MétaCan
Menu
Retour à la cohorte
Enregistrement W2915763999 · doi:10.1182/blood-2018-99-118775

Infectious Complications in the Outpatient and Inpatient Autologous Stem Cell Transplantation Setting for Patients with Multiple Myeloma. Princess Margaret Cancer Center Experience

2018· article· en· W2915763999 sur OpenAlexaff
Anna S. Nikonova, Christina Zeglinski, Shahid Husain, Miranda So, Eshetu G. Atenafu, Donna Reece, Suzanne Trudel, Vishal Kukreti, Rodger E. Tiedemann, Anca Prica, Norman Franke, Jane Huynh, Leeping Tao, Christine I. Chen

Notice bibliographique

RevueBlood · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueNeutropenia and Cancer Infections
Établissements canadiensUniversity Health NetworkSinai Health SystemPrincess Margaret Cancer CentreUniversity of TorontoSt. Michael's Hospital
Organismes subventionnairesnon disponible
Mots-clésMedicineMultiple myelomaFebrile neutropeniaInternal medicineTransplantationAutologous stem-cell transplantationPopulationNeutropeniaCohortCancerRetrospective cohort studySurgeryChemotherapy

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Autologous stem cell transplant (ASCT) for multiple myeloma (MM) can be feasible and safe in the outpatient setting and has become standard of care at many centers. Limited literature, however, exists on the types of infectious complications, including specific pathogenic isolates and resistance patterns in the outpatient (OP) setting and whether these differ from the inpatient (IP) setting. This creates uncertainty and variation among local treatment guidelines on antibiotic prophylaxis and treatment of infections in the outpatient population. Methods: In this retrospective study, at total of 240 patients who underwent ASCT at our institution from 2015 to 2016 were reviewed. Study objectives included: 1) to describe the types of infections and pathogenic isolates in MM patients during the acute transplant period and 2) compare isolate results between patients undergoing OP vs IP ASCT. We also aimed to assess 30-day post-ASCT all-cause mortality, readmission rates, and incidence of multidrug resistant bacterial infections in each cohort. As per standard transplant protocol at our institution, all patients received ciprofloxacin and fluconazole prophylaxis and standardized initial therapy for febrile neutropenia with piperacillin-tazocin. Daily GCSF support was routinely used starting day +7 for IPs, and on demand only for OPs. Results: Patient, disease and transplant characteristics: Baseline demographics of both OP and IP cohorts are shown in Table 1 (total n=240; 109 OP, 131 IP). As expected, IPs had poorer performance status (KPS<90), more comorbidities (HCT-CI ≥3), more advanced stage MM, had worse pre-transplant renal function, and were more likely to receive Melphalan dose reductions. Median time to engraftment was similar between groups - 12 days for IP and 13 days for OP (range 9-25), with duration of neutropenia <0.5x10^9/L exceeding 7 days in 46% of the cohort. Median length of stay in hospital was 17 days (12-55) for the inpatients. In the OP cohort, 63.9% of patients required readmission to hospital, with median 3-day hospital stay. In total, only 4 (1.7%) patients required ICU admission. Infections in total cohort (OP and IP): Overall, 121 of 240 patients (50.4%) developed febrile neutropenia, with most common causes including: blood stream infection (BSI) (n=35, 29%), pneumonia (n=18, 14.8%) and respiratory virus infections (n=16, 13.2%). Opportunistic infections were uncommon (n=6, 2.5%) with 1 case of invasive aspergillosis and 5 cases of CMV infection. Of the 43 cases of BSI, 33 (76%) were identified as central line associated blood stream infections (CLABSI), 20 (46.5%) due to gram positive and 20 (46.5%) due to gram negative organisms. Multi-drug resistant gram negative organism isolates were observed in 22 patients (51%), including 5 cases of extended spectrum beta lactamase producing bacteria (ESBL; 11.6%), 9 cases of gram negative bacteria carrying inducible AmpC gene (SPICE; 20.1%), and 10 (23%) cases of quinolone resistant gram negative BSI. Comparison of IP vs OP infections: Although the OP cohort were less frail with fewer comorbidities than the IP cohort, they had more episodes of febrile neutropenia (64% vs 51%; p=0.042), worse mucositis (22.0% vs 10.8%, p= 0.021), and more BSI (24.7% vs 12.9% p=0.019). In the multivariable analysis, only OP status (OR 2.4, p=0.03) and baseline ANC<1.5 pre ASCT (OR 6.3, p=0.003) predicted for BSI occurrence. At 18 months, OS was 98.5% and PFS was 68% for all patients, with no difference between IP and OP (p=0.772). PFS was worse in patients with BSI (p=0.0031, HR 8.7), with gram positive infections in particular (p=0.0264, HR 4.9) Conclusions: In our autotransplant experience, blood stream and lung infections are common, with multi-drug resistance a concern. We were surprised to report that patients undergoing outpatient-based transplant had more BSI, presumably central line-related, and that this may impact disease outcomes (PFS). We hypothesize that outpatients may undergo additional line manipulation or inferior line hygiene, suggesting that enhanced patient/staff education on infection control measures should be a focus. In general, though, outpatient ASCT patients had excellent outcomes, with similar engraftment rates, short readmission rates, low ICU usage, as the entire cohort. Disclosures Tiedemann: Novartis: Consultancy; Celgene: Consultancy; Bristol-Myers Squibb: Consultancy; Janssen: Consultancy; Amgen: Consultancy; Takeda: Consultancy; Merck: Consultancy; Roche: Consultancy. Chen:Amgen: Honoraria.

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,008
Score d'incertitude au seuil0,296

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,012
Tête enseignante GPT0,262
Écart entre enseignants0,251 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2018
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueBloodMême sujetNeutropenia and Cancer InfectionsTravaux en français237 207