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Record W2592647070 · doi:10.21037/tlcr.2017.02.05

Risk assessment in relation to the detection of small pulmonary nodules

2017· review· en· W2592647070 on OpenAlexaboutno aff
John K. Field, Michael W. Marcus, Matthijs Oudkerk

Bibliographic record

VenueTranslational Lung Cancer Research · 2017
Typereview
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsnot available
FundersNational Institute for Health and Care Research
KeywordsMedicineNational Lung Screening TrialLung cancer screeningLung cancerRadiologyNodule (geology)LungTask forceComputed tomographyMedical physicsInternal medicine

Abstract

fetched live from OpenAlex

The National Lung Cancer Screening trial (NLST) demonstrated that individuals assigned to the LDCT screening arm had a 20% lower mortality than those who were assigned to the conventional chest radiography. The NLST was thoroughly analyzed by the US Preventive Task Force on CT Screening and they recommended that lung cancer screening should be implemented. A number of other countries have also recommended implementation, whilst others are awaiting the outcome of the NELSON Trial. However, recommendations for the management of CT screen detected nodules have only recently had any clarity. The management of CT detected nodules in the NLST was based on the identification and reporting of 4 mm diameter nodules found on the CT screens but there was no NLST radiology protocol in place for the management of nodules. The use of volumetric analysis is not routinely used in the USA and there is still a reliance on utilising the CT nodule diameter as the management parameter. The first pulmonary risk model was developed by the Canadians, utilising data sets from the Pan-Canadian Early detection of Lung cancer (PanCan) and validated in the chemoprevention trial dataset at the British Columbian Agency. This Canadian model, known as the Brock Model, is currently available and has been integrated into the British Thoracic Society guidelines on the management of pulmonary nodules. The American College of Radiology setup a Lung Cancer Screening Committee subgroup on Lung-RADS, to standardize lung cancer screening CT reporting and provide management recommendations. However, it has been recommended that the Lung-RADS system should be revised as the system as it has never been studied in a prospective fashion. The NELSON trial introduced a third screening test, the "indeterminate" screening test result, this was done with the aim to reduce the false-positives CT screening results and also utilized by the UKLS trial successfully. On comparing the radiological CT screen volumetric and diameter based protocols in the NELSON trial, the sensitivity and negative predictive value appeared to be comparable, however a higher specificity and positive predictive value was found for the volume-based protocols, thus confirming the advantage of utilising the volumetric approach over diameter The British Thoracic Society (BTS) has undertaken an in-depth piece of work developing guidelines on the management of pulmonary nodules, utilising the wealth of data published by the NELSON team and support the use of volumetric analysis for the management of pulmonary nodules.

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)0.013
metaresearch head score (Gemma)0.032
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: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.077
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.032
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.005
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.177
GPT teacher head0.509
Teacher spread0.332 · 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

Citations15
Published2017
Admission routes1
Has abstractyes

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