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Positron emission tomography/computed tomography (PET/CT) for the diagnosis of recurrent cancer (PETREC): A multicenter, prospective cohort study.

2012· article· en· W2600850467 on OpenAlexaffabout
John J. You, Richard Inculet, Sukhbinder Dhesy‐Thind, Adrien Chan, Marc Freeman, Kathryn Cline, Kathleen I. Pritchard, Ian S. Dayes, Chu‐Shu Gu, Jim A. Julian, Karen Y. Gulenchyn, William K. Evans, Mark N. Levine

Bibliographic record

VenueJournal of Clinical Oncology · 2012
Typearticle
Languageen
FieldMedicine
TopicRadiomics and Machine Learning in Medical Imaging
Canadian institutionsHamilton Health SciencesUniversity of TorontoUniversity Health NetworkOntario Clinical Oncology GroupThunder Bay Regional Health Sciences CentreSunnybrook Health Science CentreJuravinski Cancer CentreLondon Health Sciences CentreMcMaster University
Fundersnot available
KeywordsMedicinePositron emission tomographyProspective cohort studyRadiologyBreast cancerEsophageal cancerLymphomaPET-CTLung cancerCancerNuclear medicineInternal medicine

Abstract

fetched live from OpenAlex

6049 Background: The clinical utility of PET/CT in patients with suspected cancer recurrence remains unclear. The aim of this multi-center, prospective, comparative effectiveness study is to assess the impact of PET/CT on clinical management of patients with suspected cancer recurrence. Methods: Patients were eligible if cancer recurrence (non-small cell lung, breast, head and neck, ovarian, esophageal, Hodgkin’s or non-Hodgkin’s lymphoma) was clinically suspected, and if conventional imaging (e.g. X-ray, ultrasound, CT, or MRI) was non-diagnostic. As a pre-requisite to PET/CT booking, clinicians were asked at enrolment to indicate their planned management if PET/CT were not available. Patients then underwent 18FDG-PET/CT. Clinicians were then asked to indicate their management plan based on PET/CT findings. Patients were followed up once at 3 months. The primary outcome was change in planned management after PET/CT and was assessed independently and in duplicate by external outcome adjudicators using all available source documents. Results: 101 patients (mean age 64 y, 45% male, median 1.3 y since last treatment) were enrolled from 4 centers in Ontario, Canada between April 2009 and June 2011. Distribution of tumor types was: non-small cell lung (55%), breast (19%), ovarian (10%), esophageal (6%), lymphoma (6%), head and neck (4%). 8 patients did not complete the study (non-adherence to protocol, 2; death, 5; disease progression prior to PET/CT, 1), of whom 2 did not receive PET/CT. PET/CT changed planned management in 52 (53%) patients (Table). At 3 months, planned management was carried out in 46/52 (88%) patients. Conclusions: In patients with suspected cancer recurrence, PET/CT changes planned management from non-treatment to treatment for approximately 1 in every 3 patients (“number needed to scan” = 3) and contributes importantly to clinical management. [Table: see text]

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)0.003
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 score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.050
GPT teacher head0.459
Teacher spread0.409 · 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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Citations1
Published2012
Admission routes2
Has abstractyes

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