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Enregistrement W4385285672 · doi:10.1016/j.ctarc.2023.100747

Survival outcomes and predicting intracranial metastasis in stage III non-small cell lung cancer treated with definitive chemoradiation: Real-world data from a tertiary cancer center

2023· article· en· W4385285672 sur OpenAlexaff
Stéphane Thibodeau, Mahbuba Meem, Wilma M. Hopman, Simran Sandhu, Osbert C. Zalay, Andrea S. Fung, Adi Kartolo, Geneviève C. Digby, Shahad Al-Ghamdi, Andrew Robinson, A. Ashworth, Timothy Owen, Aamer Mahmud, Kit Tam, T Olding, Fábio Ynoe de Moraes

Notice bibliographique

RevueCancer Treatment and Research Communications · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueBrain Metastases and Treatment
Établissements canadiensJuravinski Cancer CentreHamilton Health SciencesKingston Health Sciences CentreOttawa HospitalQueen's University
Organismes subventionnairesnon disponible
Mots-clésMedicineLung cancerCenter (category theory)OncologyStage (stratigraphy)Internal medicineTertiary careBrain metastasisDistant metastasisMetastasisReal world dataCancerBiologyComputer scienceChemistry

Résumé

récupéré en direct d'OpenAlex

PURPOSE/OBJECTIVE: Around 30% of patients with non-small cell lung cancers (NSCLC) are diagnosed with stage III disease at presentation, of which about 50% are treated with definitive chemoradiation (CRT). Around 65-80% of patients will eventually develop intracranial metastases (IM), though associated risk factors are not clearly described. We report survival outcomes and risk factors for development of IM in a cohort of patients with stage III NSCLC treated with CRT at a tertiary cancer center. MATERIALS/METHODS: We identified 195 patients with stage III NSCLC treated with CRT from January 2010 to May 2021. Multivariable logistic regression was used to generate odds ratios for covariates associated with development of IM. Kaplan-Meier analysis with the Log Rank test was used for unadjusted time-to-event analyses. P-value for statistical significance was set at < 0.05 with a two-sided test. RESULTS: Out of 195 patients, 108 (55.4%) had stage IIIA disease and 103 (52.8%) had adenocarcinoma histology. The median age and follow-up (in months) was 67 (IQR 60-74) and 21 (IQR 12-43), respectively. The dose of radiation was 60 Gy in 30 fractions for148 patients (75.9%). Of the 77 patients who received treatment since immunotherapy was available and standard at our cancer center, 45 (58.4%) received at least one cycle. During follow-up, 84 patients (43.1%) developed any metastasis, and 33 (16.9%) developed IM (either alone or with extracranial metastasis). 150 patients (76.9%) experienced a treatment delay (interval between diagnosis and treatment > 4 weeks). Factors associated with developing any metastasis included higher overall stage at diagnosis (p = 0.013) and higher prescribed dose (p = 0.022). Factors associated with developing IM included higher ratio of involved over sampled lymph nodes (p = 0.001) and receipt of pre-CRT systemic or radiotherapy for any reason (p = 0.034). On multivariate logistical regression, treatment delay (OR 3.9, p = 0.036) and overall stage at diagnosis (IIIA vs. IIIB/IIIC) (OR 2.8, p = 0.02) predicted development of IM. These findings were sustained on sensitivity analysis using different delay intervals. Median OS was not reached for the overall cohort, and was 43.1 months for patients with IM and 40.3 months in those with extracranial-only metastasis (p = 0.968). In patients with any metastasis, median OS was longer (p = 0.003) for those who experienced a treatment delay (48.4 months) compared to those that did not (12.2 months), likely due to expedited diagnosis and treatment in patients with a higher symptom burden secondary to more advanced disease. CONCLUSIONS: In patients with stage III NSCLC treated with definitive CRT, the risk of IM appears to increase with overall stage at diagnosis and, importantly, may be associated with experiencing a treatment delay (> 4 weeks). Metastatic disease of any kind remains the primary life-limiting prognostic factor in these patients with advanced lung cancer. In patients with metastatic disease, treatment delay was associated with better survival. Patients who experience a treatment delay and those initially diagnosed at a more advanced overall stage may warrant more frequent surveillance for early diagnosis and treatment of IM. Healthcare system stakeholders should strive to mitigate treatment delay in patients with locally NSCLC to reduce the risk of IM. Further research is needed to better understand factors associated with survival, treatment delay, and the development of IM after CRT in the immunotherapy era.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,084
Score d'incertitude au seuil0,823

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,173
Tête enseignante GPT0,434
Écart entre enseignants0,261 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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