Elia Biganzoli1, Christine Desmedt2, Marco Fornili3, Evandro de Azambuja4, Nathalie Cornez5, Fernand Ries6, Marie-Thérèse Closon-Dejardin7, Joseph Kerger4, Christian Focan8, Angelo Di Leo9, Jean-Marie Nogaret10, Christos Sotiriou11, Martine Piccart4, Romano Demicheli3. 1. Unit of Medical Statistics, Biometry and Bioinformatics "Giulio A. Maccacaro", Department of Clinical Sciences and Community Health, University of Milan Campus Cascina Rosa, Fondazione IRCCS Istituto Nazionale Tumori, 20133 Milan, Italy. Electronic address: elia.biganzoli@unimi.it. 2. Breast Cancer Translational Research Laboratory, Université Libre de Bruxelles (U.L.B.), Institut Jules Bordet, 1000 Brussels, Belgium. Electronic address: christine.desmedt@bordet.be. 3. Unit of Medical Statistics, Biometry and Bioinformatics "Giulio A. Maccacaro", Department of Clinical Sciences and Community Health, University of Milan Campus Cascina Rosa, Fondazione IRCCS Istituto Nazionale Tumori, 20133 Milan, Italy. 4. Department of Medical Oncology, Institut Jules Bordet, Université Libre de Bruxelles (U.L.B.), 1000 Brussels, Belgium. 5. Department of Oncology, CHC-Clinique Saint-Joseph, 4000 Liège, Belgium. 6. Centre Hospitalier de Luxembourg, 1210 Luxembour, GD Luxembourg, Belgium. 7. Department of Radiotherapy, CHU Liège, 4000 Liège, Belgium. 8. Department of Internal Medicine and Oncology, Clinique St-Joseph Espérance, 4000 Liège, Belgium. 9. Sandro Pitigliani Medical Oncology Unit, Hospital of Prato, Instituto Toscano Tumori, 59100 Prato, Italy. 10. Department of Surgery, Institut Jules Bordet, Université Libre de Bruxelles (U.L.B.), 1000 Brussels, Belgium. 11. Breast Cancer Translational Research Laboratory, Université Libre de Bruxelles (U.L.B.), Institut Jules Bordet, 1000 Brussels, Belgium.
Abstract
BACKGROUND: In cancer follow-up, in addition to the evaluation of survival probabilities, there is a fundamental need of assessing recurrence dynamics for optimal disease management. Although the time-dependent effect of the oestrogen receptor (ER) status of the tumour has already been described, so far no factor has proven to disentangle the multi-peak behaviour observed for breast cancer recurrences. Here, we aimed at investigating whether adiposity at diagnosis, reflected by increased patient's body mass index (BMI), could be associated with breast cancer recurrence patterns over time after primary cancer therapy. METHODS: We retrieved BMI from 734 of 777 patients with node-positive breast cancer from a phase III randomised clinical trial, which compared different chemotherapy regimens and had a median follow-up of 15.4 years. Cumulative incidence estimation as well as piecewise exponential models were carried out to estimate the distant recurrence dynamics, in all patients, as well as in subgroups based on the ER status, with the ER-positive group being further split according to the menopausal status. RESULTS: In patients with ER-negative breast cancer, time-dependent analyses revealed that the hazard of late relapses could mainly be attributed to the overweight and obese patients. Within the subgroup of premenopausal patients with ER-positive tumours, obesity was associated with an early high narrow peak of distant recurrences followed by another main peak after 5 years of follow-up. The risk for overweight patients was intermediate between obese and normal-weight patients. In the postmenopausal subgroup of patients with ER-positive tumours, the distant recurrence rate was significantly more elevated in the overweight patients compared to the other BMI categories, and a second late peak of recurrences was also observed for the obese patients. CONCLUSION: These results demonstrate that the patient's BMI at diagnosis is associated with cancer recurrence dynamics. Patient adiposity should therefore be central to the exploration of late adjuvant treatment modalities.
RCT Entities:
BACKGROUND: In cancer follow-up, in addition to the evaluation of survival probabilities, there is a fundamental need of assessing recurrence dynamics for optimal disease management. Although the time-dependent effect of the oestrogen receptor (ER) status of the tumour has already been described, so far no factor has proven to disentangle the multi-peak behaviour observed for breast cancer recurrences. Here, we aimed at investigating whether adiposity at diagnosis, reflected by increased patient's body mass index (BMI), could be associated with breast cancer recurrence patterns over time after primary cancer therapy. METHODS: We retrieved BMI from 734 of 777 patients with node-positive breast cancer from a phase III randomised clinical trial, which compared different chemotherapy regimens and had a median follow-up of 15.4 years. Cumulative incidence estimation as well as piecewise exponential models were carried out to estimate the distant recurrence dynamics, in all patients, as well as in subgroups based on the ER status, with the ER-positive group being further split according to the menopausal status. RESULTS: In patients with ER-negative breast cancer, time-dependent analyses revealed that the hazard of late relapses could mainly be attributed to the overweight and obesepatients. Within the subgroup of premenopausal patients with ER-positive tumours, obesity was associated with an early high narrow peak of distant recurrences followed by another main peak after 5 years of follow-up. The risk for overweight patients was intermediate between obese and normal-weight patients. In the postmenopausal subgroup of patients with ER-positive tumours, the distant recurrence rate was significantly more elevated in the overweight patients compared to the other BMI categories, and a second late peak of recurrences was also observed for the obesepatients. CONCLUSION: These results demonstrate that the patient's BMI at diagnosis is associated with cancer recurrence dynamics. Patient adiposity should therefore be central to the exploration of late adjuvant treatment modalities.
Authors: Maria Alice Franzoi; Daniel Eiger; Lieveke Ameye; Noam Ponde; Rafael Caparica; Claudia De Angelis; Mariana Brandão; Christine Desmedt; Serena Di Cosimo; Nuria Kotecki; Matteo Lambertini; Ahmad Awada; Martine Piccart; Evandro de Azambuja Journal: J Natl Cancer Inst Date: 2021-04-06 Impact factor: 13.506
Authors: Jennifer Y Sheng; Cesar A Santa-Maria; Amanda L Blackford; David Lim; Ashley Carpenter; Karen L Smith; Gary I Cohen; Janelle Coughlin; Lawrence J Appel; Vered Stearns; Claire Snyder Journal: J Cancer Surviv Date: 2021-05-20 Impact factor: 4.062
Authors: Mélanie Bousquenaud; Flavia Fico; Giovanni Solinas; Curzio Rüegg; Albert Santamaria-Martínez Journal: Breast Cancer Res Date: 2018-09-04 Impact factor: 6.466