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Record W2340840224 · doi:10.1097/coc.0000000000000215

ACR Appropriateness Criteria® Diffuse Large B-Cell Lymphoma

2015· review· en· W2340840224 on OpenAlexaff
Bouthaina S. Dabaja, Ranjana H. Advani, David Hodgson, Sughosh Dhakal, Christopher R. Flowers, Chul S. Ha, Bradford S. Hoppe, Nancy P. Mendenhall, Monika L. Metzger, John P. Plastaras, Kenneth B. Roberts, Ronald Shapiro, Sonali M. Smith, Stephanie A. Terezakis, Karen M. Winkfield, Anas Younes, Louis S. Constine

Bibliographic record

VenueAmerican Journal of Clinical Oncology · 2015
Typereview
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineAppropriate Use CriteriaGuidelineMedical physicsPositron emission tomographyRadiation therapyDiffuse large B-cell lymphomaAppropriateness criteriaMultidisciplinary approachLymphomaRadiologyInternal medicinePathology

Abstract

fetched live from OpenAlex

The management of diffuse large B-cell lymphoma depends on the initial diagnosis including molecular and immunophenotypic characteristics, Ann Arbor staging, and International Prognostic Index (IPI score). Treatment approaches with different chemotherapy regimens used is discussed in detail. The role of radiation as a consolidation is discussed including: (1) the prerituximab randomized trials that challenged the role of radiation, (2) recent prospective studies (UNFOLDER/RICOVER-60), and (3) retrospective studies; the last 2 showed a potential benefit of radiation both for early and advanced stage. The document also discusses the role of positron emission tomography/computed tomography for predicting outcome and potentially guiding therapy. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed every 3 years by a multidisciplinary expert panel. The guideline development and review include an extensive analysis of current medical literature from peer-reviewed journals and the application of a well-established consensus methodology (modified Delphi) to rate the appropriateness of imaging and treatment procedures by the panel. In those instances where evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment.

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)0.003
metaresearch head score (Gemma)0.010
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: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.005
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.005

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 head0.177
GPT teacher head0.522
Teacher spread0.345 · 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
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

Citations10
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Clinical OncologySame topicLymphoma Diagnosis and TreatmentFrench-language works237,207