2020
DOI: 10.1186/s12874-020-01187-5
|View full text |Cite
|
Sign up to set email alerts
|

A multi-country comparison of stochastic models of breast cancer mortality with P-splines smoothing approach

Abstract: Background Precise predictions of incidence and mortality rates due to breast cancer (BC) are required for planning of public health programs as well as for clinical services. A number of approaches has been established for prediction of mortality using stochastic models. The performance of these models intensely depends on different patterns shown by mortality data in different countries. Methods The BC mortality data is retrieved from the Global … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
6
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
6
1
1

Relationship

3
5

Authors

Journals

citations
Cited by 9 publications
(6 citation statements)
references
References 53 publications
0
6
0
Order By: Relevance
“…Breast cancer (BC) is the most commonly diagnosed cancer among women and linked with considerable years of life lost (14.9 million DALYs), leading to increased cancer-related morbidity and mortality worldwide [1] , [2] . The burden of the BC is still increasing in form of incidence and mortality both in developing and developed countries characterizing it as one of the most severe burdensome cancer worldwide [3] , [4] . This increasing trend may be an outcome of the obesity epidemic together with dwindling parity [5] .…”
Section: Introductionmentioning
confidence: 99%
“…Breast cancer (BC) is the most commonly diagnosed cancer among women and linked with considerable years of life lost (14.9 million DALYs), leading to increased cancer-related morbidity and mortality worldwide [1] , [2] . The burden of the BC is still increasing in form of incidence and mortality both in developing and developed countries characterizing it as one of the most severe burdensome cancer worldwide [3] , [4] . This increasing trend may be an outcome of the obesity epidemic together with dwindling parity [5] .…”
Section: Introductionmentioning
confidence: 99%
“…The LC-based modeling frameworks are viewed in the current literature as among the most efficient and transparent methods of modeling and projecting mortality improvements. Previously, scholars have used this approach to forecast all-cause and causespecific mortality in different countries (22)(23)(24)(25)(26). The general expression of the model is expressed as: m x,t = e a x +b x +k t +ε x,t , where, m x,t is the central mortality rate at age x and year t, and a x is the average (over time) log-mortality at age x, and b x measures the response at age x to changes in the overall level of mortality over time, and k t represents the overall level of mortality in year t, and ε x,t is the residual term.…”
Section: Discussionmentioning
confidence: 99%
“…This research covers a broad range of applications as well as adaptations to the P-Spline method itself, including modifications to the penalty term, as well as the addition of secondary penalty terms to which this work also contributes. P-Splines have been applied within many different domains, including in a medical context such as with Mubarik et al (2020) [14] applying P-Splines to breast cancer mortality data while managing to outperform existing non-smoothing models, and also within a geospatial environment such as with Rodriguez (2018) [15] using P-Splines to model random spatial variation within plant breeding experiments while taking advantage of properties such as a stable and fast estimate and being able to handle missing data and being able to model a non-normal response. P-Splines have also been adapted to be used within a Bayesian context by Lang and Brezger (2004) [16] and are shown in several works to improve predictive modelling, such as with Brezger and Steiner's (2012) [17] work of modelling demand for brands of orange juice and also with Bremhorst and Lambert's (2016) [18] work using survival analysis data.…”
Section: P-splines (Penalized B-splines)mentioning
confidence: 99%