Mayu Uchikawa1, Masayuki Hashiguchi2, Tsuyoshi Shiga3. 1. The Jikei University School of Medicine, Tokyo, Japan. 2. Department of Clinical Pharmacology and Therapeutics, The Jikei University School of Medicine, 3-25-8 Nishi-shinbashi, Minato-ku, Tokyo, 105-8461, Japan. 3. Department of Clinical Pharmacology and Therapeutics, The Jikei University School of Medicine, 3-25-8 Nishi-shinbashi, Minato-ku, Tokyo, 105-8461, Japan. shiga@jikei.ac.jp.
Abstract
BACKGROUND: Drugs with new mechanisms of action are continually being developed, but it is difficult to capture whether a drug induces QT prolongation/torsade de pointes (TdP) in preclinical and preapproval clinical trials. OBJECTIVE: To evaluate drugs associated with drug-induced QT prolongation/TdP using a real-world database in Japan. PATIENTS AND METHODS: A search was performed in the Japanese Adverse Drug Event Report (JADER) database for QT prolongation and TdP. The reporting odds ratio (ROR) was calculated to identify potential drug-induced QT prolongation/TdP association. RESULTS: Among the reported 4,326,484 data entries, 3410 patients exhibited QT prolongation/TdP (2707 with QT prolongation, 703 with TdP) with the suspected drugs. Of these patients, 53.9% were females. The highest occurrence was in the 70- to 79-year-old age group (24.7%). The most common types of drugs involved were cardiovascular drugs, central nervous system (CNS) drugs, anticancer drugs, and anti-infective drugs; the rate of overdose was reportedly very low at 1.6%. The highest adjusted RORs were observed for nifekalant (351.41, 95% confidence interval (CI) 235.85-523.59), followed by vandetanib (182.55, 95% CI 108.11-308.24), evocalcet (181.59, 95% CI 132.96-248.01), bepridil (160.37, 95% CI 138.17-186.13), diarsenic trioxide (79.43, 95% CI 63.98-98.62), and guanfacine (78.29, 95% CI 58.51-104.74). Among the drugs launched in Japan during the last decade, vandetanib had the highest adjusted RORs. CONCLUSIONS: This study using the JADER database showed that antiarrhythmic drugs, calcium-sensing receptor agonists, small-molecule targeted anticancer drugs, and CNS drugs are associated with QT prolongation/TdP. Further pharmacoepidemiological studies, such as cohort studies using large databases, are needed to prove these causal relationships.
BACKGROUND: Drugs with new mechanisms of action are continually being developed, but it is difficult to capture whether a drug induces QT prolongation/torsade de pointes (TdP) in preclinical and preapproval clinical trials. OBJECTIVE: To evaluate drugs associated with drug-induced QT prolongation/TdP using a real-world database in Japan. PATIENTS AND METHODS: A search was performed in the Japanese Adverse Drug Event Report (JADER) database for QT prolongation and TdP. The reporting odds ratio (ROR) was calculated to identify potential drug-induced QT prolongation/TdP association. RESULTS: Among the reported 4,326,484 data entries, 3410 patients exhibited QT prolongation/TdP (2707 with QT prolongation, 703 with TdP) with the suspected drugs. Of these patients, 53.9% were females. The highest occurrence was in the 70- to 79-year-old age group (24.7%). The most common types of drugs involved were cardiovascular drugs, central nervous system (CNS) drugs, anticancer drugs, and anti-infective drugs; the rate of overdose was reportedly very low at 1.6%. The highest adjusted RORs were observed for nifekalant (351.41, 95% confidence interval (CI) 235.85-523.59), followed by vandetanib (182.55, 95% CI 108.11-308.24), evocalcet (181.59, 95% CI 132.96-248.01), bepridil (160.37, 95% CI 138.17-186.13), diarsenic trioxide (79.43, 95% CI 63.98-98.62), and guanfacine (78.29, 95% CI 58.51-104.74). Among the drugs launched in Japan during the last decade, vandetanib had the highest adjusted RORs. CONCLUSIONS: This study using the JADER database showed that antiarrhythmic drugs, calcium-sensing receptor agonists, small-molecule targeted anticancer drugs, and CNS drugs are associated with QT prolongation/TdP. Further pharmacoepidemiological studies, such as cohort studies using large databases, are needed to prove these causal relationships.
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