":"","lastName":"Yoshino","suffix":""}],"badges":[],"createdAt":"2024-03-31 02:29:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4193962/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4193962/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55058165,"identity":"4dadce83-876f-46f6-81c6-5868d6cb232f","added_by":"auto","created_at":"2024-04-22 01:59:48","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":63760,"visible":true,"origin":"","legend":"\u003cp\u003ePrognosis of nmCRPC patients. (A) Overall survival (OS), cancer-specific survival (CSS), progression-free survival (PFS), and time to second progression or death (PFS2) were analyzed by Kaplan–Meier method.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4193962/v1/5d67dcc88af15735dfb4d070.jpg"},{"id":55059460,"identity":"8add85da-f292-48fa-a9c4-0be59681db79","added_by":"auto","created_at":"2024-04-22 02:15:48","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":82561,"visible":true,"origin":"","legend":"\u003cp\u003ePrognostic comparison of nmCRPC patients treated by NHT and Vintage for whole cohort and propensity-score-matched pair cohort.\u003c/p\u003e\n\u003cp\u003eThe whole cohort of (A) overall survival (OS), (B) cancer-specific survival (CSS), (C) progression-free survival (PFS), and (D) time to second progression or death (PFS2) of nmCRPC patients treated with NHT and Vintage were analyzed using the Kaplan–Meier method. Propensity score-matched pair cohorts of (E) OS, (F) CSS, (G) PFS, and (H) PFS2 of nmCRPC patients treated with NHT and Vintage were analyzed using the Kaplan–Meier method. Statistical significance was evaluated using the log-rank test. The hazard risk (HR) was evaluated using a proportional hazard model.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4193962/v1/7af2aac04dad4fd223bc1176.jpg"},{"id":55059088,"identity":"fdaaf06c-e0a2-44af-a73a-584bc469be4a","added_by":"auto","created_at":"2024-04-22 02:07:48","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":68682,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of PSA doubling time (PSADT) and the time-dependent AUC of PSADT derived by survival forest.\u003c/p\u003e\n\u003cp\u003e(A) Distribution of PSA doubling time (PSADT). (B) Percentage of PSADT ≤ 4.65 months and \u0026gt; 4.65 months. Time-dependent AUC of PSADT 4.65 months derived by survival tree and median PSADT 5.26 months for OS (C) and CSS (D). Time-dependent AUC of PSADT 2.85 months derived by survival tree and median PSADT 5.26 months for PFS and PFS2.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4193962/v1/347cf3881447e9970a62266d.jpg"},{"id":55059086,"identity":"fd05dd7a-9e69-4043-8fd0-27697399437a","added_by":"auto","created_at":"2024-04-22 02:07:48","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":73696,"visible":true,"origin":"","legend":"\u003cp\u003ePrognostic significance of PSA doubling time (PSADT) cut-off derived by survival tree.\u003c/p\u003e\n\u003cp\u003e(A) Overall survival (OS), and (B) cancer-specific survival (CSS) of nmCRPC patients with PSADT cut-offs of \u0026lt; 4.65 months and ≥ 4.65 months were analyzed by Kaplan–Meier method. (C) Progression-free survival (PFS) and (D) time to second progression or death (PFS2) of nmCRPC patients with PSADT cut-offs of \u0026lt; 2.85 months and ≥ 2.85 months were analyzed by Kaplan–Meier method. Statistical significance was evaluated by log-rank test. Hazard risk (HR) was evaluated by proportional hazard model.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4193962/v1/08b8aab93a30cdb31a02b91d.jpg"},{"id":55060273,"identity":"ffeacba1-e312-4c45-aeb0-43a11bc326ed","added_by":"auto","created_at":"2024-04-22 02:23:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":563835,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4193962/v1/8f5bfb13-d489-4544-94a3-c4992bc98080.pdf"},{"id":55058167,"identity":"9379a3f4-f7cb-47be-a25b-acd897f00e0e","added_by":"auto","created_at":"2024-04-22 01:59:48","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":222847,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupporting Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S1.\u003c/strong\u003e Prognostic comparison of nmCRPC patients with PSADT ≤ 10 months treated by NHT and Vintage.\u003c/p\u003e\n\u003cp\u003e(A) Overall survival (OS), (B) cancer-specific survival (CSS), (C) progression-free survival (PFS), and (D) time to second progression or death (PFS2) of nmCRPC patients with PSADT ≤ 10 months treated by NHT and Vintage were analyzed by Kaplan–Meier method. Statistical significances were evaluated by log-rank test. Hazard risk (HR) was evaluated by proportional hazard model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S2.\u003c/strong\u003e Prognostic comparison of nmCRPC patients treated by NHT and Vintage with PSADT \u0026lt; 4.65 months.\u003c/p\u003e\n\u003cp\u003e(A) Overall survival (OS) and (B) cancer-specific survival (CSS) of nmCRPC patients treated by NHT and Vintage with PSADT ≤ 4.65 months were analyzed by Kaplan–Meier method. Statistical significances were evaluated by log-rank test. Hazard risk (HR) was evaluated by proportional hazard model.\u003c/p\u003e","description":"","filename":"SuppleTableandfigure.docx","url":"https://assets-eu.researchsquare.com/files/rs-4193962/v1/1889ff5291d1cce57c1f766d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"PSA Doubling Time 4.65 months as an Optimal Cut-off of Japanese Nonmetastatic Castration-Resistant Prostate Cancer: Multi-institutional Study of Japanese Urological Oncology Group (JUOG)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eProstate cancer is the leading cause of male death in the United States\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The development of castration-resistant prostate cancer (CRPC) is a key factor affecting the prognosis of patients with prostate cancer. Among localized prostate cancers, treated by radical prostatectomy and radiation therapy eventually relapse and require adjuvant hormonal therapy. Despite the presence of predictive factors, approximately 20% of patients eventually develop castration resistance without radiographic progression and develop nonmetastatic castration-resistant prostate cancer (nmCRPC)(Baba et al., 2022; Suzuki et al., 2008; Takeuchi et al., 2018).\u003c/p\u003e \u003cp\u003eRecent phase III clinical trials such as PROSPER, SPARTAN, and ARAMIS have indicated the prognostic advantage of novel hormonal therapy (NHT) in patients with high-risk nmCRPC\u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. The PSA doubling time (PSADT) is associated with the development of metastasis or death in nnCRPC\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Based on the entry criteria of these clinical trials, a PSADT of \u0026le;\u0026thinsp;10 months should be the cutoff point for patients with nmCRPC who are treated with NHT. Although recent novel imaging based on prostate-specific membrane antigen ligand positron emission tomography (PSMA-PET) has indicated the presence of distant metastasis in approximately 55% of nmCRPC patients\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, the majority of clinical trials and daily practice are still based on conventional imaging. Thus, PSADT plays a key role in determining the treatment strategy for patients with nmCRPC. Previous phase III clinical trials have demonstrated the prognostic advantage of combined androgen deprivation therapy with bicalutamide and luteinizing hormone-releasing hormone (LH-RH) over LH-RH monotherapy in Japanese patients with locally advanced prostate cancer without metastasis\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Thus, Japanese patients with non-metastatic prostate cancer have traditionally been treated with vintage nonsteroidal antiandrogen agents (vintage) because of their relatively high sensitivity and low financial burden\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAs the treatment landscape of Japanese patients with nmCRPC is unique, the aim of this study was to conduct a multi-institutional study to examine the prognostic difference between patients who received Vintage and NHT, and to identify the optimal cut-off for PSADT.