Evidence map›Paper›PMID 36945495›Full record

ArticlemedRxiv : the preprint server for health sciences2023

Integrating 4 Measures to Evaluate Physical Function in Patients with Cancer (In4M): Protocol for a prospective study.

Gita Thanarajasingam, Paul G Kluetz, Vishal Bhatnagar, Abbie Brown, Elizabeth Cathcart-Rake, Matthew Diamond, Louis Faust, Mallorie H Fiero, Scott F Huntington, Molly Moore Jeffery and 11 more

Registry-linked trialAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05214144 (The In4M Study), 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.

NCT05214144 completednot on this map

The In4M Study: Integrating 4 Methods to Assess Physical Function in Cancer Patients

TypeobservationalSponsorYale UniversityRan2022 to 2024Enrolled208ConditionsPhysical Function, Cancer, Breast, Lymphoma, Patient EmpowermentArmsPRO Instruments assessment questionnaire, Baseline Survey Clinician- reported (ClinRO) ECOG, Fitbit, Hugo Health ("Hugo"), 6 Minute Walk Test (6MWT)
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

5 · Who and what money

Authors and funding

21 authors.

Gita ThanarajasingamDivision of Hematology, Mayo Clinic, Rochester, Minnesota, USA.
Paul G KluetzU.S. Food and Drug Administration, Silver Spring, Maryland, USA.
Vishal BhatnagarU.S. Food and Drug Administration, Silver Spring, Maryland, USA.
Abbie BrownHealth Education and Content Services, Mayo Clinic, Rochester, Minnesota, USA.
Elizabeth Cathcart-RakeDepartment of Medical Oncology, Mayo Clinic, Rochester, Minnesota, USA.
Matthew DiamondU.S. Food and Drug Administration, Silver Spring, Maryland, USA.
Louis FaustDivision of Health Care Delivery Research, Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA.
Mallorie H FieroU.S. Food and Drug Administration, Silver Spring, Maryland, USA.
Scott F HuntingtonDepartment of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
Molly Moore JefferyDivision of Health Care Delivery Research, Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA.
Lee JonesPatient advocate, Arlington, Virginia, USA.
Brie N NobleDepartment of Quantitative Health Sciences, Mayo Clinic, Phoenix, Arizona, USA.
Jonas PaludoDivision of Hematology, Mayo Clinic, Rochester, Minnesota, USA.
Brad PowersCancerHacker Lab, Boston, Massachusetts, USA.
Joseph S RossDepartment of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
Jessica D RitchieYale-New Haven Center for Outcomes Research and Evaluation (CORE), New Haven, Connecticut, USA.
Kathryn J RuddyDepartment of Medical Oncology, Mayo Clinic, Rochester, Minnesota, USA.
Sarah E SchellhornDepartment of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
Michelle E TarverU.S. Food and Drug Administration, Silver Spring, Maryland, USA.
Amylou C DueckDepartment of Quantitative Health Sciences, Mayo Clinic, Phoenix, Arizona, USA.
Cary P GrossDepartment of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.

Funding

Yale-Mayo FDA Center for Excellence in Regulatory Science and InnovationU01FD005938 · FDA · YALE UNIVERSITY · PI Joseph Solomon Ross · 2016 to 2026
$25.4M
Leveraging Physician Networks to Improve Care and Outcomes for Low-Income PopulationsR01HL144644 · NHLBI · YALE UNIVERSITY · PI NDUMELE, CHIMA · 2019 to 2021
$1.6M
AHRQ HHS R01 HS022882AHRQ HHS R01 HS025164FDA HHS U01 FD005938NHLBI NIH HHS R01 HL144644
6 · The paper itself

Abstract

Introduction: Accurate, patient-centered evaluation of physical function in patients with cancer can provide important information on the functional impacts experienced by patients both from the disease and its treatment. Increasingly, digital health technology is facilitating and providing new ways to measure symptoms and function. There is a need to characterize the longitudinal measurement characteristics of physical function assessments, including clinician-reported physical function (ClinRo), patient-reported physical function (PRO), performance outcome tests (PerfO) and wearable data, to inform regulatory and clinical decision-making in cancer clinical trials and oncology practice. Methods and analysis: In this prospective study, we are enrolling 200 English- and/or Spanish-speaking patients with breast cancer or lymphoma seen at Mayo Clinic or Yale University who will receive standard of care intravenous cytotoxic chemotherapy. Physical function assessments will be obtained longitudinally using multiple assessment modalities. Participants will be followed for 9 months using a patient-centered health data aggregating platform that consolidates study questionnaires, electronic health record data, and activity and sleep data from a wearable sensor. Data analysis will focus on understanding variability, sensitivity, and meaningful changes across the included physical function assessments and evaluating their relationship to key clinical outcomes. Additionally, the feasibility of multi-modal physical function data collection in real-world patients with cancer will be assessed, as will patient impressions of the usability and acceptability of the wearable sensor, data aggregation platform, and PROs. Ethics and dissemination: This study has received approval from IRBs at Mayo Clinic, Yale University, and the U.S. Food & Drug Administration. Results will be made available to participants, funders, the research community, and the public. Registration Details: The trial registration number for this study is NCT05214144. Strengths & Limitations: This study addresses an important unmet need by characterizing the performance characteristics of multiple patient-centered physical function measures in patients with cancerPhysical function is an important and undermeasured clinical outcome. Scientifically rigorous capture and measurement of physical function constitutes a key component of cancer treatment tolerability assessment both from a regulatory and clinical perspective.This study will include patients with lymphoma or breast cancer receiving a broad range of cytotoxic chemotherapy regimens. While recruitment will occur at two academic sites, patients who ultimately receive treatment at local community sites will be included.A patient-centered health data aggregating platform facilitates the delivery of patient-reported outcome measures and collection of wearable data to researchers, while reducing patient burden compared to traditional patient-generated data collection and aggregation methodsHeterogeneity in patient willingness or comfort engaging with mobile products including smartphones and wearables, enrollment primarily at large academic centers, and the modest sample size are potential limitations to the external validity of the study.

Identifiers

PMID36945495
PMCPMC10029056

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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.