COMPARISON OF SINGLE, TANDEM, AND SECOND AUTOLOGOUS STEM CELL TRANSPLANTATION IN PATIENTS WITH MULTIPLE MYELOMA AT SASKATCHEWAN CANCER AGENCY: A RETROSPECTIVE POPULATION-BASED STUDY
Notice bibliographique
Résumé
Multiple myeloma (MM) is a malignant plasma cell disorder that ranks as the second most common hematological malignancy globally. It primarily affects older adults and poses a significant burden on both patients and healthcare systems due to its chronic relapsing nature and associated complications. For transplant-eligible patients, autologous stem cell transplantation (ASCT) is considered the standard of care and is typically performed following induction chemotherapy. While single ASCT has long been the conventional approach, emerging evidence suggests potential advantages of alternative transplant strategies, including tandem ASCT (two planned sequential transplants within 3-6 months) as an upfront therapy and second ASCT as a salvage therapy in relapsed disease. However, the comparative outcome and safety of these strategies, particularly in real-world settings, require additional scrutiny. This retrospective chart review study was conducted to compare the outcomes of single, tandem, and second ASCT among MM patients treated at Saskatchewan Cancer Agency (SCA) between 2010 and 2025. Data were collected from SCA database using REDCap and were analyzed using SPSS (version 27). Patients’ demographics, disease characteristics, baseline laboratory findings, and transplant details were assessed. The main aims of the study were overall survival, progression-free survival, and transplant-related mortality (TRM) in different transplant groups. The study also explored high-risk myeloma subgroup outcomes, as defined by International Myeloma Working Group (IMWG). A total of 211 patients were included and followed up for the mean period of 5.4 ± 3.3 years (range: 1–14 years). Patients were categorized into single ASCT (n = 166), tandem ASCT (n = 19), and second ASCT (n = 26) groups. Mean age of patients at diagnosis was 58.3 ± 7.7 years. Common comorbidities comprised diabetes (14.2%), chronic pulmonary disease (11.4%), and chronic kidney disease (10.9%). High-risk myeloma was present in 29.9% of the patients. At diagnosis, 71.1% had bone lesions, 58.6% had anemia, 26.1% had hypercalcemia, and 38.6% had renal insufficiency. The mean overall survival for single ASCT was 8.2 ± 0.4 years, for tandem ASCT was 7.7 ± 1.3 years, and for second ASCT was 11.0 ± 0.7 years (p = 0.117). Among high-risk myeloma patients (n = 63), the mean overall survival for single ASCT was 5.5 ± 0.7 years, for tandem ASCT was 3.5 ± 0.3 years, and for second ASCT was 7.9 ± 0.8 years (p = 0.057). The mean progression-free survival after first-line ASCT for single ASCT was 5.8 ± 0.4 years and for tandem ASCT 5.2 ± 1.0 years (p = 0.780). Among high-risk myeloma patients, the mean progression-free survival for single ASCT was 3.6 ± 0.5, and for tandem ASCT was 3.1 ± 0.4 years (p = 0.472). Upon progression following single ASCT, patients who received a second salvage ASCT had markedly longer progression-free survival compared to those who received non-transplant salvage treatments (3.4 ± 0.6 vs. 1.8 ± 0.3 years, respectively; p = 0.009). This advantage was also observed among the high-risk myeloma subgroup (3.2 ± 1.1 vs. 0.8 ± 0.2 years, respectively; p = 0.012). Only one TRM occurred after a second ASCT, which was 1.25% of total deaths (n = 80). In conclusion, this study provides real-world, population-based evidence comparing outcomes of single, tandem, and second ASCT in patients with MM, offering valuable insights for optimizing transplant strategies. While survival outcomes were similar between upfront single and tandem ASCT, patients who underwent a second ASCT after relapse experienced significantly longer progression-free survival compared to those who proceeded with non-transplant salvage treatments. Similarly, among high-risk myeloma patients, a second ASCT was associated with markedly improved progression-free survival. Overall, these results support the role of second ASCT as an effective and safe salvage approach, demonstrating favourable outcomes with minimal TRM rate.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».