Editorial: Editor's challenge: Dr. Luciano Mutti - what is the true impact of ICIs on survival in the treatment of thoracic malignancies?
Notice bibliographique
Résumé
The possibility that the human immune system can act to prevent cancer was first proposed in 1909 by Ehrlich and is often described as immune-surveillance) (1). One of the evasion mechanisms utilized by cancer cells involves the expression a series of surface regulatory markers (called checkpoint molecules) that prevent the activation of immune system responses. This has led to the development of what are called immune checkpoint inhibitors (ICIs), which are now a mainstay therapy in the treatment of many cancers including thoracic malignancies (2). Despite the development of these agents, they are not completely effective and many patients either fail to respond to ICIs (3, 4), initially respond but subsequently relapse, developing ICI resistance (5), or develop immune-related adverse events (irAEs) (6).In this topic we asked the research community whether ICIs in their present form have a true impact on patient survival. A study by Ravi Salgia and colleagues examined the impact of irAEs on non-small cell lung cancer (NSCLC) patient survival, and explored if prior treatment with tyrosine receptor kinases (TKIs) played a role in patient responses, and found that indeed patients experiencing an irAE were found to have a significantly longer OS and PFS compared to patients who did not (7). It must be noted that this analysis is based off a single institution, and larger cross-institutional studies will be required to confirm this interesting finding. Reliable biomarkers for ICI therapy remain a core challenge for patient stratification (8), and a new candidate biomarker based on mutations in the tumor suppressor RB1 was described by Wang et al (9). In this study mutated RB1 was associated with poor responses to ICI outperforming both tumor mutational burden (TMB) and PD-L1 positivity. Again the study was limited to a single institution and will require further validation.Systematic reviews are helping to assess ICI efficacy and identify new options for more effective patient stratification or treatment. Mao and colleagues conducted a systematic review and meta-analysis on histological subtypes of NSCLC (Squamous versus non-Squamous) to see if these subtypes had any effect on efficacy or outcome (10). From an analysis of 40 clinical trials this study was able to conclude that both histologies benefited from ICI therapy (either as monotherapy or combinatorial therapy), and also demonstrated that under combinatorial therapy non-squamous patients derived more significant survival benefit. In a similar fashion, Molina and colleagues conducted a systematic review in NSCLC to assess clinicopathological and bio-molecular features that affected survival upon treatment with ICIs (11). From an analysis of 23 randomized controlled trials (RCTs) the authors identified wild-type EGFR, high PD-L1 expression, and high blood-based TMB (bTMB) as features associated with a significant OS benefit from ICI therapy, whereas unmutated EGFR, low PD-L1 expression, or low bTMB did not demonstrate any clear OS benefit. Subgroup analysis demonstrated that the observed OS benefit was achieved regardless of regardless of sex, age, ECOG PS, histology, smoking history, baseline brain metastasis, race, or region. These results effective confirm PD-L1 and high TMB as effective biomarkers for ICI therapy, and suggest that non-mutated EGFR be considered as part of the treatment algorithm for ICI therapy. Whilst PD-L1 positivity is normally required for ICI therapy in NSCLC, it is well established that a subset of patients with negative PD-L1 expression (PD-L1 < 1%) show objective responses to ICI (12, 13). Li et al conducted a network meta-analysis to assess whether such patients derive better benefit from chemotherapy combined with antiangiogenic versus chemotherapy combined with ICIs as no head-to-head clinical trials comparing the two exist (14). Their analysis suggests that for patients with advanced NSCLC with negative PD-L1 expression, combinations of chemotherapy plus ICI provide the best benefit. The field of immunotherapy is still young, and the data presented in this special topic suggests that whilst it remains increasingly clear that ICIs display clear survival benefit in thoracic malignancy, more research will be required to truly define their long-term impact on patient survival.
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 | 0,004 | 0,028 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,002 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,006 | 0,006 |
| Science ouverte | 0,005 | 0,001 |
| Intégrité de la recherche | 0,018 | 0,021 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 0,016 |
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 ».