Evidence map›Paper›PMID 38666456›Full record

ArticleThoracic cancer2024

Exploring previously used thresholds for computed tomography-defined low skeletal muscle mass in predicting functional limitations among lung cancer patients.

Shiva Raj Timsina, Wiwatana Tanomkiat, Sarayut L Geater, Natee Ina

Open access · goldAbstract read
In one paragraph

Article in Thoracic cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-weighted citation impact, top 25% of its field
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

3 citing papers in PubMed, 3 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Shiva Raj TimsinaDepartment of Radiology, Faculty of Medicine, Prince of Songkla University, Songkla, Thailand.ORCID 0009-0002-2662-6856
Wiwatana TanomkiatDepartment of Radiology, Faculty of Medicine, Prince of Songkla University, Songkla, Thailand.ORCID 0000-0002-9881-9713
Sarayut L GeaterUnit of Respiratory and Respiratory Critical Care Medicine, Department of Medicine, Faculty of Medicine, Prince of Songkla University, Songkla, Thailand.ORCID 0000-0002-3494-8268
Natee InaDepartment of Radiology, Faculty of Medicine, Prince of Songkla University, Songkla, Thailand.ORCID 0000-0002-1257-2394
Prince of Songkla University · TH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVarious cutoffs have been used to diagnose computed tomography (CT)-defined low skeletal muscle mass; however, the impact of this variability on predicting physical functional limitations (PFL) remains unclear. In the present study we aimed to evaluate the diagnostic test metrics for predicting PFLs using a fixed cutoff value from previous reports and sought to create a prediction score that incorporated the skeletal muscle index (SMI) and other clinical factors.

methodsIn this cross-sectional study including 237 patients with lung cancer, the SMI was assessed using CT-determined skeletal muscle area at the third lumbar vertebra. Physical function was assessed using the short physical performance battery (SPPB) test, with PFL defined as an SPPB score ≤9. We analyzed the diagnostic metrics of the five previous cutoffs for CT-defined low skeletal muscle mass in predicting PFL.

resultsThe mean age of participants was 66.0 ± 10.4 years. Out of 237 patients, 158 (66.7%) had PFLs. A significant difference was observed in SMI between individuals with and without PFLs (35.7 cm

conclusionFixed cutoffs for CT-defined low skeletal muscle mass may inadequately predict PFLs, potentially overlooking declining physical functions in patients with lung cancer.

Indexed as

Lung NeoplasmsMuscle, SkeletalTomography, X-Ray ComputedAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedSarcopenialung cancerphysical functionssarcopeniaskeletal muscle massSPPB

Identifiers

PMID38666456
PMCPMC11147667
OpenAlexW4395677750

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.