Evidence map›Paper›PMID 34921544›Full record

ArticleJMIR cancer2022

The Use of Telemedicine in Cancer Clinical Trials: Connect-Patient-to-Doctor Prospective Study.

Yasmine Meghiref, Charles Parnot, Claire Duverger, Françoise Lilly Difoum, Audrey Gourden, Halima Yssaad, Caroline Leiterer, Caroline Bedekovic, Julien Blanchard, Houria Nait Ammar and 3 more

Abstract read
In one paragraph

Article in JMIR cancer, 2022. 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.

  1. Article
  2. Article
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  5. Article
  6. What Is Ailing Oncology Clinical Trials? Can We Fix Them?Current oncology (Toronto, Ont.) · 2024
    Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. 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.

Yasmine Meghiref *Bégin Military Teaching Hospital, Saint-Mandé, France.ORCID https://orcid.org/0000-0002-0838-7719
Charles ParnotCureety, Dinan, France.ORCID https://orcid.org/0000-0002-7346-5883
Claire DuvergerBégin Military Teaching Hospital, Saint-Mandé, France.ORCID https://orcid.org/0000-0001-6406-5805
Françoise Lilly DifoumBégin Military Teaching Hospital, Saint-Mandé, France.ORCID https://orcid.org/0000-0001-9467-3940
Audrey GourdenBégin Military Teaching Hospital, Saint-Mandé, France.ORCID https://orcid.org/0000-0002-3560-0327
Halima YssaadBégin Military Teaching Hospital, Saint-Mandé, France.ORCID https://orcid.org/0000-0002-1951-3792
Caroline LeitererBégin Military Teaching Hospital, Saint-Mandé, France.ORCID https://orcid.org/0000-0001-7035-200X
Caroline BedekovicBégin Military Teaching Hospital, Saint-Mandé, France.ORCID https://orcid.org/0000-0001-8607-8527
Julien BlanchardBégin Military Teaching Hospital, Saint-Mandé, France.ORCID https://orcid.org/0000-0002-8507-7861
Houria Nait AmmarBégin Military Teaching Hospital, Saint-Mandé, France.ORCID https://orcid.org/0000-0001-6294-956X
Antoine SchernbergBégin Military Teaching Hospital, Saint-Mandé, France.ORCID https://orcid.org/0000-0002-2513-4721
Hélène VanquaethemBégin Military Teaching Hospital, Saint-Mandé, France.ORCID https://orcid.org/0000-0002-8262-9085
Carole HelisseyBégin Military Teaching Hospital, Saint-Mandé, France.ORCID https://orcid.org/0000-0002-7774-349X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTelemedicine is currently being adopted for the management of patients in routine care. However, its use remains limited in the context of clinical trials.

objectiveThis study aimed to demonstrate the feasibility of telemonitoring and patient-reported outcomes collection in the context of clinical trials.

methodsThe patients who were included in an interventional oncology clinical trial were eligible. The patients were registered with a digital tool to respond to a patient-reported outcomes questionnaire (ePRO) based on CTCAE (The Common Terminology Criteria for Adverse Events, National Cancer Institute), version 5.0, personalized to their pathology and treatment. An algorithm evaluated the health status of the patient based on the reported adverse events, with a classification in 4 different states (correct, compromise, state to be monitored, or critical state). The main objective was to evaluate the feasibility of remote monitoring via a connected platform of patients included in a clinical trial.

resultsFrom July 1, 2020, to March 31, 2021, 39 patients were included. The median age was 71 years (range 41-94); 74% (n=29) were male, and 59% (n=23) had metastatic disease. Out of the 969 ePRO questionnaires completed over the course of the study, 77.0% (n=746) were classified as "correct," 10.9% (n=106) as "compromised," and 12.1% (n=117) as "to be monitored" or "critical." The median response time was 7 days (IQR 7-15.5), and 76% (25/33) of the patients were compliant. Out of the 35 patients who answered a satisfaction questionnaire, 95% (n=33) were satisfied or very satisfied with the tool, and 85% (n=30) were satisfied with their relationship with the health care team. There were 5 unscheduled hospitalizations during the study period.

conclusionsRemote monitoring in clinical trials is feasible, with a high level of patient participation and satisfaction. It benefits patients, but it also ensures the high quality of the trial through the early management of adverse events and better knowledge of the tolerance profile of experimental treatments. This e-technology will likely be deployed more widely in our clinical trials.

Indexed as

clinical trialneoplasmspatient-reported outcome measurestelemedicine

Identifiers

PMID34921544
PMCPMC8832259

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.