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Record W2072198650 · doi:10.1002/cyto.10065

Increase of sensitivity of sputum cytology using high‐resolution image cytometry: Field study results

2002· article· en· W2072198650 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCytometry · 2002
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsBC Cancer Agency
FundersBC Cancer Agency
KeywordsSputumPapanicolaou stainLung cancerCytologyMedicinePathologyCancerStainAdenocarcinomaCarcinomaTuberculosisInternal medicineGastroenterologyStainingCervical cancer

Abstract

fetched live from OpenAlex

Lung cancer remains the leading cause of cancer deaths in the developed world. There is no widely accepted method to screen for this cancer. The most commonly used method remains conventional sputum cytology, but this method is hampered by low sensitivity. We tested the hypothesis that sensitivity of sputum cytology for early lung cancer can be greatly improved by using image analysis of sputum cells, at a modest reduction of specificity. The study was double-blinded and used sputum samples from subjects with well-characterized clinical diagnoses. There were 177 cancers, 98 dysplasias, and 558 normals. The study samples were separated into two independent sets: training set and test set. Sputum samples were collected prospectively from subjects with a high probability of having lung cancer. Seven institutions from five countries participated in the study. All subjects had complete clinical diagnoses which included, as a minimum, negative chest x-rays for all negative cancers, while all cancers had confirmed tissue pathology. Samples were prepared according to the Saccomanno method. For conventional cytology, slides were stained using Papanicolaou stain. For image analysis, slides were stained using a DNA-specific (Feulgen-Thionin) stain. An automated, high-resolution image cytometer was used for measurements. At 90% specificity, sensitivity of 60% can be achieved for adenocarcinoma, compared to only 14% sensitivity of conventional cytology (at 99% specificity). Similarly, 45% sensitivity at 90% specificity can be reached for stages 0 and I lung cancer, compared to only 14% (at 99% specificity) using conventional cytology.Cytometry combined with conventional cytology shows an increase in sensitivity to early-stage cancer and to adenocarcinomas compared to conventional cytology alone. While the results are encouraging, the sensitivity to detect early lung cancer should be further improved to 70-80% at 90-95% specificity before this test can be considered for screening of high-risk individuals for lung cancer. Cytometry (Clin. Cytometry) 50:168-176, 2002.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.079
Threshold uncertainty score0.660

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.315
Teacher spread0.286 · 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