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatient characteristics\u003c/h2\u003e \u003cp\u003eThe demographic characteristics of the 450 patients at presentation are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The median follow-up period in the entire cohort was 33 months, and the median age at diagnosis was 71 years. The median PSA level at the time of diagnosis of nmCRPC was 3.3 ng/ml. Lymph node metastasis was positive in 17.3% of the patients. The number of patients treated with primary radical prostatectomy, radiation therapy, and androgen deprivation therapy, including Vintage/LH-RH, were 97 (22.1%), 153 (34.9%), and 188 (42.9%), respectively. There were 180 and 270 patients in the vintage and NHT groups, respectively. In the NHT group, 121 (44.8%), 49 (18.1%), 47 (17.4%), and 47 (17.4%), respectively; and 6 patients received docetaxel. In the Vintage group, 173 (96.1%) patients received vintage drugs, and seven (1.6%) patients received LH-RH alone. There was a significant difference between the groups in terms of PSA value (p\u0026thinsp;=\u0026thinsp;0.0121) and Gleason Score (GS)\u0026thinsp;\u0026ge;\u0026thinsp;8 (p\u0026thinsp;=\u0026thinsp;0.0180), with no other significant difference observed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePrognostic outcomes in nmCRPC patients\u003c/h2\u003e \u003cp\u003eIn the 450 nmCRPC patients, the median OS, PFS, and PFS2 were 94.8, 18.1, and 55.8 months, respectively, whereas CSS did not reach the median (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Survival was significantly longer in the NHT group than in the Vintage group for PFS(Hazard Ratio: HR 0.38, p \u0026lt;. 0001) and PFS2 (HR 0.45, p\u0026thinsp;\u0026lt;\u0026thinsp;.0001), but not for OS (HR 1.11, p\u0026thinsp;=\u0026thinsp;0.6562) or CSS (HR 1.07, p\u0026thinsp;=\u0026thinsp;0.7920) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-D). We conducted a propensity score-matched analysis to adjust for patient background between groups (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). In the matched cohort, the prognostic trends for Vintage and NHT were similar, and significant differences were found for PFS and PFS2, but not for OS and CSS (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE-H). To enable a comparison with previous clinical trials that adopted the entry criteria of PSADT\u0026thinsp;\u0026le;\u0026thinsp;10 months, we performed a sub-analysis of nmCRPC patients with PSADT\u0026thinsp;\u0026le;\u0026thinsp;10 months. Our data indicated longer PSA-PFS and OS in the control arm than in previous clinical trials of nmCRPC\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. The prognostic trends were similar between the Vintage and NHT groups, with significant differences in PFS and PFS2, but not in OS and CSS (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eOptimal cut-off value of PSADT\u003c/h2\u003e \u003cp\u003eTo further elucidate the prognostic significance of PSADT, a survival tree was used to identify the optimal cut-off values of PSADT to distinguish between good and poor prognoses. The overall median PSADT was 5.26 months (range, 0.32\u0026ndash;82.25 months) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). A survival forest was adapted. The optimal cutoff for PSADT identified was 2.85 months for PFS and 4.65 months for OS and CSS. The proportion of patients with PSADT\u0026thinsp;\u0026lt;\u0026thinsp;4.65 months was 43% and that with PSADT\u0026thinsp;\u0026ge;\u0026thinsp;4.65 months was 57% (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Time-dependent AUC demonstrated that PSADT 4.65 months derived by survival tree for OS and CSS, consistently showed better AUC at any time point compared to the AUC of the median PSADT of 5.26 months. Similarly, PSADT 2.85 months derived by survival tree for PFS demonstrated better AUC compared to the AUC of median PSADT 5.26 months after 30 months of CRPC treatment.\u003c/p\u003e \u003cp\u003ePatients with PSADT\u0026thinsp;\u0026lt;\u0026thinsp;4.65 months had significantly shorter survival than those with PSADT\u0026thinsp;\u0026ge;\u0026thinsp;4.65 months. For PFS and PFS2, patients with PSADT\u0026thinsp;\u0026lt;\u0026thinsp;2.85 months had significantly shorter survival times than those with PSADT\u0026thinsp;\u0026ge;\u0026thinsp;2.85 months (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBased on proportional hazard analysis, PSADT\u0026thinsp;\u0026lt;\u0026thinsp;4.65 months was independently associated with OS (HR 2.96, p\u0026thinsp;=\u0026thinsp;0.0003) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) and CSS (HR 3.66, p\u0026thinsp;\u0026lt;\u0026thinsp;.0001) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), and PSADT\u0026thinsp;\u0026lt;\u0026thinsp;2.85 months was an independent prognostic factor for PFS (HR 1.87, p\u0026thinsp;\u0026lt;\u0026thinsp;.0001) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). To assess the presence of prognostic differences between NHT and Vintage among high-risk cohorts, we also performed a sub-analysis of patients with PSADT\u0026thinsp;\u0026lt;\u0026thinsp;4.65 months. No significant differences in OS and CSS were observed between the NHT and Vintage groups (Fig. S2). A comparison between recent nmCRPC clinical trials and current data is summarized in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Among PSADT\u0026thinsp;\u0026le;\u0026thinsp;10 months, our cohorts in the control arm showed longer overall survival (approximately 20 months) compared to the survival in the control arm of global clinical trials.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present results show a significant association between PSADT and prognosis in Japanese patients with nmCRPC. The survival tree identified an optimal PSADT cutoff value of 2.85 months for PFS and 4.65 months for OS and CSS. Furthermore, patients with nmCRPC treated with NHT showed prolonged PFS and PFS2 compared to those treated with Vintage. In contrast, no significant difference was observed between the two groups in terms of OS or CSS. The current data indicate the prognostic value of PSADT and the prognostic advantage of NHT over Vintage for PFS and PFS2 among Japanese patients with nmCRPC.\u003c/p\u003e \u003cp\u003ePrevious evidence has indicated that PSA kinetics are associated with the risk of disease progression and mortality among patients with nmCRPC. Higher baseline PSA and shorter PSADT were associated with shorter time to bone metastasis-free survival (BMFS) and mortality among 201 nmCRPC patients\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Among 331 patients with nmCRPC, higher baseline PSA and higher PSA velocity were associated with shorter OS and shorter BMFS\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. In the denosumab study, analysis of the placebo arm demonstrated that a PSADT of \u0026lt;\u0026thinsp;8 months was associated with BMFS and OS. PSADT\u0026thinsp;\u0026le;\u0026thinsp;10 months and PSADT\u0026thinsp;\u0026le;\u0026thinsp;6 months were associated with shortening of BMFS and OS by 3 and 7 months, respectively; however, baseline PSA was not associated with BMFS\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. In agreement with these results, the current study demonstrated that PSADT remained an independent prognostic factor for PFS, OS, and CSS, whereas PSA level did not. PSADT appears to be a key predictor of prognosis in Japanese patients with nmCRPC.