Safety of Memantine in Combination with Potentially Interactive Drugs in the Real World: A Pharmacovigilance Study Using the Japanese Adverse Drug Event Report (JADER) Database

Background: Memantine, an NMDA receptor antagonist, is used for the treatment of Alzheimer’s disease. There is a caution to refrain from administrating memantine in combination with some specific drugs such as amantadine or dextromethorphan due to potential interactions that might augment the adverse effects of memantine. Objective: This notification has not been validated in real-world data, which we aim to address using a large self-reporting database from Japan. Methods: We conducted a disproportionality analysis using the Japanese Adverse Drug Event Report (JADER) database reported between April 2004 and March 2019 for detecting the neuropsychiatric adverse event (AE) signals associated with memantine and other potentially interactive drugs including amantadine, dextromethorphan, cimetidine, ranitidine, procainamide, quinidine, acetazolamide, citrate, and bicarbonate. Drug-drug interactions between memantine and these drugs were assessed using multiplicative and additive models. Results: There was no statistically robust evidence to support multiplicative or additive interactions between memantine and the aforementioned drugs to increase the reporting of any included neuropsychiatric AEs or AE categories. Conclusion: The real-world JADER data did not raise the concern about the interactive increase in the neuropsychiatric AEs in patients with dementia taking memantine in combination with amantadine or dextromethorphan, suggesting there may be no urgent need to prohibit the co-administration of these drugs presently.

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Adverse drug event presentation and tracking (ADEPT): semiautomated, high throughput pharmacovigilance using real-world data

JAMIA Open ◽

10.1093/jamiaopen/ooaa031 ◽

2020 ◽

Vol 3 (3) ◽

pp. 413-421

Author(s):

Alon Geva ◽

Jason P Stedman ◽

Shannon F Manzi ◽

Chen Lin ◽

Guergana K Savova ◽

...

Keyword(s):

Language Processing ◽

High Throughput ◽

Adverse Drug Event ◽

Real World ◽

High Efficiency ◽

Signs And Symptoms ◽

Drug Event ◽

Computer Assisted ◽

Real World Data ◽

World Data

Abstract Objective To advance use of real-world data (RWD) for pharmacovigilance, we sought to integrate a high-sensitivity natural language processing (NLP) pipeline for detecting potential adverse drug events (ADEs) with easily interpretable output for high-efficiency human review and adjudication of true ADEs. Materials and methods The adverse drug event presentation and tracking (ADEPT) system employs an open source NLP pipeline to identify in clinical notes mentions of medications and signs and symptoms potentially indicative of ADEs. ADEPT presents the output to human reviewers by highlighting these drug-event pairs within the context of the clinical note. To measure incidence of seizures associated with sildenafil, we applied ADEPT to 149 029 notes for 982 patients with pediatric pulmonary hypertension. Results Of 416 patients identified as taking sildenafil, NLP found 72 [17%, 95% confidence interval (CI) 14–21] with seizures as a potential ADE. Upon human review and adjudication, only 4 (0.96%, 95% CI 0.37–2.4) patients with seizures were determined to have true ADEs. Reviewers using ADEPT required a median of 89 s (interquartile range 57–142 s) per patient to review potential ADEs. Discussion ADEPT combines high throughput NLP to increase sensitivity of ADE detection and human review, to increase specificity by differentiating true ADEs from signs and symptoms related to comorbidities, effects of other medications, or other confounders. Conclusion ADEPT is a promising tool for creating gold standard, patient-level labels for advancing NLP-based pharmacovigilance. ADEPT is a potentially time savings platform for computer-assisted pharmacovigilance based on RWD.

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Best Paper Selection

Yearbook of Medical Informatics ◽

10.1055/s-0041-1726515 ◽

2021 ◽

Vol 30 (01) ◽

pp. 237-238

Keyword(s):

Electronic Health Record ◽

High Throughput ◽

Adverse Drug Event ◽

Real World ◽

Drug Event ◽

Health Record ◽

Real World Data ◽

Patient Reported ◽

High Throughput Phenotyping ◽

Temporal Sequences

Bell SK, Delbanco T, Elmore JG, Fitzgerald PS, Fossa A, Harcourt K, Leveille SG, Payne TH, Stametz RA, Walker J, DesRoches CM. Frequency and types of patient-reported errors in electronic health record ambulatory care notes. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2766834 Estiri H, Strasser ZH, Murphy SN. High-throughput phenotyping with temporal sequences. https://academic.oup.com/jamia/article-lookup/doi/10.1093/jamia/ocaa288 Geva A, Stedman JP, Manzi SF, Lin C, Savova GK, Avillach P, Mandl KD. Adverse drug event presentation and tracking (ADEPT): semiautomated, high throughput pharmacovigilance using real-world data. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660953/ Zhang Z, Yan C, Mesa DA, Sun J, Malin BA. Ensuring electronic medical record simulation through better training, modeling, and evaluation. https://academic.oup.com/jamia/article/27/1/99/5583723

