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The growth law of primary breast cancer as inferred from mammography screening trials data.

机译:从乳腺X线摄影筛查试验数据可以推断出原发性乳腺癌的生长规律。

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摘要

Despite considerable progress in understanding tumour development, the law of growth for human tumours is still a matter of some dispute. In this study, we used large-scale mammography screening trial data to deduce the growth law of primary breast cancer. We compared the empirical tumour population size distributions of primary breast cancer inferred from these data to the distributions that correspond to various possible theoretical growth functions. From this, we showed that the data are inconsistent with the exponential, logistic and Gompertz laws, but support power law growth (exponent approximately 0.5). This law indicates unbounded growth but with slowing mass-specific growth rate and doubling time. In the clinical size ranges, it implies a greater decline in the mass-specific growth rate than would be predicted by the Gompertz law using the accepted parameters. This suggests that large tumours would be less sensitive to cycle-specific therapies, and be better treated first by non-cell cycle-specific agents. We discussed the use of our study to estimate the sensitivity of mammography for the detection of small tumours. For example, we estimated that mammography is about 30% less sensitive in the detection of tumours in the 1 to 1.5-cm range than it is in detecting larger tumours.
机译:尽管在理解肿瘤发展方面有相当大的进步,但是人类肿瘤的生长规律仍存在一些争议。在这项研究中,我们使用了大型乳腺摄影筛查试验数据来推断原发性乳腺癌的生长规律。我们将根据这些数据推断出的原发性乳腺癌的经验性肿瘤种群大小分布与对应于各种可能的理论增长函数的分布进行了比较。由此可见,数据与指数,逻辑和Gompertz定律不一致,但支持幂律增长(指数约0.5)。该定律表明无限制的增长,但是特定质量的增长速度减慢,时间加倍。在临床大小范围内,这意味着质量比增长率的下降幅度大于Gompertz法则使用接受参数所预测的幅度。这表明大肿瘤对周期特异性疗法的敏感性较低,并且首先应通过非细胞周期特异性药物进行更好的治疗。我们讨论了使用我们的研究来估计乳腺X线摄影对检测小肿瘤的敏感性。例如,我们估计乳房X线照相术在检测1到1.5厘米范围内的肿瘤时的敏感性要比检测更大的肿瘤时低30%。

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