Evidence map›Paper›PMID 28193195›Full record

ArticleBMC psychiatry2017

Assessing the burden of treatment-emergent adverse events associated with atypical antipsychotic medications.

Pierre-Michel Llorca, Christophe Lançon, Ann Hartry, T Michelle Brown, Dana B DiBenedetti, Siddhesh A Kamat, Clément François

Open access · goldAbstract read
In one paragraph

Article in BMC psychiatry, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 22% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Review
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

7 authors at 5 institutions in 2 countries.

Pierre-Michel LlorcaCMP B CHU Clermont-Ferrand, Université Clermont-Auvergne, Clermont Ferrand, Cedex 1, France.
Christophe LançonLaboratoire de Santé Publique Évaluation des Systèms de Soins et Santé Perçue, Université de la Méditerranée, Marseille 5, France.
Ann HartryLundbeck, Deerfield, IL, USA. AHRY@lundbeck.com.
T Michelle BrownRTI Health Solutions, Research Triangle Park, Charlotte, NC, USA.
Dana B DiBenedettiRTI Health Solutions, Research Triangle Park, Charlotte, NC, USA.
Siddhesh A KamatOtsuka Pharmaceutical Development Corporation, Princeton, NJ, USA.
Clément FrançoisLundbeck, Deerfield, IL, USA.
RTI Health Solutions · USCentre Hospitalier Universitaire de Clermont-Ferrand · FRDeerfield (United States) · USLundbeck (United States) · USOtsuka (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTreatment of schizophrenia and major depressive disorder (MDD) with atypical antipsychotics (AAPs) show improved efficacy and reduced side effect burden compared with older antipsychotic medications. However, a risk of treatment-emergent adverse events (TEAEs) remains. TEAEs are hard to quantify and perspectives on the importance of TEAEs differ across patients and between patients and physicians. The current study is a qualitative assessment that investigates TEAEs of AAPs from both patient and physician perspectives to provide better understanding of the occurrence and burden of TEAEs associated with these medications.

methodsFocus groups comprised of patients with MDD and interviews with patients with schizophrenia were conducted at two qualitative research facilities, along with a physician focus group at one of the facilities. Information collected from patients included an exhaustive list of TEAEs experienced, and the frequency and level of bother of each TEAE; from psychiatrists, information included an exhaustive list of TEAEs based on personal observations and patient report, frequency of TEAEs, clinically important TEAEs, and levels of patient-perceived bother. Standard qualitative analysis methods were used to identify, quantify, characterize, and summarize patterns found in the data collected.

resultsA total of 42 patients (25 with MDD and 17 with schizophrenia) and 4 psychiatrists participated in the study. TEAEs reported as bothersome across both patients groups included cognitive issues, weight gain and/or increased appetite, low energy, extrapyramidal symptoms (EPS), and need to sleep/excessive sleep/excessive sleepiness. TEAEs considered more bothersome by patients with schizophrenia were weight gain, low energy, EPS, mental anxiety, and increased positive symptoms; those considered more bothersome by patients with MDD were cognitive issues, somnolence/sedation, and flat/restricted affect. TEAEs considered most clinically important by psychiatrists included metabolic syndrome, weight gain, neutropenia, hyperglycemia, and QT prolongation; those TEAEs considered most bothersome to patients from physicians' perspectives included weight gain, reduced sexual desire or performance, EPS, akathisia, and hormonal issues.

conclusionsThe wide range of TEAEs that are both frequent and bothersome and the variation in perceived burden according to diagnosis highlight the need for a tailored TEAE-awareness approach when choosing an AAP.

Indexed as

AdultAgedAntipsychotic AgentsAttitude of Health PersonnelFemaleFocus GroupsHumansMajor Depressive DisorderMaleMiddle AgedPsychiatryQualitative ResearchSchizophreniaSelf ReportYoung AdultAntipsychotic AgentsAtypical antipsychoticsMajor depressive disorderSchizophreniaTreatment-emergent adverse events

Identifiers

PMID28193195
PMCPMC5307846
OpenAlexW2589120816

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.