MP17-13 PROGNOSTIC VALUE OF PRETREATMENT LUNG IMMUNE PROGNOSTIC INDEX IN PATIENTS WITH METASTATIC HORMONE-SENSITIVE AND CASTRATION-RESISTANT PROSTATE CANCER

Abstract

You have accessJournal of UrologyCME1 Apr 2023MP17-13 PROGNOSTIC VALUE OF PRETREATMENT LUNG IMMUNE PROGNOSTIC INDEX IN PATIENTS WITH METASTATIC HORMONE-SENSITIVE AND CASTRATION-RESISTANT PROSTATE CANCER Zhipeng Wang, Haoyang Liu, Jinge Zhao, Pengfei Shen, and Hao Zeng Zhipeng WangZhipeng Wang More articles by this author , Haoyang LiuHaoyang Liu More articles by this author , Jinge ZhaoJinge Zhao More articles by this author , Pengfei ShenPengfei Shen More articles by this author , and Hao ZengHao Zeng More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003237.13AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The lung prognostic index (LIPI), which combines the derived neutrophil-to-lymphocyte Ratio (dNLR) and lactate dehydrogenase (LDH) levels, was first proposed to predict the effectiveness of immune checkpoint inhibitors (ICIs) in metastatic non-small cell lung cancer (mNSCLC) patients in 2018, and was subsequently found to be an important prognostic biomarker irrespective of treatment modality for mNSCLC patients. In this study, we aim to explore the prognostic value of the LIPI in patients with metastatic hormone-sensitive prostate cancer (mHSPC) and metastatic castration-resistant prostate cancer (mCRPC). METHODS: We retrospectively analyzed data of 502 mHSPC patients primarily treated with maximal androgen blockade and 158 mCRPC patients receiving abiraterone. All cases were classified into the LIPI-Good, LIPI-Intermediate, and LIPI-Poor groups based on their LIPI score calculated by the derived neutrophil-to-lymphocyte ratio and lactate dehydrogenase. The potential of LIPI in predicting mCRPC-free survival (CFS), PSA response, PSA-progression-free survival (PSA-PFS), and overall survival (OS) were analyzed. A propensity score matching (PSM) methodology was performed to balance the baseline factors of different groups. RESULTS: In the mHSPC cohort, patients of the LIPI-Good (mCFS: 25.7-mo; mOS: 93.3-mo), LIPI-Intermediate (mCFS: 14.8-mo; mOS: 51.9-mo) and LIPI-Poor group (mCFS: 6.8-mo; mOS: 18.5-mo) had sequentially worse clinical outcomes (p<0.001 for all pairwise comparisons). The results remain consistent after PSM. Multivariate Cox regression further confirmed that LIPI was an independent predictor of survival outcomes. Subgroup analysis verified that LIPI was associated with unfavorable prognosis in all subgroups except for cases with visceral metastases or receiving abiraterone/docetaxel. As for patients with CRPC receiving abiraterone, LIPI was also an indicator of poor prognosis. Specifically, cases in the LIPI-Good, LIPI-Intermediate and LIPI-Poor group had a ladder-shaped worse PSA response (71.4% [50/70] vs. 56.5% [39/69] vs. 36.8% [7/12], p=0.015), PSA-PFS (14.9- vs. 9.3- vs. 3.1-mo, p<0.001) and OS (14.6- vs. 32.3- vs. 53.4-mo, p<0.001). The results were robust even after PSM. Multivariate Cox regression confirmed that LIPI was an independent prognosticator of abiraterone. CONCLUSIONS: This study firstly demonstrated that baseline LIPI was a significant prognostic biomarker for both mHSPC and mCRPC patients and could potentially facilitate risk classification and treatment-decision making in clinical practice. Source of Funding: This work was supported by the National Natural Science Foundation of China (NSFC 82172785, 82103097, 81974398, 81902577, and 81872107) © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e218 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Zhipeng Wang More articles by this author Haoyang Liu More articles by this author Jinge Zhao More articles by this author Pengfei Shen More articles by this author Hao Zeng More articles by this author Expand All Advertisement PDF downloadLoading ...