Adrenal oligometastasis cured with stereotactic ablative radiotherapy
Bibliographic record
Abstract
Stereotactic ablative radiotherapy (SABR) has emerged as an effective, noninvasive alternative to surgery in patients with oligometastatic disease. Historically, select patients with adrenal oligometastases have been treated with adrenalectomies which can offer durable local control and reasonable survival rates. SABR is a promising noninvasive treatment alternative to surgery capable of delivering ablative doses of radiation to the tumor with the goal of achieving durable local control of adrenal metastases. We report on a case of a patient who underwent initial surgical resection for a locally advanced lung adenocarcinoma and subsequently developed an early, biopsy-proven, oligometastatic recurrence in the adrenal gland. He underwent chemotherapy and SABR using CyberKnife to the adrenal metastasis and is in remission 7 years after treatment with no late toxicity. Fractionated SABR is an attractive noninvasive alternative to surgery for adrenal metastases. This case demonstrates that select patients with adrenal oligometastases, can achieve long-term remission and even cure following SABR.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".