Molecular testing and patterns of treatment in patients with NSCLC: An IASLC analysis of ASCO CancerLinQ Discovery Data.
Notice bibliographique
Résumé
9128 Background: Precision medicine has resulted in improved outcomes for non-small cell lung cancer (NSCLC); while molecular testing is considered critical for guiding treatment decisions for advanced stage NSCLC, adoption of testing in routine practice is variable. We analyzed the factors contributing to molecular testing and treatment patterns in patients with lung cancer. Methods: The ASCO CancerLinQ Discovery dataset was queried to identify patients diagnosed with lung cancer between the years 2010-2018. Data on demographics, tumor stage, histology and treatments were extracted, and receipt of molecular testing was investigated as the primary outcome. Univariate association of each clinicopathological variable with molecular testing outcome was performed using chi-square test for categorical variables and ANOVA test for numerical variables. A multivariable logistic regression analysis with backward selection at an alpha of 0.05 was reported. All analyses were conducted using SAS 9.4. Results: A total of 37,925 NSCLC patients with stage IV disease were analyzed. Patient characteristics: median age 65 years, 51% male, 68% white, 33.5% adenocarcinoma. Approximately 22% of all NSCLC patients had molecular testing results. In adenocarcinoma patients, 49% had molecular testing results available. In the stage IV group, 47% were treated with chemotherapy, 16% with immunotherapy and 3% with targeted therapy. On multivariable analysis, females were more likely to have molecular testing compared to males [(OR: 1.29 (1.22-1.37); p < 0.001]. Compared to White patients, Black patients were less likely to have molecular testing [OR: 0.89 (0.81-0.97); p = 0.009] and Asians were more likely to undergo testing [OR: 2.22 (1.79-2.75); p < 0.001]. Hispanic patients were more likely to undergo molecular testing compared to non-Hispanics [OR:1.24 (1.02-1.52); p = 0.03]. Additionally, treatment with immunotherapy [OR: 1.86 (1.72-2.01); p < 0.001] and targeted therapy [OR: 2.29 (2.00-2.64); p < 0.001] were associated with significantly higher likelihood of having molecular testing. These results were also confirmed on a subgroup analysis of adenocarcinoma patients. Conclusions: In this analysis of a US-based real-world dataset of stage IV NSCLC patients, White race and female sex are associated with higher likelihood of having molecular test performed. The percentage of patients undergoing testing remains sub-optimal.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».