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晚期前列腺癌患者因糖尿病状态导致的非计划性住院:一项基于人群的研究。

Unplanned hospitalization among advanced prostate cancer patients by diabetes status: a population-based study.

作者信息

Shaver Amy L, Gandhi Krupa, Keith Scott W, Nikita Nikita, Yang Christopher C, Kim Felix J, Yang Hushan, Kelly William Kevin, Freedland Stephen J, Lu-Yao Grace

机构信息

Division of Population Science, Department of Medical Oncology, Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA, United States.

Sidney Kimmel Comprehensive Cancer Center at Thomas Jefferson University, Philadelphia, PA, United States.

出版信息

JNCI Cancer Spectr. 2025 Sep 1;9(5). doi: 10.1093/jncics/pkaf070.

DOI:10.1093/jncics/pkaf070
PMID:40668753
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12404530/
Abstract

BACKGROUND

Older adults with advanced prostate cancer and type 2 diabetes mellitus are underrepresented in trials of androgen receptor pathway inhibitors. This study examined changes in unplanned hospitalization rates in patients receiving androgen receptor pathway inhibitors by type 2 diabetes mellitus status and assessed if unplanned hospitalization varies according to androgen receptor pathway inhibitors.

METHODS

This population-based study of advanced prostate cancer patients aged older than 66 years used Surveillance, Epidemiology, and End Results-Medicare data. Prepost androgen receptor pathway inhibitor initiation changes and androgen receptor pathway inhibitor differences in unplanned hospitalization rates were estimated by adjusted incidence rate ratio with considerations for interactions between period, androgen receptor pathway inhibitor, and type 2 diabetes mellitus status. Linear contrasts were used to estimate and test conditional incidence rate ratios. Tests were 2-sided, and a P value less than .05 was considered statistically significant.

RESULTS

The study included 12 240 patients: 3160 (25.8%) with type 2 diabetes mellitus, 7191 (58.8%) received abiraterone acetate with prednisone, and 5049 (41.2%) received enzalutamide. Unplanned hospitalization rates increased after androgen receptor pathway inhibitor initiation by 65% among patients with type 2 diabetes mellitus complications (adjusted incidence rate ratio = 1.65, 95% confidence interval [CI] = 1.37 to 1.98) and 109% in nondiabetics (adjusted incidence rate ratio = 2.09, 95% CI = 1.94 to 2.26). Among patients with type 2 diabetes mellitus without complications, the increase in unplanned hospitalization rates depended on the androgen receptor pathway inhibitor initiated: 103% after abiraterone acetate with prednisone (adjusted incidence rate ratio = 2.03, 95% CI = 1.70 to 2.43) and 47% after enzalutamide (adjusted incidence rate ratio = 1.47, 95% CI = 1.21 to 1.80) and a 38% greater increase in unplanned hospitalization rates after abiraterone acetate with prednisone than enzalutamide (ratio of abiraterone acetate with prednisone adjusted incidence rate ratio divided by enzalutamide adjusted incidence rate ratio = 1.38, 95% CI = 1.06 to 1.80).

CONCLUSIONS

All patients had higher unplanned hospitalization rates after androgen receptor pathway inhibitor. Our findings highlight the importance of using real-world data to better understand the interplay between preexisting health conditions and treatment outcomes, a critical step toward precision medicine.

摘要

背景

患有晚期前列腺癌和2型糖尿病的老年人在雄激素受体通路抑制剂试验中的代表性不足。本研究通过2型糖尿病状态检查接受雄激素受体通路抑制剂患者的非计划住院率变化,并评估非计划住院是否因雄激素受体通路抑制剂而异。

方法

这项基于人群的66岁以上晚期前列腺癌患者研究使用了监测、流行病学和最终结果-医疗保险数据。通过调整发病率比估计雄激素受体通路抑制剂起始前后的变化以及非计划住院率的雄激素受体通路抑制剂差异,并考虑时期、雄激素受体通路抑制剂和2型糖尿病状态之间的相互作用。线性对比用于估计和检验条件发病率比。检验为双侧检验,P值小于0.05被认为具有统计学意义。

结果

该研究纳入了12240名患者:3160名(25.8%)患有2型糖尿病,7191名(58.8%)接受醋酸阿比特龙联合泼尼松治疗,5049名(41.2%)接受恩杂鲁胺治疗。在患有2型糖尿病并发症的患者中,启动雄激素受体通路抑制剂后非计划住院率增加了65%(调整发病率比=1.65,95%置信区间[CI]=1.37至1.98),在非糖尿病患者中增加了109%(调整发病率比=2.09,95%CI=1.94至2.26)。在没有并发症的2型糖尿病患者中,非计划住院率的增加取决于启动的雄激素受体通路抑制剂:醋酸阿比特龙联合泼尼松治疗后增加103%(调整发病率比=2.03,95%CI=1.70至2.43),恩杂鲁胺治疗后增加47%(调整发病率比=1.47,95%CI=1.21至1.80),醋酸阿比特龙联合泼尼松治疗后的非计划住院率增加比恩杂鲁胺高38%(醋酸阿比特龙联合泼尼松调整发病率比除以恩杂鲁胺调整发病率比的比值=1.38,95%CI=1.06至1.80)。

结论

所有患者在接受雄激素受体通路抑制剂治疗后非计划住院率均较高。我们的研究结果强调了使用真实世界数据来更好地理解既往健康状况与治疗结果之间相互作用的重要性,这是迈向精准医学的关键一步。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d02/12404530/cdf5836fa9eb/pkaf070f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d02/12404530/d08a7efeced7/pkaf070f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d02/12404530/cdf5836fa9eb/pkaf070f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d02/12404530/d08a7efeced7/pkaf070f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d02/12404530/cdf5836fa9eb/pkaf070f2.jpg

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