The real-world experience of adjuvant docetaxel and cyclophosphamide (TC) chemotherapy in HER-2 negative breast cancer.
Notice bibliographique
Résumé
538 Background: Adjuvant chemotherapy in breast cancer (BC) substantially improves overall survival (OS) and the risk of recurrence. The short and long-term side effects of anthracycline, and its modest benefits in the adjuvant setting, led to controversy about its role in comparison with TC. We aim to compare the OS of TC with anthracycline-based regimens in Ontario, the most populous province in Canada. Methods: We conducted a retrospective population-based cohort study using the Institute for Clinical Evaluative Sciences (ICES) database, involving females with stage I-III BC HER2-negative. Patients were treated with adjuvant chemotherapy between January 2009 to December 2017. The anthracycline regimens for comparison were as follows, FEC-D: Fluorouracil, Epirubicin, Cyclophosphamide, followed by Docetaxel; and ACT: Doxorubicin, Cyclophosphamide, followed by Docetaxel or Paclitaxel. Exclusion criteria included missing baseline characteristics, a prior history of malignancy or chemotherapy starting more than 120 days from breast surgery. The end of follow-up was March 31st, 2018. Adjusted analyses to compare OS by positive axillary lymph nodes (LN) and chemotherapy regimens were conducted with Cox proportional hazards models. Results: Of a total 10634 female patients with BC, 60% were ≥ 50 years-old, with 19.6% stage I, 61.1% stage II, and 19.3% stage III and 7130 (67%) women were classified as ER+ and 2379 (22.4%) as ER-. Among 5764 (54.2%) patients with positive LN, 4300 (40.4%) had LN 1-3 and 1464 (13.8%) had LN ≥ 4. There were 4945 (46.5%) high-grade cases. There were 2487 (23.5%) patients treated with TC, 2981 (28%) with ACT, and 5166 (48.5%) with FEC-D. With a median follow-up of 5.5 years, the OS comparison for the entire study population showed hazard ratio (HR) of TC vs ACT was 1.47 (95% CI 1.14 – 1.90), p = 0.0027 and TC vs FEC-D HR was 1.48 (95% CI 1.18 – 1.86), p = 0.0007. For ER+ patients treated with TC, the OS comparison of LN 1-3 and LN ≥ 4 vs. LN 0 showed HR 1.34 (95% CI 0.81 – 2.21), p = 0.26, and HR 4.29 (95% CI 2.09 – 8.79), p < 0.0001, respectively. For ER+ LN 0 patients, the OS HR of TC vs. ACT was 1.15 (95% CI 0.58 – 2.35), p = 0.67, and TC vs. FEC-D HR was 1.38 (95% CI 0.81 – 2.33), p = 0.23. For ER- patients treated with TC, the OS comparison of LN 1-3 and LN ≥ 4 vs. LN 0 showed HR 1.12 (95% CI 0.42 – 3.01), p = 0.82 and HR 4.41 (95% CI 1.33 – 14.59), p = 0.015, respectively. For ER- LN 0 patients, the OS HR for TC vs. ACT was 2.04 (95% CI 1.09 – 3.81), p = 0.025, and TC vs. FEC-D HR was 2.05 (95% CI 1.08 – 3.90), p = 0.028. Conclusions: Patients treated with adjuvant TC who had four or more axillary LN had significantly lower OS when compared to patients with LN 0. For women with ER- disease, TC demonstrated a significant unfavourable survival outcome when compared to anthracycline-based treatments.
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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,001 | 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 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 ».