Literature DB >> 10883676

Identification of long-term survivors in primary breast cancer by dynamic modelling of tumour response.

D A Cameron1, W M Gregory, A Bowman, E D Anderson, P Levack, P Forouhi, R C Leonard.   

Abstract

Although clinical response to primary chemotherapy in stage II and III breast cancer is associated with a survival advantage, it is the degree of pathological response in the breast and ipsilateral axilla that best identifies patients with a good long-term outcome. A mathematical model of the initial response of 39 locally advanced tumours to anthracycline-based primary chemotherapy has been previously shown to predict subsequent clinical tumour size. This model allows for the possibility of primary resistant disease, the presence of which should therefore be associated with a worse outcome. This study reports the application of this model to an additional five patients with locally advanced breast cancer, as well as to 63 patients with operable breast cancer, and confirms the biological reality of the model parameters for these 100 breast cancers treated with primary anthracycline-based chemotherapy. The tumours that responded to chemotherapy had higher cell-kill (P < 0.0005), lower resistance (P < 0.0001) and slower tumour regrowth (P < 0.002). Furthermore, ER-negative tumours had higher cell-kill (P < 0.05), as compared with ER-positive tumours. All patients with a pathological complete response had zero resistance according to the model. Furthermore, the long-term implication of chemo-resistant disease was demonstrated by survival analysis of these two groups of patients. At a median follow-up of 3.7 years, there was a statistically significantly worse survival for the 37 patients with locally advanced breast cancer identified by the model to have more than 8% primary resistant tumour (P < 0.003). The specificity of this putative prognostic indicator was confirmed in the 63 patients presenting with operable disease where, at a median follow-up of 7.7 years, those women with a resistant fraction of greater than 8% had a significantly worse survival (P < 0.05). Application of this model to patients treated with neoadjuvant chemotherapy may allow earlier identification of clinically significant resistance and permit intervention with alternative non-cross-resistant therapies such as taxoids.

Entities:  

Mesh:

Substances:

Year:  2000        PMID: 10883676      PMCID: PMC2374548          DOI: 10.1054/bjoc.2000.1216

Source DB:  PubMed          Journal:  Br J Cancer        ISSN: 0007-0920            Impact factor:   7.640


  20 in total

1.  Breast cancer prognostic factors: evaluation guidelines.

Authors:  W L McGuire
Journal:  J Natl Cancer Inst       Date:  1991-02-06       Impact factor: 13.506

2.  Primary chemotherapy to avoid mastectomy in tumors with diameters of three centimeters or more.

Authors:  G Bonadonna; U Veronesi; C Brambilla; L Ferrari; A Luini; M Greco; C Bartoli; G Coopmans de Yoldi; R Zucali; F Rilke
Journal:  J Natl Cancer Inst       Date:  1990-10-03       Impact factor: 13.506

3.  Preoperative chemotherapy in operable breast cancer.

Authors:  G Bonadonna; P Valagussa; C Brambilla; L Ferrari
Journal:  Lancet       Date:  1993-06-05       Impact factor: 79.321

4.  Measurement and management of carcinoma of the breast.

Authors:  R H Thomlinson
Journal:  Clin Radiol       Date:  1982-09       Impact factor: 2.350

5.  Neoadjuvant chemotherapy in 126 operable breast cancers.

Authors:  E Bélembaogo; V Feillel; P Chollet; H Curé; P Verrelle; F Kwiatkowski; J L Achard; G Le Bouëdec; J Chassagne; Y J Bignon
Journal:  Eur J Cancer       Date:  1992       Impact factor: 9.162

6.  Effects of primary chemotherapy in conservative treatment of breast cancer patients with operable tumors larger than 3 cm. Results of a randomized trial in a single centre.

Authors:  L Mauriac; M Durand; A Avril; J M Dilhuydy
Journal:  Ann Oncol       Date:  1991-05       Impact factor: 32.976

7.  High complete remission rates with primary neoadjuvant infusional chemotherapy for large early breast cancer.

Authors:  I E Smith; G Walsh; A Jones; J Prendiville; S Johnston; B Gusterson; F Ramage; H Robertshaw; N Sacks; S Ebbs
Journal:  J Clin Oncol       Date:  1995-02       Impact factor: 44.544

8.  Prediction of response to neoadjuvant chemoendocrine therapy in primary breast carcinomas.

Authors:  A Makris; T J Powles; M Dowsett; C K Osborne; P A Trott; I N Fernando; S E Ashley; M G Ormerod; J C Titley; R K Gregory; D C Allred
Journal:  Clin Cancer Res       Date:  1997-04       Impact factor: 12.531

9.  Using mathematical models to estimate drug resistance and treatment efficacy via CT scan measurements of tumour volume.

Authors:  W M Gregory; R H Reznek; M Hallett; M L Slevin
Journal:  Br J Cancer       Date:  1990-10       Impact factor: 7.640

10.  Primary systemic therapy for operable breast cancer.

Authors:  E D Anderson; A P Forrest; R A Hawkins; T J Anderson; R C Leonard; U Chetty
Journal:  Br J Cancer       Date:  1991-04       Impact factor: 7.640

View more
  2 in total

Review 1.  A Review of Mathematical Models for Tumor Dynamics and Treatment Resistance Evolution of Solid Tumors.

Authors:  Anyue Yin; Dirk Jan A R Moes; Johan G C van Hasselt; Jesse J Swen; Henk-Jan Guchelaar
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2019-08-09

2.  Cell killing and resistance in pre-operative breast cancer chemotherapy.

Authors:  Paolo Ubezio; David Cameron
Journal:  BMC Cancer       Date:  2008-07-21       Impact factor: 4.430

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.