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Scientific evidence on personalized population screening for breast cancer assessed by Spanish AQuAS
In October 2019, the Agency for Health Quality and Assessment of Catalonia (AQuAS) published an assessment report on scientific evidence on personalized population screening for breast cancer in Spain.
This work aimed to summarize the available scientific evidence regarding the development of prediction models of individual irrigation and the development of proposals of personalized screening that means
- To describe and evaluate the evidence on the clinical efficacy of the existing models where to calculate the individual risk of breast cancer
- To describe and evaluate the evidence of the clinical efficacy of the existing strategies for a personalized screening of breast cancer.
The AQuAS came to the following conclusions:
- Regarding the models for individualized risk prediction (Objective 1):
- Twenty-one models for personalized risk prediction were assessed. Although they identify risk groups, they were originally designed to identify candidate women for primary chemoprophylaxis and showed a moderate predictive capacity what makes difficult to recommend a standard for the development of strategies of screening personalized
- All the models of prediction included in this report, except one, developed out of the context of the screening, what limits its applicability
- In the more frequently used models for risk prediction, risk factors were included as the age, the family antecedents of breast cancer, the breast density and the personal antecedents of benign lesion
- Some of the variables considered in the models of prediction can not be easily accessible in all contexts of screening
- The innovative information related to the genetic expression needs an evaluation more evaluation to confirm or not its impact prediction capacity
- The differences in the distribution of the risk factors in those populations included in the prediction models can affect its applicability in different contexts, by which it is recommended to validate them for diverse populations
- The nature of breast cancer could influence a low power of screening in the prediction model. Different subtypes of breast cancer could have various risk factors
- The available evidence allows to recommend the development and evaluation of new models for individualized risk prediction directed to offering different screening strategies to the population, which include variables as the age, the family antecedents of breast cancer, the breast density, the menopause, the mammographic patterns, the Body Mass Index (BMI), the Hormone Replacement Therapy (HRT) and the genetic expression
- Regarding the personalized strategies (Objective 2):
- Nine studies of mathematical simulation, three controlled randomized clinical trials and one observational study that they have evaluated have found different strategies of personalized
- Among the studies of mathematical modeling, the groups of risk, the strategies of screening, and the measures of assessed results were very heterogeneous. From the current evidence, it is not possible to recommend a strategy specific to personalized of the screening
- Despite the high heterogeneity in the measures of evaluated results, all the studies of mathematical modeling reviewed conclude that a personalized screening strategy is more efficient than the current approach of uniform screening. The measures of those results evaluated more frequently have been the variation in the quality-adjusted life-year (QALY), the costs for gained QALY, the total costs, and the incremental cost-effectiveness ratio. None of them had evaluated mortality or overdiagnostic
- Three clinical trials included a limited number of strategies. Up to the publication date of this report, none have published their results. Two of them envisioned to stratify by profiles using models for individualized risk prediction in breast cancer, but the proposed models differed in each trial. However, there were coincides in applying the age, family antecedents of breast cancer, personal antecedents of breast lesion and density as risk factors for the stratification
- The genetic information was considered highly relevant for the correct stratification of the screened women according to their risk
- Regarding the general discussion:
- The current evidence does not allow to recommend any concrete models for individualized risk prediction for breast cancer, but it allows to recommend the development and evaluation of new models for individualized risk prediction directed to offering different strategies to the screening of the population
- The applicability of the models (and the included variables) for the personalized of the screening will have to be based on the availability of more precise strategies or tests for those subgroups of women with the mentioned risk factors
- There is not any strategy of mammographic screening based on individual risk with enough evidence on efficacy and effectiveness to be recommended. However, the evidence of the studies of mathematical modeling suggests that a personalized strategy would be more effective than the current one based on uniform screening related to terms of quality-adjusted life-year (QALY) costs, or incremental cost-effectiveness ratio
- Apart from defining groups of risk from a model of prediction and establishing strategies of personalized validated, it would be necessary to work to get currently the required information, especially that one related to breast density and genetic aspects
- The implantation of a personalized strategy of screening requires the acceptance of healthcare professionals as well as the target population. Important organizational changes should not be neglected
- Informing about the individual risk and the proposed strategies requires more education and training for healthcare professionals. The shared decision making will play a key role
- Incorporating people who are representatives of the target population for screening seems to be appropriate and necessary when agreeing on recommendations to approach changes towards a personalized population screening
See the full health technology assessment report in Spanish here.
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