Effects of Tumor Localization, Age, and Stage on the Outcomes of Gastric and Colorectal Signet Ring Cell Adenocarcinomas
Bibliographic record
Abstract
Signet ring cell adenocarcinomas (SRCCs) are a rare histological adenocarcinoma subtype, classically thought to have a worse prognosis than conventional adenocarcinomas. The majority of these cancers occur in the stomach, colon, and rectum. Their rarity means that most epidemiological studies into their pathology are often underpowered, and interpretations from these reports are mixed. In this study, we use the Surveillance, Epidemiology, and End Results Program (SEER) database to examine the effects of tumor localization, age, and stage on gastric and colorectal cancer outcomes. For early onset localized and regional gastric cancers, SRCCs have the same overall risk of mortality compared to conventional adenocarcinomas. Over the age of 50 years, SRCCs have worse outcomes across all stages. Gastric SRCCs are 2-3-fold more likely in younger patients, and more heavily favor the distal stomach. Like conventional adenocarcinomas, proximal gastric SRCCs have decreased survival. Across all ages, stages, and locations, colorectal SRCCs have worse outcomes. SRCCs favor the right colon, but outcomes are significantly worse for the left colon and rectal cancers. Relative to adenocarcinomas, colorectal SRCCs have the worst outcomes in younger patients. Overall, these results provide insights into SRCC disease patterns that cannot be surmised outside of population-level data.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".