Clinical pathways implementation in a community-based oncology practice: Real-world outcomes in patients with non-small cell lung cancer segmented by disease stage at diagnosis.
Notice bibliographique
Résumé
e18719 Background: Clinical pathways have been introduced as tools to optimize cancer care delivery, but evidence of their value in the real world is limited. This retrospective study was performed to assess treatment patterns and clinical outcomes in patients with non-small cell lung cancer (NSCLC) before and after pathway implementation at Tennessee Oncology (TO). Methods: Chart data were abstracted for patients (≥18 years) diagnosed with Stage I-IV NSCLC who initiated first-line (1L) systemic treatment at a TO clinic and had follow-up for ³6 months or until death. Patients were divided into two cohorts: pre-pathways (treatment initiation 2014–2015) and post-pathways (treatment initiation 2016–2018). Patient characteristics, treatment patterns, and outcomes were described and compared across cohorts. An exploratory study endpoint was the evaluation of outcomes based on disease stage at diagnosis. Results: Among 501 patients (251 pre-pathways and 250 post-pathways), most had advanced or metastatic NSCLC at diagnosis (Stage III: 40%; Stage IV: 42%). Chemotherapy comprised almost all 1L systemic therapy used pre-pathways (Stage I/II: 100%; Stage III: 96%; Stage IV: 83%). Post-pathways, chemotherapy remained the most common 1L therapy in patients with Stage I/II (89%) and Stage III (72%) disease, but among patients with Stage IV disease, use of chemotherapy decreased (47%) and immuno-oncology (IO) therapy alone or in combination became common (45%). Median duration of 1L therapy was longer post-pathways in patients with Stage III (2.1 months vs 1.4 months pre-pathways; P < 0.01) and Stage IV disease (3.3 months vs 2.3 months pre-pathways; P < 0.01) but did not differ among Stage I/II patients. Median progression-free survival was significantly longer post-pathways in patients with Stage IV disease (7.0 months vs 4.2 months pre-pathways; P < 0.05), but not in other disease-stage subgroups. Median overall survival increased non-significantly post-pathways for all disease stage subgroups (Stage I/II: 26 months vs 20 months pre-pathways; Stage III: 26 months vs 20 months; Stage IV: 10 months vs 9 months). For each disease stage, rates of severe adverse events were similar between cohorts. Conclusions: While outcomes for patients diagnosed with Stage III/IV NSCLC were generally improved following the implementation of clinical pathways, this change coincided with a dramatic shift in available treatment options. Improvements post-pathways were mainly observed in patients diagnosed with advanced disease. Thus, differences in outcomes between pre-pathways and post-pathways cohorts in our study are more likely attributable to other evolving practices in cancer care, particularly the availability of newer, more effective treatments such as IO therapy as part of standard practice, than implementation of the clinical pathways.
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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 | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».