Using semi-Markov processes to study timeliness and tests used in the diagnostic evaluation of suspected breast cancer.
Using semi-Markov processes to study timeliness and tests used in the diagnostic evaluation of suspected breast cancer.
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DOI：
10.1002/sim.7055
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发表时间：
2016-11-30
影响因子：
2
通讯作者：
Inoue, L. Y. T.
中科院分区：
文献类型：
--
作者：
Hubbard, R. A.;Lange, J.;Zhang, Y.;Salim, B. A.;Stroud, J. R.;Inoue, L. Y. T.
由于筛查乳房X光检查结果异常而对疑似乳腺癌进行诊断评估很常见，这会给女性带来焦虑，并且对医疗保健系统来说成本高昂。及时评估并尽量减少额外的诊断测试是最大程度地减少焦虑和成本的关键。在本文中，我们提出了一种贝叶斯半马尔可夫模型，该模型允许对停留时间分布进行灵活的半参数指定，并将我们的模型应用于异常筛查乳房X光检查后使用乳房X光摄影、超声和活检进行诊断评估的过程的研究。我们还调查了与诊断测试之间的停留时间相关的风险因素。通过利用半马尔可夫过程，我们扩展了之前的工作，通过提供额外的信息来描述第一次测试的时间，例如平均解决时间和 90 天后乳房 X 光检查未解决的女性比例，这些信息需要不同的测试序列才能得出明确的诊断。总体而言，我们发现老年女性更有可能在 90 天后出现未解决的乳房 X 光检查阳性结果。影像学评估和活检的时间差异通常为数天，因此并不代表诊断延迟的临床重要差异。
Diagnostic evaluation of suspected breast cancer due to abnormal screening mammography results is common, creates anxiety for women and is costly for the healthcare system. Timely evaluation with minimal use of additional diagnostic testing is key to minimizing anxiety and cost. In this paper we propose a Bayesian Semi-Markov model that allows for flexible, semi-parametric specification of the sojourn time distributions and apply our model to an investigation of the process of diagnostic evaluation with mammography, ultrasound and biopsy following an abnormal screening mammogram. We also investigate risk factors associated with the sojourn time between diagnostic tests. By utilizing Semi-Markov processes we expand on prior work which described the timing of the first test received by providing additional information such as the mean time to resolution and proportion of women with unresolved mammograms after 90 days for women requiring different sequences of tests in order to reach a definitive diagnosis. Overall, we found that older women were more likely to have unresolved positive mammograms after 90 days. Differences in the timing of imaging evaluation and biopsy were generally on the order of days and thus did not represent clinically important differences in diagnostic delay.
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影响因子：
3.8
作者：
Hubbard, Rebecca A.;Zhu, Weiwei;Horblyuk, Ruslan;Karliner, Leah;Sprague, Brian L.;Henderson, Louise;Lee, David;Onega, Tracy;Buist, Diana S. M.;Sweet, Alison
通讯作者：
Sweet, Alison
影响因子：
2.1
作者：
Kang, Minhee;Lagakos, Stephen W.
通讯作者：
Lagakos, Stephen W.
影响因子：
1.9
作者：
Titman, Andrew C.;Sharples, Linda D.
通讯作者：
Sharples, Linda D.
影响因子：
1.9
作者：
Smith, RA;Duffy, SW;Chen, THH
通讯作者：
Chen, THH
影响因子：
1.9
作者：
Perron, F;Mengersen, K
通讯作者：
Mengersen, K