External validation of the albumin, C-reactive protein and lactate dehydrogenase model in patients with metastatic renal cell carcinoma receiving second-line axitinib therapy in a Japanese multi-center cohort

Author:

Tamura Keita1ORCID,Osawa Takahiro2,Takeuchi Ario3,Minami Keita4,Nakai Yasutomo5,Ueda Kosuke6,Ozawa Michinobu7,Uemura Motohide8,Sugimoto Mikio9,Ohba Kojiro10,Suzuki Toshihiro11,Anai Satoshi12,Shindo Tetsuya13ORCID,Kusakabe Naohisa14,Komiyama Motokiyo15,Tanaka Ken16,Yokomizo Akira17,Kohei Naoki18,Shinohara Nobuo2,Miyake Hideaki1,

Affiliation:

1. Department of Urology, Hamamatsu University School of Medicine, Hamamatsu, Japan

2. Department of Urology, Hokkaido University Hospital, Sapporo, Japan

3. Department of Urology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan

4. Department of Urology, Sapporo City General Hospital, Sapporo, Japan

5. Department of Urology, Osaka International Cancer Institute, Osaka, Japan

6. Department of Urology, Kurume University Hospital, Kurume, Japan

7. Department of Urology, Yamagata University Faculty of Medicine, Yamagata, Japan

8. Department of Urology, Osaka University Hospital, Suita, Japan

9. Department of Urology, Kagawa University, Takamatsu, Japan

10. Department of Urology, Nagasaki University Hospital, Nagasaki, Japan

11. Department of Urology, Shinshu University Hospital, Matsumoto, Japan

12. Department of Urology, Nara Medical University, Kashihara, Japan

13. Department of Urology, Sapporo Medical University, Sapporo, Japan

14. Department of Urology, Obihiro Kosei Hospital, Obihiro, Japan

15. Department of Urology, National Cancer Center Hospital, Chiba, Japan

16. Department of Urology, University of Tsukuba Hospital, Tsukuba, Japan

17. Department of Urology, Harasanshin Hospital, Fukuoka, Japan

18. Department of Urology, Shizuoka General Hospital, Shizuoka, Japan

Abstract

Abstract Purpose To externally validate the utility of the albumin, C-reactive protein and lactate dehydrogenase model to predict the overall survival of previously treated metastatic renal cell carcinoma patients. Patients and methods The ability of the albumin, C-reactive protein and lactate dehydrogenase model to predict overall survival was validated and compared with those of other prognostication models using data from 421 metastatic renal cell carcinoma patients receiving second-line axitinib therapy at 36 hospitals belonging to the Japan Urologic Oncology Group. Results The following factors in this cohort were independently associated with poor overall survival in a multivariate analysis: a low Karnofsky performance status, <1 year from diagnosis to targeted therapy, a high neutrophil count, and low albumin, elevated C-reactive protein, and elevated lactate dehydrogenase, and the Japan Urologic Oncology Group model was newly developed based on the presence/absence of these independent factors. In this cohort, 151 (35.9%), 125 (27.7%) and 145 (34.4%) patients were classified into the favorable, intermediate and poor risk groups, respectively, according to the albumin, C-reactive protein and lactate dehydrogenase model; however, the proportions of patients in the intermediate risk group stratified by the Japan Urologic Oncology Group, Memorial Sloan Kettering Cancer Center and International Metastatic Renal Cell Carcinoma Database Consortium models were >50%. The superiority of the albumin, C-reactive protein and lactate dehydrogenase model to the Memorial Sloan Kettering Cancer Center and International Metastatic Renal Cell Carcinoma Database Consortium models, but not the Japan Urologic Oncology Group model, was demonstrated by multiple statistical analyses. Conclusions The utility of the albumin, C-reactive protein and lactate dehydrogenase model as a simple and objective prognostication tool was successfully validated using data from 421 metastatic renal cell carcinoma patients receiving second-line axitinib.

Funder

Japan Clinical Oncology Group

Publisher

Oxford University Press (OUP)

Subject

Cancer Research,Radiology Nuclear Medicine and imaging,Oncology,General Medicine

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