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前列腺癌生存估计:分段危险函数推导的一个应用。

Prostate cancer survival estimates: An application with piecewise hazard function derivation.

作者信息

Bhattacharjee Atanu, Budukh Atul, Dikshit Rajesh

机构信息

Centre for Cancer Epidemiology, The Advanced Centre for Treatment, Research and Education in Cancer, Tata Memorial Centre, Navi Mumbai, Maharastra, India.

出版信息

South Asian J Cancer. 2019 Jul-Sep;8(3):150-159. doi: 10.4103/sajc.sajc_245_18.

Abstract

BACKGROUND

The hazard function is defined as time-dependent. However, it is an overlooked area of research about the estimation of hazard function within the frame of time. The possible explanation could be carried by estimating function through the changes of time points. It is expected that it will provide us the overall idea of survival trend. This work is dedicated to propose a method to work with piecewise hazard rate. It is a data-driven method and provides us the estimates of hazard function with different time points.

METHODS

The proposed method is explored with prostate cancer patients, registered in the Surveillance, Epidemiology, and End Results Program and having aged at diagnosis with range 40-80 years and above. A total of 610,814 patients are included in this study. The piecewise hazard rate is formulated to serve the objective. The measurement of piecewise hazard rate is compared with Wald-type test statistics, and corresponding function is provided. The duration of follow-ups is split into different intervals to obtain the piecewise hazard rate estimates.

RESULTS

The maximum duration of follow-up observed in this study is 40 years. The piecewise hazard rate changes at different intervals of follow-ups are observed almost same except few later intervals in the follow-up. The likelihood of hazard in earlier aged patients observed lower in comparison to older patients. The hazard rates in different grades of prostate cancer also observed separately.

CONCLUSION

The application of piecewise hazard helps to generate statistical inference in a deeper manner. This analysis will provide us the better understanding of a requirement of effective treatment toward prolonged survival benefit for different aged patients.

摘要

背景

风险函数被定义为随时间变化。然而,在时间框架内对风险函数估计的研究领域却被忽视了。可能的解释是通过时间点的变化来估计函数。期望它能为我们提供生存趋势的总体概念。这项工作致力于提出一种处理分段风险率的方法。这是一种数据驱动的方法,能为我们提供不同时间点的风险函数估计值。

方法

对在监测、流行病学和最终结果计划中登记的前列腺癌患者进行了该方法的探索,这些患者诊断时年龄在40至80岁及以上。本研究共纳入610814名患者。制定分段风险率以实现该目标。将分段风险率的测量与 Wald 型检验统计量进行比较,并提供相应的函数。随访持续时间被划分为不同区间以获得分段风险率估计值。

结果

本研究中观察到的最长随访持续时间为40年。除了随访后期的少数区间外,在不同随访区间观察到的分段风险率变化几乎相同。与老年患者相比,观察到老年前期患者的风险可能性较低。还分别观察了不同前列腺癌分级的风险率。

结论

分段风险的应用有助于更深入地进行统计推断。该分析将使我们更好地理解针对不同年龄患者延长生存获益的有效治疗需求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bb59/6699225/7211f73c0a16/SAJC-8-150-g010.jpg

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