Screening for breast cancer with mammography
Notice bibliographique
Résumé
Background A variety of estimates of the benefits and harms of mammographic screening for breast cancer have been published and national policies vary. This is an update of a review previously updated 2013 and originally published 2001. Objectives To assess the effect of screening for breast cancer with mammography on mortality and morbidity. Search methods For this 2023 update, we searched PubMed, CENTRAL, the Cochrane Breast Cancer Group Specialised Register, the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) and ClinicalTrials.gov up to 28 February 2023. Selection criteria Randomised clinical trials (RCTs) comparing mammographic screening with no mammographic screening. Data collection and analysis Two authors independently extracted data. Study authors were contacted for additional information. Our main outcomes of interest were deaths due to breast cancer, any cancer, and due to any cause, and harms measured as overdiagnosis, number of mastectomies, lumpectomies, use of radiotherapy and of chemotherapy. Certainty of evidence was assessed with GRADE. Main results Eight eligible trials from Europe and North America that compared women offered screening mammography with women not offered screening were included. We excluded a trial because the randomisation failed to produce comparable groups. The eligible trials included 600,000 women in the age range 39 to 74 years. The trials with adequate randomisation did not show a benefit in terms of a reduction in breast cancer mortality at 13 years (risk ratio (RR) 0.90, 95% confidence interval (CI) 0.79 to 1.02; 33 vs 30 deaths from breast cancer per 10,000 women; 3 RCTs; 292,153 participants). The findings at 24 years were similar to those at 13 years. Our certainty in both estimates was downgraded 1 level to 'low' due to changes in technology and treatment (indirectness) and due to imprecision. The trials with suboptimal randomisation showed a reduction in breast cancer mortality at 13 years with an RR of 0.75 (95% CI 0.67 to 0.83; 4 RCTs; 306,937 participants; very low certainty evidence). In women below age 50 years, the results from adequately randomised trials did not show a reduction in breast cancer mortality at 13 years of follow-up (RR 0.87, CI 0.73 to 1.03; 28 vs 24 deaths from breast cancer per 10,000 women; 3 RCTs; 218,697 participants, low certainty evidence), nor for women at least 50 years (RR 0.94, CI 0.77 to 1.15; 53 vs 50 deaths from breast cancer per 10,000 women; 2 RCTs; 74,261 participants, low certainty evidence). Only one trial included women aged 70 years and above and could not provide a reliable effect estimate.We found that breast cancer mortality was an unreliable outcome that was biased in favour of screening, mainly because of the risk of differential misclassification of cause of death. The trials with adequate randomisation did not find an effect of screening on total cancer mortality, including breast cancer, (RR 1.00, 95% CI 0.96 to 1.04; 288 vs 288 cancer deaths per 10,000 women; 3 RCTs; 292,954 participants; moderate certainty evidence; the follow-up was 10.5 years for Canada, 9 years for Malmo and 23 years for the UK age trial). All-cause mortality was not reduced (RR 0.98, 95% CI 0.94 to 1.03 after 7 years; RR 0.99, 95% CI 0.95 to 1.03 after 13 years; 324 vs 328 deaths per 10,000 women; and RR 1.01, 95% CI 0.99 to 1.04 after 24 years; 773 vs 765 deaths per 10,000 women; 2 RCTs; 250,671 participants; moderate certainty evidence) in the adequately randomised trials. There were more lumpectomies and mastectomies combined in the screened groups, likely reflecting overtreatment (RR 1.31, 95% CI 1.22 to 1.42; 164 vs 214 operations per 10,000 women; 2 RCTs; 132,321 participants; moderate certainty evidence), as were the number of mastectomies alone (RR 1.20, 95% CI 1.08 to 1.32; 122 vs 102 per 10,000 women; 2 RCTs; 132,321; moderate certainty evidence). The use of radiotherapy was similarly increased whereas there was no difference in the use of chemotherapy (data for each outcome available from only one adequately randomised trial; low certainty evidence). Breast screening increased the number of breast cancer diagnoses (overdiagnosis)(RR 1.25, CI 1.18 to 1.34, 142 vs 113 diagnoses at 7 to 9 years of follow-up; 3 RCTs, 292,979 participants; moderate certainty evidence) in trials that did not screen the control group after the intervention phase. Authors' conclusions Because of substantial changes in screening technology, treatment, and breast cancer awareness since the trials were done, the estimates from the trials are uncertain in today's setting. As breast cancer mortality is an unreliable outcome that is biased in favour of screening, it is noteworthy that screening did not reduce total cancer mortality or total mortality. Breast screening does not meet the criteria that population screening should be based on rigorously performed randomised trials that show that the benefits outweigh the harms. No studies have been completed in low income countries and one small study from Colombia has yet to provide data on long term outcomes. Women, clinicians and policy makers should consider the trade-offs and the uncertainties carefully when they decide whether or not to attend or support breast screening programmes.
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 | 0,011 | 0,046 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,004 |
| Bibliométrie | 0,008 | 0,007 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 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 ».