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Pretransplant Alpha-Fetoprotein Slope and Milan Criteria Are Strong Predictors of Hepatocellular Carcinoma Recurrence after Transplantation

2012· article· en· W2334280385 on OpenAlexaff
Teodora Dumitra, Sinziana Dumitra, Prosanto Chaudhury, Marc Deschênes, Mazen Hassanain, Steven Paraskevas, Alan Barkun, Peter Metrakos, Jean Tchervenkov

Bibliographic record

VenueTransplantation · 2012
Typearticle
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineHepatocellular carcinomaDemographicsMilan criteriaUnivariate analysisInternal medicineLogistic regressionLiver transplantationAlpha-fetoproteinGastroenterologyTransplantationMultivariate analysisOncologySurgeryDemography

Abstract

fetched live from OpenAlex

Introduction: Hepatocellular Carcinoma (HCC) is a major cause of orthotropic liver transplants (OTL) worldwide. However, tumor recurrence remains a major concern. Our group has shown that a rising natural alpha-fetoprotein slope (NAS) correlates with tumor characteristics. We want to assess if a rising PAS predicts tumor recurrence in a logistic model. Methods: Patients who underwent first OTL for HCC and survived 90 days post-OTL (n=144) at our institution from 1992 to 2010 were reviewed. Patients with less than two alpha-fetoprotein (AFP) values prior to any treatment, whether therapy or OTL, were excluded (n=52). Of the remaining 92 patients, 12 recurred. A positive NAS was defined as >0.1 (n=28); the remainder (n=64) presented a stable or negative NAS. Demographics, pre-transplant trans-arterial chemoembolization (TACE), adherence to Milan's criteria, number of lesions (< 5, ≥5), total tumor size (< 5 cm, ≥5 cm), tumor grade (< 2/4 or more), and presence of micro-vascular invasion were collected. Statistical analysis was done using ANOVA for demographics, logistic regression for recurrence and Chi-square or Fisher's exact tests for univariate analysis. Results: Demographics were similar among the recurrence and non-recurrence groups. Patients who recurred post-OTL received more TACE therapy (50.0%vs17.5%, OR 4.71,95%CI 1.06-20.22,p-value=0.020), had a higher number of lesions (41.7%vs13.8%,OR 4.48,95%CI 1.23-19.65,p-value=0.032), a greater total tumor size (75.0%vs25.0%,OR 9.00,95%CI 1.94-55.12,p-value=0.001) and a greater incidence of microvascular invasion (58.3%vs23.8%,OR 4.49,95%CI 1.07-19.8,p-value=0.013). More patients exceeded Milan's criteria (75.0%vs31.3%,OR 6.60,95%CI 1.45-4.05,p-value=0.008) and had a rising NAS (58.3%vs26.3%,OR 3.20,95%CI 1.11-9.22,p-value=0.024) amongst the recurrence group. However, tumor grade was comparable between recurring and non-recurring patients (33.3%vs17.5%,p-value=0.241). Furthermore, NAS is a strong predictor of microvascular invasion found in pathology (46.15%vs24.24%,OR 1.96,95%CI 1.04-3.68,p-value=0.040). Given that Milan's criteria is based on tumor size and the number of lesions, we used it as a representative of these values in the logistic model. After correcting for age and sex, both a rising NAS (OR 3.84,95%CI 0.99-14.82,p-value=0.051) and non-adherence to Milan's criteria (OR 7.64,95%CI 1.68-35.70,p-value=0.008) were strong predictors of recurrence post-OTL. Conclusion: The natural AFP slope is a predictor of microvascular invasion, a finding exclusive to pathology and in itself a predictor of HCC recurrence. The NAS and Milan's criteria were able to predict the risk of recurrence after OTL, both separately and in a logistic model. Although sample size is small, these results encourage a frequent monitoring of AFP variations prior to liver transplantation.

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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)0.001
metaresearch head score (Gemma)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.249
Teacher spread0.234 · 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
GenreEmpirical

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".

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Citations0
Published2012
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