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Record W4322584010 · doi:10.2196/44264

The Fatty Liver, Cirrhosis, and Liver Cancer Study (TENDENCY): Protocol for a Multicenter Case-Control Study

2023· article· en· W4322584010 on OpenAlexvenueno aff
Yaqza Hussain, Ayman Bannaga, Neil Fisher, Ashwin Krishnamoorthy, Peter Kimani, Ahmad Malik, Maria Truslove, Shivam Joshi, Megan P. Hitchins, Abdullah Abbasi, Christopher Corbett, Matthew Brookes, Harpal Randeva, Nwe Ni Than, Ramesh Arasaradnam

Bibliographic record

VenueJMIR Research Protocols · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced Chemical Sensor Technologies
Canadian institutionsnot available
FundersUniversity Hospitals Coventry and Warwickshire NHS Trust
KeywordsCirrhosisMedicineHepatocellular carcinomaLiver cancerUrineNonalcoholic fatty liver diseaseInternal medicineLiver diseaseGastroenterologyUrinary systemCancerFatty liverDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Hepatocellular cancer (HCC) is associated with high mortality, and early diagnosis leads to better survival. Patients with cirrhosis, especially due to nonalcoholic fatty liver disease and viral hepatitis, are at higher risk of developing HCC and form the main screening group. The current screening methods for HCC (6-monthly screening with serum alpha fetoprotein and ultrasound liver) have low sensitivity; hence, there is a need for better screening markers for HCC. OBJECTIVE: Our study, TENDENCY, aims to validate the novel screening markers (methylated septin 9, urinary volatile organic compounds, and urinary peptides) for HCC diagnosis and study these noninvasive biomarkers in liver disease. METHODS: This is a multicenter, nested case-control study, which involves comparing the plasma levels of methylated septin 9 between confirmed HCC cases and patients with cirrhosis (control group). It also includes the comparison of urine samples for the detection of HCC-specific volatile organic compounds and peptides. Based on the findings of a pilot study carried out at University Hospital Coventry & Warwickshire, we estimated our sample size to be 308 (n=88, 29% patients with HCC; n=220, 71% patients with cirrhosis). Urine and plasma samples will be collected from all participants and will be frozen at -80 °C until the end of recruitment. Gas chromatography-mass spectrometry will be used for urinary volatile organic compounds detection, and capillary electrophoresis-mass spectrometry will be used for urinary peptide identification. Real-time polymerase chain reaction will be used for the qualitative detection of plasma methylated septin 9. The study will be monitored by the Research and Development department at University Hospital Coventry & Warwickshire. RESULTS: The recruitment stage was completed in March 2023. The TENDENCY study is currently in the analysis stage, which is expected to finish by November 2023. CONCLUSIONS: There is lack of effective screening tests for hepatocellular cancer despite higher mortality rates. The application of more sensitive plasma and urinary biomarkers for hepatocellular cancer screening in clinical practice will allow us to detect the disease at earlier stages and hence, overall, improve HCC outcomes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/44264.

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)0.026
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.026
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.016
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0020.003
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0250.005

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 head0.207
GPT teacher head0.519
Teacher spread0.312 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreProtocol

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

Citations2
Published2023
Admission routes1
Has abstractyes

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