Detection Algorithms for Gastrointestinal Perforation Cases in the Medical Information Database Network (MID-NET®) in Japan.

BACKGROUND: The Medical Information Database Network (MID-NET®) in Japan is a vast repository providing an essential pharmacovigilance tool. Gastrointestinal perforation (GIP) is a critical adverse drug event, yet no well-established GIP identification algorithm exists in MID-NET®. METHODS: This study evaluated 12 identification algorithms by combining ICD-10 codes with GIP therapeutic procedures. Two sites contributed 200 inpatients with GIP-suggestive ICD-10 codes (100 inpatients each), while a third site contributed 165 inpatients with GIP-suggestive ICD-10 codes and antimicrobial prescriptions. The positive predictive values (PPVs) of the algorithms were determined, and the relative sensitivity (rSn) among the 165 inpatients at the third institution was evaluated. RESULTS: A trade-off between PPV and rSn was observed. For instance, ICD-10 code-based definitions yielded PPVs of 59.5%, whereas ICD-10 codes with CT scan and antimicrobial information gave PPVs of 56.0% and an rSn of 97.0%, and ICD-10 codes with CT scan and antimicrobial information as well as three types of operation codes produced PPVs of 84.2% and an rSn of 24.2%. The same algorithms produced statistically significant differences in PPVs among the three institutions. Combining diagnostic and procedure codes improved the PPVs. The algorithm combining ICD-10 codes with CT scan and antimicrobial information and 80 different operation codes offered the optimal balance (PPV: 61.6%, rSn: 92.4%). CONCLUSION: This study developed valuable GIP identification algorithms for MID-NET®, revealing the trade-offs between accuracy and sensitivity. The algorithm with the most reasonable balance was determined. These findings enhance pharmacovigilance efforts and facilitate further research to optimize adverse event detection algorithms.

Lower Risks of Gastrointestinal Perforation and Intestinal Obstruction in Patients with Atypical Antipsychotics in Comparison with Typical Antipsychotics Based on Real-World Data from the MID-NET® in Japan.

Intestinal perforation and obstruction are known to be one of the adverse events caused by antipsychotics; however, warning information on package inserts varies among antipsychotics. To investigate the risks of gastrointestinal perforation and intestinal obstruction in patients prescribed atypical antipsychotics compared with those in patients prescribed typical antipsychotics, a nested case-control study was conducted utilizing real-world data from the MID-NET® medical information database in Japan. The study period spanned from January 1, 2009, to December 31, 2018. We found that the risks of gastrointestinal perforation and intestinal obstruction in patients prescribed atypical antipsychotics were significantly lower than those in patients prescribed typical antipsychotics (adjusted odds ratio, 0.48; 95% confidence interval, 0.29-0.80). This finding was supported with prolonged periods for the exposure definition in the sensitivity analyses. In addition, no major differences in the risks of atypical antipsychotics, such as risperidone, quetiapine, olanzapine, and aripiprazole, were identified in this study. The safety profile regarding the lower risks of gastrointestinal perforation and intestinal obstruction in patients prescribed atypical antipsychotics should be considered when choosing antipsychotics in clinical practice in terms of the proper use of such drugs.

Descriptive Analysis for the Trend of Pharmacovigilance Planning in Risk Management Plans on New Drugs Approved During 2016-2019.

BACKGROUND: Japanese pharmaceutical authorities have conducted regulatory renovations of pharmacovigilance planning (PVP) since implementing new procedures for developing post-marketing study plans in 2018 in order to promote more focused and scientific approaches. This study aimed to descriptively assess the effects of those regulatory renovations on PVP for new drugs in Japan. METHODS: We identified PVP information (drug characteristics, efficacy and safety issues, and additional activities) from the first version of risk management plans for new drugs approved between 2016 and 2019. The following indicators were analyzed: (1) proportion of the number of drugs with at least one efficacy issue among all the drugs, (2) proportion of the number of safety issues with additional activity among all the safety issues, and (3) proportion of database studies among all additional activities. RESULTS: In total, 168 drugs, 1212 safety issues, and 301 additional activities were identified. The proportion of drugs with at least one efficacy issue decreased from 91.4% in 2016 to 27.3% in 2019, and the proportion of safety issues with additional activity also decreased from 93.9% in 2016 to 53.7% in 2019. In contrast, the proportion of database studies increased from 0 to 19.2%. The percentages of additional activities targeting important identified and potential risks also gradually decreased during the 4-year period. CONCLUSION: Notable changes in the three indicators during 2016-2019 were observed, which suggests that regulatory renovation has affected PVP in Japan.

