TY - JOUR
T1 - Individual risk profiling for breast cancer recurrence
T2 - Towards tailored follow-up schemes
AU - Kraeima, J.
AU - Siesling, S.
AU - Vliegen, I. M.H.
AU - Klaase, J. M.
AU - Ijzerman, M. J.
PY - 2013/8/20
Y1 - 2013/8/20
N2 - Background: Breast cancer follow-up is not tailored to the risk of locoregional recurrences (LRRs) in individual patients or as a function of time. The objective of this study was to identify prognostic factors and to estimate individual and time-dependent LRR risk rates. Methods: Prognostic factors for LRR were identified by a scoping literature review, expert consultation, and stepwise multivariate regression analysis based on 5 years of data from women diagnosed with breast cancer in the Netherlands in 2005 or 2006 (n=17 762). Inter-patient variability was elucidated by examples of 5-year risk profiles of average-, medium-, and high-risk patients, whereby 6-month interval risks were derived from regression estimates. Results: Eight prognostic factors were identified: age, tumour size, multifocality, gradation, adjuvant chemo-, adjuvant radiation-, hormonal therapy, and triple-negative receptor status. Risk profiles of the low-, average-, and high-risk example patients showed non-uniform distribution of recurrence risks (2.9, 7.6, and 9.2%, respectively, over a 5-year period). Conclusion: Individual risk profiles differ substantially in subgroups of patients defined by prognostic factors for recurrence and over time as defined in 6-month time intervals. To tailor follow-up schedules and to optimise allocation of scarce resources, risk factors, frequency, and duration of follow-up should be taken into account.
AB - Background: Breast cancer follow-up is not tailored to the risk of locoregional recurrences (LRRs) in individual patients or as a function of time. The objective of this study was to identify prognostic factors and to estimate individual and time-dependent LRR risk rates. Methods: Prognostic factors for LRR were identified by a scoping literature review, expert consultation, and stepwise multivariate regression analysis based on 5 years of data from women diagnosed with breast cancer in the Netherlands in 2005 or 2006 (n=17 762). Inter-patient variability was elucidated by examples of 5-year risk profiles of average-, medium-, and high-risk patients, whereby 6-month interval risks were derived from regression estimates. Results: Eight prognostic factors were identified: age, tumour size, multifocality, gradation, adjuvant chemo-, adjuvant radiation-, hormonal therapy, and triple-negative receptor status. Risk profiles of the low-, average-, and high-risk example patients showed non-uniform distribution of recurrence risks (2.9, 7.6, and 9.2%, respectively, over a 5-year period). Conclusion: Individual risk profiles differ substantially in subgroups of patients defined by prognostic factors for recurrence and over time as defined in 6-month time intervals. To tailor follow-up schedules and to optimise allocation of scarce resources, risk factors, frequency, and duration of follow-up should be taken into account.
UR - http://www.scopus.com/inward/record.url?scp=84883195448&partnerID=8YFLogxK
U2 - 10.1038/bjc.2013.401
DO - 10.1038/bjc.2013.401
M3 - Article
C2 - 23860534
AN - SCOPUS:84883195448
SN - 0007-0920
VL - 109
SP - 866
EP - 871
JO - British Journal of Cancer
JF - British Journal of Cancer
IS - 4
ER -