Evidence map›Paper›PMID 24687538›Full record

Trial reportSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2014

Automated monitoring of symptoms during ambulatory chemotherapy and oncology providers' use of the information: a randomized controlled clinical trial.

Kathi H Mooney, Susan L Beck, Robert H Friedman, Ramesh Farzanfar, Bob Wong

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2014. 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 49 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed, 5 pooled it
–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.

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

49 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  4. Patient-reported outcome use in oncology: a systematic review of the impact on patient-clinician communication.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2018
    Pooled it
  5. Pooled it
  6. Trial
  7. Patient-Reported Outcome-Based Symptom Management Versus Usual Care After Lung Cancer Surgery: A Multicenter Randomized Controlled Trial.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2022
    Trial
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  10. Wearable-derived postdischarge mobility as a digital biomarker for 90-day readmission and mortality in metastatic cancer.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Observational
  11. Observational
  12. The experience of time toxicity in cancer patients: a meta-synthesis of qualitative research.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Review
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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

5 authors.

Kathi H MooneyUniversity of Utah College of Nursing, 10 South 2000 East, Salt Lake City, UT, 84112, USA, kathi.mooney@nurs.utah.edu.
Susan L Beck
Robert H Friedman
Ramesh Farzanfar
Bob Wong

Funding

University of Utah Center for Clinical and Translational ScienceUL1TR001067 · NCATS · UNIVERSITY OF UTAH · PI DERE, WILLARD H., HESS, RACHEL · 2013 to 2017
$19.8M
TELEPHONE LINKED CARE FOR CANCER SYMPTOM MANAGEMENTR01CA089474 · NCI · UNIVERSITY OF UTAH · PI MOONEY, KATHLEEN H · 2001 to 2003
$1.5M
NCATS NIH HHS UL1 TR001067NCI NIH HHS R01 CA089474NCI NIH HHS R01 CA89474
6 · The paper itself

Abstract

purposeMonitoring patient-reported symptoms is necessary to adjust and improve supportive care during chemotherapy. Continuing advances in computerized approaches to symptom monitoring can enhance communication about unrelieved symptoms between patients and oncology providers and may facilitate intensified symptom treatment.

methodsAn automated IT-based telephone monitoring system was developed to enable oncology providers to receive and act on alert reports from patients about unrelieved symptoms during chemotherapy treatment. Daily, 250 participants (randomized to treatment or attentional control) were asked to call the automated system to report presence, severity, and distress for common chemotherapy-related symptoms (1-10 scale if present). For the treatment group, symptoms exceeding preset thresholds for moderate-to-severe intensity levels generated emailed alert reports to both the patient's oncologist and oncology nurse.

resultsPatients reported high satisfaction and ease of use of the automated system. Over 80 % of providers reported usefulness of the symptom alert reports. Ten monitored symptoms resulted in, on average, nine moderate-to-severe intensity alerts per patient over 45 study days. However, providers rarely contacted patients after receiving alerts. There were no significant differences in change of symptom severity between the two groups (mean difference = 0.06, p = 0.58).

conclusionDespite patients' use of a daily symptom monitoring system and providers' receipt of information about unrelieved symptoms of moderate-to-severe intensity, oncology physicians and nurses did not contact patients to intensify symptom treatment nor did symptoms improve. Further research is indicated to determine if oncology providers initiated follow-up to intensify symptom treatment, whether symptom outcomes would improve.

Indexed as

Electronic MailSelf ReportTelephoneAdultAgedAged, 80 and overAntineoplastic AgentsFemaleHumansInternetMaleMiddle AgedMonitoring, PhysiologicNeoplasmsPatient SatisfactionSelf CareAntineoplastic Agents

Identifiers

PMID24687538
PMCPMC4290846

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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.