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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

Overview of attention for article published in BMC Cancer, September 2018
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Title
Development and validation of a new predictive model for breast cancer survival in New Zealand and comparison to the Nottingham prognostic index
Published in
BMC Cancer, September 2018
DOI 10.1186/s12885-018-4791-x
Pubmed ID
Authors

J. Mark Elwood, Essa Tawfiq, Sandar TinTin, Roger J. Marshall, Tung M. Phung, Ian Campbell, Vernon Harvey, Ross Lawrenson

Abstract

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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Other 3 17%
Researcher 3 17%
Student > Master 3 17%
Student > Bachelor 2 11%
Lecturer 1 6%
Other 1 6%
Unknown 5 28%
Readers by discipline Count As %
Medicine and Dentistry 8 44%
Nursing and Health Professions 2 11%
Biochemistry, Genetics and Molecular Biology 1 6%
Social Sciences 1 6%
Psychology 1 6%
Other 0 0%
Unknown 5 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 October 2018.
All research outputs
#15,557,505
of 23,881,329 outputs
Outputs from BMC Cancer
#3,807
of 8,483 outputs
Outputs of similar age
#207,536
of 343,311 outputs
Outputs of similar age from BMC Cancer
#79
of 158 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,483 research outputs from this source. They receive a mean Attention Score of 4.4. This one has gotten more attention than average, scoring higher than 50% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 343,311 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 158 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.