THE IMPACT OF TARGETED THERAPY ON SURVIVAL AFTER SPINE METASTASIS: A SYSTEMATIC REVIEW AND POOLED DATA ANALYSIS
Notice bibliographique
Résumé
Tumor specific targeted immunotherapy has substantially impacted the quality and quantity of life for patients with spinal metastatic malignancies. Numerous scoring utilities such as the Tokuhashi, Tomita or Spinal Instability Neoplastic score (SINS) are often used to prognosticate treatment and guide surgical management. However, many of these scoring systems are potentially outdated and do not reflect the recent advances made in medical oncology and targeted therapeutic treatment. The primary aim of this research was to investigate the current state of the literature and treatment options pertaining to advancements in targeted systemic therapy compared to other forms of medical management for metastatic spinal tumors. A systematic literature review and pooled data analysis were performed to evaluate the median overall survival (mOS) for patients with metastatic spinal tumors originating from five (lung, breast, renal, melanoma, thyroid) common primary cancers. A comprehensive search of PubMed was conducted by two authors to identify relevant articles for review. Following PRISMA guidelines, 28 of 1834 initially identified articles met our inclusion criteria, encompassing the five primary tumor locations. Lung cancer articles (n=16) reported a weighted mOS of 6.8 months, while articles on breast cancer (n=5) showed 24.0 months, renal cancer (n=3) demonstrated 58.1 months, and thyroid cancer (n=1) exhibited 123.0 months. 15/16 identified articles on lung cancer with spinal metastases included targeted therapy (TT), primarily utilizing EGFR-TKI, resulting in significant improvements in mOS (21.0 months) compared to those without TT (5.65 months). Six of these articles reported statistically significant (p < 0 .05) hazard ratios (HR), and the pooled HR was found to be 0.486. Breast cancer patients who received TT also had a higher overall mOS (83.2 months) compared to those without TT (overall mOS = 32.86). All three melanoma papers reported patients receiving TT, with two showing a mOS improvement, and notably, one paper indicated significance thereof (HR: 0.32, CI: 0.17-0.58, p=0.0002). Of all included articles, only five studies utilized bisphosphonate therapy. Among these, four demonstrated an extension in mOS when compared to non-treatment groups, with three of them showing statistically significant improvements (p < 0 .05). Among the five lung cancer papers that reported outcomes for both chemotherapy and non-chemotherapy groups, four indicated higher mOS with chemotherapy, with one showing statistical significance (p < 0 .001). Similarly, the breast cancer paper reporting chemotherapy outcomes demonstrated a significant mOS improvement (p=0.013). Articles were excluded if they did not consistently report chemotherapy use or provide survival outcomes. Based on this review and pooled data analysis, targeted therapy, especially in lung and breast cancers, demonstrated the most notable improvements in mOS. Our study provides valuable insights into the recent advancement of medical management of metastatic spinal tumors. Future indications include incorporating this literature into personalized treatment approaches to metastatic spine tumors.
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 | 0,032 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,015 | 0,021 |
| Bibliométrie | 0,013 | 0,015 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».