@article{katalog9450,
           title = {RISK PREDICTION MODELS ON ADVERSE DRUG REACTIONS: A REVIEW},
         journal = {Pharmacy Education Journal},
       publisher = {International Pharmaceutical Federation},
           pages = {11--15},
            year = {2024},
           month = {October},
          author = {Rizaldy Taslim Pinzon},
          volume = {23},
          number = {4},
        keywords = {Adverse drug reaction, Model, Prediction, Risk},
             url = {https://katalog.ukdw.ac.id/9450/},
        abstract = {Background: The risk prediction model has become increasingly popular in recent years in helping clinical decision-making. Existing models cannot be directly applied in Indonesia.   

Objective: To review the existing prediction models and their limitations.     

Method: A search related to the prediction of ADR risk was conducted using several journal databases: PubMed, Scopus and Google Scholar. Articles were screened to match specified criteria and further studied.   

Result: Nine articles met the criteria and were then analysed. Studies were carried out in various countries. The study population include; the elderly ({\ensuremath{>}}65 years, three studies), age (?15 years, three studies), patients with Chronic Kidney Disease (CKD) (?18 years, one study) and two studies in cancer patients. The outcomes were; ADR (five studies), ADE ( two studies), DRPs (one study), and cardiovascular effects (one study). The methods for determining the predictors of ADRs all used multivariable logistic regression.    

Conclusion: Each country has different treatment patterns, prescribing practices, traditions and drug distribution, so it is necessary to develop a prediction model for ADRs that is country-specific.}
}