\u003c/p\u003e \u003cp\u003eJapan has a relatively unique history of hormonal treatment of prostate cancer. Patients were prescribed 80 mg bicalutamide, which is higher than the 50 mg prescribed in Western countries. The prognosis of prostate cancer patients treated with Vintage androgen deprivation therapy is longer than that of patients in Western countries; thus, revision of high-risk and high-volume criteria may be argued\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Previous phase 3, double-blind, randomized trials have demonstrated that combined androgen blockade of bicalutamide 80 mg plus an LH-RH agonist prolonged treatment failure, time to progression, and OS compared to LH-RH monotherapy in patients with locally advanced prostate cancer without metastasis\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. However, no survival advantage has been observed for combined androgen blockade over LH-RH monotherapy in metastatic hormone-sensitive prostate cancer \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Therefore, the non-metastatic stage of prostate cancer has been regarded as the main target of vintage. Recent sub-analyses of global clinical trials and real-world data of Japanese nmCRPC patients have also demonstrated the prognostic significance of NHT in terms of PFS and metastasis-free survival\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, but its effect on overall survival has not been documented. The present study demonstrated the outcomes of OS and CSS for the first time in a large Japanese population with nmCRPC. Our data indicate the advantages of NHT over Vintage for PFS and PFS2, but not for OS and CSS. In the present study, the median PFS and OS in the non-NHT group (Vintage) were 6.0 and 76.7 months, respectively, among patients with PSADT\u0026thinsp;\u0026le;\u0026thinsp;10 months. When compared with previous global clinical trials, the current data show an increase of 2 months in PFS and 20 months in OS\u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. As the median follow-up period in our study was only 33 months, further follow-up is required to objectively assess the long-term outcomes in patients with nmCRPC.\u003c/p\u003e \u003cp\u003eSurvival tree has been applied to the treatment of various cancers\u003csup\u003e\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Compared with conventional statistical analysis, a survival tree can handle greater amounts of data and comprehend the rules and patterns behind the data\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. In the field of prostate cancer, radiographic images and diagnostic accuracy have been examined using machine learning and Python\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e; however, the prognostic factors of localized and metastatic prostate cancer, especially during androgen deprivation therapy, have not been well studied. To optimize the prognostic cutoff value of PSADT, we used a survival tree by Python. We identified a PSADT of 2.35 months for PFS and 4.65 months for OS/CSS. Among all clinical factors, including baseline PSA level, the cutoff value of PSADT was the only independent prognostic factor. Although PSADT\u0026thinsp;\u0026lt;\u0026thinsp;4.65 months was identified as an unfavorable prognostic factor for nmCRPC, no significant difference in OS/CSS was observed between NHT and Vintage, even within this group. A recent study reported that PSMA-PET identified nearly 55% of metastases among patients with nmCRPC who were diagnosed using conventional imaging\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Metastatic-directed therapy may have a further prognostic advantage among high-risk nmCRPC patients\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe present study has several limitations. First, we conducted a retrospective analysis and included only a limited number of patients. Second, metastasis-free survival could not be assessed due to heterogeneity and a lack of consensus in identifying radiographic progression in a real-world setting. Third, the median follow-up was 32.7 months, which limits the precise assessment of long-term outcomes in patients with prostate cancer. Further follow-up analysis of currently registered patients is in progress. In conclusion, PSADT is significantly associated with the prognosis of Japanese patients with nmCRPC. In particular, a PSADT cut-off of 4.65 months may be used to identify the poor prognosis group and personalize treatment strategies. Further follow-up will elucidate the long-term outcomes of Japanese nmCRPC.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePatients and clinical variables\u003c/h2\u003e \u003cp\u003eThis retrospective study analyzed the data of 450 of 515 patients who were treated for nmCRPC collected from 25 hospitals in collaboration with the Japanese Urological Oncology Group (JUOG). Sixty-five cases were excluded from the analysis due to duplicate data, missing treatment information, or missing recurrence information. The primary endpoint was overall survival (OS), and the secondary endpoints were cancer-specific survival (CSS), PSA level, progression-free survival (PFS), and time to second progression or death (PFS2)\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Patients were subdivided into Vintage and NHT groups. The Vintage group included patients who received bicalutamide, flutamide, LH-RH therapy, and surgical castration. The NHT group included patients who received abiraterone, apalutamide, enzalutamide, or darolutamide. Seven patients treated with docetaxel were included in the NHT group. Progression was determined on the basis of PSA progression, radiographic progression, or death. PSA progression was determined based on the definition of PCWG3\u003csup\u003e22,23\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eUnivariate and multivariate Cox proportional models and the Kaplan\u0026ndash;Meier method were used for predictive analyses. The log-rank test was used for the statistical comparison of groups using the Kaplan\u0026ndash;Meier method. Fisher\u0026rsquo;s exact test was used to analyze the association between Vintage and NHT groups. P-values were set at significance levels of \u0026le;\u0026thinsp;0.05 and marginal significance levels of \u0026le;\u0026thinsp;0.10. Statistical computations were performed using the JMP Pro 15 software (SAS Institute, Cary, NC, USA). Propensity score-matched analysis was performed based on factors including age, PSA, and Gleason Score.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eDetermination of optimal PSADT using Survival Tree\u003c/h2\u003e \u003cp\u003eThe optimal cutoff value for PSADT was identified using a survival tree, as described previously\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Briefly, a survival tree predicts the cumulative hazard function after considering survival time and censoring data. It calculates the case hazard function by majority voting over decision trees that predict survival. The threshold value of each node feature amount was calculated to maximize the difference in hazard between cases. We adopted the value of PSADT calculated in this manner as the threshold. The time-dependent area under the curve (AUC) was compared between median cut-off and the identified cut-off of PSADT.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAR: androgen receptor\u003c/p\u003e\n\u003cp\u003eNHT: novel hormonal therapy\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCRPC: castration-resistant prostate cancer\u003c/p\u003e\n\u003cp\u003enmCRPC: nonmetastatic castration-resistant prostate cancer\u003c/p\u003e\n\u003cp\u003ePSA: prostate-specific antigen\u003c/p\u003e\n\u003cp\u003ePSADT: PSA doubling time\u003c/p\u003e\n\u003cp\u003ePS match: propensity score match\u003c/p\u003e\n\u003cp\u003eVintage: vintage nonsteroidal antiandrogen agent\u003c/p\u003e\n\u003cp\u003eOS: Overall\u0026nbsp;survival\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePFS:\u0026nbsp;Progression-free survival\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCSS:\u0026nbsp;Cancer-specific survival\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLH-RH: Luteinizing hormone-releasing hormone\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthical approval\u003c/h2\u003e \u003cp\u003e This study was approved by the Institutional Review Board of Chiba University Hospital (approval No. 4221) and the regional medical research review boards of all 24 hospitals participating in JUOG. The present study was conducted in accordance with ethical standards that promote and ensure respect and integrity for all human subjects and the Declaration of Helsinki. All experiments were performed in accordance with relevant named guidelines and regulations.