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Parameter Optimization for Real-World ENSO Forecast in an Intermediate Coupled Model

Monthly Weather Review ◽

10.1175/mwr-d-18-0199.1 ◽

2019 ◽

Vol 147 (5) ◽

pp. 1429-1445 ◽

Cited By ~ 3

Author(s):

Yuchu Zhao ◽

Zhengyu Liu ◽

Fei Zheng ◽

Yishuai Jin

Keyword(s):

Data Assimilation ◽

Parameter Optimization ◽

Real World ◽

Climate Models ◽

Coupled Model ◽

Prediction Skill ◽

Model Parameters ◽

Real World Data ◽

The Real ◽

Advection Term

Abstract We performed parameter estimation in the Zebiak–Cane model for the real-world scenario using the approach of ensemble Kalman filter (EnKF) data assimilation and the observational data of sea surface temperature and wind stress analyses. With real-world data assimilation in the coupled model, our study shows that model parameters converge toward stable values. Furthermore, the new parameters improve the real-world ENSO prediction skill, with the skill improved most by the parameter of the highest climate sensitivity (gam2), which controls the strength of anomalous upwelling advection term in the SST equation. The improved prediction skill is found to be contributed mainly by the improvement in the model dynamics, and second by the improvement in the initial field. Finally, geographic-dependent parameter optimization further improves the prediction skill across all the regions. Our study suggests that parameter optimization using ensemble data assimilation may provide an effective strategy to improve climate models and their real-world climate predictions in the future.

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In Silico Approach to Predict Severe Cutaneous Adverse Reactions Using the Japanese Adverse Drug Event Report Database

Clinical and Translational Science ◽

10.1111/cts.12944 ◽

2021 ◽

Author(s):

Kaori Ambe ◽

Kazuyuki Ohya ◽

Waki Takada ◽

Masaharu Suzuki ◽

Masahiro Tohkin

Keyword(s):

Adverse Drug Event ◽

In Silico ◽

Adverse Reactions ◽

Drug Event ◽

Event Report ◽

Severe Cutaneous Adverse Reactions ◽

Cutaneous Adverse Reactions

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Trastuzumab-based palliative chemotherapy for HER2-positive gastric cancer: a single-center real-world data

BMC Cancer ◽

10.1186/s12885-021-08058-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Tae-Hwan Kim ◽

Hun Do Cho ◽

Yong Won Choi ◽

Hyun Woo Lee ◽

Seok Yun Kang ◽

...

Keyword(s):

Gastric Cancer ◽

Real World ◽

Group Performance ◽

Eastern Cooperative Oncology Group ◽

Conversion Surgery ◽

Single Center ◽

Her2 Positive ◽

Real World Data ◽

World Data ◽

The Real

Abstract Background Since the results of the ToGA trial were published, trastuzumab-based chemotherapy has been used as the standard first-line treatment for HER2-positive recurrent or primary metastatic gastric cancer (RPMGC). However, the real-world data has been rarely reported. Therefore, we investigated the outcomes of trastuzumab-based chemotherapy in a single center. Methods This study analyzed the real-world data of 47 patients with HER2-positive RPMGC treated with trastuzumab-based chemotherapy in a single institution. Results With the median follow-up duration of 18.8 months in survivors, the median overall survival (OS) and progression-free survival were 12.8 and 6.9 months, respectively, and the overall response rate was 64%. Eastern Cooperative Oncology Group performance status 2 and massive amount of ascites were independent poor prognostic factors for OS, while surgical resection before or after chemotherapy was associated with favorable OS, in multivariate analysis. In addition, 5 patients who underwent conversion surgery after chemotherapy demonstrated an encouraging median OS of 30.8 months, all with R0 resection. Conclusions Trastuzumab-based chemotherapy in patients with HER2-positive RPMGC in the real world demonstrated outcomes almost comparable to those of the ToGA trial. Moreover, conversion surgery can be actively considered in fit patients with a favorable response after trastuzumab-based chemotherapy.

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