Influence of Metabolic Profiles on Drug Safety in Routine Care

Conditions

D50.0 Y57.9 D62 D65.1 D68.33 D68.35 D69.80 D69.9 G45 G95.1 H11.3 H21.0 H31.3 H34.0 H34.1 H34.2 H34.8 H34.9 H35.6 H43.1 H45.0 H92.2 I21 I22 I23 I24 I25 I26 I60 I61 I62 I63 I64 I65 I66 I71 I72 I74 I79.0 I80 I81 I82 I85.0 I87.0 J94.2 K26.0 K26.1 K26.2 K26.4 K26.5 K26.6 K25.0 K25.1 K25.2 K25.4 K25.5 K25.6 K27.0 K27.1 K27.2 K27.4 K27.5 K27.6 K28.0 K28.1 K28.2 K28.4 K28.5 K28.6 K29.0 K31.82 K55.0 K55.1 K55.22 K57.01 K57.03 K57

Veronica Atemnkeng Ntam, Tatjana Huebner, Michael Steffens, Christoph Roethlein, Britta Haenisch et al. (8 authors)

PLoS ONE2024-10-101 citations

10.1371/journal.pone.0311267

Evaluation of the EMPAR study population on the basis of metabolic phenotypes of selected pharmacogenes.

Fracowiak J, Huebner T, Heß S, Roethlein C, Langner D, Schneider U, Falkenberg F, Scholl C, Linder R, Stingl J, Haenisch B, Steffens M.

2022-01-311 citations

10.1038/s41397-022-00268-6

Influence of metabolic profiles on the safety of drug therapy in routine care in Germany: protocol of the cohort study EMPAR

Tatjana Huebner, Michael Steffens, Roland Linder, Jochen Fracowiak, Daria Langner et al. (11 authors)

BMJ Open2020-04-012 citations

10.1136/bmjopen-2019-032624

Interventions

Group 1: In the course of this study, the pharmacogenetic profiles of participants will be investigated by analysis of their buccal swab. The genetic variant information provided by these profiles wil

Eligibility

Sex/Gender

All

Age

18 Years to No maximum

Inclusion criteria

Inclusion criteria: Age of =18 years / Initial prescription of at least one anticoagulant or cholesterol lowering agent in a time frame of 01.01.2014-31.12.2017 or intake of at least one drug with verified pharmacogenetic effect, especially due to CYP2C9-, CYP2C19- und CYP2D6-variants that caused at least one Y57.9! diagnosis (ICD-10 code) in 2014-2017 / Written informed consent

Exclusion criteria

Exclusion criteria: Inapplicable metabolic profile results / Oncologic phenotype (ICD 10: all C-diagnoses and D0x, D4x, D37, D38, D39) / Severe F-diagnoses ( ICD 10: F0x.x, F2x.x, F7x.x, F8x.x, F31.x, F33.x, F38.x, F39.x, F42.x, F43.x, F44.x, F60.x, F61.x, F62.x, F63.x, F69.x, F91.x, F92.x, F93.x, F94.x, F95.x, F98.x, F1x.2, F1x.3, F1x.4, F1x.5, F1x.6, F1x.7, F1x.8, F1x.9, F30.1, F30.2, F30.8, F30.9, F32.2, F32.3, F32.8, F32.9, F34.8 ,F34.9, F45.2, F45.4, F45.8, F45.9, F48.1, F48.8, F48.9, F50.4, F50.5, F53.1, F53.8, F53.9, F65.2, F65.3, F65.4, F65.6, F65.8, F65.9, F68.1, F68.8, F90.1) / Known genetic hematopoietic diseases upon initial prescription of anticoagulant (ICD 10 Code: D55, D56 D57, D58, D61.0, D64.0, D64.4, D66, D67, D68.0, D68.1, D68.2, D71, D72.0, D74.0, D80.0, D82) / Y69! diagnosis (Unspecified misadventure during surgical and medical care) in parallel with Y57.9! diagnosis / Myopathy, myositis or muscle pain before initial prescription of cholesterol lowering agents (ICD 10 Code: M60.1, M60.8, M60.9, G72.0, M62.8, M62.9, M79.1, M79.7) / Criteria due to TK customer management

Design outcomes

Primary

Measure	Time frame
On the basis of the primary outcomes, the study will examine whether genetic differences have an impact on the incidence of adverse drug reactions and therefore, the utilization of statutory health insurance services. In 2013-2019 the subsequent primary outcomes provided via routine care data of the health insurance provider Techniker Krankenkasse will be assessed: Utilisation of health care insurance services / Hospitalization due to adverse drug reactions / Referral to a specialist due to medication problems / Change of medication during the observation period / Incidence of incapacity for work	—

Measure

Time frame

On the basis of the primary outcomes, the study will examine whether genetic differences have an impact on the incidence of adverse drug reactions and therefore, the utilization of statutory health insurance services. In 2013-2019 the subsequent primary outcomes provided via routine care data of the health insurance provider Techniker Krankenkasse will be assessed: Utilisation of health care insurance services / Hospitalization due to adverse drug reactions / Referral to a specialist due to medication problems / Change of medication during the observation period / Incidence of incapacity for work

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Secondary

Measure	Time frame
On the basis of the secondary outcomes, the study will examine whether there is a possible benefit of cost reductions for health insurance services by determining the metabolic profile to predict and prevent adverse drug reactions in routine care. Thus, the effect of pharmacogenetic profiles on the incidence of adverse drug reactions and therefore, on the costs due to health insurance services will be examined. In 2013-2019 the subsequent secondary outcomes provided via routine care data of the health insurance provider Techniker Krankenkasse will be assessed: Costs for drugs and treatment / Sickness benefit	—

Measure

Time frame

On the basis of the secondary outcomes, the study will examine whether there is a possible benefit of cost reductions for health insurance services by determining the metabolic profile to predict and prevent adverse drug reactions in routine care. Thus, the effect of pharmacogenetic profiles on the incidence of adverse drug reactions and therefore, on the costs due to health insurance services will be examined. In 2013-2019 the subsequent secondary outcomes provided via routine care data of the health insurance provider Techniker Krankenkasse will be assessed: Costs for drugs and treatment / Sickness benefit

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Countries

Germany

Contacts

Public Contact- -

EMPAR Hotline, TKgesundheit GmbH

-040-46 06 6 26-380

Outcome results

None listed