Notice bibliographique
Résumé
The Canadian Breast Screening Studies 1 and 2 (CNBSS) were set up to estimate the effect of breast cancer screening on mortality from the disease (1,2). Since the first publications of mortality results, they have been the subject of considerable debate, mainly focusing on the possibility of nonrandom allocation to screening or control, the appropriateness or otherwise of design aspects of the studies, and the quality of mammography (1–4). The year 2021 saw the online publication of an article by Yaffe et al documenting eyewitness statement that random allocation to the screening or control arms was a clear protocol violation in at least one center, and that symptomatic patients were routinely recruited to the trial in another (5). This bombshell is augmented by two articles in the current issue of the Journal of Breast Imaging (6,7). The first article reports on a survey of professional staff involved with the CNBSS, including radiologists, both within the trial and independent reviewers, radiographic technologists, study coordinators, and others (6). The survey explores issues of clarity of design, training of staff, inclusion/exclusion, integrity of random allocation, and quality of mammography. While the survey is pragmatic rather than systematic, it is clear from the responses that the quality of mammography was often inadequate, and that symptomatic women were not excluded from the CNBSS. For staff at several centers, training was inadequate, and there was little transparency of trial processes. This last is particularly important. As noted in the second article in this issue, the chief methodological concern raised by commentators on CNBSS was the possibility of the randomization being a clear protocol violation to preferentially include women with a suspicion of breast cancer in the screening arm, evidenced by an excess of advanced tumors at initiation in this arm (4). In the past, systematic reviewers have dismissed this possibility, on the basis of similar distributions of breast cancer risk factors in the total populations in the screening and control arms (8). First, this ignores the fact that the shift of a small but crucial number of women with pre-existing symptomatic breast cancer would have no discernible effect on the risk factor distributions in the entire randomized population (5). Second, and more importantly, now that there is eyewitness statement that this differential allocation did indeed occur in at least one center (5,7), there can no longer be any justification for assuming that it did not happen or did not bias the results of CNBSS. The second article also documents other major concerns with CNBSS, notably the inclusion/exclusion policy, which allowed recruitment of symptomatic women and the poor quality of mammography (7). It also points out a lack of transparency of study policy, which allowed considerable variation among centers in terms of interpretation of recruitment and allocation procedures. Both papers conclude that CNBSS can no longer be considered safe to include as evidence to inform screening policy. Sadly, this reader can only come to the same conclusion. One might ask how much it matters in 2022. Unfortunately, CNBSS is still cited prominently as evidence against breast cancer screening, particularly in the age subgroup 40–49 years (9), and the above indicates that such citation is inappropriate. What should be done to remedy the situation? In the first instance, one should congratulate the witnesses who have spoken out about shortcomings of CNBSS, notably those who have reported serious issues with allocation (5,7). This must have taken some courage. Second, systematic reviews and meta-analyses can no longer justify the inclusion of CNBSS as providing evidence of adequate quality on the efficacy of breast cancer screening. There is an urgent need to re-review the evidence excluding CNBSS, particularly in terms of target age groups for screening. None declared.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,328 | 0,556 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,003 |
| Méta-épidémiologie (sens large) | 0,004 | 0,003 |
| Bibliométrie | 0,021 | 0,041 |
| Études des sciences et des technologies | 0,015 | 0,010 |
| Communication savante | 0,012 | 0,004 |
| Science ouverte | 0,015 | 0,007 |
| Intégrité de la recherche | 0,004 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».