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eConflict of interest\u003c/h2\u003e \u003cp\u003eShinichi Sakamoto received honoraria from Janssen Pharmaceutical, K.K.. Shintaro Narita received honoraria from Janssen Pharmaceutical, and AstraZeneca K.K.. Masaki Shiota received honoraria from Janssen, AstraZeneca, Astellas, Sanofi, and Bayer K.K. and research funding support from Daiichi Sankyo.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eEthics Statement\u003c/h2\u003e \u003cp\u003e The research protocol was approved by the Institutional Review Board of Chiba University Hospital (approval No. 4221) and regional medical research review boards of all 24 hospitals.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding information\u003c/h2\u003e \u003cp\u003eThe present study was supported by grants from the Grant-in-Aid for Scientific Research (KAKENHI) (20H03813 to TI, and 20K09555 to SS).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eKS, TK, YM, YS, KH, HM, SN, JM, RM, TK, TS, RT, MS, JA, NT, SS, TK, ST, YY, YT and TK contributed to the design and implementation of the research, EK, KS, and SS to the analysis of the results and to the writing of the manuscript. HK, and TI conceived the original and supervised the project. KS and EK performed a survival tree analysis.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003e We wish to thank the members of the Japanese Urological Oncology Group (JUOG) for supporting the data collection and coordinating ethical approval. The rest of the authors who contributed to the study are listed in the Appendix. We also thank Akira Kurozumi from the department of Urology, Asahi General Hospital, Akinori Takei and Satoshi Fukasawa from the Department of Urology, Funabashi Municipal Medical Center, Koichiro Akakura, Hiroki Kito from the Department of Urology, Japan Community Health Care Organization, Hiroki Watanabe, Takahiro Shimizu, Satoshi Yamamoto and Kazuyoshi Nakamura from the Department of Urology, Kimitsu Chuo Hospital for supporting data collection and coordinating ethical approval. We extend special thanks to the Department of Urology, Chiba University School of Medicine, for their technical assistance. We also thank Lim Jasmine from the Department of Surgery, Faculty of Medicine, University of Malaya, for scientific advice.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available from the Japanese Urological Oncology Group (JUOG), but restrictions apply to the availability of these data, which were used under license for the current study and so are not publicly available. The data are, however, available from the authors upon reasonable request and with the permission of the Japanese Urological Oncology Group (JUOG). The contact should be made to a corresponding author: Shinichi Sakamoto, E-mail: [email protected], Chiba University Graduate School of Medicine, 1-8-1 Inohana, Chuou-ku, Chiba, Japan.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSiegel, R. L., Miller, K. D., Fuchs, H. E. \u0026amp; Jemal, A. Cancer statistics, 2022. CA Cancer J Clin 72, 7\u0026ndash;33 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaba, H. \u003cem\u003eet al.\u003c/em\u003e Tumor Location and a Tumor Volume over 2.8 cc Predict the Prognosis for Japanese Localized Prostate Cancer. Cancers (Basel) 14, 5823 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTakeuchi, N. \u003cem\u003eet al.\u003c/em\u003e Biparametric Prostate Imaging Reporting and Data System version2 and International Society of Urological Pathology Grade Predict Biochemical Recurrence after Radical Prostatectomy. 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Cancer 117, 2077\u0026ndash;2085 (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanesaka, M. \u003cem\u003eet al.\u003c/em\u003e Revision of CHAARTED and LATITUDE criteria among Japanese de novo metastatic prostate cancer patients. Prostate Int 9, 208\u0026ndash;214 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUsami, M. \u003cem\u003eet al.\u003c/em\u003e Bicalutamide 80 mg combined with a luteinizing hormone-releasing hormone agonist (LHRH-A) versus LHRH-A monotherapy in advanced prostate cancer: findings from a phase III randomized, double-blind, multicenter trial in Japanese patients. Prostate Cancer Prostatic Dis 10, 194\u0026ndash;201 (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYokomizo, A. \u003cem\u003eet al.\u003c/em\u003e Real-world use of enzalutamide in men with nonmetastatic castration-resistant prostate cancer in Japan. Int J Clin Oncol 27, 418\u0026ndash;426 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu, W., Xie, L., Han, J. \u0026amp; Guo, X. The Application of Deep Learning in Cancer Prognosis Prediction. Cancers (Basel) 12, 603 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRakha, E. A., Reis-Filho, J. S. \u0026amp; Ellis, I. O. Combinatorial biomarker expression in breast cancer. Breast Cancer Res Treat 120, 293\u0026ndash;308 (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKourou, K., Exarchos, T. P., Exarchos, K. P., Karamouzis, M. V. \u0026amp; Fotiadis, D. I. Machine learning applications in cancer prognosis and prediction. Comput Struct Biotechnol J 13, 8\u0026ndash;17 (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu, H. \u003cem\u003eet al.\u003c/em\u003e Predicting Prostate Cancer Upgrading of Biopsy Gleason Grade Group at Radical Prostatectomy Using Machine Learning-Assisted Decision-Support Models. Cancer Manag Res 12, 13099\u0026ndash;13110 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBulten, W. \u003cem\u003eet al.\u003c/em\u003e Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study. Lancet Oncol 21, 233\u0026ndash;241 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRogowski, P. \u003cem\u003eet al.\u003c/em\u003e Radiotherapy of oligometastatic prostate cancer: a systematic review. Radiation Oncology 16, 50 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScher, H. I. \u003cem\u003eet al.\u003c/em\u003e Trial Design and Objectives for Castration-Resistant Prostate Cancer: Updated Recommendations From the Prostate Cancer Clinical Trials Working Group 3. Journal of Clinical Oncology 34, 1402\u0026ndash;1418 (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaito, S. \u003cem\u003eet al.\u003c/em\u003e Machine-learning predicts time-series prognosis factors in metastatic prostate cancer patients treated with androgen deprivation therapy. Sci Rep 13, 6325 (2023).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"643\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\"\u003e\n \u003cp\u003eTable 1. Patient characteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003eOverall\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003eVintage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003eNHT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003eNumber\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\n \u003cp\u003e0.1734\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003ePSA at biopsy (ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e20.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e24.