| Title |
Budget impact model for oncopharmacogenetics from the perspective of mandatory basic health insurance in Switzerland using the example of breast cancer
|
|---|---|
| Published in |
Pharmacogenomics and Personalized Medicine, April 2018
|
| DOI | 10.2147/pgpm.s154368 |
| Pubmed ID | |
| Authors |
Thomas D Szucs, Kevin P Szillat, Eva Blozik |
| Abstract |
Single-nucleotide polymorphisms (SNPs) can severely impact individual drug response and health outcomes in cancer patients. Genetic tests to screen for marker SNPs are available to adjust the drug dose of oncologicals to the patient's needs. However, it is unclear whether the positive effects outbalance the increased costs or even lead to an overall cost reduction. This very pragmatic analysis used three frequently used oncologicals for the treatment of breast cancer to evaluate whether preemptive pharmacogenetic testing may have a cost-reducing impact on health care spending in the Swiss health care system. Our results indicate that oncopharmacogenetics might help to reduce health care costs (ie, by avoiding adverse drug effects) and to increase efficiency of drugs in oncologic patients. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 27 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 22% |
| Other | 2 | 7% |
| Unspecified | 2 | 7% |
| Student > Master | 2 | 7% |
| Student > Doctoral Student | 2 | 7% |
| Other | 8 | 30% |
| Unknown | 5 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Economics, Econometrics and Finance | 5 | 19% |
| Biochemistry, Genetics and Molecular Biology | 4 | 15% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 11% |
| Nursing and Health Professions | 2 | 7% |
| Unspecified | 2 | 7% |
| Other | 5 | 19% |
| Unknown | 6 | 22% |
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 29 April 2018.
All research outputs
#16,848,023
of 25,748,735 outputs
Outputs from Pharmacogenomics and Personalized Medicine
#1
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Outputs of similar age
#210,102
of 344,843 outputs
Outputs of similar age from Pharmacogenomics and Personalized Medicine
#1
of 1 outputs
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