Driving Best Practices Throughout the Treatment Journey for Patients with NSCLC with Actionable Alterations: A Podcast Discussion
Notice bibliographique
Résumé
Non-small cell lung cancer (NSCLC) treatment has been revolutionized by the advent of targeted therapies for tumors harboring specific actionable alterations. Targeted agents are now approved for use in patients with advanced NSCLC with various drivers including ALK rearrangements, BRAF V600E mutations, EGFR mutations, ERBB2 mutations, KRAS G12C mutations, MET exon 14 skipping alterations, NTRK fusions, RET rearrangements, and ROS1 rearrangements. Importantly, the availability of these agents has raised the clinical question of how to optimally sequence their use alongside chemotherapy and/or immunotherapy strategies, which are indicated for broader populations. Key considerations include (i) evidence for better outcomes when first-line treatment is initiated following availability of molecular profiling data; (ii) the decreasing proportion of patients able to receive therapy in each successive treatment line; (iii) the efficacy of targeted agents demonstrated in either single-arm trials or head-to-head comparisons with chemotherapy and/or immunotherapy, as compared with evidence for poor or modest efficacy of immunotherapy in patients with tumors with actionable drivers; (iv) real-world data showing better outcomes of patients with tumors with actionable alterations who received targeted therapies compared with those who did not; (v) the generally favorable safety profile of targeted therapies, as well as the potential for increased toxicity when immunotherapy precedes certain targeted agents; and (vi) patient-centric factors including the greater ease of administration of oral targeted therapies over intravenous chemotherapy or immunotherapy strategies. In line with these considerations, guidelines typically recommend most targeted agents approved for first-line use as initial therapy over chemotherapy and/or immunotherapy. In this podcast, the authors discuss the current therapeutic landscape of NSCLC with actionable alterations and provide their perspectives on treatment algorithms, and how to optimally sequence therapies for patients with tumors harboring actionable alterations, using patient cases to illustrate key principles. Several targeted therapies are now available for the treatment of patients with advanced non-small cell lung cancer that has certain genetic alterations. These medicines specifically target the genetic alterations in cancer cells that increase their ability to grow and spread. Targeted therapies are approved for patients whose tumors have changes in genes such as ALK, BRAF, EGFR, and others. In this podcast, three oncologists engage in a discussion on the optimal use of targeted therapies alongside other treatments like chemotherapy and immunotherapy. Their discussion highlights the importance of analyzing the tumor’s genetic makeup before treatment to determine if targeted therapy is an option. Cancer guidelines typically recommend using targeted therapies as the first treatment option in patients with non-small cell lung cancer with specific genetic alterations, if approved for this use. Since many patients will receive only one therapy, informed selection of the initial treatment is especially important. The authors also consider the data from clinical trials showing the effectiveness and manageable side-effect profile of targeted therapies. In contrast, there is evidence that immunotherapies may be less effective in patients whose tumors have certain genetic alterations. Real-world data support the importance of using targeted therapies in patients who are eligible. In addition, targeted therapies are often taken as oral tablets, which may be preferred by patients to intravenous treatment with chemotherapy or immunotherapy. Finally, the authors use example patient cases to show important factors to consider when choosing between targeted therapies and other types of treatment.
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 | 0,012 | 0,033 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,009 | 0,014 |
| Science ouverte | 0,004 | 0,005 |
| Intégrité de la recherche | 0,015 | 0,032 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,022 | 0,007 |
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 ».