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\n \u003cp\u003e0.1806\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003ePSA (ng/mL)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\n \u003cp\u003e0.0121*\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003ePSADT (M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e5.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e5.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e5.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\n \u003cp\u003e0.7717\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003eHb (g/dL)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e13.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e13.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\n \u003cp\u003e0.4625\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003ePerformance status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;PS\u0026ge;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e98 (23.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e40 (24.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e58 (22.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\n \u003cp\u003e0.7398\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;PS\u0026lt;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e321 (76.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e125 (75.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e196 (77.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;unknown\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003eBiopsy Gleason score\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;GS\u0026ge;8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e272 (70.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e95 (63.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e177 (74.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\n \u003cp\u003e0.0180*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;GS\u0026lt;8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e115 (29.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e55 (36.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e60 (25.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;unknown\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e63\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e30\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e33\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003ecT stage at biopsy\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;cT\u0026ge;３\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e98 (60.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e134 (58.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\n \u003cp\u003e0.605\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;cT\u0026lt;３\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e63 (39.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e96 (41.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; unknown\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003ecN stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;cN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e72 (17.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e25 (15.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e47 (18.3%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\n \u003cp\u003e0.5176\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;cN0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e343 (82.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e133 (84.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e210 (81.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;unknown\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003ePrimary Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Prostatectomy\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e97 (22.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e35 (20.1%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e62 (23.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\n \u003cp\u003e0.4417\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Radiation Therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e153 (34.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e58 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e95 (36.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Vintage・ADT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e188 (42.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e81 (46.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e107 (40.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;unknown\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003eTreatment for nmCRPC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Enzalutamide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e121 (26.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e121 (44.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Abiraterone\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e49 (10.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e49 (18.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Apalutamide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e47 (10.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e47 (17.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Darolutamide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e47 (10.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e47 (17.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Docetaxel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e6 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\n \u003cp\u003e6 (2.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Vintage \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e173 (38.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e173 (96.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.50388802488336%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;LH-RH\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.018662519440124%\"\u003e\n \u003cp\u003e7 (1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.530326594090202%\"\u003e\n \u003cp\u003e7 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.77293934681182%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.174183514774494%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\"\u003e\n \u003cp\u003eNHT; novel hormonal therapy, cN1; clinical positive pelvic lymph node metastasis, cT stage; clinical T stage, Hb; hemoglobin, HR; hazard ratio, nmCRPC; nonmetastatic CRPC, PS; performance status, PSA; prostate-specific antigen, PSADT; PSA doubling time, Vintage; Vintage androgen receptor antagonist, * P \u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"588\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\"\u003e\n \u003cp\u003eTable 2. Univariate and multivariate Cox proportional hazard models for OS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.522920203735143%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.069609507640067%\" colspan=\"2\"\u003e\n \u003cp\u003eUnivariate Analysis\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.5466893039049237%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"37.86078098471987%\" colspan=\"2\"\u003e\n \u003cp\u003eMultivariate Analysis\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.522920203735143%\"\u003e\n \u003cp\u003eVariable\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.69439728353141%\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.375212224108658%\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.5466893039049237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.619694397283531%\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.522920203735143%\"\u003e\n \u003cp\u003ePS \u0026ge;１\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.69439728353141%\"\u003e\n \u003cp\u003e1.91 (1.17\u0026ndash;3.