Peritoneal Seeding and Subsequent Progression of Mantle Cell Lymphoma after Splenectomy for Debulking
Bibliographic record
Abstract
BACKGROUND: Peritoneal seeding after abdominal surgery is a well known route of metastasis in intra-abdominal solid tumours. Direct mechanical contamination, local peritoneal trauma and subsequent inflammation, postoperative immunosuppression, and laparoscopic surgery are the proposed predisposing factors for this type of metastasis. These factors probably result in enhanced adhesion or growth of tumour cells. However, this route of metastasis has not yet been reported for lymphomas. Here, we report the first case of peritoneal seeding of lymphoma cells after an abdominal surgery. CASE DESCRIPTION: A 47-year-old man with mantle cell lymphoma had ascites because of infiltration of the liver. He underwent debulking splenectomy. The postoperative ascites cytology and control abdominal computed tomography imaging both confirmed peritoneal involvement and lymphoma progression. Demonstration of negative peritoneal involvement before surgery and close timing of peritoneal involvement after splenectomy suggested to us that the debulking surgery was the main cause of peritoneal seeding of lymphoma cells in our case. CONCLUSIONS: Factors similar to those in solid tumour seeding may also be valid for lymphomas. Peritoneal seeding and consequent disease progression may be a potential complication of abdominal surgery in lymphoma with extensive intra-abdominal involvement.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".