[The scientific basis for population screening for breast cancer in the Netherlands]
Bibliographic record
Abstract
A recent Cochrane review stated that there was a lack of evidence for a decrease in mortality as a result of population breast-cancer screening. The principal data were drawn from five Swedish randomized controlled trials and one Canadian trial. However, the studies cannot be so easily combined because there were important differences in the attendance rate, detection rate, technical quality, referral rate, clinical baseline situation and screening interval. For example, in one of the studies the women from the control arm underwent an annual clinical palpation carried out by a trained nurse or physician, which could have led to an underestimation of the screening effect. Further breast-cancer mortality might not be a good outcome measure because this was not reliably determined; only total mortality was to be observed. This is clinically and methodologically incorrect because breast-cancer mortality was meticulously studied, documented and validated. In the Cochrane review it is suggested that the randomisation was inadequate, but evidence for this was not supplied. The discussion about age differences as a marker for incorrect randomisation is out of date and has been revealed to be unjust. It seems likely that an important part of the decreasing trend in breast-cancer mortality in several countries (including the Netherlands) is due to screening programmes. However, the evaluation of breast-cancer mortality over the next five years is crucial, if greater certainty is to be gained about this.
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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 | 0.055 | 0.277 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.011 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".