The iBreastExam versus clinical breast examination for breast evaluation in high risk and symptomatic Nigerian women: a prospective study
Notice bibliographique
Résumé
BACKGROUND: The iBreastExam electronically palpates the breast to identify possible abnormalities. We assessed the iBreastExam performance compared with clinical breast examination for breast lesion detection in high risk and symptomatic Nigerian women. METHODS: This prospective study was done at the Obafemi Awolowo University Teaching Hospital Complex (OAUTHC) in Nigeria. Participants were Nigerian women aged 40 years or older who were symptomatic and presented with breast cancer symptoms or those at high risk with a first-degree relative who had a history of breast cancer. Participants underwent four breast examinations: clinical breast examination (by an experienced surgeon), the iBreastExam (performed by recent nursing school graduates, who finished nursing school within the previous year), ultrasound, and mammography. Sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV) of the iBreastExam and clinical breast examination for detecting any breast lesion and suspicious breast lesions were calculated, using mammography and ultrasound as the reference standard. FINDINGS: Between June 19 and Dec 5, 2019, 424 Nigerian women were enrolled (151 [36%] at high risk of breast cancer and 273 [64%] symptomatic women). The median age of participants was 46 years (IQR 42-52). 419 (99%) women had a breast imaging-reporting and data system (BI-RADS) assessment and were included in the analysis. For any breast finding, the iBreastExam showed significantly better sensitivity than clinical breast examination (63%, 95% CI 57-69 vs 31%, 25-37; p<0·0001), and clinical breast examination showed significantly better specificity (94%, 90-97 vs 59%, 52-66; p<0·0001). For suspicious breast findings, the iBreastExam showed similar sensitivity to clinical breast examination (86%, 95% CI 70-95 vs 83%, 67-94; p=0·65), and clinical breast examination showed significantly better specificity (50%, 45-55 vs 86%, 83-90; p<0·0001). The iBreastExam and clinical breast examination showed similar NPVs for any breast finding (56%, 49-63 vs 52%, 46-57; p=0·080) and suspicious findings (98%, 94-99 vs 98%, 96-99; p=0·42), whereas the PPV was significantly higher for clinical breast examination in any breast finding (87%, 77-93 vs 66%, 59-72; p<0·0001) and suspicious findings (37%, 26-48 vs 14%, 10-19; p=0·0020). Of 15 biopsy-confirmed cancers, clinical breast examination and the iBreastExam detected an ipsilateral breast abnormality in 13 (87%) women and missed the same two cancers (both <2 cm). INTERPRETATION: The iBreastExam by nurses showed a high sensitivity and NPV, but lower specificity than surgeon's clinical breast examination for identifying suspicious breast lesions. In locations with few experienced practitioners, the iBreastExam might provide a high sensitivity breast evaluation tool. Further research into improved specificity with device updates and cost feasibility in low-resource settings is warranted. FUNDING: Prevent Cancer Foundation Global Community Grant Award with additional support from the P30 Cancer Center Support Grant (P30 CA008748).
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,012 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».