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In the largest, 15 readers classified 900 lesions with and without the software. Their area under the ROC curve was 0.87 with it and 0.83 without, a statistically significant difference. In another study, the commercial version left readers' area under the curve at 0.82, while two experimental versions raised it. In the Spanish study, following the software would have cut biopsies of 50 lesions rated BI-RADS 3 to 24, with none of the seven cancers missed. AQuAS found that a reader's sensitivity and area under the curve were equal or higher with the software. It warns that a high risk of selection bias may have inflated these results. 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Llinàs-Mallol L, Guzmán Aroca F, Estrada Sabadell MD, Vivanco-Hidalgo RM. Herramienta de apoyo en el diagnóstico ecográfico para la clasificación de nódulos mamarios. Ficha de evaluación de tecnologías sanitarias nuevas y emergentes. Barcelona: AQuAS, 2024. NIPO 133-24-102-2. Puntos clave.","title":"Herramienta de apoyo en el diagnóstico ecográfico para la clasificación de nódulos mamarios","url":"https://redets.sanidad.gob.es/productos/buscarProductos.do?metodo=descargarFichero&idProducto=1360","written_by":"independent","quote":"Respecto a la validez diagnóstica de la tecnología, se ha observado que la sensibilidad y la abcROC de un evaluador es superior o igual con el uso de Koios DS Breast™, sin embargo, el elevado riesgo de sesgo relacionado con la selección de los pacientes podría haber sobreestimado los resultados de utilidad diagnóstica."}]}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["evidence"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"sources[].upstream_sources":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"strategic_assessments[]":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"strategic assessments"},"summary":{"state":"value_present","value":{"kind":"record_fields","fields":{"summary":"AQuAS found in four retrospective studies that readers' sensitivity and area under the ROC curve were equal or higher with Koios DS Breast. Selection bias may have inflated the results.","account":"Koios Medical of Chicago makes Koios DS Breast, deep-learning software that gives radiologists a second opinion on whether a breast nodule on ultrasound is benign or malignant. AQuAS, Catalonia's agency for health quality and assessment, reviewed it for Spain's network of assessment agencies in 2024. It found four retrospective studies, three in the United States and one in Spain. In the largest, 15 readers classified 900 lesions with and without the software. Their area under the ROC curve was 0.87 with it and 0.83 without, a statistically significant difference. In another study, the commercial version left readers' area under the curve at 0.82, while two experimental versions raised it. In the Spanish study, following the software would have cut biopsies of 50 lesions rated BI-RADS 3 to 24, with none of the seven cancers missed. AQuAS found that a reader's sensitivity and area under the curve were equal or higher with the software. It warns that a high risk of selection bias may have inflated these results. 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AQuAS, Catalonia's agency for health quality and assessment, reviewed it for Spain's network of assessment agencies in 2024. It found four retrospective studies, three in the United States and one in Spain. In the largest, 15 readers classified 900 lesions with and without the software. Their area under the ROC curve was 0.87 with it and 0.83 without, a statistically significant difference. In another study, the commercial version left readers' area under the curve at 0.82, while two experimental versions raised it. In the Spanish study, following the software would have cut biopsies of 50 lesions rated BI-RADS 3 to 24, with none of the seven cancers missed. AQuAS found that a reader's sensitivity and area under the curve were equal or higher with the software. It warns that a high risk of selection bias may have inflated these results. 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