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Screening for Liver Cancer: The Rush to Judgment

2012· letter· en· W1972262570 on OpenAlexaboutno aff
Morris Sherman, Jordi Bruix

Bibliographic record

VenueAnnals of Internal Medicine · 2012
Typeletter
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHepatocellular carcinomaFamily medicineLiver cancerHepatologyCancerTraditional medicineGerontologyInternal medicine

Abstract

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Letters21 August 2012Screening for Liver Cancer: The Rush to JudgmentMorris Sherman, MBBCh, PhD and Jordi Bruix, MDMorris Sherman, MBBCh, PhDFrom University of Toronto, Toronto, Ontario M5G 2N2, Canada, and Hospital Clínic, University of Barcelona, 08036 Barcelona, Spain.Search for more papers by this author and Jordi Bruix, MDFrom University of Toronto, Toronto, Ontario M5G 2N2, Canada, and Hospital Clínic, University of Barcelona, 08036 Barcelona, Spain.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-157-4-201208210-00021 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail TO THE EDITOR:Lederle and Pocha (1) criticize the 2005 American Association for the Study of Liver Diseases recommendations for hepatocellular carcinoma (HCC) screening (2), arguing that the trial on which the recommendation was based (3) was incorrectly analyzed and invalid. Furthermore, they suggest that the study is not necessarily applicable to Western populations because it was conducted in a hepatitis B population in China, and most HCC in North America is caused by hepatitis C. In their view, because level I evidence is lacking, screening should not be recommended.As noted by Lederle and Pocha, however, other guidelines, including ...References1. Lederle FA, Pocha C. Screening for liver cancer: the rush to judgment. Ann Intern Med. 2012;156:387-9. [PMID: 22393134] LinkGoogle Scholar2. Bruix J, Sherman M; American Association for the Study of Liver Diseases. Management of hepatocellular carcinoma: an update. Hepatology. 2011;53:1020-2. [PMID: 21374666] CrossrefMedlineGoogle Scholar3. Zhang BH, Yang BH, Tang ZY. Randomized controlled trial of screening for hepatocellular carcinoma. J Cancer Res Clin Oncol. 2004;130:417-22. [PMID: 15042359] CrossrefMedlineGoogle Scholar4. Ferenci P, Fried M, Labrecque D, Bruix J, Sherman M, Omata M, et al; World Gastroenterology Organization. Hepatocellular carcinoma (HCC): a global perspective. J Clin Gastroenterol. 2010;44:239-45. [PMID: 20216082] CrossrefMedlineGoogle Scholar5. European Association for the Study of the Liver. EASL-EORTC clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol. 2012;56:908-43. [PMID: 22424438] CrossrefMedlineGoogle Scholar6. Kudo M, Izumi N, Kokudo N, Matsui O, Sakamoto M, Nakashima O, et al; HCC Expert Panel of Japan Society of Hepatology. Management of hepatocellular carcinoma in Japan: consensus-based clinical practice guidelines proposed by the Japan Society of Hepatology (JSH) 2010 updated version. Dig Dis. 2011;29:339-64. [PMID: 21829027] CrossrefMedlineGoogle Scholar7. Poon D, Anderson BO, Chen LT, Tanaka K, Lau WY, Van Cutsem E, et al; Asian Oncology Summit. Management of hepatocellular carcinoma in Asia: consensus statement from the Asian Oncology Summit 2009. Lancet Oncol. 2009;10:1111-8. [PMID: 19880065] CrossrefMedlineGoogle Scholar8. Poustchi H, Farrell GC, Strasser SI, Lee AU, McCaughan GW, George J. Feasibility of conducting a randomized control trial for liver cancer screening: is a randomized controlled trial for liver cancer screening feasible or still needed? Hepatology. 2011;54:1998-2004. [PMID: 21800340] CrossrefMedlineGoogle Scholar9. Sherman M, Peltekian KM, Lee C. Screening for hepatocellular carcinoma in chronic carriers of hepatitis B virus: incidence and prevalence of hepatocellular carcinoma in a North American urban population. Hepatology. 1995;22:432-8. [PMID: 7543434] MedlineGoogle Scholar10. Livraghi T, Meloni F, Di Stasi M, Rolle E, Solbiati L, Tinelli C, et al. Sustained complete response and complications rates after radiofrequency ablation of very early hepatocellular carcinoma in cirrhosis: Is resection still the treatment of choice? Hepatology. 2008;47:82-9. [PMID: 18008357] CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAuthors: Morris Sherman, MBBCh, PhD; Jordi Bruix, MDAffiliations: From University of Toronto, Toronto, Ontario M5G 2N2, Canada, and Hospital Clínic, University of Barcelona, 08036 Barcelona, Spain.Disclosures: Dr. Bruix: Consultancy: Sumitomo, Pharmexa, Eisai, Biocompatibles, Bioalliance, Angiodynamics, Kowa, Bayer Schering, Lilly, Arqule, Schering Plough; Grants/grants pending (money to institution): Bayer, Lilly, Pharmexa, Eisai, Novartis; Payment for lectures including service on speakers bureaus: Bayer, Biocompatibles; Payment for development of educational presentations: Bayer. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoScreening for Liver Cancer: The Rush to Judgment Frank A. Lederle and Christine Pocha Screening for Liver Cancer: The Rush to Judgment Frank A. Lederle and Christine Pocha Metrics Cited byBlood-based biomarkers for hepatocellular carcinoma screening: Approaching the end of the ultrasound era?How Can We Boost Colorectal and Hepatocellular Cancer Screening Among Underserved Populations?Hepatocellular screening in hepatitis-B infected Asian Americans 21 August 2012Volume 157, Issue 4 Page: 300-301 Keywords Cancer screening Cirrhosis Hepatitis B Hepatitis C Hepatocellular carcinoma Liver Liver diseases Mortality Population statistics ePublished: 21 August 2012 Issue Published: 21 August 2012 Copyright & PermissionsCopyright © 2012 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...

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)0.063
metaresearch head score (Gemma)0.301
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.063
Threshold uncertainty score0.335

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0630.301
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0050.003
Science and technology studies0.0050.015
Scholarly communication0.0120.025
Open science0.0070.005
Research integrity0.0350.073
Insufficient payload (model declined to judge)0.0130.012

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 head0.262
GPT teacher head0.365
Teacher spread0.103 · 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 designNot applicable
Domainnot available
GenreEditorial

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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Citations4
Published2012
Admission routes1
Has abstractyes

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