Data · dataset · 2020
PDA_MR
Listed in Teesside University Research Data Repository
Description
We aimed to predict residual tumor (R) classification and overall survival (OS) in patients who underwent first-line surgery for pancreatic ductal adenocarcinoma (PDA) using preoperative magnetic resonance imaging (MRI). 210 patients with PDA who underwent MRI and first-line surgery were randomly categorized into a test group (n=150) and a validation group (n=60). The R classification was divided into R0 (no residual tumor) and R1/R2 (microscopic/macroscopic residual tumor).
Preoperative MRI findings associated with R classification and OS were assessed by using logistic regression and Cox proportional hazard models. In addition, the prediction models for the R classification and OS were validated using calibration plots and C statistics. On preoperative MRI, portal vein encasement (odds ratio 4.755) was an independent predictor for R1/R2 resection (P=0.040).
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Tumor size measured on MRI (hazard ratio [HR] per centimeter 1.539) was a predictor of OS, along with pathologic N1 and N2 stage (HR 1.944 and 3.243, respectively), R1/R2 resection (HR 3.273), and adjuvant chemoradiation therapy (HR 0.250) (Ps<0.050). These results have been validated. In conclusion, preoperative MRI was valuable for predicting R1/R2 resection using portal vein encasement, and was useful for predicting OS after surgery for PDA using tumor size.
Links
Where it is published
- DOI doi.org/10.17632/k7gc59d86x.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Medicine & Health · Social Science
- Inferred from text
- Cancer 65% · Imaging 75% · Magnetic resonance imaging 75% · Oncology and carcinogenesis 72%
Provenance · 1 source records, 15 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/k7gc59d86x.1 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[disease].local:disease:cancer | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (65%) |
| concepts[field].anzsrc:group:3211 | enrichment · researchdata tees ac uk | taxonomy-embedding@1.0.0 | title+keywords+description (72%) |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:imaging | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:mri | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |