Evidence map›Paper›PMID 36108208›Full record

ReviewClinical journal of oncology nursing2022

Ovarian Cancer Symptom Clusters: Use of the NIH Symptom Science Model for Precision in Symptom Recognition and Management.

Diane E Mahoney, Janet D Pierce

Abstract readReview
In one paragraph

Review in Clinical journal of oncology nursing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. The Role of the Human Microbiome in Epithelial Ovarian Cancer.Advances in experimental medicine and biology · 2024
    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

2 authors.

Diane E MahoneyUniversity of Kansas.
Janet D PierceUniversity of Kansas.

Funding

Using Integrated Omics to Identify Dysfunctional Genetic Mechanisms Influencing Schizophrenia and Sleep DisturbancesP20GM130423 · NIGMS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI Diane E Mahoney · 2019 to 2026
$21.5M
Extracellular Vesicle Proteomic Fingerprinting of Ovarian Cancer for Early Detection with a Nanoengineered MicrosystemR01CA260132 · NCI · UNIVERSITY OF KANSAS MEDICAL CENTER · PI GODWIN, ANDREW K., ZENG, YONG · 2021 to 2025
$3.4M
NCI NIH HHS R01 CA260132NIGMS NIH HHS P20 GM130423
6 · The paper itself

Abstract

backgroundIn the United States, ovarian cancer remains the deadliest gynecologic cancer because most women are diagnosed with advanced disease. Although early-stage ovarian tumors are considered asymptomatic, women experience symptoms throughout disease.

objectivesThis review identifies ovarian cancer symptom clusters and explores the applicability of the National Institutes of Health Symptom Science Model (NIH-SSM) for prompt symptom recognition and clinical intervention.

methodsA focused CINAHL® and PubMed® database search was conducted for studies published from January 2000 to May 2022 using combinations of key terms.

findingsThe NIH-SSM can guide the delivery of precision-focused interventions that address racial disparities and foster equity in symptom- focused care. Enhanced understanding of symptom biology can support clinical oncology nurses in ambulatory and inpatient settings.

Indexed as

Ovarian NeoplasmsCarcinoma, Ovarian EpithelialFemaleHumansMedical OncologyNational Institutes of Health (U.S.)SyndromeUnited Statesovarian cancerquality of lifesymptom clusterssymptom management

Identifiers

PMID36108208
PMCPMC9951395

What OpenQuestion holds

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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.