Evidence map›Paper›PMID 39448968›Full record

ArticleBMC cancer2024

Anthropometric equation has sufficient diagnostic capacity to identify sarcopenia in women with breast cancer.

Thalita Gonçalves Santos, Larissa Leopoldino da Silva, Rayne de Almeida Marques Bernabé, Ben-Hur Albergaria, Janine Martins Machado, José Luiz Marques-Rocha, Valdete Regina Guandalini

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Article in BMC cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Thalita Gonçalves SantosDepartment of Integrated Health Education, Health Sciences Center, Federal University of Espírito Santo, Vitória, ES, Brazil.
Larissa Leopoldino da SilvaDepartment of Integrated Health Education, Health Sciences Center, Federal University of Espírito Santo, Vitória, ES, Brazil.
Rayne de Almeida Marques BernabéPostgraduate Program in Nutrition and Health, Health Sciences Center, Federal University of Espírito Santo, Vitória, ES, Brazil.
Ben-Hur AlbergariaCassiano Antonio Moraes University Hospital, Federal University of Espirito Santo, Vitoria, ES, Brazil.
Janine Martins MachadoCassiano Antonio Moraes University Hospital, Federal University of Espirito Santo, Vitoria, ES, Brazil.
José Luiz Marques-RochaDepartment of Integrated Health Education, Health Sciences Center, Federal University of Espírito Santo, Vitória, ES, Brazil.
Valdete Regina GuandaliniDepartment of Integrated Health Education, Health Sciences Center, Federal University of Espírito Santo, Vitória, ES, Brazil. valdete.guandalini@ufes.br.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSarcopenia is a common condition in women with breast cancer, however still presents limitations for an effective diagnosis. This study aimed to evaluate the agreement and diagnostic accuracy of an anthropometric equation in diagnosing sarcopenia in women with breast cancer based on different constructs.

methodsCross-sectional study carried out with women with breast cancer aged ≥ 20 years. Sarcopenia was identified according to the European Working Group on Sarcopenia in Older People 2 (EWGSOP2) criteria. Muscle strength was obtained by the handgrip strength test (HGS) and muscle mass (MM) by dual-energy x-ray absorptiometry (DXA) and by the anthropometric predictive equation. For the diagnosis of sarcopenia, eight constructs were proposed based on the MM assessment method (equation or DXA) and different cutoff points. Agreement analyses using Cohen's Kappa test and diagnostic performance measures were performed. The significance level for all tests was 5%.

resultsA total of 122 women, with a mean age of 55.3 ± 11.4 years, were evaluated. There was a predominance of brown participants (50.8%), insufficiently active (57.4%), with diagnosis time ≤ 3 months (54.1%), and with invasive breast carcinoma (69.7%). The prevalence of sarcopenia ranged from 3.3 to 8.2%, depending on the construct used. The constructs determined from the cutoff points < 16.0 kg/< 7.58 m² and < 23.0 kg/< 7.58 m² were the ones that showed the best ability to detect sarcopenia.

conclusionThe anthropometric equation showed sufficient diagnostic capacity to be used as an alternative in identifying sarcopenia in women with breast cancer.

Indexed as

Absorptiometry, PhotonAnthropometryBreast NeoplasmsHand StrengthSarcopeniaAdultAgedCross-Sectional StudiesFemaleHumansMiddle AgedPrevalenceAnthropometryBreast neoplasmMuscle massMuscle strength

Identifiers

PMID39448968
PMCPMC11515378

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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.