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A novel prognostic model of de novo metastatic hormone-sensitive prostate cancer to optimize treatment intensity

Background The treatment and prognosis of de novo metastatic hormone-sensitive prostate cancer (mHSPC) vary. We established and validated a novel prognostic model for predicting cancer-specific survival (CSS) in patients with mHSPC using retrospective data from a contemporary cohort. Methods 1092 Ja...

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Published in:International journal of clinical oncology 2024-10, Vol.29 (10), p.1574-1585
Main Authors: Fujiwara, Hiroshi, Kubota, Masashi, Hidaka, Yu, Ito, Kaoru, Kawahara, Takashi, Kurahashi, Ryoma, Hattori, Yuto, Shiraishi, Yusuke, Hama, Yusuke, Makita, Noriyuki, Tashiro, Yu, Hatano, Shotaro, Ikeuchi, Ryosuke, Nakashima, Masakazu, Utsunomiya, Noriaki, Takashima, Yasushi, Somiya, Shinya, Nagahama, Kanji, Fujimoto, Takeru, Shimizu, Kosuke, Imai, Kazuto, Takahashi, Takehiro, Sumiyoshi, Takayuki, Goto, Takayuki, Morita, Satoshi, Kobayashi, Takashi, Akamatsu, Shusuke
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container_issue 10
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container_title International journal of clinical oncology
container_volume 29
creator Fujiwara, Hiroshi
Kubota, Masashi
Hidaka, Yu
Ito, Kaoru
Kawahara, Takashi
Kurahashi, Ryoma
Hattori, Yuto
Shiraishi, Yusuke
Hama, Yusuke
Makita, Noriyuki
Tashiro, Yu
Hatano, Shotaro
Ikeuchi, Ryosuke
Nakashima, Masakazu
Utsunomiya, Noriaki
Takashima, Yasushi
Somiya, Shinya
Nagahama, Kanji
Fujimoto, Takeru
Shimizu, Kosuke
Imai, Kazuto
Takahashi, Takehiro
Sumiyoshi, Takayuki
Goto, Takayuki
Morita, Satoshi
Kobayashi, Takashi
Akamatsu, Shusuke
description Background The treatment and prognosis of de novo metastatic hormone-sensitive prostate cancer (mHSPC) vary. We established and validated a novel prognostic model for predicting cancer-specific survival (CSS) in patients with mHSPC using retrospective data from a contemporary cohort. Methods 1092 Japanese patients diagnosed with de novo mHSPC between 2014 and 2020 were registered. The patients treated with androgen deprivation therapy and first-generation anti-androgens (ADT/CAB) were assigned to the Discovery ( N  = 467) or Validation ( N  = 328) cohorts. Those treated with ADT and androgen-receptor signaling inhibitors (ARSIs) were assigned to the ARSI cohort ( N  = 81). Results Using the Discovery cohort, independent prognostic factors of CSS, the extent of disease score ≥ 2 or the presence of liver metastasis; lactate dehydrogenase levels > 250U/L; a primary Gleason pattern of 5, and serum albumin levels ≤ 3.7 g/dl, were identified. The prognostic model incorporating these factors showed high predictability and reproducibility in the Validation cohort. The 5-year CSS of the low-risk group was 86% and that of the high-risk group was 22%. Approximately 26.4%, 62.7%, and 10.9% of the patients in the Validation cohort defined as high-risk by the LATITUDE criteria were further grouped into high-, intermediate-, and low-risk groups by the new model with significant differences in CSS. In the ARSIs cohort, high-risk group had a significantly shorter time to castration resistance than the intermediate-risk group. Conclusions The novel model based on prognostic factors can predict patient outcomes with high accuracy and reproducibility. The model may be used to optimize the treatment intensity of de novo mHSPC.
