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Record W4389394573 · doi:10.1002/jmri.29168

Percentage of Pancreatic Cysts on <scp>MRI</scp> With a Pancreatic Carcinoma: Systematic Review and Meta‐Analysis

2023· review· en· W4389394573 on OpenAlexafffund
Nika Elmi, David McEvoy, Matthew D. F. McInnes, Mostafa Alabousi, Elizabeth M. Hecht, Lyndon Luk, Sunna Asghar, Ankush Jajodia, Tiago Lins de Carvalho, W. Warnica, Nanxi Zha, Sadaf Ullah, Christian B. van der Pol

Bibliographic record

VenueJournal of Magnetic Resonance Imaging · 2023
Typereview
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsHamilton Health SciencesSt. Michael's HospitalUniversity of OttawaJuravinski HospitalMcMaster UniversityOttawa HospitalMcMaster University Medical Centre
FundersMcMaster University
KeywordsMedicineMeta-analysisConfidence intervalInternal medicineMEDLINERelative riskOncologyGastroenterologyRadiology

Abstract

fetched live from OpenAlex

BACKGROUND: Pancreatic cystic lesions (PCLs) are frequent on MRI and are thought to be associated with pancreatic adenocarcinoma (PDAC) necessitating long-term surveillance based on older studies suffering from selection bias. PURPOSE: To establish the percentage of patients with PCLs on MRI with a present or future PDAC. STUDY TYPE: Systematic review, meta-analysis. POPULATION: Adults with PCLs on MRI and a present or future diagnosis of PDAC were eligible. MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and Scopus were searched to April 2022 (PROSPERO:CRD42022320502). Studies limited to PCLs not requiring surveillance, <100 patients, or those with a history/genetic risk of PDAC were excluded. FIELD STRENGTH/SEQUENCE: ≥1.5 T with ≥1 T2-weighted sequence. ASSESSMENT: Two investigators extracted data, with discrepancies resolved by a third. QUADAS-2 assessed bias. PDAC was diagnosed using a composite reference standard. STATISTICAL TESTS: A meta-analysis of proportions was performed at the patient-level with 95% confidence intervals (95% CI). RESULTS: Eight studies with 1289 patients contributed to the percentage of patients with a present diagnosis of PDAC, and 10 studies with 3422 patients to the percentage with a future diagnosis. Of patients with PCLs on MRI, 14.8% (95% CI 2.4-34.9) had a PDAC at initial MRI, which decreased to 6.0% (2.2-11.3) for studies at low risk of bias. For patients without PDAC on initial MRI, 2.0% (1.1-3.2) developed PDAC during surveillance, similar for low risk of bias studies at 1.9% (0.7-3.6), with no clear trend of increased PDAC for longer surveillance durations. For patients without worrisome features or high-risk stigmata, 0.9% (0.1-2.2) developed PDAC during surveillance. Of 10, eight studies had a median surveillance ≥3 years (range 3-157 months). Sources of bias included retrospectively limiting PCLs to those with histopathology and inconsistent surveillance protocols. DATA CONCLUSION: A low percentage of patients with PCLs on MRI develop PDAC while on surveillance. The first MRI revealing a PCL should be scrutinized for PDAC. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.033
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0170.034
Bibliometrics0.0080.010
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.055
GPT teacher head0.362
Teacher spread0.307 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2023
Admission routes2
Has abstractyes

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