Survival analysis and development of a prognostic nomogram for bone‐metastatic prostate cancer patients: A single‐center experience in Indonesia

作者
Andika Afriansyah,Agus Rizal Ardy Hariandy Hamid,Chaidir Arif Mochtar,Rainy Umbas
出处
期刊:International Journal of Urology [Wiley]
卷期号:26 (1): 83-89 被引量:13
标识
DOI:10.1111/iju.13813
摘要

OBJECTIVES: To analyze predictive clinical factors of survival in bone-metastatic prostate cancer, and to develop a prognostic nomogram for patients with this condition. METHODS: The present study included 392 patients with bone-metastatic prostate cancer treated with androgen deprivation therapy. Pretreatment parameters were analyzed using the Cox proportional hazards model to identify the predictors of overall survival. Covariates - which showed statistical significance on multivariate analysis - were used to develop a nomogram. A linear predictor model was utilized to develop the nomogram. RESULTS: The median overall survival was 40.3 months (95% confidence interval 32.2-48.5). Univariate analysis showed that clinical T stage, Gleason score, initial prostate-specific antigen value and the number of metastatic lesions were independent prognostic factors for overall survival. These predictors remained significant as independent prognostic factors for overall survival after analysis using the multivariate Cox regression model. The nomogram constructed from those prognostic factors showed good discrimination for predicting the 5-year overall survival, with an area under the curve of 0.69. Acceptable agreement of the observed and predicted probabilities was observed in the calibration plot. CONCLUSIONS: The present prognostic nomogram might be a useful tool for predicting overall survival in pretreatment bone-metastatic prostate cancer, specifically among Indonesian patients. Further studies are required to provide external validation to support the utilization of this nomogram.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
能干煎蛋发布了新的文献求助10
刚刚
脑洞疼应助ZhangLetian采纳,获得10
刚刚
陈树人完成签到,获得积分10
刚刚
1秒前
在水一方应助Alcb1168采纳,获得10
1秒前
Lucas应助诗谙采纳,获得10
2秒前
LJJZZX完成签到,获得积分10
2秒前
哇塞的发布了新的文献求助10
3秒前
曾经的丹彤完成签到,获得积分10
3秒前
撖堡包完成签到 ,获得积分10
5秒前
库卡完成签到,获得积分10
5秒前
6秒前
CipherSage应助闲出屁国公主采纳,获得10
6秒前
大模型应助青塘龙仔采纳,获得10
7秒前
诗谙完成签到,获得积分20
7秒前
可爱的函函应助青塘龙仔采纳,获得10
8秒前
FashionBoy应助青塘龙仔采纳,获得10
8秒前
CipherSage应助青塘龙仔采纳,获得10
8秒前
ChemPu发布了新的文献求助10
8秒前
上官若男应助青塘龙仔采纳,获得10
8秒前
小马甲应助青塘龙仔采纳,获得10
8秒前
9秒前
sugar应助青塘龙仔采纳,获得10
9秒前
爆米花应助青塘龙仔采纳,获得10
9秒前
aimme应助青塘龙仔采纳,获得10
9秒前
赘婿应助青塘龙仔采纳,获得10
9秒前
10秒前
研友_VZG7GZ应助2y采纳,获得10
10秒前
应然忆完成签到 ,获得积分10
11秒前
11秒前
ZhangLetian完成签到,获得积分10
11秒前
12秒前
lalalxx完成签到,获得积分10
15秒前
15秒前
15秒前
斯文败类应助春风十里采纳,获得10
15秒前
16秒前
16秒前
健壮的秋寒完成签到,获得积分10
16秒前
16秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The Effective Clinical Neurologist 3ed 500
The Great Hymn to Šamaš 500
Moody's Ratings Rising AI spending narrows the gap, but US hyperscalers retain edge over Chinese peers 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7696327
求助须知:如何正确求助?哪些是违规求助? 9256459
关于积分的说明 20002785
捐赠科研通 7270631
什么是DOI,文献DOI怎么找? 3292686
关于科研通互助平台的介绍 2448337
邀请新用户注册赠送积分活动 2298383