doi_str_mv 10.1007/s10147-024-02577-1
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We established and validated a novel prognostic model for predicting cancer-specific survival (CSS) in patients with mHSPC using retrospective data from a contemporary cohort. Methods 1092 Japanese patients diagnosed with de novo mHSPC between 2014 and 2020 were registered. The patients treated with androgen deprivation therapy and first-generation anti-androgens (ADT/CAB) were assigned to the Discovery ( N  = 467) or Validation ( N  = 328) cohorts. Those treated with ADT and androgen-receptor signaling inhibitors (ARSIs) were assigned to the ARSI cohort ( N  = 81). Results Using the Discovery cohort, independent prognostic factors of CSS, the extent of disease score ≥ 2 or the presence of liver metastasis; lactate dehydrogenase levels &gt; 250U/L; a primary Gleason pattern of 5, and serum albumin levels ≤ 3.7 g/dl, were identified. The prognostic model incorporating these factors showed high predictability and reproducibility in the Validation cohort. The 5-year CSS of the low-risk group was 86% and that of the high-risk group was 22%. Approximately 26.4%, 62.7%, and 10.9% of the patients in the Validation cohort defined as high-risk by the LATITUDE criteria were further grouped into high-, intermediate-, and low-risk groups by the new model with significant differences in CSS. In the ARSIs cohort, high-risk group had a significantly shorter time to castration resistance than the intermediate-risk group. Conclusions The novel model based on prognostic factors can predict patient outcomes with high accuracy and reproducibility. The model may be used to optimize the treatment intensity of de novo mHSPC.</description><identifier>ISSN: 1341-9625</identifier><identifier>ISSN: 1437-7772</identifier><identifier>EISSN: 1437-7772</identifier><identifier>DOI: 10.1007/s10147-024-02577-1</identifier><identifier>PMID: 39028395</identifier><language>eng</language><publisher>Singapore: Springer Nature Singapore</publisher><subject>Aged ; Aged, 80 and over ; Androgen Antagonists - therapeutic use ; Androgen Receptor Antagonists - therapeutic use ; Androgens ; Cancer Research ; Castration ; Humans ; Japan ; L-Lactate dehydrogenase ; Liver diseases ; Male ; Medical prognosis ; Medicine ; Medicine &amp; Public Health ; Metastases ; Metastasis ; Middle Aged ; Oncology ; Original ; Original Article ; Prognosis ; Prostate cancer ; Prostatic Neoplasms - drug therapy ; Prostatic Neoplasms - pathology ; Reproducibility ; Retrospective Studies ; Risk groups ; Surgical Oncology</subject><ispartof>International journal of clinical oncology, 2024-10, Vol.29 (10), p.1574-1585</ispartof><rights>The Author(s) 2024</rights><rights>2024. The Author(s).</rights><rights>The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2024 2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c356t-d55d7151c168b01ea1c14f883ed582a7b48accb38902f8e974994de6c9cda64a3</cites><orcidid>0000-0002-1394-7506</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39028395$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Fujiwara, Hiroshi</creatorcontrib><creatorcontrib>Kubota, Masashi</creatorcontrib><creatorcontrib>Hidaka, Yu</creatorcontrib><creatorcontrib>Ito, Kaoru</creatorcontrib><creatorcontrib>Kawahara, Takashi</creatorcontrib><creatorcontrib>Kurahashi, Ryoma</creatorcontrib><creatorcontrib>Hattori, Yuto</creatorcontrib><creatorcontrib>Shiraishi, Yusuke</creatorcontrib><creatorcontrib>Hama, Yusuke</creatorcontrib><creatorcontrib>Makita, Noriyuki</creatorcontrib><creatorcontrib>Tashiro, Yu</creatorcontrib><creatorcontrib>Hatano, Shotaro</creatorcontrib><creatorcontrib>Ikeuchi, Ryosuke</creatorcontrib><creatorcontrib>Nakashima, Masakazu</creatorcontrib><creatorcontrib>Utsunomiya, Noriaki</creatorcontrib><creatorcontrib>Takashima, Yasushi</creatorcontrib><creatorcontrib>Somiya, Shinya</creatorcontrib><creatorcontrib>Nagahama, Kanji</creatorcontrib><creatorcontrib>Fujimoto, Takeru</creatorcontrib><creatorcontrib>Shimizu, Kosuke</creatorcontrib><creatorcontrib>Imai, Kazuto</creatorcontrib><creatorcontrib>Takahashi, Takehiro</creatorcontrib><creatorcontrib>Sumiyoshi, Takayuki</creatorcontrib><creatorcontrib>Goto, Takayuki</creatorcontrib><creatorcontrib>Morita, Satoshi</creatorcontrib><creatorcontrib>Kobayashi, Takashi</creatorcontrib><creatorcontrib>Akamatsu, Shusuke</creatorcontrib><title>A