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首页> 外文期刊>Advances in Epidemiology >Estimating Cancer Latency Times Using a Weibull Model
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Estimating Cancer Latency Times Using a Weibull Model

机译：使用Weibull模型估算癌症潜伏期

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Mathematical models can be useful tools in exploring population disease trends over time and can be used to gain insight into the fundamental mechanisms of cancer development. In this paper, we provide a systematic comparison between the exact and the approximate solutions for estimating the length of time between the biological initiation of cancer and diagnosis through the development of a Weibull-like survival model. A total of 1,608,484 malignant primary cancers were used in the analysis using cancer incidence data obtained from the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) program. We find that the approximate solution provides a reliable comparison of the latency periods for different types of cancer and has no significant effect on the estimation accuracy, which differs from the exact solution by 0% to 11.3%. Thirty-five of the 44 cancers in this analysis were found to progress silently for 10 years or longer prior to detection representing 89% of the patients in this analysis. The results of this analysis differentiate cancer types that progress undetected over a period of years to identify new opportunities for early detection which increases the likelihood of successful treatment and alleviates the ever-growing cancer burden.
机译：数学模型可以作为探索人口疾病随时间变化趋势的有用工具，并可用于深入了解癌症发展的基本机制。在本文中，我们提供了精确解决方案和近似解决方案之间的系统比较，以通过建立类似Weibull的生存模型来估计癌症的生物发生和诊断之间的时间长度。根据从美国国家癌症研究所的监视，流行病学和最终结果（SEER）计划获得的癌症发病率数据，总共使用了1,608,484例恶性原发癌。我们发现，近似解提供了不同类型癌症的潜伏期的可靠比较，并且对估计准确性没有显着影响，与精确解相差0％至11.3％。发现该分析中的44种癌症中有35种在检测之前静默发展了10年或更长时间，占该分析中89％的患者。这项分析的结果区分了多年来未被发现的癌症类型，从而发现了早期发现的新机会，这增加了成功治疗的可能性并减轻了日益增长的癌症负担。

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