ReviewOncology letters2025
Research progress on evaluation methods for skeletal muscle mass assessment in sarcopenia (Review).
Review in Oncology letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
8 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- From neck to abdomen: cervical (C3) muscle quantification as a surrogate to lumbar (L3) sarcopenia assessment in head and neck cancer: systematic review and meta-analysis.Skeletal radiology · 2026Pooled it
- Pretreatment creatinine-to-cystatin c ratio as a prognostic marker in digestive tract cancers: a meta-analysis with reconstructed individual patient data and trial sequential analysis.Frontiers in nutrition · 2026Pooled it
- Observational
- The Clinical Impact of Sarcopenia and Delirium in Hospitalized Elderly Patients: An Analysis Using Muscle Ultrasound.Journal of cachexia, sarcopenia and muscle · 2026Article
- The TyG Index and Obesity Indicators Predicting Low Muscle Mass in US Adults Without Diabetes: NHANES 2011-2018.Journal of nutrition and metabolism · 2026Article
- Artificial intelligence-driven assessment of sarcopenia in orthopedic geriatrics: technical progress and clinical implications.Frontiers in endocrinology · 2026Review
- Sarcopenia in breast cancer: prognostic values and emerging therapeutic strategies.Frontiers in surgery · 2026Review
- Impact of Preoperative CT-Diagnosed Sarcopenic Obesity on Outcomes After Radical Cystectomy for Bladder Cancer.Cancers · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sarcopenia, characterized by the age-related decline in muscle mass and function, especially in cancer patients, demands accurate diagnostic measures. Recent literature reflects a paradigm shift towards more accessible and diverse assessment tools. Traditional methods such as dual-energy X-ray absorptiometry and bioimpedance analysis offer precise measurements but are limited by equipment availability. By contrast, calf circumference, a simple and quick measure, has emerged as a strong predictor of overall muscle mass and health outcomes, including mortality. The Asian Working Group for Sarcopenia has refined diagnostic criteria, emphasizing the universality of calf circumference across ethnicities. Imaging modalities such as computed tomography and magnetic resonance imaging provide detailed assessments but are less accessible. Ultrasound serves as a non-invasive, portable alternative, enabling standardized muscle evaluation. Innovative self-screening tools such as the Yubi-wakka test and a simple questionnaire of sarcopenia, enhance clinical utility by identifying muscle abnormalities. The integration of these methods heralds a new era in sarcopenia diagnosis, facilitating early detection and timely intervention. The imperative for future research lies in optimizing these techniques for clinical practice and elucidating their predictive capabilities across diverse populations.
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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.