Consensus on cytokine release syndrome (CRS) monitoring practices: A Delphi approach
Notice bibliographique
Résumé
Abstract Background Cytokine release syndrome (CRS) is a well-known and potentially fatal side effect of T cell redirecting therapy including therapies with chimeric antigen receptor T-cell (CAR-T) therapy and bispecific T-cell engagers (TCE) (Kanate, 2023 & Kanate, 2020). Current consensus grading and management guidelines for CRS stipulate that patients need to be monitored for at least seven days and up to four weeks after CAR-T or TCE infusion (Lee, 2019; NCCN, 2025). As more CRS incidence data is becoming available, monitoring is shifting from hospital to the outpatient or even home-based setting. Digital remote patient monitoring (RPM) strategies can support this important safety monitoring while enhancing patient convenience and reducing clinic resource utilization. The objective of this research was to establish consensus on type of digital data needed for CRS monitoring using RPM in post-discharged patients receiving CAR-T/TCE. Methods A modified Delphi method for consensus was used. We convened a steering committee of six medical experts in hematology and oncology which comprised physician investigators, a nurse leader, and industry trialists. Consensus statements were informed by various data sources: our steering committee, a review of clinical guidelines, protocols, and treatment management guidelines, and other digital technology currently available for patient-self capture of symptoms and physiological biomarkers. A total of 57 statements, reflecting current monitoring practices, perceived benefits of remote monitoring, and signs and symptoms commonly associated with onset of CRS, were developed and tested in the first round of the Delphi survey. Altogether, 203 health care professionals with experience in CAR-T and T-cell treatment, across six countries (US = 100, UK = 20, Spain =20, Sweden=20, Australia = 20 & France = 20) were surveyed. Statements that did not reach a pre-set 75% consensus were updated and retested in the second and final round. Results were analyzed by country, occupation, and years of experience in cell therapy treatments. Results A total of 203 respondents answered our survey, of which 56.2% were oncologists/hematologists, 38.4% were oncology nurses, and 5.5% were physician assistants. In the first round, 43 out of 57 statements reached consensus with 19 statements achieving >90% agreement. More than 90% of our respondents agreed that there is a benefit in remote monitoring to improve patient experience. More than 75% also agreed that heart rate/pulse rate, oxygen saturation (SpO2), and temperature were important markers to monitor (90%). Fatigue (75%), vomiting (81%), light headedness/dizziness (84%), myalgias (84%), headache (85%), chills (91%), and dyspnea (93%) were suggested as relevant to monitoring in patients at risk of CRS. The critical post-infusion monitoring period was identified as 36-48 hours post TCE dosing (85%) and 72 to 96 hours in CAR-T (85%). There was also an agreement that remote monitoring can be discontinued after two weeks post TCE infusion (77%) and four weeks post CAR-T infusion (81%). Thresholds for each vital sign and the frequency of monitoring post discharge from hospital required a second round. Further analysis of results showed that there were geographical differences in CRS monitoring practices. Conclusion The results of this study demonstrate a clear consensus on the value and benefits of RPM in monitoring for CRS, the critical window for monitoring in TCE and CAR-T, the appropriate monitoring duration post TCE infusion and CAR-T infusion, and the key symptoms and vital signs to monitor. However, disagreement remains regarding the optimal frequency of monitoring and the specific vital sign thresholds that should trigger concern for CRS. Future research should aim to address these gaps in order to contribute to the development of an effective RPM system tailored for CRS management.
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 | 0,231 | 0,161 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,007 | 0,004 |
| Études des sciences et des technologies | 0,006 | 0,006 |
| Communication savante | 0,005 | 0,006 |
| Science ouverte | 0,004 | 0,019 |
| Intégrité de la recherche | 0,004 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».