Epidemiology of Signet Ring Cell Adenocarcinomas
Bibliographic record
Abstract
Signet ring cell adenocarcinomas (SRCCs) are a rare histological subtype of adenocarcinomas with a poor prognosis, typically due to advanced disease at diagnosis. A signet ring cell, mimicking its moniker, contains abundant intracytoplasmic mucin that pushes the nucleus to the periphery. In these cancers, this cell feature comprises more than 50% of the tumor. Despite predilection for the gastrointestinal tract, and in particular the stomach, primary SRCCs are also described in other sites, typically in case reports. This literature, however, lacks a standardized overview of the SRCC disease entity. Using a retrospective cohort approach, we summarize the clinicodemographic and mortality outcomes of SRCCs in thirteen primary sites, comprising 95% of all SRCCs in the Surveillance, Epidemiology, and End Results Program (SEER), a population-level cancer database covering nearly one-third of the United States population. SRCCs general trends compared to matching nonvariant adenocarcinomas are earlier age of onset, with initial presentation favoring higher rates of regional or distant disease presentation and poor tumor differentiation. After multivariable analysis, SRCCs typically have worse overall survivals, but substantial variances exist depending on tumor location. Identifying SRCCs at earlier disease stages is likely the single most important intervention to improving outcomes for these patients.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".