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Incorporating progesterone receptor expression into the PREDICT breast prognostic model

دمج تعبير مستقبلات البروجسترون في نموذج التنبؤ بالثدي
Authors: Grootes, Isabelle; Keeman, Renske; Blows, Fiona M; Milne, Roger L; Giles, Graham G; Swerdlow, Anthony J; Fasching, Peter A; +98 Authors

Incorporating progesterone receptor expression into the PREDICT breast prognostic model

Abstract

Predict Breast (www.predict.nhs.uk) est un outil de pronostic et de traitement en ligne pour le cancer du sein invasif précoce. L'objectif de cette étude était d'intégrer l'effet pronostique du statut de récepteur de progestérone (RP) dans une nouvelle version de PREDICT et de comparer ses performances à la version actuelle (2.2). L'effet pronostique du statut de RP était basé sur l'analyse des données de 45 088 patientes européennes atteintes d'un cancer du sein issues de 49 études du Breast Cancer Association Consortium. Des modèles de risque proportionnel de Cox ont été utilisés pour estimer le rapport de risque pour le statut de RP. Les données d'une étude néo-zélandaise portant sur 11 365 patientes atteintes d'un cancer du sein invasif précoce ont été utilisées pour une validation externe. L'étalonnage et la discrimination du modèle ont été utilisés pour tester la performance du modèle. Le fait d'avoir une tumeur PR-positive était associé à un risque de décès par cancer du sein inférieur de 23 % et de 28 % chez les femmes atteintes d'un cancer du sein à récepteurs d'œstrogènes (ER)négatifs et ER-positifs, respectivement. L'aire sous la courbe roc a augmenté avec l'ajout du statut PR de 0,807 à 0,809 pour les patients atteints de tumeurs ER-négatives (p = 0,023) et de 0,898 à 0,902 pour les patients atteints de tumeurs ER-positives (p = 2,3 × 10-6) dans la cohorte néo-zélandaise. L'étalonnage du modèle était modeste avec 940 décès observés par rapport à 1151 prévus. L'inclusion de l'effet pronostique du statut PR pour PRÉDIRE le sein a conduit à une amélioration des performances du modèle et à des prévisions plus précises du bénéfice absolu du traitement pour les patients individuels. D'autres études devraient déterminer si la fonction de danger de base nécessite un réétalonnage.

Predict Breast (www.predict.nhs.uk) es una herramienta de pronóstico y beneficio de tratamiento en línea para el cáncer de mama invasivo temprano. El objetivo de este estudio fue incorporar el efecto pronóstico del estado del receptor de progesterona (PR) en una nueva versión de PREDICT y comparar su rendimiento con la versión actual (2.2). El efecto pronóstico del estado de PR se basó en el análisis de datos de 45.088 pacientes europeas con cáncer de mama de 49 estudios en el Consorcio de la Asociación del Cáncer de Mama. Se utilizaron modelos de riesgo proporcional de Cox para estimar la relación de riesgo para el estado de PR. Los datos de un estudio de Nueva Zelanda de 11,365 pacientes con cáncer de mama invasivo temprano se utilizaron para la validación externa. La calibración del modelo y la discriminación se utilizaron para probar el rendimiento del modelo. Tener un tumor PR positivo se asoció con un riesgo 23% y 28% menor de morir por cáncer de mama para las mujeres con cáncer de mama receptor de estrógeno (ER)negativo y ER positivo, respectivamente. El área bajo la curva Roc aumentó con la adición del estado PR de 0.807 a 0.809 para pacientes con tumores ER negativos (p = 0.023) y de 0.898 a 0.902 para pacientes con tumores ER positivos (p = 2.3 × 10-6) en la cohorte de Nueva Zelanda. La calibración del modelo fue modesta con 940 muertes observadas en comparación con las 1151 predichas. La inclusión del efecto pronóstico del estado de PR para PREDECIR la mama ha llevado a una mejora del rendimiento del modelo y a predicciones absolutas más precisas del beneficio del tratamiento para pacientes individuales. Otros estudios deben determinar si la función de peligro de referencia requiere recalibración.

