Evidence map›Paper›PMID 36438264›Full record

ArticleFrontiers in public health2022

Antidepressant use pattern and disparities among cancer patients in the United States.

Jingrui Zou, Yong Zhu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 23% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
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

2 authors at 1 institution in 1 country.

Jingrui ZouDepartment of Scientific Affairs, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yong ZhuWayzek Science, St. Paul, MN, United States.
Huazhong University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many cancer patients also suffer from depression, however, pharmacotherapy of depression and related disparities in US cancer survivors have not been examined in a nationally representative sample. In the present study, 2,590 adult cancer survivors participating in the National Health and Nutrition Examination Survey 2011-2020 were included and antidepressant use pattern was investigated. To examine disparities by social-demographic characteristics and access to healthcare, multivariate logistic regression analysis was conducted in 422 cancer patients who were using antidepressants and 230 cancer patients who were not using antidepressants but were diagnosed with depression. Results suggested that 21% of adult cancer survivors were using antidepressants and selective serotonin reuptake inhibitors were the most common type of antidepressants used. Antidepressant users were more likely to be female, non-Hispanic white, those who were married or living with partner. In addition, those without a routine place to go for healthcare were less likely to use antidepressants. Disparities were not found by age, family income levels, education, or health insurance coverage. The findings highlight disparities in antidepressant use in cancer patients in the US. Policy makers need to better allocate healthcare resources and facilitate availabilities of affordable care to every patient in need.

Indexed as

Antidepressive AgentsNeoplasmsAdultFemaleHumansMaleNutrition SurveysSelective Serotonin Reuptake InhibitorsUnited StatesAntidepressive AgentsSelective Serotonin Reuptake Inhibitorsantidepressantcancerdepressionepidemiologyhealth disparities

Identifiers

PMID36438264
PMCPMC9682280
OpenAlexW4308723873

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.