INTRODUCTION: PREDICT is a prognostication tool that calculates the potential benefit of various postsurgical treatments on the overall survival (OS) of patients with nonmetastatic invasive breast cancer. Once patient, tumor, and treatment details have been entered, the tool will show the estimated 5-, 10-, and 15-year OS outcomes, both with and without adjuvant therapies. This study aimed to conduct an external validation of the prognostication tool PREDICT version 2.2 by evaluating its predictive accuracy of the 5- and 10-year OS outcomes among female patients with nonmetastatic invasive breast cancer in Japan. METHODS: All female patients diagnosed from 2001 to 2013 with unilateral, nonmetastatic, invasive breast cancer and had undergone surgical treatment at Kyushu University Hospital, Fukuoka, Japan, were selected. Observed and predicted 5- and 10-year OS rates were analyzed for the validation population and the subgroups. Calibration and discriminatory accuracy were assessed using Chi-squared goodness-of-fit test and area under the receiver operating characteristic curve (AUC). RESULTS: A total of 636 eligible cases were selected from 1, 213 records. Predicted and observed OS differed by 0.9% (p = 0.322) for 5-year OS, and 2.4% (p = 0.086) for 10-year OS. Discriminatory accuracy results for 5-year (AUC = 0.707) and 10-year (AUC = 0.707) OS were fairly well. CONCLUSION: PREDICT tool accurately estimated the 5- and 10-year OS in the overall Japanese study population. However, caution should be used for interpretation of the 5-year OS outcomes in patients that are ≥65 years old, and also for the 10-year OS outcomes in patients that are ≥65 years old, those with histologic grade 3 and Luminal A tumors, and in those considering ETx or no systemic treatment.
INTRODUCTION: PREDICT is a prognostication tool that calculates the potential benefit of various postsurgical treatments on the overall survival (OS) of patients with nonmetastatic invasive breast cancer. Once patient, tumor, and treatment details have been entered, the tool will show the estimated 5-, 10-, and 15-year OS outcomes, both with and without adjuvant therapies. This study aimed to conduct an external validation of the prognostication tool PREDICT version 2.2 by evaluating its predictive accuracy of the 5- and 10-year OS outcomes among female patients with nonmetastatic invasive breast cancer in Japan. METHODS: All female patients diagnosed from 2001 to 2013 with unilateral, nonmetastatic, invasive breast cancer and had undergone surgical treatment at Kyushu University Hospital, Fukuoka, Japan, were selected. Observed and predicted 5- and 10-year OS rates were analyzed for the validation population and the subgroups. Calibration and discriminatory accuracy were assessed using Chi-squared goodness-of-fit test and area under the receiver operating characteristic curve (AUC). RESULTS: A total of 636 eligible cases were selected from 1, 213 records. Predicted and observed OS differed by 0.9% (p = 0.322) for 5-year OS, and 2.4% (p = 0.086) for 10-year OS. Discriminatory accuracy results for 5-year (AUC = 0.707) and 10-year (AUC = 0.707) OS were fairly well. CONCLUSION: PREDICT tool accurately estimated the 5- and 10-year OS in the overall Japanese study population. However, caution should be used for interpretation of the 5-year OS outcomes in patients that are ≥65 years old, and also for the 10-year OS outcomes in patients that are ≥65 years old, those with histologic grade 3 and Luminal A tumors, and in those considering ETx or no systemic treatment.
Authors: Nirmala Bhoo-Pathy; Cheng-Har Yip; Mikael Hartman; Nakul Saxena; Nur Aishah Taib; Gwo-Fuang Ho; Lai-Meng Looi; Awang M Bulgiba; Yolanda van der Graaf; Helena M Verkooijen Journal: Eur J Cancer Date: 2012-02-25 Impact factor: 9.162
Authors: Gordon C Wishart; Emad Rakha; Andrew Green; Ian Ellis; Hamid Raza Ali; Elena Provenzano; Fiona M Blows; Carlos Caldas; Paul D P Pharoah Journal: BMC Cancer Date: 2014-12-03 Impact factor: 4.430
Authors: Francisco J Candido Dos Reis; Gordon C Wishart; Ed M Dicks; David Greenberg; Jem Rashbass; Marjanka K Schmidt; Alexandra J van den Broek; Ian O Ellis; Andrew Green; Emad Rakha; Tom Maishman; Diana M Eccles; Paul D P Pharoah Journal: Breast Cancer Res Date: 2017-05-22 Impact factor: 6.466
Authors: J Ferlay; M Colombet; I Soerjomataram; C Mathers; D M Parkin; M Piñeros; A Znaor; F Bray Journal: Int J Cancer Date: 2018-12-06 Impact factor: 7.396