Incidence and characteristics of infections in patients with multiple myeloma treated with BCMA bispecific antibodies in British Columbia
Notice bibliographique
Résumé
Abstract Background: Bispecific T-cell engagers (bispecifics) targeting BCMA have improved outcomes in relapsed/refractory multiple myeloma (RRMM) but carry substantial infectious risk. Real-world data on infection incidence, microbiology, prophylaxis, and risk factors remain limited. Methods: We retrospectively analyzed 60 RRMM patients treated with compassionate access single-agent anti-BCMA bispecifics (teclistamab 95%, elranatamab 5%) in British Columbia (May 2023-June 2025), as per standard indications. Baseline characteristics, prophylaxis, and infection outcomes were collected. Infections were graded per CTCAE v5. Univariable logistic regression assessed infection risk factors. To address lead-time bias from early death in non-responders, subgroup analyses were performed in responders (≥VGPR) (n=35). Results: Median age was 67 years (range 41–84), 47% were female, and median time from diagnosis was 4.8 years (range 0.7-15.1). Patients had a median of 4 prior lines of therapy (range 3–10); all were triple-class refractory and 43% were also penta-refractory. Pneumocystis prophylaxis with trimethoprim/sulfamethoxazole was used in 95% of patients, prophylactic anti-microbial in the first 3 months in 80% (doxycycline 54%, levofloxacin 44%, moxifloxacin 2%); valacyclovir in 100%; G-CSF in 48%. In total, 58% received intravenous immunoglobulin (IVIG), 35% of which initiated prior to first infection, either prior to bispecific (15%) or as primary prophylaxis (20%). Median time to start IVIG primary prophylaxis was 3 months (range: 0.1-10.6). During a median follow-up of 11.5 months (range 2.5–26.7), 45% experienced at least one infection. Median time to first infection was 3.3 months (range 0.1-16.2) and 48% of first infections occurred within 100 days. There was a total of 59 infectious events, including upper respiratory tract infections (22%), pneumonia (13%), respiratory syncytial virus (10%), COVID-19 (7%), cellulitis (7%), cytomegalovirus (3%), sinusitis (3%), influenza (3%), dental (3%), febrile neutropenia without a primary source of infection (3%), peritonitis (1.7%), pneumocystis jirovecii (1.7%, in a patient without prophylaxis), and urinary tract infection (1.7%). There were no cases of herpes virus infections, including shingles. Grade ≥3 infections occurred in 17%. Therapy interruption due to infection occurred in 28% with a median next cycle delay of 2 weeks (IQR 1-12). There were 2 infection-related deaths, both in the responder group: one at 1.7 month from complications of COVID-19, including bacterial pneumonia, pulmonary embolism and kidney failure, and one at 5 months from sepsis secondary to febrile neutropenia of unknown origin. Among patients on antibiotic prophylaxis (n=48), 12.5% developed bacterial infections versus 25% without prophylaxis (n=12) (p=0.3). In responders, median time on treatment was 7.9 months (range 2.3-26.1). At least one infection occurred in 66% of responders, which increased to 70% in patients remaining on treatment beyond 100 days (n=30). First infection occurred within the first 100 days in 35%, while most events (81%) were observed thereafter. Initiation of IVIG (before bispecific or as primary prophylaxis) was associated with reduced infection risk (OR 0.11, 95% CI 0.02–0.51, p=0.004). IgG levels below 4g/L were associated with increased infections (OR 5.25, 95% CI 1.22–26.5, p=0.03). There was a non-statistically significant benefit from prophylactic antibiotics (OR 0.48, 95% CI 0.06–2.57, p=0.41). Other variables such as utilization of tocilizumab and corticosteroids for the treatment of cytokine release syndrome or immune effector cell-associated neurotoxicity syndrome, age, sex, line of therapy and white blood cell count at time of therapy initiation were not associated with infection risk. Conclusion: Infections were frequent in RRMM patients receiving anti-BCMA bispecific therapy, particularly respiratory infections. Early prophylactic antimicrobials may reduce bacterial infections but rates remain high beyond 100 days when these are stopped. Early immunoglobulin replacement may further mitigate infection risk across all potential pathogen classes. Valacyclovir effectively prevented herpes virus infections, including shingles. These findings highlight the need for optimized prophylaxis and vigilant monitoring with a low threshold for treatment in this population at high risk for infection.
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 | 0,000 | 0,001 |
| 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 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| 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 ».