Real-world data evaluating the value of PET-CT for mediastinal staging in patients diagnosed with non-small cell lung cancer in an area with high prevalence of granulomatous diseases: The LACOG-0114 study.
Bibliographic record
Abstract
e20065 Background: Evaluation of the mediastinum is critical for therapeutic decision in patients with operable non-small cell lung cancer. This analysis aims to evaluate specificity and positive predictive value (PPV) of PET-CT in mediastinal staging of patients diagnosed with NSCLC in South Brazil, an area with high prevalence of infectious granulomatous disease, such as tuberculosis (estimated incidence of 45 cases/100.000 and only 63.7% of cure rate) (http://www.saude.rs.gov.br/upload/1459169540_RELATÓRIO%20TUBERCULOSE%202016.pdf). Methods: Patients with stages I-III NSCLC underwent 18FDG PET-CT before invasive mediastinal staging. Different SUV cut-offs were evaluated, but for the purpose of this analysis were considered positive all PET-CTs showing any mediastinal uptake > 5 SUV. This abstract shows the specificity and the PPV associated with PET-CT when this high-uptake cut-of is considered. Results: From Aug/2014 to Aug/2016, 100 patients were enrolled, all treated at the Brazilian Public Health System, of which 85 were submitted to mediastinoscopy after PET-CT. Median age was 65 years (range 47-80). At baseline, 49 (58%) patients were male and 68 (80%) white. Current or former smokers accounted for 94% (80/85) of the sample. The prevalence of mediastinal involvement was 27% (23/85) confirmed by histopathological evaluation. PET-CT showed specificity of 79% (95% CI 67%–88%) and PPV of 54% (95% CI 40%–67%) when a SUV > 5 was used as cut-off for positivity (see table). Conclusions: These findings consolidate the clinical impression that a positive PET-CT does not confirm the diagnosis of mediastinal involvement in NSCLC patients treated in areas with high prevalence of infectious granulomatous diseases. In this scenario, all positive findings should be confirmed with histopathological evaluation to assure the diagnosis. Clinical trial information: NCT02664792. [Table: see text]
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".