Evidence map›Paper›PMID 25711974›Full record

Trial reportCancer2015

Automated pain intervention for underserved minority women with breast cancer.

Karen O Anderson, Guadalupe R Palos, Tito R Mendoza, Charles S Cleeland, Kai-Ping Liao, Michael J Fisch, Araceli Garcia-Gonzalez, Alyssa G Rieber, L Arlene Nazario, Vicente Valero and 3 more

Registry-linked trialOpen access · greenAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Cancer, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05221697 (Effect of an Electronic Alert Management System Using Caregivers' Observations and Machine Learning Algorithm to Reduce the Use of Emergency Department Visits and Unplanned Hospitalizations Among Older People), which is not on this map. Cited by 19 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 5 pooled it
1.7field-weighted citation impact, top 14% 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.

NCT05221697 naunknown statusnot on this mapstarted 2020, after this paper: background citation

Effect of an Electronic Alert Management System Using Caregivers' Observations and Machine Learning Algorithm to Reduce the Use of Emergency Department Visits and Unplanned Hospitalizations Among Older People

TypeinterventionalSponsorPresageRan2020 to 2024Enrolled800ConditionsEmergenciesArmsPRESAGE CARE
3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 5 syntheses or guidelines pooled it, 36 citations in OpenAlex.

  1. Pooled it
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  5. Pooled it
  6. Trial
  7. Trial
  8. Article
  9. Article
  10. Article
  11. Review
  12. Breast Cancer Disparities and the Digital Divide.Current breast cancer reports · 2022
    Review
  13. Supportive health education reduces health care utilization and costs in Latinas with breast cancer and their caregivers.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2021
    Article
  14. Digital health for optimal supportive care in oncology: benefits, limits, and future perspectives.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2020
    Review
  15. Review
  16. Designing for impact: identifying stakeholder-driven interventions to support recovery after major cancer surgery.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2018
    Article
  17. Article
  18. Review
  19. 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

13 authors at 3 institutions in 3 countries.

Karen O AndersonDepartment of Symptom Research, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Guadalupe R PalosOffice of Cancer Survivorship, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Tito R MendozaDepartment of Symptom Research, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Charles S CleelandDepartment of Symptom Research, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Kai-Ping LiaoDepartment of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Michael J FischDepartment of General Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Araceli Garcia-GonzalezDepartment of Symptom Research, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Alyssa G RieberDepartment of General Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
L Arlene NazarioDepartment of General Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Vicente ValeroDepartment of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Karin M HahnLondon Regional Cancer Program, London Health Sciences Center, London, Ontario, Canada.
Cheryl L PersonDepartment of Psychiatry and Behavioral Sciences, The University of Texas Health Sciences Center, Houston, Texas.
Richard PayneDuke Institute on Care at the End of Life, Duke University Divinity School, Durham, North Carolina.
The University of Texas MD Anderson Cancer Center · USDuke University · USLondon Health Sciences Centre · CA

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
NCI NIH HHS P30 CA016672
6 · The paper itself

Abstract

backgroundMinority patients with breast cancer are at risk for undertreatment of cancer-related pain. The authors evaluated the feasibility and efficacy of an automated pain intervention for improving pain and symptom management of underserved African American and Latina women with breast cancer.

methodsSixty low-income African American and Latina women with breast cancer and cancer-related pain were enrolled in a pilot study of an automated, telephone-based, interactive voice response (IVR) intervention. Women in the intervention group were called twice weekly by the IVR system and asked to rate the intensity of their pain and other symptoms. The patients' oncologists received e-mail alerts if the reported symptoms were moderate to severe. The patients also reported barriers to pain management and received education regarding any reported obstacles.

resultsThe proportion of women in both groups reporting moderate to severe pain decreased during the study, but the decrease was significantly greater for the intervention group. The IVR intervention also was associated with improvements in other cancer-related symptoms, including sleep disturbance and drowsiness. Although patient adherence to the IVR call schedule was good, the oncologists who were treating the patients rated the intervention as only somewhat useful for improving symptom management.

conclusionsThe IVR intervention reduced pain and symptom severity for underserved minority women with breast cancer. Additional research on technological approaches to symptom management is needed.

Indexed as

Black or African AmericanHispanic or LatinoAutomationBreast NeoplasmsFemaleHumansMiddle AgedPainPain ManagementPain MeasurementPovertyTelemedicineVulnerable Populationsassessmentbreast cancerminority groupspainsymptoms

Identifiers

PMID25711974
PMCPMC4527331
OpenAlexW1523530360

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

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.