Data · dataset · 2025
Skeletal muscle index based on CT images and inflammatory index predict the clinical prognosis of patients with colorectal cancer
Listed in ScienceDB
Objective This study by measuring based on computed tomography (CT) scan the third lumbar level image skeletal muscle area, to explore the effect of skeletal muscle index (SMI) from the clinical prognosis of colorectal cancer (CRC) patients and its relationship with systemic inflammatory indicators.
Description
Methods
Patients with pathologically diagnosed with CRC in the First Affiliated Hospital of Kunming Medical University from January 2015 to December 2020 and underwent abdominal CT examination and laboratory examination within 7 days before treatment were retrospectively collected. The basic demographic information and laboratory index data at initial diagnosis were collected, the skeletal muscle area was measured, the inflammatory index and SMI were further calculated, and the clinical prognosis was followed up.Results A total of 493 patients were included in the study, including 293 males and 200 females.
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Univariate Cox regression analysis showed that low BMI, clinical stage (III, IV), CEA, albumin and PNI were important factors in reducing overall survival and progression-free survival (all P <0.05). In multifactor Cox regression analyses, patients with 25% less than the SMI quantile had an increased risk of reduced overall survival and progression-free survival. SMI and SMI subgroups had low positive correlation with albumin and PNI (0＜r＜0.3, P <0.05).Conclusion SMI in CRC patients at diagnosis is valuable as an independent predictor of clinical prognosis, and SMI is associated with systemic inflammation.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.j00253.01901 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Cancer 75% · Computed tomography 75% · Image 75%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.j00253.01901 | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[disease].local:disease:cancer | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[modality].local:modality:ct | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:image | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |