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Uncovering the natural history of cancer from post-mortem cross-sectional diameters of hepatic metastases

机译:从肝转移的死后横截面直径揭示癌症的自然史

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We develop a mathematical and statistical methodology for estimation of important unobservable characteristics of the individual natural history of cancer from a sample of cross-sectional diameters of liver metastases measured at autopsy. Estimation of the natural history of cancer is based on a previously proposed stochastic model of cancer progression tailored to this type of observations. The model accounts for primary tumour growth, shedding of metastases, their selection, latency and growth in a given secondary site. The model was applied to the aforementioned data on 428 liver metastases detected in one untreated small cell lung cancer patient. Identifiable model parameters were estimated by the method of maximum likelihood and through minimizing the L-2 distance between theoretical and empirical cumulative distribution functions. The model with optimal parameters provided an excellent fit to the data. Results of data analysis support, if only indirectly, the hypothesis of the existence of stem-like cancer cells in the case of small cell lung carcinoma and point to the possibility of suppression of metastatic growth by a large primary tumour. They also lead to determination of the lower and upper bounds for the age of cancer onset and expected duration of metastatic latency. Finally, model-based inference on the patient's natural history of cancer allowed us to conclude that resection of the primary tumour would most likely not have had a curative effect.
机译:我们开发了一种数学和统计方法,用于从尸检时测得的肝转移的横截面直径样本中估算出癌症个体自然病史的重要不可观察特征。癌症自然史的估算是基于针对这种类型的观察量身定制的先前癌症发展的随机模型。该模型考虑了原发肿瘤的生长,转移的脱落,其选择,潜伏期和在给定继发部位的生长。该模型应用于在未经治疗的小细胞肺癌患者中检测到的428例肝转移的上述数据。可识别的模型参数是通过最大似然法并通过最小化理论和经验累积分布函数之间的L-2距离来估计的。具有最佳参数的模型非常适合数据。数据分析的结果(仅间接地)支持小细胞肺癌情况下干细胞样癌细胞存在的假说,并指出大原发性肿瘤抑制转移性生长的可能性。它们还导致确定癌症发作年龄和转移潜伏期的预期持续时间的上限和下限。最后,基于模型的关于患者自然癌症史的推论使我们得出结论,原发肿瘤切除很可能不会产生治愈作用。

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