RE: Informing women about overdetection in breast cancer screening: Two-year outcomes from a randomized trial
Notice bibliographique
Résumé
The trial by Hersch et al. (1) entitled “Informing Women About Overdetection in Breast Cancer Screening: Two-Year Outcomes From a Randomized Trial” found that informing women of overdiagnosis with a decision aid improved knowledge of overdiagnosis but did not affect participation rates. Several other recent studies have similar findings, and these studies also only used decision aids (2-4). As a family physician, I have had strikingly different results with informing women. Since I started informing women in 2019, breast cancer screening rates for eligible low-risk women in my practice have decreased from 55% to 30%. I use the Canadian Task force 1000 women-chart (5) and spend no more than 5 minutes explaining the risk of false positives as well as overdiagnosis compared with the mortality benefit. Women are surprised and their typical response was “Why would I do the screening, with results like this?” My results may differ from published results because I directly discuss screening with women at the time of their decision. This corresponds with a Cochrane systematic review that found high-quality evidence decision aids can increase knowledge and better inform patients, but low-quality evidence helps people make decisions that are consistent with their values (6). Compounding this is the fact that overdiagnosis is difficult to communicate and an inherently difficult concept to understand (7). The intention to provide women a decision aid to make a more informed choice on breast cancer screening is admirable. However, to truly inform women and determine whether well-informed women choose less screening, a randomized controlled trial with women being informed via a direct conversation—ideally with a trusted health-care professional—at the time they make their decision would be advantageous. In addition, overdiagnosis may not only affect the women but may also have a multiplicative effect on their family members. Twenty-five percent of women 50-74 years old in my practice had a first-degree relative with breast cancer. Based on current evidence of overdiagnosis, upwards of one-quarter of these women may have been overdiagnosed (5), which means a significant proportion of family members of women diagnosed may unnecessarily carry the label and the corresponding anxiety of “higher risk for breast cancer” for their entire life. No funding was used for this correspondence. Role of the funder: Not applicable. Disclosure: The author declares no competing interests. Author contributions: Conceptualization, writing—original draft, writing—review & editing: RK. Acknowledgements: The author thanks Michelle Umali, office administrator at the medical clinic, for data analysis support, and Dr James Dickinson for review of the draft correspondence. There were no new data generated or used in this correspondence.
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 | 0,019 | 0,099 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,018 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,024 | 0,005 |
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 ».