Evidence map›Paper›PMID 33282287›Full record

ArticleMolecular and clinical oncology2021

Survey of serious adverse events and safety evaluation of oral anticancer drug treatment in Japan: A retrospective study.

Kenji Kawasumi, Azusa Kujirai, Reiko Matsui, Yohei Kawano, Masakazu Yamaguchi, Takao Aoyama

Abstract read
In one paragraph

Article in Molecular and clinical oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

6 authors.

Kenji KawasumiDepartment of Pharmacy, National Cancer Center Hospital East, Kashiwa, Chiba 277-8577, Japan.
Azusa KujiraiFaculty of Pharmaceutical Sciences, Tokyo University of Science, Noda, Chiba 278-8511, Japan.
Reiko MatsuiDepartment of Pharmacy, National Cancer Center Hospital East, Kashiwa, Chiba 277-8577, Japan.
Yohei KawanoFaculty of Pharmaceutical Sciences, Tokyo University of Science, Noda, Chiba 278-8511, Japan.
Masakazu YamaguchiDepartment of Pharmacy, National Cancer Center Hospital, Tokyo 104-0045, Japan.
Takao AoyamaFaculty of Pharmaceutical Sciences, Tokyo University of Science, Noda, Chiba 278-8511, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study assessed the safety of outpatient oral anticancer chemotherapeutic drugs by investigating the type and frequency of serious adverse effects (SAEs). Emergency hospitalization, unplanned consultations and telephone calls were investigated in 1,832 patients who received oral anticancer drug treatment at the National Cancer Center Hospital East between December 1, 2014 and November 30, 2015. Oral cytotoxic anticancer and molecular targeted drugs were administrated to 1,140 (62.2%) and 692 (37.8%) patients, respectively. A total of 52 (2.8%) SAEs were reported, with 32 (2.8%) occurring following cytotoxic anticancer drug administration and 20 (2.9%) occurring after molecular targeted drug treatment. The most common SAE was gastrointestinal toxicity. The median time to SAE occurrence was 32 days (range, 5-1,705 days). The rate of unplanned consultations and telephone calls were 5.5 and 37.9% among all patients, respectively, with skin reactions being the most common reason for unplanned consultations. SAEs often occurred early after treatment initiation. It was concluded that measures against gastrointestinal toxicity are particularly important were administering chemotherapeutic agents.

Indexed as

emergency hospitalizationoral anticancer drugsserious adverse eventtelephone callsunplanned consultation

Identifiers

PMID33282287
PMCPMC7709566

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.