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Development and validation of a new predictive model for breast cancer survival in New Zealand and comparison to the Nottingham prognostic index

BACKGROUND: The only available predictive models for the outcome of breast cancer patients in New Zealand (NZ) are based on data in other countries. We aimed to develop and validate a predictive model using NZ data for this population, and compare its performance to a widely used overseas model, the...

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Autores principales: Elwood, J. Mark, Tawfiq, Essa, TinTin, Sandar, Marshall, Roger J., Phung, Tung M., Campbell, Ian, Harvey, Vernon, Lawrenson, Ross
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6142675/
https://www.ncbi.nlm.nih.gov/pubmed/30223800
http://dx.doi.org/10.1186/s12885-018-4791-x
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author Elwood, J. Mark
Tawfiq, Essa
TinTin, Sandar
Marshall, Roger J.
Phung, Tung M.
Campbell, Ian
Harvey, Vernon
Lawrenson, Ross
author_facet Elwood, J. Mark
Tawfiq, Essa
TinTin, Sandar
Marshall, Roger J.
Phung, Tung M.
Campbell, Ian
Harvey, Vernon
Lawrenson, Ross
author_sort Elwood, J. Mark
collection PubMed
description BACKGROUND: The only available predictive models for the outcome of breast cancer patients in New Zealand (NZ) are based on data in other countries. We aimed to develop and validate a predictive model using NZ data for this population, and compare its performance to a widely used overseas model, the Nottingham Prognostic Index (NPI). METHODS: We developed a model to predict 10-year breast cancer-specific survival, using data collected prospectively in the largest population-based regional breast cancer registry in NZ (Auckland, 9182 patients), and assessed its performance in this data set (internal validation) and in an independent NZ population-based series of 2625 patients in Waikato (external validation). The data included all women with primary invasive breast cancer diagnosed from 1 June 2000 to 30 June 2014, with follow up to death or Dec 31, 2014. We used multivariate Cox proportional hazards regression to assess predictors and to calculate predicted 10-year breast cancer mortality, and therefore survival, probability for each patient. We assessed observed survival by the Kaplan Meier method. We assessed discrimination by the C statistic, and calibration by comparing predicted and observed survival rates for patients in 10 groups ordered by predicted 10-year survival. We compared this NZ model with the Nottingham Prognostic Index (NPI) in this validation data set. RESULTS: Discrimination was good: C statistics were 0.84 for internal validity and 0.83 for an independent external validity. For calibration, for both internal and external validity the predicted 10-year survival probabilities in all groups of patients, ordered by predicted survival, were within the 95% confidence intervals (CI) of the observed Kaplan-Meier survival probabilities. The NZ model showed good discrimination even within the prognostic groups defined by the NPI. CONCLUSIONS: These results for the New Zealand model show good internal and external validity, transportability, and potential clinical value of the model, and its clear superiority over the NPI. Further research is needed to assess other potential predictors, to assess the model’s performance in specific subgroups of patients, and to compare it to other models, which have been developed in other countries and have not yet been tested in NZ. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-018-4791-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-61426752018-09-21 Development and validation of a new predictive model for breast cancer survival in New Zealand and comparison to the Nottingham prognostic index Elwood, J. Mark Tawfiq, Essa TinTin, Sandar Marshall, Roger J. Phung, Tung M. Campbell, Ian Harvey, Vernon Lawrenson, Ross BMC Cancer Research Article BACKGROUND: The only available predictive models for the outcome of breast cancer patients in New Zealand (NZ) are based on data in other countries. We aimed to develop and validate a predictive model using NZ data for this population, and compare its performance to a widely used overseas model, the Nottingham Prognostic Index (NPI). METHODS: We developed a model to predict 10-year breast cancer-specific survival, using data collected prospectively in the largest population-based regional breast cancer registry in NZ (Auckland, 9182 patients), and assessed its performance in this data set (internal validation) and in an independent NZ population-based series of 2625 patients in Waikato (external validation). The data included all women with primary invasive breast cancer diagnosed from 1 June 2000 to 30 June 2014, with follow up to death or Dec 31, 2014. We used multivariate Cox proportional hazards regression to assess predictors and to calculate predicted 10-year breast cancer mortality, and therefore survival, probability for each patient. We assessed observed survival by the Kaplan Meier method. We assessed discrimination by the C statistic, and calibration by comparing predicted and observed survival rates for patients in 10 groups ordered by predicted 10-year survival. We compared this NZ model with the Nottingham Prognostic Index (NPI) in this validation data set. RESULTS: Discrimination was good: C statistics were 0.84 for internal validity and 0.83 for an independent external validity. For calibration, for both internal and external validity the predicted 10-year survival probabilities in all groups of patients, ordered by predicted survival, were within the 95% confidence intervals (CI) of the observed Kaplan-Meier survival probabilities. The NZ model showed good discrimination even within the prognostic groups defined by the NPI. CONCLUSIONS: These results for the New Zealand model show good internal and external validity, transportability, and potential clinical value of the model, and its clear superiority over the NPI. Further research is needed to assess other potential predictors, to assess the model’s performance in specific subgroups of patients, and to compare it to other models, which have been developed in other countries and have not yet been tested in NZ. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-018-4791-x) contains supplementary material, which is available to authorized users. BioMed Central 2018-09-17 /pmc/articles/PMC6142675/ /pubmed/30223800 http://dx.doi.org/10.1186/s12885-018-4791-x Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Elwood, J. Mark
Tawfiq, Essa
TinTin, Sandar
Marshall, Roger J.
Phung, Tung M.
Campbell, Ian
Harvey, Vernon
Lawrenson, Ross
Development and validation of a new predictive model for breast cancer survival in New Zealand and comparison to the Nottingham prognostic index
title Development and validation of a new predictive model for breast cancer survival in New Zealand and comparison to the Nottingham prognostic index
title_full Development and validation of a new predictive model for breast cancer survival in New Zealand and comparison to the Nottingham prognostic index
title_fullStr Development and validation of a new predictive model for breast cancer survival in New Zealand and comparison to the Nottingham prognostic index
title_full_unstemmed Development and validation of a new predictive model for breast cancer survival in New Zealand and comparison to the Nottingham prognostic index
title_short Development and validation of a new predictive model for breast cancer survival in New Zealand and comparison to the Nottingham prognostic index
title_sort development and validation of a new predictive model for breast cancer survival in new zealand and comparison to the nottingham prognostic index
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6142675/
https://www.ncbi.nlm.nih.gov/pubmed/30223800
http://dx.doi.org/10.1186/s12885-018-4791-x
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