Evidence map›Paper›PMID 42098537›Full record

ArticleOncology and therapy2026

Augmenting Performance Status: A Preliminary Study of Objective Kinematic Assessment Using Motion Capture.

Christopher Wang, Ajay Prasad, Elizabeth Qi, Jonathan Pai, Jade Law, Krithika Chennapan, Grant Jirka, Peter Kuhn, Mihir Tale, Luciano Nocera and 1 more

Registry-linked trialAbstract read
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In one paragraph

Article in Oncology and therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07082257 (Precision Performance Status Compared With ECOG Performance Status- A Pilot Cross Sectional Observational Study), which is not on this map. Not yet cited in PubMed.

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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.

NCT07082257 terminatednot on this map

Precision Performance Status Compared With ECOG Performance Status- A Pilot Cross Sectional Observational Study

TypeobservationalSponsorUniversity of Southern CaliforniaRan2022 to 2026Enrolled41ConditionsHematopoietic and Lymphatic System Neoplasm, Malignant Solid NeoplasmArmsFunctional Assessment, Timed Get Up and Go Test
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

11 authors.

Christopher WangDivision of Medical Oncology, Department of Medicine, USC Norris Comprehensive Cancer Center, Los Angeles, CA, USA. Christopher.wang2@med.usc.edu.ORCID http://orcid.org/0009-0004-4608-1851
Ajay PrasadUSC Keck School of Medicine, Los Angeles, CA, USA.
Elizabeth QiUSC Michelson Center for Convergent Bioscience, Los Angeles, CA, USA.
Jonathan PaiDivision of Medical Oncology, Department of Medicine, USC Norris Comprehensive Cancer Center, Los Angeles, CA, USA.
Jade LawDivision of Medical Oncology, Department of Medicine, USC Norris Comprehensive Cancer Center, Los Angeles, CA, USA.
Krithika ChennapanDivision of Medical Oncology, Department of Medicine, USC Norris Comprehensive Cancer Center, Los Angeles, CA, USA.
Grant JirkaDivision of Medical Oncology, Department of Medicine, USC Norris Comprehensive Cancer Center, Los Angeles, CA, USA.
Peter KuhnUSC Michelson Center for Convergent Bioscience, Los Angeles, CA, USA.
Mihir TaleUSC Viterbi School of Engineering, Los Angeles, CA, USA.
Luciano NoceraUSC Viterbi School of Engineering, Los Angeles, CA, USA.
Jorge NievaDivision of Medical Oncology, Department of Medicine, USC Norris Comprehensive Cancer Center, Los Angeles, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionUnderstanding performance status (PS) is an essential aspect of oncologic care. PS is traditionally evaluated using the Karnofsky Performance Status (KPS) or Eastern Cooperative Oncology Group (ECOG) performance scales. Despite their ubiquity, these tools rely on subjective clinician interpretation and broad clinical categories, which contribute to poor inter-rater reliability and imprecise patient characterization. This study explores digital approaches to PS by leveraging three-dimensional video recordings and kinematic movement data to provide more objective, granular evaluations.

methodsIn this single-center observational study, 34 oncology patients performed a standardized chair-to-table (CTT) movement. Of these participants, 52.9% were male and 47.1% were female. Patient movement was recorded using the Microsoft Kinect v2 sensor, which captures both color video (RGB) and depth-based skeletal tracking (Skeleton). Four oncologists independently reviewed the recordings and assigned KPS scores. Inter-rater reliability was assessed using the intraclass correlation coefficient (ICC). Pelvic acceleration metrics extracted from the Kinect data were correlated with summed KPS scores using Spearman's rank correlation.

resultsThe ICC for KPS scoring was 0.844 for RGB and 0.790 for Skeleton recordings, indicating good inter-rater reliability despite notable inter-observer variability. Vertical pelvic acceleration (mean and median) strongly correlated with summed KPS scores in both RGB (ρ ≈ 0.73-0.75, p < 0.0001) and Skeleton recordings (ρ ≈ 0.69-0.72, p < 0.0001). Horizontal and maximum acceleration showed weaker or nonsignificant associations.

conclusionKinect-derived motion capture offers an objective and reproducible approach to characterizing a patient's PS. Strong correlations between vertical pelvic acceleration and clinician-assigned KPS scores support its potential to augment both the accuracy and granularity of PS evaluation. TRIAL REGISTRY: ClinicalTrials.gov ID: NCT07082257.

Indexed as

Digital motion captureInter-rater reliabilityKarnofsky Performance StatusMicrosoft KinectOncologyPerformance status

Identifiers

PMID42098537
PMCPMC13304051

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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.