Validation of the Web-Based IBTR! 2.0 Nomogram to Predict for Ipsilateral Breast Tumor Recurrence After Breast-Conserving Therapy.
To evaluate the IBTR! 2.0 nomogram, which predicts 10-year ipsilateral breast tumor recurrence (IBTR) after breast-conserving therapy with and without radiation therapy for breast cancer, by using a large, external, and independent cancer center database.



We retrospectively identified 1898 breast cancer cases, treated with breast-conserving therapy and radiation therapy at the University Hospital Leuven from 2000 to 2007, with requisite data for the nomogram variables. Clinicopathologic factors were assessed. Two definitions of IBTR were considered where simultaneous regional or distant recurrence were either censored (conform IBTR! 2.0) or included as event. Validity of the prediction algorithm was tested in terms of discrimination and calibration. Discrimination was assessed by the concordance probability estimate and Harrell's concordance index. The mean predicted and observed 10-year estimates were compared for the entire cohort and for 4 risk groups predefined by nomogram-predicted IBTR risks, and a calibration plot was drawn.



Median follow-up was 10.9 years. The 10-year IBTR rates were 1.3% and 2.1%, according to the 2 definitions of IBTR. The validation cohort differed from the development cohort with respect to the administration of hormonal therapy, surgical section margins, lymphovascular invasion, and tumor size. In univariable analysis, younger age (P=.002) and a positive nodal status (P=.048) were significantly associated with IBTR, with a trend for the omission of hormonal therapy (P=.061). The concordance probability estimate and concordance index varied between 0.57 and 0.67 for the 2 definitions of IBTR. In all 4 risk groups the model overestimated the IBTR risk. In particular, between the lowest-risk groups a limited differentiation was suggested by the calibration plot.



The IBTR! 2.0 predictive model for IBTR in breast cancer patients shows substandard discriminative ability, with an overestimation of the risk in all subgroups.
Department of Oncology, KU Leuven - University of Leuven, Leuven, Belgium; Department of Radiation Oncology, University Hospitals Leuven, Leuven, Belgium. Electronic address: Isabelle.kindts@uzleuven.be.
Isabelle
I
Kindts
Leuven Biostatistics and Statistical Bioinformatics Center (L-Biostat), KU Leuven - University of Leuven, Leuven, Belgium.
Annouschka
A
Laenen
Department of Oncology, KU Leuven - University of Leuven, Leuven, Belgium; Department of Radiation Oncology, University Hospitals Leuven, Leuven, Belgium.
Stephanie
S
Peeters
Department of Oncology, KU Leuven - University of Leuven, Leuven, Belgium; Department of Radiation Oncology, University Hospitals Leuven, Leuven, Belgium.
Hilde
H
Janssen
Department of Oncology, KU Leuven - University of Leuven, Leuven, Belgium; Department of Radiation Oncology, University Hospitals Leuven, Leuven, Belgium.
Tom
T
Depuydt
Department of Oncology, KU Leuven - University of Leuven, Leuven, Belgium; Department of Surgical Oncology, University Hospitals Leuven, Leuven, Belgium.
Ines
I
Nevelsteen
Department of Oncology, KU Leuven - University of Leuven, Leuven, Belgium; Department of Radiation Oncology, University Hospitals Leuven, Leuven, Belgium.
Erik
E
Van Limbergen
Department of Oncology, KU Leuven - University of Leuven, Leuven, Belgium; Department of Radiation Oncology, University Hospitals Leuven, Leuven, Belgium.
Caroline
C
Weltens
D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D001530:Belgium / Q000453:epidemiology; D001943:Breast Neoplasms / Q000453:epidemiology* / Q000628:therapy*; D015331:Cohort Studies; D003198:Computer Simulation; D005260:Female; D006801:Humans; D020407:Internet; D008137:Longitudinal Studies; D015412:Mastectomy, Segmental / Q000706:statistics & numerical data*; D008875:Middle Aged; D009364:Neoplasm Recurrence, Local / Q000453:epidemiology* / Q000517:prevention & control; D049451:Nomograms; D017063:Outcome Assessment, Health Care / Q000379:methods*; D015995:Prevalence; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D012189:Retrospective Studies; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D012986:Software Validation; D016896:Treatment Outcome; D014584:User-Computer Interface