Evidence map›Paper›PMID 28900321›Full record

ArticleIndian journal of medical and paediatric oncology : official journal of Indian Society of Medical & Paediatric Oncology

Pattern of Adverse Drug Reactions to Anticancer Drugs: A Quantitative and Qualitative Analysis.

Shruti Singh, D C Dhasmana, Manisha Bisht, Prashant Kumar Singh

Open access · greenAbstract read
In one paragraph

Article in Indian journal of medical and paediatric oncology : official journal of Indian Society of Medical & Paediatric Oncology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.2field-weighted citation impact, top 19% of its field
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

10 citing papers in PubMed, 21 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Shruti SinghDepartment of Pharmacology, AIIMS, Patna, Bihar, India.
D C DhasmanaDepartment of Pharmacology, HIMS, Dehradun, India.
Manisha BishtDepartment of Pharmacology, AIIMS, Rishikesh, Uttarakhand, India.
Prashant Kumar SinghDepartment of Surgery, AIIMS, Patna, Bihar, India.
All India Institute of Medical Sciences Raipur · INAll India Institute of Medical Sciences Bhopal · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAnticancer drugs contribute significantly to the global burden of adverse drug reactions (ADRs). Any attempt to quantify their magnitude and provide upgraded knowledge would help oncologists in writing safer prescriptions.

aimThis observational follow-up study was conducted on newly diagnosed cancer patients receiving anticancer therapy with an aim to determine the frequency, severity, causality, predictability, and preventability of ADRs. SUBJECTS AND

methodsThe patients were followed up for 6 months for the appearance of adverse events. Data were analyzed using IBM SPSS Statistics for Windows, Version 22.0. (Armonk, NY) and presented in the form of descriptive statistics.

resultsEach patient was prescribed approximately 6.85 ± 1.51 (mean ± standard error) drugs on average. All the patients (100%) receiving anticancer chemotherapy had ADRs. Alopecia, nausea and vomiting, burning tingling, and numbness were the most frequently encountered ADRs. The incidence of alopecia (

conclusionMultiple ADRs were seen in newly diagnosed cancer patients. Most of them were predictable, of mild-to-moderate severity, nonserious, and preventable. A majority of the ADRs recovered over time.

Indexed as

Adverse drug reactionsanticancer drugspredictabilitypreventabilityseverity

Identifiers

PMID28900321
PMCPMC5582550
OpenAlexW2949243606

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

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.