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全因死亡率作为评估乳腺癌筛查的指标的价值。

The Value of All-Cause Mortality as a Metric for Assessing Breast Cancer Screening.

机构信息

Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada.

Department of Medical Biophysics, University of Toronto, Toronto, Canada.

出版信息

J Natl Cancer Inst. 2020 Oct 1;112(10):989-993. doi: 10.1093/jnci/djaa025.

Abstract

Although screening mammography has been demonstrated to contribute to reducing mortality due to breast cancer, some have suggested that reduced all-cause mortality should constitute the burden of proof for effectiveness. Using a microsimulation model of the development, detection, and treatment of breast cancer, it is straightforward to demonstrate that this is an unrealistic expectation for trials of practical size and period of observation, even where the reduction of breast cancer mortality is substantial. Estimates of all-cause mortality will depend not only on the efficacy of the screening intervention but also on the alignment between the age distribution of the effect of screening on reduction of deaths and that of the other major causes of death. The size of a randomized trial required to demonstrate a reduction in all-cause mortality will, therefore, depend on the length and timing of the observation period and will typically be at least 10 times larger than the size of a trial powered to test for a reduction in deaths due to breast cancer. For breast cancer, which represents a small fraction of overall deaths, all-cause mortality is neither a practical nor informative metric for assessing the effectiveness of screening.

摘要

虽然筛查乳房 X 光检查已被证明有助于降低乳腺癌死亡率,但有人认为,降低全因死亡率应该构成有效性的证据负担。使用乳腺癌发生、检测和治疗的微观模拟模型,很明显,即使乳腺癌死亡率的降低幅度很大,对于实际规模和观察期的试验来说,这是不切实际的期望。全因死亡率的估计不仅取决于筛查干预的效果,还取决于筛查对降低死亡的影响的年龄分布与其他主要死亡原因的年龄分布之间的一致性。因此,为了证明全因死亡率降低,需要进行随机试验的规模将取决于观察期的长度和时间安排,并且通常至少是为了测试因乳腺癌死亡而减少的试验规模的 10 倍。对于仅占总死亡人数一小部分的乳腺癌,全因死亡率既不是评估筛查有效性的实际指标,也不是信息丰富的指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1eff/7566389/81108e4d97fc/djaa025f1.jpg

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