Evidence map›Paper›PMID 41930312›Full record

ReviewESMO real world data and digital oncology2026

Digital symptom monitoring and activity tracking in chemoradiation-lessons from the CAM experience.

J Fu, A Pepin, C Hollawell, K Tang, J S Bryer, A Munter, S Sinha, A Goel

Registry-linked trialAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in ESMO real world data and digital oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05318027 (Use of Natural Language Processing ChatBot and Automated Continuous Activity Monitoring Via Mobile Phones for Early Detection and Management of Symptoms in Patients Undergoing Cancer Treatment), which is not on this map. Not yet cited in PubMed.

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

NCT05318027 phase2active not recruitingnot on this map

Use of Natural Language Processing ChatBot and Automated Continuous Activity Monitoring Via Mobile Phones for Early Detection and Management of Symptoms in Patients Undergoing Cancer Treatment

TypeinterventionalSponsorAbramson Cancer Center at Penn MedicineRan2023 to 2026Enrolled70ConditionsLung Cancer, Gastrointestinal Cancer, Head and Neck CancerArmsChatBot
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

J FuDepartment of Radiation Oncology, University of Pennsylvania, Philadelphia, USA.
A PepinDepartment of Radiation Oncology, University of Pennsylvania, Philadelphia, USA.
C HollawellDepartment of Radiation Oncology, University of Pennsylvania, Philadelphia, USA.
K TangDepartment of Radiation Oncology, University of Pennsylvania, Philadelphia, USA.
J S BryerDepartment of Radiation Oncology, University of Pennsylvania, Philadelphia, USA.
A MunterDepartment of Radiation Oncology, University of Pennsylvania, Philadelphia, USA.
S SinhaDepartment of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, USA.
A GoelDepartment of Radiation Oncology, University of Pennsylvania, Philadelphia, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) is increasingly being explored as a way to improve supportive care during chemoradiotherapy (CRT). Through our CAM 1.0 and CAM 2.0 studies, we examined how AI-supported remote patient monitoring could be integrated into CRT care, revealing both its potential benefits and its challenges in real-world implementation. We observed how AI can facilitate remote patient monitoring beyond routine visits, yet also how it may create additional tasks for providers, magnify digital inequities, and leave patients still seeking human connection. These experiences underscore that AI's impact in oncology will be defined not only by its technical capabilities but by how it fits into workflows, addresses barriers to access, and preserves the relational aspects of care. This perspectives piece aims to highlight the practical insights from CAM 1.0 and 2.0 that may inform how oncologists, developers, and health systems approach future AI integration into oncology workflows, particularly in the context of CRT. NCT: NCT05318027.

Indexed as

artificial intelligencechatbotchemoradiotherapycontinuous activity monitoringdigital oncologygastrointestinal cancerhead and neck cancerremote patient monitoringthoracic cancer

Identifiers

PMID41930312
PMCPMC13040924

What OpenQuestion holds

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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.