[Estimation of adverse drug reactions by the evaluation scores of subjective symptoms (complaints) and background of patients. II. Drug-induced extrapyramidal symptoms]

[Development and Validation of Estimate Equations for Adverse Drug Reactions Using Risk Factors and Subjective Symptoms]

The purpose of this study was to develop and validate estimate equations for preventing adverse drug reactions (ADRs). We conducted five case-control studies to identify individual risk factors and subjective symptoms associated with the following five ADRs: drug-induced ischemic heart disease; renal damage; muscle disorder; interstitial pneumonia; and leucopenia. We performed logistic regression analysis and obtained eight regression equations for each ADR. We converted these to ADR estimate equations for predicting the likelihood of ADRs. We randomly selected 50 cases with non-individual ADRs from the Case Reports of Adverse Drug Reactions and Poisoning Information System (CARPIS) database of over 65000 case reports of ADRs, and assigned these cases to a validation case group. We then calculated the predictive probability for 50 cases using the eight estimate equations for each ADR. The highest probability for each ADR was set as the probability of each ADR. If the probability was over 50%, the case was interpreted as ADR-positive. We calculated and evaluated the sensitivity, specificity, and positive likelihood ratio of this system. Sensitivity of the estimate equations for muscle disorder and interstitial pneumonia were ≥90%. Specificity and positive likelihood ratios of estimate equations for renal damage, interstitial pneumonia and leucopenia were ≥80% and ≥5, respectively. Our estimate equations thus showed high validity, and are therefore helpful for the prevention or early detection of ADRs.

[Risk factors and subjective symptoms of drug-induced leucopenia]

The present study investigated risk factors and subjective symptoms associated with drug-induced leucopenia. We selected 248 patients with drug-induced leucopenia from the Case Reports of Adverse Drug Reactions and Poisoning Information System (CARPIS) database of over 47000 case reports of adverse drug reactions and assigned them to a case group. We also randomly selected 743 cases of adverse drug reactions not associated with leucopenia as a control group. A comparison of patient characteristic data between the two groups using logistic-regression analysis revealed that female sex, autoimmune disease and renal damage were background risk factors for drug-induced leucopenia. In addition, thiamazole, ritodrine, propylthiouracil, ticlopidine, allopurinol, minocycline and captopril administration significantly increased the risk of drug-induced leucopenia. A significant association was also found for fever, chills and pharyngeal abnormalities. Based on these findings, we developed two estimated regression equations to help prevent drug-induced leucopenia in the community pharmacy setting.

[Estimation of adverse drug reactions by the evaluation scores of subjective symptoms (complaints) and background of patients--VI. Drug-induced metabolic disorders]

OBJECTIVES

The purpose of this study was to develop, implement, and assess estimation procedures to prevent adverse drug reactions (ADRs), especially drug-induced metabolic disorders, based on the subjective symptoms (complaints) of patients.

METHODS

Our own database called CARPIS (Case Reports of Adverse Drug Reaction and Poisoning Information System) was started in 1987 and now contains ca. 23,000 case reports of ADRs. We extracted 264 cases of drug-induced metabolic disorders from CARPIS, such as hyperglycemia, hypoglycemia, and hypokalemia. Evaluation scores were created based on the subjective symptoms and the backgrounds of these patients. The scores were applied to the 264 cases to demonstrate their efficiency in estimation of ADRs.

RESULTS

The evaluation scores estimated ADRs as follows: 39.6% of the 96 hyperglycemia cases, 53.6% of the 84 hypoglycemia cases, and 59.5% of the 84 hypokalemia cases. The validity measures of the evaluation scores were estimated to be as follows: for hyperglycemia sensitivity (SE) = 39.6%, specificity (SP) = 99.0%, predictive value of positive test (PVP) = 97.4%, positive likelihood ratio (PLR) = 39.6, and negative likelihood ratio (NLR) = 0.61; for hypoglycemia, SE = 53.6%, SP = 93.0%, PVP = 86.5%, PLR = 7.7 and NLR = 0.50; and for hypokalemia, SE = 59.5%, SP = 99.0%, PVP = 98.0%, PLR = 59.5, and NLR = 0.41.

CONCLUSIONS

The proposed evaluation scores are a reliable estimation method to detect ADRs related to drug-induced metabolic disorders. The scores should be incorporated into the integrated ADR estimation system available at a Web site our institution is developing, along with other evaluation scores of drug-induced liver disorders, extrapyramidal symptoms, and leakopenia, and druy eruptions.