PURPOSE: Circulating tumor cells (CTC) represent a new outcome-associated biomarker independent from known prognostic factors in metastatic breast cancer (MBC). The objective here was to develop and validate nomograms that combined baseline CTC counts and the other prognostic factors to assess the outcome of individual patients starting first-line treatment for MBC. EXPERIMENTAL DESIGN: We used a training set of 236 patients with MBCs starting a first-line treatment from the M.D. Anderson Cancer Center (Houston, TX) to establish nomograms that calculated the predicted probability of survival at different time points: 1, 2, and 5 years for overall survival (OS) and 6 months and 1 and 2 years for progression-free survival (PFS).The covariates computed in the model were age, disease subtype, visceral metastases, performance status, and CTC counts by CellSearch. Nomograms were independently validated with 210 patients with MBCs from the Institut Curie (Paris, France) who underwent first-line chemotherapy. The discriminatory ability and accuracy of the models were assessed using Harrell c-statistic and calibration plots at different time points in both training and validation datasets. RESULTS: Median follow-up was of 23 and 29 months in the MD Anderson and Institut Curie cohorts, respectively. Nomograms showed good c-statistics: 0.74 for OS and 0.65 for PFS and discriminated OS prediction at 1, 2, and 5 years, and PFS prediction at 6 months and 1 and 2 years. CONCLUSIONS: Nomograms, which relied on CTC counts as a continuous covariate, easily facilitated the use of a web-based tool for estimating survival, supporting treatment decisions and clinical trial stratification in first-line MBCs.
PURPOSE: Circulating tumor cells (CTC) represent a new outcome-associated biomarker independent from known prognostic factors in metastatic breast cancer (MBC). The objective here was to develop and validate nomograms that combined baseline CTC counts and the other prognostic factors to assess the outcome of individual patients starting first-line treatment for MBC. EXPERIMENTAL DESIGN: We used a training set of 236 patients with MBCs starting a first-line treatment from the M.D. Anderson Cancer Center (Houston, TX) to establish nomograms that calculated the predicted probability of survival at different time points: 1, 2, and 5 years for overall survival (OS) and 6 months and 1 and 2 years for progression-free survival (PFS).The covariates computed in the model were age, disease subtype, visceral metastases, performance status, and CTC counts by CellSearch. Nomograms were independently validated with 210 patients with MBCs from the Institut Curie (Paris, France) who underwent first-line chemotherapy. The discriminatory ability and accuracy of the models were assessed using Harrell c-statistic and calibration plots at different time points in both training and validation datasets. RESULTS: Median follow-up was of 23 and 29 months in the MD Anderson and Institut Curie cohorts, respectively. Nomograms showed good c-statistics: 0.74 for OS and 0.65 for PFS and discriminated OS prediction at 1, 2, and 5 years, and PFS prediction at 6 months and 1 and 2 years. CONCLUSIONS: Nomograms, which relied on CTC counts as a continuous covariate, easily facilitated the use of a web-based tool for estimating survival, supporting treatment decisions and clinical trial stratification in first-line MBCs.
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