Validity of identification algorithms combining diagnostic codes with other measures for acute ischemic stroke in MID-NET®.

PURPOSE: We aimed to develop a reliable identification algorithm combining diagnostic codes with several treatment factors for inpatients with acute ischemic stroke (AIS) to conduct pharmacoepidemiological studies using the administrative database MID-NET® in Japan. METHODS: We validated 11 identification algorithms based on 56 different diagnostic codes (International Classification of Diseases, Tenth Revision; ICD-10) using Diagnosis Procedure Combination (DPC) data combined with information on AIS therapeutic procedures added as "AND" condition or "OR" condition. The target population for this study was 366 randomly selected hospitalized patients with possible cases of AIS, defined as relevant ICD-10 codes and diagnostic imaging and prescription or surgical procedure, in three institutions between April 1, 2015 and March 31, 2017. We determined the positive predictive values (PPVs) of these identification algorithms based on comparisons with a gold standard consisting of chart reviews by experienced specialist physicians. Additionally, the sensitivities of them among 166 patients with the possible cases of AIS at a single institution were evaluated. RESULTS: The PPVs were 0.618 (95% confidence interval [CI]: 0.566-0.667) to 0.909 (95% CI: 0.708-0.989) and progressively increased with adding or limiting information on AIS therapeutic procedures as "AND" condition in the identification algorithms. The PPVs for identification algorithms based on diagnostic codes I63.x were >0.8. However, the sensitivities progressively decreased to a maximum of ~0.2 after adding information on AIS therapeutic procedures as "AND" condition. CONCLUSIONS: The identification algorithms based on the combination of appropriate ICD-10 diagnostic codes in DPC data and other AIS treatment factors may be useful to studies for AIS at a national level using MID-NET®.

Identification of gastrointestinal perforation based on ICD-10 code in a Japanese administrative medical information database and associated drug exposure risk factors.

PURPOSE: The purpose of this study is to evaluate the accuracy of gastrointestinal (GI) perforation ICD-10 coding in the Diagnosis Procedure Combination (DPC) database and to examine drug exposure risk factors for GI perforation. METHODS: A total of 100 patients with GI perforation ICD-10 codes were selected randomly from Kagawa University Hospital's DPC database between April 2011 and December 2016. Two experienced specialist physicians independently reviewed the medical records and classified cases as "definite A," "definite B," "probable," or "no GI perforation." The positive predictive values (PPVs) of "definite A/B" cases were calculated after stratification by sex, age, ICD-10 code, and diagnostic information in the DPC data. The number of prescribed drugs with side effects of GI perforation according to historical data was compared between "definite A/B" and "no GI perforation" cases. RESULTS: The overall PPV was 47.0% (95% confidence interval [CI], 36.9-57.2). However, the PPVs for the three categories of diagnostic information in the DPC data ("main diagnosis," "diagnosis causing admission," and "most resource-intensive diagnosis") were each more than 70% after excluding inappropriate patients. Additionally, the PPV focused on these three categories was 76.3% (95% CI, 59.8-88.6). Prescribed drugs with side effects of GI perforation were more frequently detected in "definite A/B" cases (P = .028). CONCLUSIONS: Although the overall PPV for GI perforation based on ICD-10 code was low, our results suggest that the PPV could be improved by appropriate selection of DPC diagnosis category and that use of multiple medications enhances the risk of GI perforation.