Development and validation of a new predictive model for breast cancer survival in New Zealand and comparison to the Nottingham prognostic index.
Development and validation of a new predictive model for breast cancer survival in New Zealand and comparison to the Nottingham prognostic index.
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DOI：
10.1186/s12885-018-4791-x
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发表时间：
2018-09-17
期刊：
影响因子：
3.8
通讯作者：
Lawrenson R
中科院分区：
文献类型：
--
作者：
Elwood JM;Tawfiq E;TinTin S;Marshall RJ;Phung TM;Campbell I;Harvey V;Lawrenson R
新西兰（NZ）乳腺癌患者预后的唯一可用预测模型是基于其他国家的数据。我们的目的是开发和验证一个预测模型，使用新西兰的数据为这一人群，并比较其性能广泛使用的海外模型，诺丁汉预后指数（NPI）。我们使用新西兰最大的基于人群的区域乳腺癌登记处（奥克兰，9182例患者）前瞻性收集的数据，开发了一个模型来预测10年乳腺癌特定生存率，并评估了其在该数据集中的性能（内部验证）和在一个独立的基于新西兰人群的系列中的性能。怀卡托的2625名患者（外部验证）。数据包括2000年6月1日至2014年6月30日期间诊断出患有原发性浸润性乳腺癌的所有女性，随访至死亡或2014年12月31日。我们使用多变量考克斯比例风险回归来评估预测因子，并计算预测的10年乳腺癌死亡率，从而计算每个患者的生存概率。我们通过Kaplan Meier方法评估观察生存率。我们通过C统计量评估区分度，并通过比较10组患者的预测和观察生存率进行校准，按预测的10年生存率排序。我们比较了这个新西兰模型与诺丁汉预后指数（NPI）在这个验证数据集。区分度良好：内部效度的C统计值为0.84，独立外部效度为0.83。对于校准，对于内部和外部有效性，所有患者组的预测10年生存概率（按预测生存率排序）均在观察到的Kaplan-Meier生存概率的95%置信区间（CI）内。即使在NPI定义的预后组中，NZ模型也显示出良好的区分力。新西兰模型的这些结果显示了该模型良好的内部和外部有效性、可移植性和潜在的临床价值，以及其明显优于NPI。还需要进一步的研究来评估其他潜在的预测因子，评估该模型在特定患者亚组中的表现，并将其与其他国家开发的尚未在新西兰进行测试的其他模型进行比较。本文的在线版本（10.1186/s12885-018-4791-x）包含补充材料，可供授权用户使用。
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). 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. 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. 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. The online version of this article (10.1186/s12885-018-4791-x) contains supplementary material, which is available to authorized users.