Cargando…

Mathematical modelling of tumour response in primary breast cancer.

Although breast cancer is perceived to be relatively chemosensitive, cytotoxic drug therapy only leads to cure in the adjuvant setting. In advanced disease, primary resistance and inadequate cell kill may be important in determining the lack of a durable response to cytotoxics, but for an individual...

Descripción completa

Detalles Bibliográficos
Autores principales: Cameron, D. A., Gregory, W. M., Bowman, A., Leonard, R. C.
Formato: Texto
Lenguaje:English
Publicado: Nature Publishing Group 1996
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2074487/
https://www.ncbi.nlm.nih.gov/pubmed/8645588
_version_ 1782137977179209728
author Cameron, D. A.
Gregory, W. M.
Bowman, A.
Leonard, R. C.
author_facet Cameron, D. A.
Gregory, W. M.
Bowman, A.
Leonard, R. C.
author_sort Cameron, D. A.
collection PubMed
description Although breast cancer is perceived to be relatively chemosensitive, cytotoxic drug therapy only leads to cure in the adjuvant setting. In advanced disease, primary resistance and inadequate cell kill may be important in determining the lack of a durable response to cytotoxics, but for an individual patient's tumour there is no consistent way of determining the importance of these two factors. An adaptation of Skipper's log cell kill model of tumour response to chemotherapy was applied to serial tumour measurements of 46 locally advanced primary breast carcinomas undergoing neoadjuvant chemotherapy. Assuming a log-normal distribution of errors in the clinically measured volumes, the model produced, for each tumour separately, in vivo estimates of proportional cell kill, initial resistance and tumour doubling times during therapy. After 4 weeks' treatment, these data could then be used to predict subsequent tumour volumes with good accuracy. In addition, for the 13 tumours that became operable after the neoadjuvant chemotherapy, there was a significant association between the final volume as predicted by the model and the final pathological volume (P < 0.05). This approach could be usefully employed to determine those tumours that are primarily resistant to the treatment regimen, permitting changes of therapy to more effective drugs at a time when the tumour is clinically responding but destined to progress.
format Text
id pubmed-2074487
institution National Center for Biotechnology Information
language English
publishDate 1996
publisher Nature Publishing Group
record_format MEDLINE/PubMed
spelling pubmed-20744872009-09-10 Mathematical modelling of tumour response in primary breast cancer. Cameron, D. A. Gregory, W. M. Bowman, A. Leonard, R. C. Br J Cancer Research Article Although breast cancer is perceived to be relatively chemosensitive, cytotoxic drug therapy only leads to cure in the adjuvant setting. In advanced disease, primary resistance and inadequate cell kill may be important in determining the lack of a durable response to cytotoxics, but for an individual patient's tumour there is no consistent way of determining the importance of these two factors. An adaptation of Skipper's log cell kill model of tumour response to chemotherapy was applied to serial tumour measurements of 46 locally advanced primary breast carcinomas undergoing neoadjuvant chemotherapy. Assuming a log-normal distribution of errors in the clinically measured volumes, the model produced, for each tumour separately, in vivo estimates of proportional cell kill, initial resistance and tumour doubling times during therapy. After 4 weeks' treatment, these data could then be used to predict subsequent tumour volumes with good accuracy. In addition, for the 13 tumours that became operable after the neoadjuvant chemotherapy, there was a significant association between the final volume as predicted by the model and the final pathological volume (P < 0.05). This approach could be usefully employed to determine those tumours that are primarily resistant to the treatment regimen, permitting changes of therapy to more effective drugs at a time when the tumour is clinically responding but destined to progress. Nature Publishing Group 1996-06 /pmc/articles/PMC2074487/ /pubmed/8645588 Text en https://creativecommons.org/licenses/by/4.0/This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/.
spellingShingle Research Article
Cameron, D. A.
Gregory, W. M.
Bowman, A.
Leonard, R. C.
Mathematical modelling of tumour response in primary breast cancer.
title Mathematical modelling of tumour response in primary breast cancer.
title_full Mathematical modelling of tumour response in primary breast cancer.
title_fullStr Mathematical modelling of tumour response in primary breast cancer.
title_full_unstemmed Mathematical modelling of tumour response in primary breast cancer.
title_short Mathematical modelling of tumour response in primary breast cancer.
title_sort mathematical modelling of tumour response in primary breast cancer.
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2074487/
https://www.ncbi.nlm.nih.gov/pubmed/8645588
work_keys_str_mv AT cameronda mathematicalmodellingoftumourresponseinprimarybreastcancer
AT gregorywm mathematicalmodellingoftumourresponseinprimarybreastcancer
AT bowmana mathematicalmodellingoftumourresponseinprimarybreastcancer
AT leonardrc mathematicalmodellingoftumourresponseinprimarybreastcancer