BACKGROUND: Adjuvant! is a web-based program that calculates individualised 10-year survival probabilities and predicted benefit of adjuvant systemic therapy. The Adjuvant! model has not been validated in any large European series. The aim of our study was to validate Adjuvant! in Dutch patients, investigating both its calibration and discriminatory accuracy. METHODS: Patients who were at least partly treated at the Netherlands Cancer Institute for breast cancer between 1987 and 1998 were included if they met the following criteria: tumour size T1 (< or =2 cm), T2 (2-5 cm), or T3 (>5 cm), invasive breast carcinoma, with information about involvement of axillary lymph nodes available, no distant metastases, primary surgery, axillary staging, and radiotherapy according to national guidelines. Clinicopathological characteristics and adjuvant treatment data were retrieved from hospital records and medical registries and were entered into the Adjuvant! (version 8.0) batch processor with blinding to outcome. Endpoints were overall survival and the proportion of patients that did not die from breast cancer (breast-cancer-specific survival [BCSS]). FINDINGS: 5380 patients were included with median follow-up of 11.7 years (range 0.03-21.8). The 10-year observed overall survival (69.0%) and BCSS (78.6%) and Adjuvant! predicted overall survival (69.1%) and BCSS (77.8%) were not statistically different (p=0.87 and p=0.18, respectively). Moreover, differences between predicted and observed outcomes were within 2% for most relevant clinicopathological subgroups. In patients younger than 40 years, Adjuvant! overestimated overall survival by 4.2% (p=0.04) and BCSS by 4.7% (p=0.01). The concordance index, which indicates discriminatory accuracy at the individual level, was 0.71 for BCSS in the entire cohort. INTERPRETATION: Adjuvant! accurately predicted 10-year outcomes in this large-scale Dutch validation study and is of use for adjuvant treatment decision making, although the results may be less reliable in some subgroups.
BACKGROUND: Adjuvant! is a web-based program that calculates individualised 10-year survival probabilities and predicted benefit of adjuvant systemic therapy. The Adjuvant! model has not been validated in any large European series. The aim of our study was to validate Adjuvant! in Dutch patients, investigating both its calibration and discriminatory accuracy. METHODS:Patients who were at least partly treated at the Netherlands Cancer Institute for breast cancer between 1987 and 1998 were included if they met the following criteria: tumour size T1 (< or =2 cm), T2 (2-5 cm), or T3 (>5 cm), invasive breast carcinoma, with information about involvement of axillary lymph nodes available, no distant metastases, primary surgery, axillary staging, and radiotherapy according to national guidelines. Clinicopathological characteristics and adjuvant treatment data were retrieved from hospital records and medical registries and were entered into the Adjuvant! (version 8.0) batch processor with blinding to outcome. Endpoints were overall survival and the proportion of patients that did not die from breast cancer (breast-cancer-specific survival [BCSS]). FINDINGS: 5380 patients were included with median follow-up of 11.7 years (range 0.03-21.8). The 10-year observed overall survival (69.0%) and BCSS (78.6%) and Adjuvant! predicted overall survival (69.1%) and BCSS (77.8%) were not statistically different (p=0.87 and p=0.18, respectively). Moreover, differences between predicted and observed outcomes were within 2% for most relevant clinicopathological subgroups. In patients younger than 40 years, Adjuvant! overestimated overall survival by 4.2% (p=0.04) and BCSS by 4.7% (p=0.01). The concordance index, which indicates discriminatory accuracy at the individual level, was 0.71 for BCSS in the entire cohort. INTERPRETATION: Adjuvant! accurately predicted 10-year outcomes in this large-scale Dutch validation study and is of use for adjuvant treatment decision making, although the results may be less reliable in some subgroups.
Authors: H A Azim; S Michiels; F Zagouri; S Delaloge; M Filipits; M Namer; P Neven; W F Symmans; A Thompson; F André; S Loi; C Swanton Journal: Ann Oncol Date: 2013-01-20 Impact factor: 32.976
Authors: Joseph A Sparano; Robert J Gray; Peter M Ravdin; Della F Makower; Kathleen I Pritchard; Kathy S Albain; Daniel F Hayes; Charles E Geyer; Elizabeth C Dees; Matthew P Goetz; John A Olson; Tracy Lively; Sunil S Badve; Thomas J Saphner; Lynne I Wagner; Timothy J Whelan; Matthew J Ellis; Soonmyung Paik; William C Wood; Maccon M Keane; Henry L Gomez Moreno; Pavan S Reddy; Timothy F Goggins; Ingrid A Mayer; Adam M Brufsky; Deborah L Toppmeyer; Virginia G Kaklamani; Jeffrey L Berenberg; Jeffrey Abrams; George W Sledge Journal: N Engl J Med Date: 2019-06-03 Impact factor: 91.245
Authors: Lusine Yaghjyan; Rulla M Tamimi; Kimberly A Bertrand; Christopher G Scott; Matthew R Jensen; V Shane Pankratz; Kathy Brandt; Daniel Visscher; Aaron Norman; Fergus Couch; John Shepherd; Bo Fan; Yunn-Yi Chen; Lin Ma; Andrew H Beck; Steven R Cummings; Karla Kerlikowske; Celine M Vachon Journal: Breast Cancer Res Treat Date: 2017-06-17 Impact factor: 4.872
Authors: Ahmed B Ashraf; Sara C Gavenonis; Dania Daye; Carolyn Mies; Mark A Rosen; Despina Kontos Journal: IEEE Trans Med Imaging Date: 2012-09-19 Impact factor: 10.048