Evidence map›Paper›PMID 33052514›Full record

ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2021

Feasibility of implementing a text-based symptom-monitoring program of endometrial, ovarian, and breast cancer patients during treatment.

Michelle J Naughton, Ritu Salani, Juan Peng, Maryam Lustberg, Cecilia DeGraffinreid, Jennifer Moon, Hibaq Loyan, Chloe M Beverly Hery, Electra D Paskett

Abstract read
In one paragraph

Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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  10. Using feedback tools to enhance the quality and experience of care.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2021
    Article
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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

9 authors.

Michelle J NaughtonDivision of Cancer Prevention and Control, College of Medicine, The Ohio State University, 1590 N. High St, Suite 525, Columbus, OH, 43201, USA. michelle.naughton@osumc.edu.ORCID http://orcid.org/0000-0001-6037-1522
Ritu SalaniDivision of Gynecologic Oncology, School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
Juan PengDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.
Maryam LustbergDivision of Medical Oncology, College of Medicine, The Ohio State University, Columbus, OH, USA.
Cecilia DeGraffinreidDivision of Cancer Prevention and Control, College of Medicine, The Ohio State University, 1590 N. High St, Suite 525, Columbus, OH, 43201, USA.
Jennifer MoonDivision of Cancer Prevention and Control, College of Medicine, The Ohio State University, 1590 N. High St, Suite 525, Columbus, OH, 43201, USA.
Hibaq LoyanDivision of Cancer Prevention and Control, College of Medicine, The Ohio State University, 1590 N. High St, Suite 525, Columbus, OH, 43201, USA.
Chloe M Beverly HeryDivision of Cancer Prevention and Control, College of Medicine, The Ohio State University, 1590 N. High St, Suite 525, Columbus, OH, 43201, USA.
Electra D PaskettDivision of Cancer Prevention and Control, College of Medicine, The Ohio State University, 1590 N. High St, Suite 525, Columbus, OH, 43201, USA.

Funding

Translational Therapeutics Research Program (TT)P30CA016058 · NCI · OHIO STATE UNIVERSITY · PI Tasleem J Padamsee · 1985 to 2026
$132.3M
Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863NCI NIH HHS P30 CA016058
6 · The paper itself

Abstract

purposeTo evaluate the feasibility of implementing systematic patient symptom monitoring during treatment using a smartphone.

methodsEndometrial [n = 50], ovarian [n = 70] and breast [n = 193] cancer patients participated in text-based symptom reporting for up to 12 months. In order to promote equity, patients without a smartphone were provided with a device, with the phone charges paid by program funds. Each month, patients completed the Patient Health Questionnaire (PHQ-9), and 4 single items assessing fatigue, sleep quality, pain, and global quality of life during the past 7 days rated on a 0 (low) -10 (high) scale. Patients' responses were captured using REDCap, with oncologists receiving monthly feedback. Lay navigators provided assistance to patients with non-medical needs.

resultsPatients utilizing this voluntary program had an overall mean age of 60.5 (range 26-87), and 85% were non-Hispanic white. iPhones were provided to 42 patients, and navigation services were used by 69 patients. Average adherence with monthly surveys ranged between 75-77%, with breast patients having lower adherence after 5 months. The most commonly reported symptoms across cancer types were moderate levels (scores of 4-7) of fatigue and sleep disturbance. At 6 months, 71-77% of all patients believed the surveys were useful to them and their health care team.

conclusionsWe established the feasibility of initiating and managing patients in a monthly text-based symptom-monitoring program. The provision of smartphones and patient navigation were unique and vital components of this program.

Indexed as

Breast NeoplasmsFatigueFeasibility StudiesFemaleHumansMiddle AgedQuality of LifeSurveys and QuestionnairesBreast cancerEndometrial cancerOvarian cancerSmartphonesSymptom assessmentText-based monitoring

Identifiers

PMID33052514
PMCPMC8528739

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.