1996
DOI: 10.1002/(sici)1097-0142(19961115)78:10<2170::aid-cncr19>3.0.co;2-w
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Prognostic relevance of the intrinsic growth deceleration of the first passage xenografts of human renal cell carcinomas

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Cited by 6 publications
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“…Mathematical modelling of tumour growth can provide not only key insights into tumour biology but also tools for, e.g., optimization of screening programs, cancer patient prognosis [1], scheduling of chemotherapy [2], and assessment of tumour spread [3,4]. For example, Norton et al showed that, considering the mathematical growth model of breast cancer tumours, patients must be treated with condensed-dose chemotherapy, and a clinical trial showed the significant benefit for the patients treated with the new method compared with the patients treated with the standard treatment [5,6].…”
Section: Introductionmentioning
confidence: 99%
“…Mathematical modelling of tumour growth can provide not only key insights into tumour biology but also tools for, e.g., optimization of screening programs, cancer patient prognosis [1], scheduling of chemotherapy [2], and assessment of tumour spread [3,4]. For example, Norton et al showed that, considering the mathematical growth model of breast cancer tumours, patients must be treated with condensed-dose chemotherapy, and a clinical trial showed the significant benefit for the patients treated with the new method compared with the patients treated with the standard treatment [5,6].…”
Section: Introductionmentioning
confidence: 99%
“…Studying natural tumour growth is valuable for understanding tumour biology, optimising screening programs, prognostication [1], optimal scheduling of chemotherapy [2], and assessing tumour spread (number and size distribution of metastases, including micro-metastases) [3,4]. Mathematical models such as the exponential and the Gompertzian growth models are usually used to describe tumour growth.…”
Section: Introductionmentioning
confidence: 99%