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.375212224108658%\"\u003e\n \u003cp\u003e0.0055*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.5466893039049237%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\"\u003e\n \u003cp\u003e1.10 (0.56\u0026ndash;2.13)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.619694397283531%\"\u003e\n \u003cp\u003e0.7835\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.522920203735143%\"\u003e\n \u003cp\u003eAge \u0026ge; 71 (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.69439728353141%\"\u003e\n \u003cp\u003e2.60 (1.61\u0026ndash;4.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.375212224108658%\"\u003e\n \u003cp\u003e\u0026lt;.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.5466893039049237%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\"\u003e\n \u003cp\u003e2.83 (1.57\u0026ndash;5.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.619694397283531%\"\u003e\n \u003cp\u003e0.0005*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.522920203735143%\"\u003e\n \u003cp\u003ecT \u0026ge; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.69439728353141%\"\u003e\n \u003cp\u003e1.57 (0.95\u0026ndash;2.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.375212224108658%\"\u003e\n \u003cp\u003e0.0700\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.5466893039049237%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.619694397283531%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.522920203735143%\"\u003e\n \u003cp\u003ecN1 (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.69439728353141%\"\u003e\n \u003cp\u003e2.52 (1.54\u0026ndash;4.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.375212224108658%\"\u003e\n \u003cp\u003e0.0002*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.5466893039049237%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\"\u003e\n \u003cp\u003e2.47 (1.25\u0026ndash;4.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.619694397283531%\"\u003e\n \u003cp\u003e0.0089*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.522920203735143%\"\u003e\n \u003cp\u003eHb \u0026ge; 13.1 (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.69439728353141%\"\u003e\n \u003cp\u003e0.59 (0.36\u0026ndash;0.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.375212224108658%\"\u003e\n \u003cp\u003e0.0229*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.5466893039049237%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\"\u003e\n \u003cp\u003e0.56 (0.32\u0026ndash;0.98)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.619694397283531%\"\u003e\n \u003cp\u003e0.0422*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.522920203735143%\"\u003e\n \u003cp\u003ePSADT \u0026lt; 4.65 (months)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.69439728353141%\"\u003e\n \u003cp\u003e3.16 (1.94\u0026ndash;5.14)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.375212224108658%\"\u003e\n \u003cp\u003e\u0026lt;.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.5466893039049237%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\"\u003e\n \u003cp\u003e2.96 (1.65\u0026ndash;5.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.619694397283531%\"\u003e\n \u003cp\u003e0.0003*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.522920203735143%\"\u003e\n \u003cp\u003ePSA \u0026ge; 3.3 (ng/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.69439728353141%\"\u003e\n \u003cp\u003e1.76 (1.12\u0026ndash;2.74)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.375212224108658%\"\u003e\n \u003cp\u003e0.0132*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.5466893039049237%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\"\u003e\n \u003cp\u003e0.84 (0.47\u0026ndash;1.51)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.619694397283531%\"\u003e\n \u003cp\u003e0.5625\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.522920203735143%\"\u003e\n \u003cp\u003eNHT vs. Vintage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.69439728353141%\"\u003e\n \u003cp\u003e1.10 (0.71\u0026ndash;1.72)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.375212224108658%\"\u003e\n \u003cp\u003e0.6562\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.5466893039049237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.24108658743633%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.619694397283531%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\"\u003e\n \u003cp\u003eNHT; novel hormonal therapy, cN1; clinical positive pelvic lymph nodes metastasis, cT stage; clinical T stage, Hb; Hemoglobin, HR; hazard ratio, OS; overall survival, PS; Performance status, PSA; Prostate specific antigen, PSADT; PSA doubling time, Vintage; Vintage androgen receptor antagonist, * P \u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"593\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\"\u003e\n \u003cp\u003eTable 3. Univariate and multivariate Cox proportional hazard models for CSS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.655986509274875%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"35.750421585160204%\" colspan=\"2\"\u003e\n \u003cp\u003eUnivariate Analysis\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.564924114671164%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"31.02866779089376%\" colspan=\"2\"\u003e\n \u003cp\u003eMultivariate Analysis\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.655986509274875%\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.236087689713322%\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.51433389544688%\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.564924114671164%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.05564924114671%\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.97301854974705%\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.655986509274875%\"\u003e\n \u003cp\u003ePS \u0026ge;１\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.236087689713322%\"\u003e\n \u003cp\u003e1.96 (1.16\u0026ndash;3.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.51433389544688%\"\u003e\n \u003cp\u003e0.0124*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.564924114671164%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.05564924114671%\"\u003e\n \u003cp\u003e1.49 (0.78\u0026ndash;2.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.97301854974705%\"\u003e\n \u003cp\u003e0.2278\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.655986509274875%\"\u003e\n \u003cp\u003eAge \u0026ge; 71 (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.236087689713322%\"\u003e\n \u003cp\u003e2.60 (1.57\u0026ndash;4.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.51433389544688%\"\u003e\n \u003cp\u003e0.0002*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.564924114671164%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.05564924114671%\"\u003e\n \u003cp\u003e3.11 (1.71\u0026ndash;5.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.97301854974705%\"\u003e\n \u003cp\u003e0.0002*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.655986509274875%\"\u003e\n \u003cp\u003ecT \u0026ge; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.236087689713322%\"\u003e\n \u003cp\u003e1.53 (0.91\u0026ndash;2.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.51433389544688%\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.564924114671164%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.05564924114671%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.97301854974705%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.655986509274875%\"\u003e\n \u003cp\u003ecN1(+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.236087689713322%\"\u003e\n \u003cp\u003e2.70 (1.61\u0026ndash;4.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.51433389544688%\"\u003e\n \u003cp\u003e0.0002*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.564924114671164%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.05564924114671%\"\u003e\n \u003cp\u003e2.47 (1.29\u0026ndash;4.