Evidence map›Paper›PMID 41783859›Full record

ArticleExploratory research in clinical and social pharmacy2026

Assessing safety trends of withdrawn medications: A data-driven pharmacovigilance approach using growth models.

Samadhan Ghubade, Sharvari Shukla

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Article in Exploratory research in clinical and social pharmacy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Samadhan GhubadeSymbiosis Statistical Institute, Symbiosis International (Deemed University), Pune, India.
Sharvari ShuklaSymbiosis Statistical Institute, Symbiosis International (Deemed University), Pune, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Adverse drug reactions (ADRs) are critical in evaluating a medicine's safety profile during development and post-marketing surveillance. This study focuses on medications linked to major adverse drug reactions (ADRs) that were later taken off the market or removed from usage. Adverse drug reaction (ADR) reports were gathered from VigiAccess and the U.S. FDA (United States Food and Drug Administration) Adverse Event Reporting System (FAERS). Data visualization tools were then used to evaluate how reporting patterns changed over time. Although a decrease in adverse drug reaction (ADR) reports after a withdrawal may be expected, we observed various patterns over time. These included sigmoidal, exponential, and linear trends, which indicated that safety signals persisted differently. Assessment was performed using cumulative annual ADR reporting trends, supplemented by published evidence on typical latency intervals between drug exposure and event onset for the medicines of interest. Additionally, we developed a novel statistical metric termed the Detriment Index, based on curve-fitting and growth-rate modeling, to quantitatively compare the relative safety of drugs. This approach allows ranking of medicines with respect to ADR accumulation, supports identification of safer therapeutic alternatives, and provides practical decision support for clinicians and regulators.A total of 39 withdrawn medications were included based on regulatory withdrawal records documented by WHO and FDA sources. For comparative safety assessment, 15 commonly used cancer medications (including Tamoxifen, Avastin, Bleomycin, Paclitaxel, Vincristine, Methotrexate, Cisplatin, Doxorubicin, Imatinib, Docetaxel, Rituximab, Trastuzumab, Revlimid, Lenalidomide, and Pembrolizumab) were analyzed. Four distinct growth patterns were identified based on model fit: Saturation ( Methods: For analysis publicly available datasets from VigiAccess, the WHO's global database of reported potential side effects of medicinal products, and the FDA's Adverse Event Reporting System (FAERS) Public Dashboard have been used. A comprehensive analysis was performed on cumulative count of ADR reports for selected medications that have been withdrawn from the market. The investigation focused on finding patterns in the number of adverse drug reaction (ADR) reports related to the termination of these drugs. To visualize these trends, different curve-fitting methods have been used. These included both linear and non-linear statistical models, such as sigmoidal, exponential, and linear forms. A ranking was also made using an exponential growth rate model to compare the safety ratings of different cancer drugs. This model was used to look at and compare the drug's safety features. Results: When a medication is withdrawn or banned, its utilization is anticipated to cease, resulting in the absence of further reports of adverse drug reactions (ADRs). This is the predicted result for all pharmaceuticals that have been banned. The analysis of 39 medications indicated diverse linear and nonlinear patterns. Specifically, 17 drugs followed a saturation pattern, 10 showed a linear pattern, 7 exhibited an exponential pattern, and 5 displayed a sigmoidal pattern. The examples presented in this investigation demonstrated that the drugs Benoxaprofen, Rosiglitazone, Temazepam, and Rofecoxib exhibited a robust correspondence with diverse modeling approaches. Specifically, Benoxaprofen conformed to a saturating hyperbola model, achieving a R Conclusions: This study shows that adverse drug reaction (ADR) patterns, particularly those for banded/withdrawn drugs and some cancer therapies, demonstrate how safety issues alter over time. Adverse drug response (ADR) reports normally diminish after a drug is discontinued, however the rate varies. This pattern shows historical risk estimates, not those medications are safer.Analyzing the overall patterns in adverse drug reactions (ADRs) provides an additional viewpoint to established ways of monitoring drug safety. This approach allows for a more nuanced understanding of long-term safety data. The Detriment Index, a new metric based on trends, allows for the comparison of the long-term burden of adverse drug reactions (ADRs) across different medications, regardless of their regulatory history or how they are used in treatment. This method helped separate medications with lower risks, like Tamoxifen, from others that build up in the body more quickly, such as Pembrolizumab. This shows its potential for comparing safety profiles.This exploratory approach, in essence, enriches our understanding of how long post-marketing safety information lasts. It also provides a foundation for future research. This research could help support safer clinical decisions and regulatory evaluations for both pharmaceuticals that are no longer on the market and those that are still available.

Indexed as

Adverse drug reactions (ADRs)Detriment indexGrowth rateModel fittingPharmacovigilanceWithdrawn drugsWorld Health Organization (WHO)

Identifiers

PMID41783859
PMCPMC12955146

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.