novel prognostic model of de novo metastatic hormone-sensitive prostate cancer to optimize treatment intensity</title><title>International journal of clinical oncology</title><addtitle>Int J Clin Oncol</addtitle><addtitle>Int J Clin Oncol</addtitle><description>Background The treatment and prognosis of de novo metastatic hormone-sensitive prostate cancer (mHSPC) vary. We established and validated a novel prognostic model for predicting cancer-specific survival (CSS) in patients with mHSPC using retrospective data from a contemporary cohort. Methods 1092 Japanese patients diagnosed with de novo mHSPC between 2014 and 2020 were registered. The patients treated with androgen deprivation therapy and first-generation anti-androgens (ADT/CAB) were assigned to the Discovery ( N  = 467) or Validation ( N  = 328) cohorts. Those treated with ADT and androgen-receptor signaling inhibitors (ARSIs) were assigned to the ARSI cohort ( N  = 81). Results Using the Discovery cohort, independent prognostic factors of CSS, the extent of disease score ≥ 2 or the presence of liver metastasis; lactate dehydrogenase levels &gt; 250U/L; a primary Gleason pattern of 5, and serum albumin levels ≤ 3.7 g/dl, were identified. The prognostic model incorporating these factors showed high predictability and reproducibility in the Validation cohort. The 5-year CSS of the low-risk group was 86% and that of the high-risk group was 22%. Approximately 26.4%, 62.7%, and 10.9% of the patients in the Validation cohort defined as high-risk by the LATITUDE criteria were further grouped into high-, intermediate-, and low-risk groups by the new model with significant differences in CSS. In the ARSIs cohort, high-risk group had a significantly shorter time to castration resistance than the intermediate-risk group. Conclusions The novel model based on prognostic factors can predict patient outcomes with high accuracy and reproducibility. 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Kubota, Masashi ; Hidaka, Yu ; Ito, Kaoru ; Kawahara, Takashi ; Kurahashi, Ryoma ; Hattori, Yuto ; Shiraishi, Yusuke ; Hama, Yusuke ; Makita, Noriyuki ; Tashiro, Yu ; Hatano, Shotaro ; Ikeuchi, Ryosuke ; Nakashima, Masakazu ; Utsunomiya, Noriaki ; Takashima, Yasushi ; Somiya, Shinya ; Nagahama, Kanji ; Fujimoto, Takeru ; Shimizu, Kosuke ; Imai, Kazuto ; Takahashi, Takehiro ; Sumiyoshi, Takayuki ; Goto, Takayuki ; Morita, Satoshi ; Kobayashi, Takashi ; Akamatsu, Shusuke</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c356t-d55d7151c168b01ea1c14f883ed582a7b48accb38902f8e974994de6c9cda64a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Androgen Antagonists - therapeutic use</topic><topic>Androgen Receptor Antagonists - therapeutic use</topic><topic>Androgens</topic><topic>Cancer Research</topic><topic>Castration</topic><topic>Humans</topic><topic>Japan</topic><topic>L-Lactate dehydrogenase</topic><topic>Liver diseases</topic><topic>Male</topic><topic>Medical prognosis</topic><topic>Medicine</topic><topic>Medicine &amp; 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Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>International journal of clinical