Evidence map›Paper›PMID 30259689›Full record

ArticleThoracic cancer2018

Single-institution study of correlations between skeletal muscle mass, its density, and clinical outcomes in non-small cell lung cancer patients treated with first-line chemotherapy.

Alessio Cortellini, Pierpaolo Palumbo, Giampiero Porzio, Lucilla Verna, Aldo V Giordano, Carlo Masciocchi, Alessandro Parisi, Katia Cannita, Corrado Ficorella, Federico Bozzetti

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PubMed Full text at PMC Publisher
In one paragraph

Article in Thoracic cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 4 pooled it
–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

34 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  9. Exercise Prescription in Cardio-Oncology.Journal of clinical medicine · 2025
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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

10 authors.

Alessio CortelliniMedical Oncology, St. Salvatore Hospital, University of L'Aquila, L'Aquila, Italy.ORCID 0000-0002-1209-5735
Pierpaolo PalumboDepartment of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy.
Giampiero PorzioMedical Oncology, St. Salvatore Hospital, University of L'Aquila, L'Aquila, Italy.
Lucilla VernaDepartment of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy.
Aldo V GiordanoRadiology Department, St. Salvatore Hospital, University of L'Aquila, L'Aquila, Italy.
Carlo MasciocchiDepartment of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy.
Alessandro ParisiMedical Oncology, St. Salvatore Hospital, University of L'Aquila, L'Aquila, Italy.
Katia CannitaDepartment of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy.
Corrado FicorellaMedical Oncology, St. Salvatore Hospital, University of L'Aquila, L'Aquila, Italy.
Federico BozzettiFaculty of Medicine, University of Milan, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSarcopenia and muscle tissue degradation are hallmarks of the majority of chronic diseases, including non-small cell lung cancer (NSCLC). A computed tomography scan could be an easy modality to estimate the skeletal muscle mass through cross-sectional image analysis at the level of the third lumbar vertebra.

methodsBaseline skeletal muscle mass (SMM) was evaluated through the skeletal muscle index (SMI), together with skeletal muscle radiodensity (SMD), in NSCLC patients undergoing first-line chemotherapy to evaluate correlations with safety and clinical outcomes. When SMIs at different time points were available, further comparison was made between patients with worse and improved SMIs.

resultsAmong 81 stage IV NSCLC patients, 28 had low SMM and 23 had low SMD. There were no significant differences in univariate analysis of progression-free survival (PFS) between patients with baseline low and non-low SMM (P = 0.06388) or between patients with low and non-low SMD (P = 0.9126). Baseline low SMM, however, proved a significant predictor of shorter PFS in multivariate analysis (hazard ratio 0.54, 95% confidence interval 0.31-0.93; P = 0.0278), but not low SMD. There were no differences in overall survival (OS) between patients with baseline low and non-low SMM or low and non-low SMD. No differences in PFS and OS between evaluable patients with worse or improved SMI were found. A significant difference in hematological toxicities between patients with baseline low and non-low SMM (P = 0.0358) was observed.

conclusionsLow SMM is predictive of shorter PFS, while consecutive changes in muscular mass do not seem to be a predictor of PFS or OS. The role of muscle radiodensity remains a matter of debate.

Indexed as

Muscle, SkeletalAdultAgedAged, 80 and overAntineoplastic Combined Chemotherapy ProtocolsBody Weights and MeasuresCarcinoma, Non-Small-Cell LungFemaleHumansLung NeoplasmsMaleMiddle AgedNeoplasm GradingNeoplasm StagingOrgan SizePrognosisBMIlung cancermuscle densityNSCLCsarcopenia

Identifiers

PMID30259689
PMCPMC6275826

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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.