The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Nomograms to Predict Pathologic Complete Response and Metastasis-Free Survival After Preoperative Chemotherapy for Breast Cancer
Abstract
Purpose: To combine clinical variables associated with pathologic complete response (pCR) and distant metastasis–free survival (DMFS) after preoperative chemotherapy (PC) into a prediction nomogram. Patients and Methods: Data from 496 patients treated with anthracycline PC at the Institut Gustave Roussy were used to develop and calibrate a nomogram for pCR based on multivariate logistic regression. This nomogram was tested on two independent cohorts of patients treated at the M.D. Anderson Cancer Center. The first cohort (n = 337) received anthracycline; the second cohort (n = 237) received a combination of paclitaxel and anthracycline PC. A separate nomogram to predict DMFS was developed using Cox proportional hazards regression model. Results: The pCR nomogram based on clinical stage, estrogen receptor status, histologic grade, and number of preoperative chemotherapy cycles had good discrimination and calibration in the training and the anthracycline-treated validation sets (concordance indices, 0.77, 0.79). In the paclitaxel plus anthracycline group, when the predicted pCR rate was less than 14%, the observed rate was 7.5%; for a predicted rate of ≥ 38%, the actual rate was 85%. For a predicted rate between 14% to 38%, the observed rates were 50% with weekly and 27% with 3-weekly paclitaxel. This indicates that patients with intermediate chemotherapy sensitivity benefit the most from the optimized schedule of paclitaxel. Patients unlikely to achieve pCR to anthracylines remain at low probability for pCR, even after inclusion of paclitaxel. The nomogram for DMFS had a concordance index of 0.72 in the validation set and outperformed other prediction tools (P = .02). Conclusion: Our nomograms predict pCR accurately and can serve as a basis to integrate future molecular markers into a clinical prediction model.
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Effect of preoperative chemotherapy on the outcome of women with operable breast cancer.
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Self-citationNeoadjuvant Versus Adjuvant Systemic Treatment in Breast Cancer: A Meta-Analysis
Mauri, D., Pavlidis, N., & Ioannidis, J. P. A. (2005) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/dji021 · Cited by 1,200
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Neoadjuvant Chemotherapy in Breast Cancer: Significantly Enhanced Response With Docetaxel
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Cited by
Moons, K. G. M., Altman, D. G., Reitsma, J. B., Ioannidis, J. P. A., Macaskill, P., Steyerberg, E. W., Vickers, A. J., Ransohoff, D. F., & Collins, G. S. (2015) · Annals of Internal Medicine · doi:10.7326/m14-0698 · Cited by 5,147
Supervised Risk Predictor of Breast Cancer Based on Intrinsic Subtypes
Parker, J. S., Mullins, M., Cheang, M. C. U., Leung, S., Voduc, D., Vickery, T., Davies, S., Fauron, C., He, X., Hu, Z., et al. (2009) · Journal of Clinical Oncology · doi:10.1200/jco.2008.18.1370 · Cited by 4,721
The Triple Negative Paradox: Primary Tumor Chemosensitivity of Breast Cancer Subtypes
Carey, L. A., Dees, E. C., Sawyer, L., Gatti, L., Moore, D. T., Collichio, F., Ollila, D. W., Sartor, C. I., Graham, M. L., & Perou, C. M. (2007) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-06-1109 · Cited by 2,087
Hess, K. R., Anderson, K., Symmans, W. F., Valero, V., Ibrahim, N., Mejia, J. A., Booser, D., Theriault, R. L., Buzdar, A. U., Dempsey, P. J., et al. (2006) · Journal of Clinical Oncology · doi:10.1200/jco.2006.05.6861 · Cited by 721
Self-citationCommercialized Multigene Predictors of Clinical Outcome for Breast Cancer
Ross, J. S., Hatzis, C., Symmans, W. F., Pusztai, L., & Hortobágyi, G. N. (2008) · The Oncologist · doi:10.1634/theoncologist.2007-0248 · Cited by 259
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Metadata
- Authors
- Rouzier, R., Pusztai, L., Delaloge, S., Gonzalez-Angulo, A. M., Andre, F., Hess, K. R., Buzdar, A. U., Garbay, J.-R., Spielmann, M., Mathieu, M.-C., Symmans, W. F., Wagner, P., Atallah, D., Valero, V., Berry, D. A., & Hortobagyi, G. N.
- Venue
- Journal of Clinical Oncology
- Published
- 2005-11-20
- Volume
- 23
- Issue
- 33
- Pages
- 8331-8339
- ISSN
- 0732-183X (ISSN-L)
- 1527-7755
- OpenAlex
- W2170003495
- Cited by
- 286
- References
- 21
- FWCI
- 4.80
- Type
- journal article
- Language
- en
- Open access
- closed
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- Rouzier, R., Pusztai, L., Delaloge, S., Gonzalez-Angulo, A. M., Andre, F., Hess, K. R., Buzdar, A. U., Garbay, J.-R., Spielmann, M., Mathieu, M.-C., Symmans, W. F., Wagner, P., Atallah, D., Valero, V., Berry, D. A., & Hortobagyi, G. N. (2005). Nomograms to Predict Pathologic Complete Response and Metastasis-Free Survival After Preoperative Chemotherapy for Breast Cancer. Journal of Clinical Oncology. https://doi.org/10.1200/jco.2005.01.2898
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