oncology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fujiwara, Hiroshi</au><au>Kubota, Masashi</au><au>Hidaka, Yu</au><au>Ito, Kaoru</au><au>Kawahara, Takashi</au><au>Kurahashi, Ryoma</au><au>Hattori, Yuto</au><au>Shiraishi, Yusuke</au><au>Hama, Yusuke</au><au>Makita, Noriyuki</au><au>Tashiro, Yu</au><au>Hatano, Shotaro</au><au>Ikeuchi, Ryosuke</au><au>Nakashima, Masakazu</au><au>Utsunomiya, Noriaki</au><au>Takashima, Yasushi</au><au>Somiya, Shinya</au><au>Nagahama, Kanji</au><au>Fujimoto, Takeru</au><au>Shimizu, Kosuke</au><au>Imai, Kazuto</au><au>Takahashi, Takehiro</au><au>Sumiyoshi, Takayuki</au><au>Goto, Takayuki</au><au>Morita, Satoshi</au><au>Kobayashi, Takashi</au><au>Akamatsu, Shusuke</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A novel prognostic model of de novo metastatic hormone-sensitive prostate cancer to optimize treatment intensity</atitle><jtitle>International journal of clinical oncology</jtitle><stitle>Int J Clin Oncol</stitle><addtitle>Int J Clin Oncol</addtitle><date>2024-10-01</date><risdate>2024</risdate><volume>29</volume><issue>10</issue><spage>1574</spage><epage>1585</epage><pages>1574-1585</pages><issn>1341-9625</issn><issn>1437-7772</issn><eissn>1437-7772</eissn><abstract>Background The treatment and prognosis of de novo metastatic hormone-sensitive prostate cancer (mHSPC) vary. We established and validated a novel prognostic model for predicting cancer-specific survival (CSS) in patients with mHSPC using retrospective data from a contemporary cohort. Methods 1092 Japanese patients diagnosed with de novo mHSPC between 2014 and 2020 were registered. The patients treated with androgen deprivation therapy and first-generation anti-androgens (ADT/CAB) were assigned to the Discovery ( N  = 467) or Validation ( N  = 328) cohorts. Those treated with ADT and androgen-receptor signaling inhibitors (ARSIs) were assigned to the ARSI cohort ( N  = 81). Results Using the Discovery cohort, independent prognostic factors of CSS, the extent of disease score ≥ 2 or the presence of liver metastasis; lactate dehydrogenase levels &gt; 250U/L; a primary Gleason pattern of 5, and serum albumin levels ≤ 3.7 g/dl, were identified. The prognostic model incorporating these factors showed high predictability and reproducibility in the Validation cohort. The 5-year CSS of the low-risk group was 86% and that of the high-risk group was 22%. Approximately 26.4%, 62.7%, and 10.9% of the patients in the Validation cohort defined as high-risk by the LATITUDE criteria were further grouped into high-, intermediate-, and low-risk groups by the new model with significant differences in CSS. In the ARSIs cohort, high-risk group had a significantly shorter time to castration resistance than the intermediate-risk group. Conclusions The novel model based on prognostic factors can predict patient outcomes with high accuracy and reproducibility. The model may be used to optimize the treatment intensity of de novo mHSPC.</abstract><cop>Singapore</cop><pub>Springer Nature Singapore</pub><pmid>39028395</pmid><doi>10.1007/s10147-024-02577-1</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-1394-7506</orcidid><oa>free_for_read</oa></addata></record>
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identifier ISSN: 1341-9625
ispartof International journal of clinical oncology, 2024-10, Vol.29 (10), p.1574-1585
issn 1341-9625
1437-7772
1437-7772
language eng
recordid cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11420339
source Springer Nature
subjects Aged
Aged, 80 and over
Androgen Antagonists - therapeutic use
Androgen Receptor Antagonists - therapeutic use
Androgens
Cancer Research
Castration
Humans
Japan
L-Lactate dehydrogenase
Liver diseases
Male
Medical prognosis
Medicine
Medicine & Public Health
Metastases
Metastasis
Middle Aged
Oncology
Original
Original Article
Prognosis
Prostate cancer
Prostatic Neoplasms - drug therapy
Prostatic Neoplasms - pathology
Reproducibility
Retrospective Studies
Risk groups
Surgical Oncology
title A novel prognostic model of de novo metastatic hormone-sensitive prostate cancer to optimize treatment intensity
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