Evidence map›Paper›PMID 35438159›Full record

ArticleJapanese journal of clinical oncology2022

Classification based on skeletal muscle mass and the severity of lung emphysema impacts on clinical outcomes after anatomical resection for lung cancer.

Norifumi Tsubokawa, Takeshi Mimura, Kazuki Tadokoro, Yoshinori Yamashita

Erratum issuedAbstract read
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In one paragraph

Article in Japanese journal of clinical oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.4field-weighted citation impact, top 43% of its field
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Norifumi TsubokawaDepartment of General Thoracic Surgery, National Hospital Organization Kure Medical Center and Chugoku Cancer Center, Kure city, Hiroshima, Japan.ORCID 0000-0003-1966-1709
Takeshi MimuraDepartment of General Thoracic Surgery, National Hospital Organization Kure Medical Center and Chugoku Cancer Center, Kure city, Hiroshima, Japan.ORCID 0000-0002-2809-4833
Kazuki TadokoroDepartment of General Thoracic Surgery, National Hospital Organization Kure Medical Center and Chugoku Cancer Center, Kure city, Hiroshima, Japan.
Yoshinori YamashitaDepartment of General Thoracic Surgery, National Hospital Organization Kure Medical Center and Chugoku Cancer Center, Kure city, Hiroshima, Japan.
National Hospital Organization · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesBoth sarcopenia and lung emphysema are prognostic factors in lung cancer and can be easily assessed using the psoas muscle index and Goddard score, respectively. We investigated the clinical significance of the classification based on psoas muscle index and Goddard score in non-small cell lung cancer.

methodsA total of 303 consecutive patients who underwent anatomical resection for non-small cell lung cancer were retrospectively analyzed. The psoas muscle at the level of the third lumbar vertebrae and Goddard score were measured on preoperative computed tomography. The psoas muscle was adjusted by height as the psoas muscle index (cm2/m2). We divided patients into three groups: low-, middle- and high-risk, using cut-off values of psoas muscle index < 6.36 cm2/m2 for males and 3.92 cm2/m2 for females and Goddard score higher than 7. The predictors of postoperative complications and prognosis were examined.

resultsHigh-, middle- and low-risk were present in 30 (10%), 164 (54%) and 109 (36%) patients, respectively. High risk was significantly associated with male sex, low pulmonary function, more comorbidities and increased postoperative complications. High-risk patients showed poorer overall survival than middle- and low-risk patients (P < 0.001). Multivariable analysis revealed that high risk was an independent risk factor for postoperative complications and unfavorable prognostic factors (P = 0.011, P = 0.014, respectively).

conclusionsClassification based on psoas muscle index and Goddard score is significantly associated with short- and long-term outcomes in patients with lung cancer. This method can be easily assessed for patients and may help select patients for nutritional support and rehabilitation before surgery.

Indexed as

Carcinoma, Non-Small-Cell LungEmphysemaLung NeoplasmsPostoperative ComplicationsPulmonary EmphysemaSarcopeniaFemaleHumansLungMaleMuscle, SkeletalPrognosisPsoas MusclesRetrospective Studiescomplicationsemphysemalung cancerprognosissarcopenia

Identifiers

PMID35438159
OpenAlexW4224245711

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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.