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.97301854974705%\"\u003e\n \u003cp\u003e0.0062*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.655986509274875%\"\u003e\n \u003cp\u003eHb \u0026ge; 13.1 (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.236087689713322%\"\u003e\n \u003cp\u003e0.64 (0.38\u0026ndash;1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.51433389544688%\"\u003e\n \u003cp\u003e0.0946\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.564924114671164%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.05564924114671%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.97301854974705%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.655986509274875%\"\u003e\n \u003cp\u003ePSADT \u0026lt; 4.65 (months)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.236087689713322%\"\u003e\n \u003cp\u003e3.72 (2.18\u0026ndash;6.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.51433389544688%\"\u003e\n \u003cp\u003e\u0026lt;.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.564924114671164%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.05564924114671%\"\u003e\n \u003cp\u003e3.66 (2.01\u0026ndash;6.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.97301854974705%\"\u003e\n \u003cp\u003e\u0026lt;.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.655986509274875%\"\u003e\n \u003cp\u003ePSA \u0026ge; 3.3 (ng/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.236087689713322%\"\u003e\n \u003cp\u003e1.80 (1.11\u0026ndash;2.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.51433389544688%\"\u003e\n \u003cp\u003e0.0167*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.564924114671164%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.05564924114671%\"\u003e\n \u003cp\u003e1.52 (0.85\u0026ndash;2.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.97301854974705%\"\u003e\n \u003cp\u003e0.1627*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.655986509274875%\"\u003e\n \u003cp\u003eNHT vs. Vintage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.236087689713322%\"\u003e\n \u003cp\u003e1.07 (0.66\u0026ndash;1.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.51433389544688%\"\u003e\n \u003cp\u003e0.7920\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.564924114671164%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.05564924114671%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.97301854974705%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\"\u003e\n \u003cp\u003eNHT; novel hormonal therapy, cN1; clinical positive pelvic lymph node metastasis, cT stage; clinical T stage, Hb; hemoglobin, PS; performance status, HR; hazard ratio, PSA; prostate-specific antigen, PSADT; PSA doubling time, Vintage; Vintage androgen receptor antagonist, *P \u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"636\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\"\u003e\n \u003cp\u003eTable 4. Univariate and multivariate Cox proportional hazard models for PFS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.54716981132076%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.40251572327044%\" colspan=\"2\"\u003e\n \u003cp\u003eUnivariate Analysis\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.70440251572327%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.345911949685533%\" colspan=\"2\"\u003e\n \u003cp\u003eMultivariate Analysis\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.54716981132076%\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.767295597484278%\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.477987421383649%\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.70440251572327%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.82389937106918%\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.679245283018869%\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.54716981132076%\"\u003e\n \u003cp\u003ePS\u0026nbsp;\u0026ge;\u0026nbsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.767295597484278%\"\u003e\n \u003cp\u003e1.27 (0.95\u0026ndash;1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.477987421383649%\"\u003e\n \u003cp\u003e0.1074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.70440251572327%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.82389937106918%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.679245283018869%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.54716981132076%\"\u003e\n \u003cp\u003eAge \u0026ge; 71 (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.767295597484278%\"\u003e\n \u003cp\u003e1.37 (1.07\u0026ndash;1.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.477987421383649%\"\u003e\n \u003cp\u003e0.0139*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.70440251572327%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.82389937106918%\"\u003e\n \u003cp\u003e1.16 (0.89\u0026ndash;1.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.679245283018869%\"\u003e\n \u003cp\u003e0.2616\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.54716981132076%\"\u003e\n \u003cp\u003ecT \u0026ge; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.767295597484278%\"\u003e\n \u003cp\u003e1.18 (0.91\u0026ndash;1.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.477987421383649%\"\u003e\n \u003cp\u003e0.2100\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.70440251572327%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.82389937106918%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.679245283018869%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.54716981132076%\"\u003e\n \u003cp\u003ecN1(+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.767295597484278%\"\u003e\n \u003cp\u003e1.38 (1.00\u0026ndash;1.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.477987421383649%\"\u003e\n \u003cp\u003e0.0498\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.70440251572327%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.82389937106918%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.679245283018869%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.54716981132076%\"\u003e\n \u003cp\u003eHb \u0026ge; 13.1 (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.767295597484278%\"\u003e\n \u003cp\u003e0.86 (0.66\u0026ndash;1.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.477987421383649%\"\u003e\n \u003cp\u003e0.2566\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.70440251572327%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.82389937106918%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.679245283018869%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.54716981132076%\"\u003e\n \u003cp\u003ePSADT \u0026lt; 2.85 (months)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.767295597484278%\"\u003e\n \u003cp\u003e2.06 (1.47\u0026ndash;2.89)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.477987421383649%\"\u003e\n \u003cp\u003e\u0026lt;.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.70440251572327%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.82389937106918%\"\u003e\n \u003cp\u003e2.07 (1.47\u0026ndash;2.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.679245283018869%\"\u003e\n \u003cp\u003e\u0026lt;.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.54716981132076%\"\u003e\n \u003cp\u003ePSA \u0026ge; 3.3 (ng/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.767295597484278%\"\u003e\n \u003cp\u003e0.99 (0.78\u0026ndash;1.26)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.477987421383649%\"\u003e\n \u003cp\u003e0.9483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.70440251572327%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.82389937106918%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.679245283018869%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.54716981132076%\"\u003e\n \u003cp\u003eNHT vs. Vintage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.767295597484278%\"\u003e\n \u003cp\u003e0.39 (0.30\u0026ndash;0.49)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.477987421383649%\"\u003e\n \u003cp\u003e\u0026lt;.