Multiple Lung Cancers: Independent Primary Tumors or Intrapulmonary Metastases, A Case Report
Bibliographic record
Abstract
Abstract Background The prevalence of multiple primary lung cancers is rising, highlighting the need for tools to distinguish independent primary tumors from metastases. Molecular markers and hisopathologic comparison are useful to aid in this distinction, but they have significant limitations. Case Presentation A 76-year old woman presented with recurrent bronchorrhea, non-productive cough, and dyspnea upon exertion. She was a former smoker (15 pack-year history). Computerized tomography imaging revealed multiple lung masses: 1.9 × 2.3 cm nodule in the right upper lobe, and a 6.5 cm mass in the right lower lobe. Histologic examination of the tumors showed that the right lower lobe mass was an adenosquamous carcinoma with a mucinous adenocarcinoma component. This tumor showed visceral pleural invasion, and direct invasion of one intrapulmonary peribronchial lymph node. The upper lobe lesion was characterized by pure invasive mucinous adenocarcinoma with no squamous component. Abdominal and pelvic imaging was performed to rule out alternative primary sites, and no evidence of disease was identified outside of the chest. A cancer mutation and rearrangement panel on the adenosquamous carcinoma did not reveal any mutations. Conclusions In this interesting case, a patient presented with two lung tumors which had some morphologic similarities, but also some important differences, and no specific genetic mutations were present to establish the relationship between the tumors. Although current tools are useful, this case highlights an example of a case where it remains extremely difficult to determine whether two lung cancers are independent primary tumors or intrapulmonary metastases.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.009 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".