Breast metastasis from primary lung cancer and its association with ablative radiotherapy: A case report
Bibliographic record
Abstract
This is a case report of a patient with PD-L1 positive metastatic lung adenocarcinoma who underwent palliative and ablative dose radiotherapy directed to metastatic axillary nodal disease and went on to develop localized followed by diffuse breast and cutaneous metastases. This case serves as an example of the potential utility of ablative dose radiotherapy for controlling sites of progression and highlights the risk of ablative radiotherapy for altering lymphatic drainage and promoting retrograde spread of disease. Given the increased incidence of oligometastatic NSCLC, and the increased utilization of ablative dose radiotherapy to treat metastatic sites in this clinical setting, we believe that this article may inform clinical practice. Our results provide additional support for the utility of ablative dose radiotherapy for this patient population and highlight the need for clinicians to employ a patient-specific approach when deciding on treatment, understanding that the use ablative doses of radiotherapy may provide a better chance for radiologic control, but may come at the cost of an increased risk of altered lymphatic drainage and retrograde spread of disease. The case was overseen by a multidisciplinary team consisting of primary care, medical and radiation oncologists as well as palliative care physicians.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".