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.70440251572327%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.82389937106918%\"\u003e\n \u003cp\u003e0.38 (0.29\u0026ndash;0.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.679245283018869%\"\u003e\n \u003cp\u003e\u0026lt;.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\"\u003e\n \u003cp\u003eNHT; novel hormonal therapy, cN1; clinical positive pelvic lymph node metastasis, cT stage; clinical T stage, Hb; hemoglobin, HR; hazard ratio, PS; performance status, PFS; progression-free survival, PSA; prostate-specific antigen, PSADT; PSA doubling time, Vintage; Vintage androgen receptor antagonist, *P \u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"640\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\"\u003e\n \u003cp\u003eTable 5. Summary of clinical trials and the current study\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.15625%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.875%\"\u003e\n \u003cp\u003eSPARTAN (apalutamide)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.65625%\"\u003e\n \u003cp\u003ePROSPER (enzalutamide)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003eARAMIS (darolutamide)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.8125%\" colspan=\"2\"\u003e\n \u003cp\u003eJUOG Study\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.15625%\"\u003e\n \u003cp\u003eEntry\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.875%\"\u003e\n \u003cp\u003ePSADT ≦ 10 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.65625%\"\u003e\n \u003cp\u003ePSADT ≦ 10 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003ePSADT ≦ 10 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.21875%\"\u003e\n \u003cp\u003ePSADT ≦ 10 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.59375%\"\u003e\n \u003cp\u003eWhole cohort\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.15625%\"\u003e\n \u003cp\u003eMedian PSADT (months)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.875%\"\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.65625%\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.21875%\"\u003e\n \u003cp\u003e4.3\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.59375%\"\u003e\n \u003cp\u003e5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.15625%\"\u003e\n \u003cp\u003ePSA (ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.875%\"\u003e\n \u003cp\u003e7.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.65625%\"\u003e\n \u003cp\u003e9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003e9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.21875%\"\u003e\n \u003cp\u003e3.1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.59375%\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.15625%\"\u003e\n \u003cp\u003eF/U periods\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.875%\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.65625%\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.21875%\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.59375%\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.15625%\"\u003e\n \u003cp\u003ePSA-PFS (months) ARAT/cont\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.875%\"\u003e\n \u003cp\u003eNR/3.7 (HR 0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.65625%\"\u003e\n \u003cp\u003e37.2/3.9 (HR 0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003eNR/NR (HR 0.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.21875%\"\u003e\n \u003cp\u003e29.4/6.0 (HR 0.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.59375%\"\u003e\n \u003cp\u003e29.7/8.2 (HR 0.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.15625%\"\u003e\n \u003cp\u003eOS (months) ARAT/cont\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.875%\"\u003e\n \u003cp\u003e73.9/59.9 (HR 0.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.65625%\"\u003e\n \u003cp\u003e67.0/56.3 (HR 0.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003eNR/NR (HR 0.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.21875%\"\u003e\n \u003cp\u003eNR/76.7 months (HR 1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.59375%\"\u003e\n \u003cp\u003eNR/94.8 months (HR 1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\"\u003e\n \u003cp\u003eNHT; novel hormonal therapy, Cont; control, \u0026nbsp;F/U periods; follow-up periods, HR; hazard ratio, NR; not reached, OS; overall survival, PSA; prostate specific antigen, PSADT; PSA doubling time, PFS; progression-free survival\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"NHT, nmCRPC, Prostate cancer, PSA doubling time, Vintage","lastPublishedDoi":"10.21203/rs.3.rs-4193962/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4193962/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eA multicenter study of nonmetastatic castration-resistant prostate cancer (nmCRPC) was conducted to examine the prognostic to identify the optimal cut-off value of prostate-specific antigen (PSA) doubling time (PSADT) in Japanese nmCRPC. Of the 515 patients diagnosed and treated for nmCRPC at 25 participating Japanese Urological Oncology Group centers, 450 patients with complete clinical information were included. The prognostic values of clinical factors were evaluated with respect to prostate specific antigen progression-free (PFS), cancer-specific survival (CSS), and overall survival (OS). The optimal cutoff value of PSADT was identified using survival tree analysis by Python. The Median PSA and PSADT at diagnosis of nmCRPC were 3.3 ng/ml, and 5.2 months, respectively. Patients treated with novel hormonal therapy (NHT) showed significantly longer PFS (HR: Hazard Ratio 0.38, p \u0026lt; .0001) and PFS2 (HR 0.45, p \u0026lt; .0001) than those treated with vintage nonsteroidal antiandrogen agent (Vintage). The survival tree identified 4.65 months as the most prognostic PSADT cutoff point. Among the clinical and pathological factors PSADT of \u0026lt; 4.65 months remained an independent prognostic factor for OS (HR 2.96, p = .0003) and CSS (HR 3.66, p \u0026lt; .0001). Current data represented optimal cut-off of PSADT 4.65 months for a Japanese nmCRPC.\u003c/p\u003e","manuscriptTitle":"PSA Doubling Time 4.65 months as an Optimal Cut-off of Japanese Nonmetastatic Castration-Resistant Prostate Cancer: Multi-institutional Study of Japanese Urological Oncology Group (JUOG)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-22 01:59:43","doi":"10.21203/rs.3.rs-4193962/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-05-15T16:52:18+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-14T10:11:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-28T14:05:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"e72fb845-e9eb-4c9f-93be-f33ad5d7cb99","date":"2024-04-24T13:15:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1f09cc21-ef31-484c-aded-dc5ff15389cf","date":"2024-04-22T12:52:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-22T12:51:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-17T12:42:50+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-04-14T05:21:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-14T05:18:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-03-31T02:25:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9283439f-1908-4c56-8a68-bfad278cef32","owner":[],"postedDate":"April 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":30645148,"name":"Health sciences/Urology/Prostate"},{"id":30645149,"name":"Health sciences/Medical research/Outcomes research"}],"tags":[],"updatedAt":"2024-06-25T17:56:10+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-22 01:59:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4193962","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4193962","identity":"rs-4193962","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}