Predict Breast (www.predict.nhs.uk) is an online prognostication and treatment benefit tool for early invasive breast cancer. The aim of this study was to incorporate the prognostic effect of progesterone receptor (PR) status into a new version of PREDICT and to compare its performance to the current version (2.2).The prognostic effect of PR status was based on the analysis of data from 45,088 European patients with breast cancer from 49 studies in the Breast Cancer Association Consortium. Cox proportional hazard models were used to estimate the hazard ratio for PR status. Data from a New Zealand study of 11,365 patients with early invasive breast cancer were used for external validation. Model calibration and discrimination were used to test the model performance.Having a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with oestrogen receptor (ER)-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0.902 for patients with ER-positive tumours (p = 2.3 × 10-6) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1151 predicted.The inclusion of the prognostic effect of PR status to PREDICT Breast has led to an improvement of model performance and more accurate absolute treatment benefit predictions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration.

Predict Breast (www.predict.nhs.uk) هي أداة للتنبؤ والعلاج عبر الإنترنت لسرطان الثدي الغازي المبكر. كان الهدف من هذه الدراسة هو دمج التأثير التنبؤي لحالة مستقبلات البروجسترون (PR) في إصدار جديد من التنبؤ ومقارنة أدائها بالإصدار الحالي (2.2). استند التأثير التنبؤي لحالة PR إلى تحليل بيانات من 45،088 مريضًا أوروبيًا مصابًا بسرطان الثدي من 49 دراسة في اتحاد جمعية سرطان الثدي. تم استخدام نماذج الخطر التناسبي COX لتقدير نسبة الخطر لحالة PR. تم استخدام بيانات من دراسة نيوزيلندية شملت 11365 مريضًا مصابًا بسرطان الثدي الغازي المبكر للتحقق الخارجي. تم استخدام معايرة النموذج والتمييز لاختبار أداء النموذج. ارتبط وجود ورم إيجابي PR بانخفاض خطر الوفاة بسبب سرطان الثدي بنسبة 23 ٪ و 28 ٪ للنساء المصابات بمستقبلات هرمون الاستروجين (ER) - سرطان الثدي السلبي و ER - سرطان الثدي الإيجابي، على التوالي. زادت المنطقة تحت منحنى ROC مع إضافة حالة PR من 0.807 إلى 0.809 للمرضى الذين يعانون من أورام سلبية في ER (p = 0.023) ومن 0.898 إلى 0.902 للمرضى الذين يعانون من أورام إيجابية في ER (p = 2.3 × 10-6) في مجموعة نيوزيلندا. كانت معايرة النموذج متواضعة مع 940 حالة وفاة ملحوظة مقارنة بـ 1151 حالة متوقعة. أدى تضمين التأثير التنبؤي لحالة PR للتنبؤ بالثدي إلى تحسين أداء النموذج وتوقعات فائدة علاجية مطلقة أكثر دقة للمرضى الأفراد. يجب أن تحدد الدراسات الإضافية ما إذا كانت وظيفة خط الخطر الأساسية تتطلب إعادة المعايرة.

Keywords

Cancer Research, Breast Neoplasms/pathology, Receptors, Progesterone/metabolism, Receptor, ErbB-2, Receptor, ErbB-2/metabolism, THERAPY, Progesterone receptor, ErbB-2, Breast cancer, Global Cancer Incidence and Mortality Patterns, Receptors, Estrogen receptor, Internal medicine, Progesterone, Original Research, Cancer, Manchester Cancer Research Centre, Cohort, Life Sciences, PREDICT Breast, Prognosis, Oncology, Public Health and Health Services, kConFab Investigators, Medicine, Female, Cancers, Receptors, Progesterone, Life Sciences & Biomedicine, Receptor, Receptor, erbB-2, ADJUVANT TAMOXIFEN, Hazard ratio, Oncology and Carcinogenesis, ABCTB Investigators, 610, Breast Neoplasms, R Medicine, Proportional hazards model, 1117 Public Health and Health Services, breast cancer, SDG 3 - Good Health and Well-being, 3211 Oncology and carcinogenesis, Biochemistry, Genetics and Molecular Biology, 616, Breast Cancer, Health Sciences, Humans, 1112 Oncology and Carcinogenesis, CANCER PATIENTS, Oncology & Carcinogenesis, erbB-2, Science & Technology, Confidence interval, ResearchInstitutes_Networks_Beacons/mcrc; name=Manchester Cancer Research Centre, Impact of Obesity on Cancer Risk and Prognosis, ESTROGEN-RECEPTOR, Gynecology, Prognostic Markers, Molecular Research on Breast Cancer

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
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