Case Ascertainment of Pediatric Brain Tumours: The Alberta Experience.
Bibliographic record
Abstract
Estimates suggest that brain tumors are underreported in the Alberta Cancer Registry (ACR). While the reporting of malignant tumors is thought to be complete in cancer registries across Canada, the reporting of benign tumors is estimated at 33 percent of the actual number of cases expected within the country.6 There are many international studies that highlight the issues of underreporting of benign brain tumors in cancer registries. This study had 3 objectives to investigate the amount of and potential reasons for underreporting: 1) overall case ascertainment of pediatric brain tumor cases present in physician databases captured by the ACR was assessed; 2) overall case ascertainment of all known pediatric brain tumors was assessed and summarized for the ACR and physician pediatric brain tumor databases; and 3) the expected number of unknown pediatric brain tumor cases was estimated so overall case ascertainment could be assessed. Brain cancer was defined using topography codes C70 through C72, C75.1 through C75.3, and C30.0 (with morphology codes 9522 and 9523). Databases with these codes from 2 physician practices making up the primary provincial referral network for this patient population were obtained and linked with the ACR for 2004 to 2011. Estimates of the expected number of cases were made using US incidence rates. The ACR captured 309 of the 317 known pediatric brain tumor cases (97 percent) while the physician databases captured 205 cases (65 percent). The ACR also captured 197 of the 205 cases in the physician databases (96 percent). The ACR captured 309 of the 346 expected cases (89 percent) while the physician databases captured 205 of the 346 expected cases (59 percent). As some patients may not have an initial diagnosis confirmed (by specialty physicians) and others are identified through cause of death searches some discrepancies between the databases are expected. The overall underreporting may reflect a lack of referrals from radiology clinics or the case definition used by registries may not be consistent with the definition used by clinicians in Alberta. While further work is required to better understand why some cases are not appearing in the ACR, confidence should exist that ACR information reflects most cases of pediatric brain tumors in Alberta.
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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 | 0.021 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".