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Validation of a Web-Based Predictive Nomogram for Ipsilateral Breast Tumor Recurrence After Breast Conserving Therapy

2010; Lippincott Williams & Wilkins; Volume: 28; Issue: 5 Linguagem: Inglês

10.1200/jco.2009.22.6662

1527-7755

Mona Sanghani, Pauline T. Truong, Rita Abi Raad, Andrzej Niemierko, Mary Lesperance, Ivo A. Olivotto, David E. Wazer, Alphonse G. Taghian,

Global Cancer Incidence and Screening

PURPOSE IBTR! version 1.0 is a web-based tool that uses literature-derived relative risk ratios for seven clinicopathologic variables to predict ipsilateral breast tumor recurrence (IBTR) after breast-conserving therapy (BCT). Preliminary testing demonstrated over-estimation in high-risk subgroups. This study uses two independent population-based datasets to create and validate a modified nomogram, IBTR! version 2.0. METHODS Cox regression modeling was performed on 7,811 patients treated with BCT at the British Columbia Cancer Agency (median follow-up, 9.4 years). Population-based hazard ratios were generated for the seven variables in the original nomogram. A modified nomogram was then tested against 664 patients from Massachusetts General Hospital (median follow-up, 9.3 years). The mean predicted and observed 10-year estimates were compared for the entire cohort and for four groups predefined by nomogram-predicted risks: group 1: less than 3%; group 2: 3% to 5%; group 3: 5% to 10%; and group 4: more than 10%. Results IBTR! version 2.0 predicted an overall 10-year IBTR estimate of 4.0% (95% CI, 3.8 to 4.2), while the observed estimate was 2.8% (95% CI, 1.6 to 4.7; P = .10). The predicted and observed IBTR estimates were: group 1 (n = 283): 2.2% versus 1.3%, P = .40; group 2 (n = 237): 3.8% versus 3.5%, P = .80; group 3 (n = 111): 6.7% versus 3.2%, P = .05; and group 4 (n = 33): 12.5% versus 8.7%, P = .50. CONCLUSION IBTR! version 2.0 is accurate in the majority of patients with a low to moderate risk of in-breast recurrence. The nomogram still overestimates risk in a minority of patients with higher risk features. Validation in a larger prospective data set is warranted.