A way to explore the existence of “immortals” in cancer registry data – An illustration using data from ICBP SURVMARK-2
Bibliographic record
Abstract
BACKGROUND: Accurately recorded vital status of individuals is essential when estimating cancer patient survival. When deaths are ascertained by linkage with vital statistics registers, some may be missed, and such individuals will wrongly appear to be long-term survivors, and survival will be overestimated. Interval-specific relative survival that levels off above one indicates that the survival among the cancer patients is better than expected, which could be due to the presence of immortals. METHODS: We included colon cancer cases diagnosed in 1995-1999 within the 19 jurisdictions in seven countries participating in ICBP SURVMARK-2, with follow-up information available until end-2015. Interval-specific relative survival was estimated for each year following diagnosis, by country and age group at diagnosis. RESULTS: The interval-specific relative survival levels off at 1 for all countries and age groups, with two exceptions: for the age group diagnosed at age 75 years and above in Ireland, and, to a lesser extent, in New Zealand. CONCLUSION: Overall, a subset of immortals are not apparent in the early years within the ICBP SURVMARK-2 study, except for possibly in Ireland. We suggest this approach as one strategy of exploring the existence of immortals, and to be part of routine checks of cancer registry data.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".