Ten-Year Overall Survival Analysis of Current Treatments of Relapsed or Refractory Multiple Myeloma in Canada.
Notice bibliographique
Résumé
Abstract Multiple myeloma (MM) is an incurable disease with poor survival outcomes. Recent trials have suggested improved overall survival with newer agents like bortezomib (VELCADE). In the process of developing a life-time cost-effectiveness analysis of therapies for relapsed or refractory MM, we noted the lack of long-term survival data. Objective: We sought to extrapolate 1 to 3 year overall survival data to 10 years (most patients die by then) in order to estimate the number of life years expected with several MM therapies. The therapies included were bortezomib, high dose dex (HDD), thalidomide regimens and standard care. Standard care was a basket of treatments weighted by frequency of use reported in a Canadian survey of physicians treating MM patients. It included HDD, thalidomide regimens, MP, VAD, cyclophosphamide, bortezomib, and repeat stem cell transplant. Method: The APEX trial results were used to inform the 3 year clinical benefits of bortezomib and HDD for relapsed MM (Richardson, 2005). Three-year survival for bortezomib was available from the APEX study. However due to positive interim results HDD patients were allowed to switch to bortezomib, thus limiting the HDD data available to one year. One to three year survival with HDD, thalidomide and standard care therapies were estimated from published trials and observational studies. The natural history of relapsed MM patients from Kumar (2004) was used to extrapolate survival to 10 years. Kumar studied the clinical course of 578 relapsed MM patients at the Mayo clinic from 1985 to 1998. From this study, the conditional survival, S(t|t-1) was calculated as the ratio of survival at the end of year (S(t)) to the survival at the end of the year before (S(t-1)). We assumed the rate of death in years 4 to 5, 5 to 6, etc. was the same for all therapies. Results: Figure 1 illustrates the estimated 10 year overall survival by therapy. From these survival curves a method of estimating the area-under-the curve is used to obtain the average life-years for patients on each therapy. Using bortezomib as an example, at year one 80 of 100 patients would be alive - resulting in 80 life years. At year two, 57 of the patients would be alive. Thus after two years, we accumulate 138 (80+58) years of life. Continuing to 10 years, we accumulate a total of 284 life years, or 2.84 years per patient on bortezomib. Using the same method for the other treatments, patients would live on average 1.81 years with HDD, 2.39 years with thalidomide regimens and 2.25 years with standard care. Bortezomib provides the largest mean overall survival over a 10-year time horizon. In fact, bortezomib can provide up to 1.03 years of added life compared to HDD. Conclusion: This is a conservative estimate of the overall survival advantage of bortezomib. It was assumed the mortality rate in years 4 to 5, 5 to 6, etc. was the same for all therapies, thus not giving bortezomib any clinical advantage from years 4 to 10. Long-term extrapolated analyses are needed in order to capture the full benefit of therapies for which only short-term trial data is available. 10-Year Survival By Therapy 10-Year Survival By Therapy
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 | 0,001 | 0,004 |
| 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 ».