Evidence map›Paper›PMID 42177540›Full record

ReviewJournal of pharmaceutical health care and sciences2026

Evaluation of adverse drug reactions in cancer-related settings using diverse real-world data.

Ryo Inose

Abstract readReview
In one paragraph

Review in Journal of pharmaceutical health care and sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Ryo InoseLaboratory of Clinical Pharmacoepidemiology, Kyoto Pharmaceutical University, 5 Misasagi Nakauchi-cho, Yamashina-ku, Kyoto, 607-8414, Japan. inose2019@mb.kyoto-phu.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The evaluation of adverse drug reactions in cancer-related settings represents a complex clinical challenge that extends beyond the toxicities associated with anticancer therapies, including drug-induced malignancies and treatment-related complications, in heterogeneous patient populations. Since randomized controlled trials are conducted in highly selected populations, their findings are not always directly generalizable to routine clinical practice. In this context, real-world data (RWD) have become an important resource for evaluating drug safety and clinical outcomes in real-world clinical practice. This review provides an overview of RWD-based approaches for evaluating adverse drug reactions in cancer-related settings, with a particular focus on how different data sources can be used to address clinically relevant safety questions. Electronic medical records enable the detailed evaluation of patient-level clinical information and have been used to identify clinical and pharmacokinetic factors associated with adverse drug reactions. Spontaneous adverse event reporting databases are particularly useful for detecting rare and unexpected adverse events, including drug-induced malignancies. Medical claims databases enable large-scale longitudinal analyses and evaluation of the incidence and time-to-onset of adverse drug reactions. Additionally, the Diagnosis Procedure Combination database provides detailed inpatient information and has been used to evaluate treatment-related complications in routine clinical practice. As each type of RWD has distinct strengths and limitations, the choice of an appropriate data source should be guided by a specific research objective. Selecting the most suitable RWD source according to the research question is essential for appropriately evaluating adverse drug reactions. This approach enables the assessment of diverse clinically relevant safety issues in cancer-related settings and supports the generation of evidence that reflects routine clinical practice.

Indexed as

Adverse drug reactionsCancerDiagnosis procedure combinationElectronic medical recordsMedical claims databasesPharmacovigilanceReal-world dataSpontaneous reporting systems

Identifiers

PMID42177540
PMCPMC13378064

What OpenQuestion holds

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Registered trials

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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.