Dataset Information

A patient-centred web-based adverse drug reaction reporting system identifies not yet labelled potential safety issues.

ABSTRACT:

Purpose

Reporting of adverse drug reactions (ADRs) by patients is essential for a comprehensive risk-benefit evaluation of drugs after marketing, but only few data are available regarding patient-centred web-based ADR reporting systems. Hence, we aimed to analyze ADRs reported by patients with a particular emphasis on novel drugs and serious ADRs not yet labelled in the respective summary of product characteristics (SPC).

Methods

All ADR reports received by a web-based, patient-centred platform ( www.nebenwirkungen.de ) between April 1, 2019, and September 1, 2020, were descriptively analyzed. ADRs and drugs were coded automatically according to MedDRA and ATC classification system. SPC labelling of reported ADRs for novel drugs marketed since 2015 was checked manually.

Results

In total, 13,515 patient reports including 29,529 ADRs were received during the study period (serious ADRs [SADRs] n = 1,318; 4.5%). Women were affected in more than two-thirds of ADR reports. The most common patient-reported ADRs were nausea, dizziness and headache, whereas arrhythmia, intestinal obstruction and erectile dysfunction were the most frequent SADRs. Ciprofloxacin, levothyroxine and venlafaxine were the compounds most frequently suspected for causing both ADRs and SADRs. Regarding novel compounds, 289 reports including 739 ADRs were received (mainly fatigue, headache and myalgia). Three hundred thirty-one (44.8%) out of those ADRs were not yet labelled in the respective SPC, whereof twelve were SADRs.

Conclusion

The majority of patient-reported ADRs were non-serious. However, a relevant number of non-labelled even serious ADRs was reported for novel compounds by patients. Despite well-known limitations of patient-reported ADRs, this web-based ADR reporting system contributes to the identification of new ADRs and thus can help to improve patients' safety complementing other pharmacovigilance instruments.

SUBMITTER: Hasford J

PROVIDER: S-EPMC8212270 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Background/Objective: Spontaneous reporting systems (SRS) such as the Korea Adverse Event Reporting System (KAERS) are limited in their ability to detect adverse drug reaction (ADR) signals due to their limited data on drug use. Conversely, the national health insurance claim (NHIC) data include drug use information for all qualifying residents. This study aimed to compare ADR signal profiles for antidepressants between KAERS and NHIC, evaluating the extent to which detected signals belong to common ADRs and labeling information. Materials and Methods: ADR signal detection in KAERS and NHIC databases, spanning January to December 2017, employed disproportionality analysis. Signal classes were determined based on System Organ Class (SOC) of the Medical Dictionary for Regulatory Activities (MedDRA). Also, Common ADR Coverage (CAC), the proportion of detected signals deemed common ADRs, and labeling information coverage (LIC) represented by mean average precision (mAP) were calculated. Additionally, protopathic bias and relative risk (RR) evaluation were performed to check for signal robustness. Results: Signal detection revealed 51 and 62 signals in KAERS and NHIC databases, respectively. Both systems predominantly captured signals related to nervous system disorders, comprising 33.3% (N = 17) in KAERS and 50.8% (N = 31) in NHIC. Regarding the type of antidepressants, KAERS predominantly reported signals associated with tricyclic antidepressants (TCAs) (N = 21, 41.2%), while NHIC produced most signals linked to selective serotonin reuptake inhibitors (SSRIs) (N = 22, 35.5%). KAERS exhibited higher CAC (68.63% vs. 29.03%) than NHIC. LIC was also higher in KAERS than in NHIC (mAP for EB05: 1.00 vs. 0.983); i.e., NHIC identified 5 signals not documented in drug labeling information, while KAERS found none. Among the unlabeled signals, one (Duloxetine-Myelopathy) was from protopathic bias, and two (duloxetine-myelopathy and tianeptine-osteomalacia) were statistically significant in RR. Conclusion: NHIC exhibited greater capability in detecting ADR signals associated with antidepressant use, encompassing unlabeled ADR signals, compared to KAERS. NHIC also demonstrated greater potential for identifying less common ADRs. Further investigation is needed for signals detected exclusively in NHIC but not covered by labeling information. This study underscores the value of integrating different sources of data, offering substantial regulatory insights and enriching the scope of pharmacovigilance.

Project description:ObjectiveDespite having a detailed MRI-safety questionnaire check at the point of referral, we have encountered a significant number of near-misses with patients being identified with MRI-Unsafe devices at the time of appointments, making this an important safety hazard.Methods and materialsA two-part survey was performed to assess referrer compliance of asking MRI-questionnaires. 120 outpatients across 3 MRI sites were interviewed at the time of appointment to confirm whether their referrers completed the MRI questionnaires with them at the time of referral.Location:Department of Radiology, Ninewells Hospital, Perth Royal Infirmary and Stracathro Hospital in Scotland.ResultsOnly 50-55 % of patients confirmed that they were asked about presence of a pacemaker at the point of referral. Less than 50 % of patients reported being asked about other potential hazards.Suggested strategies for change: (1) Risk Alert-Sent to all MRI referrers in the organization. ( 2) Changes to MRI Safety Questionnaire. (3) Feedback mechanism to referrers-NHS trust website publications on number of recorded near-misses and wasted appointments due to MRI-safety issues. (4) Compulsory education/training of future referrers (junior doctors/allied health professionals). (5) Education of patients/public on MRI safety-Displaying patient information leaflets/posters in waiting areas of the hospital.Key measures for improvement: (1) Reduction in number of recorded near-misses. (2) System improvements, referrer and patient education, reduction of wasted MRI appointments and improvement of waiting-times for MRI appointments Effects of survey and conclusions: The survey highlights the possibility of inadequate referrer attention, and poor patient communication about MRI safety questionnaire with regards to potential hazards of MRI examination in presence of undeclared implants. It initiated several interventions resulting in improved patient safety, with no events in next 12 months, whilst promoting public and referrer's understanding of potential MRI safety issues. Such actions are recommended for all NHS centres across UK since there are significant similarities in functioning across UK.