Evidence map›Paper›PMID 39974129›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Smartphone-based measures as real-world indicators of functional status in advanced cancer patients.

Marcin Straczkiewicz, Nancy L Keating, Stephanie M Schonholz, Ursula A Matulonis, Neil Horowitz, Susana Campos, Jukka-Pekka Onnela, Alexi A Wright

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the 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.

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

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

8 authors.

Marcin StraczkiewiczDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.ORCID 0000-0002-8703-4451
Nancy L KeatingDepartment of Health Care Policy, Harvard Medical School, Boston MA 02115, USA.ORCID 0000-0002-8274-4681
Stephanie M SchonholzDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.ORCID 0009-0001-1390-3220
Ursula A MatulonisDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.ORCID 0000-0002-3103-6992
Neil HorowitzDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.ORCID 0000-0002-4854-0642
Susana CamposDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.ORCID 0000-0001-9672-473X
Jukka-Pekka OnnelaDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.ORCID 0000-0001-6613-8668
Alexi A WrightDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.ORCID 0000-0002-9776-7114

Funding

Integrating lifecourse approaches, biologic and digital phenotypes in support of heart and lung disease epidemiologic researchU01HL145386 · NHLBI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI CHAVARRO, JORGE EDUARDO, MANSON, JOANN ELISABETH · 2019 to 2025
$17.8M
Neurodevelopmental Mechanisms Underlying Stress Vulnerability during AdolescenceR37MH119194 · NIMH · HARVARD UNIVERSITY · PI Katie McLaughlin · 2020 to 2026
$10.6M
Passive Data to Improve Outcomes in Advanced CancerR21NR018532 · NINR · DANA-FARBER CANCER INST · PI ONNELA, JUKKA-PEKKA, WRIGHT, ALEXI A · 2019 to 2020
$459k
NHLBI NIH HHS U01 HL145386NIMH NIH HHS R37 MH119194NINR NIH HHS R21 NR018532
6 · The paper itself

Abstract

Objective: This study evaluated the feasibility of using smartphone-based metrics to monitor physical functioning and quality of life in patients with advanced gynecological cancers. We analyzed associations between gait (step count, cadence, stride acceleration) and measures of mobility (home time, distance traveled, number of significant locations visited) with patient-reported outcomes (PROMs). Methods: We studied raw accelerometer and GPS data from smartphones over 180-days for 85 patients with advanced gynecologic cancers. We computed measures of gait and mobility from smartphone sensor data, and PROMs (performance status, health-related quality of life, physical functioning) from smartphone surveys at baseline, 30, 90, and 180 days. We assessed longitudinal associations of digital gait and mobility measures with PROMs using linear mixed-effects models, with attention to smartphone adherence and temporal trends. Results: Smartphone adherence was high: 83% of participants reported daily smartphone usage >1 hour; 74.1% had >16 hours of daily use. Gait measures, particularly step count and stride acceleration, were statistically associated with PROMs. Worsening patient-reported ECOG performance status corresponded to reduced step count (ECOG 3 vs. 0: -1837 steps/day, Conclusion: Smartphone-based gait and mobility metrics offer robust, real-world insights into individuals' health statuses, providing a scalable, low-burden alternative to wearable devices. The high levels of smartphone use among participants underscore the feasibility of integrating this technology into routine oncology care.

Indexed as

adherencebiomarkerdigitalGaitmobilityPROMswearable

Identifiers

PMID39974129
PMCPMC11838621

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.