A case report of bone metastases from appendiceal adenocarcinoma and a review of literature
Bibliographic record
Abstract
Appendiceal adenocarcinoma (AA) is a rare cancer, accounting for less than 0.5% of all gastrointestinal cancers. As such, there is still debate surrounding both the nature of the disease and the roles of different treatment modalities in the care of this patient population. Metastases of AA, particularly distant metastases, have not been explored extensively in literature. As survival in optimally treated cases of AA continues to improve, clinicians may encounter previously unrealized complications of this disease or unlikely metastases at a higher frequency. We reported the rare case of a 50-year-old male with recurrent mucinous AA who developed painful pelvic bone metastases. To palliate his symptoms, the patient underwent 30 Gy of external beam radiation treatment (EBRT) in 10 fractions to the pelvis. The patient achieved a good pain response after completion of EBRT, with elimination of analgesic use one month post-treatment. This case demonstrates successful palliative management of bone metastases from a primary mucinous AA. Although there is a lack of evidence-based guidelines specific to the treatment of AA, there are a variety of therapies available [e.g., chemotherapy, cytoreductive surgery (CRS), radiation, etc.]. The use of these treatments is largely determined by prognostic factors.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".