Treatment Response and Predictors of Response Among Patients with Chronic Myeloid Leukemia: A Retrospective Medical Record Review
Notice bibliographique
Résumé
Abstract Abstract 4450 Objective: To assess treatment responses and predictors of response among patients with chronic myeloid leukemia (CML) in Australia, Canada, and South Korea. Methods: Oncologists and hematologists abstracted data from medical records of patients diagnosed with CML between 1/1/2005 and 9/30/2010 via a web-based data collection tool. Patients included were at least 18 years old; had chronic phase, Philadelphia chromosome and/or BCR-ABL positive CML at the time of diagnosis; received imatinib as first-line therapy; and were not enrolled in a clinical trial between the date of CML diagnosis and the end of available chart data. A subset of patients received second- and/or third-line therapy with dasatinib or nilotinib. We assessed rates of complete hematological response (CHR), complete cytogenetic response (CCyR), and complete or major molecular response (MMR) at 3, 6, 12, and 18 months. Multivariable logistic regression models were fitted to assess predictors of response (CHR, CCyR, and MMR) to 1stline therapy with imatinib. The independent and control variables incorporated into the models were age, gender, employment status, Charlson comorbidity index (CCI) score, time to initiation of therapy, imatinib dose at treatment initiation, and presence of treatment-related side effects. Follow-up was truncated if the patient had a change in dose. Only those still in chronic phase at the time of imatinib initiation who had non-missing data on the variables of interest (n=387) were included in the regression analyses. Results: Ninety-three physicians (31 in Australia, 28 in Canada, and 34 in S. Korea) provided data on 609 patients (203 in Australia, 199 in Canada, and 207 in S. Korea). The average patient age was 57 years, and 59% of the patients were male. At 3 months after imatinib initiation, CHR was attained by 67%, 83%, and 86% of patients in Australia, S. Korea, and Canada respectively. Over 85% of all patients maintained CHR at 6, 12, and 18 months. Cytogenetics were not commonly evaluated at 3 and 6 months in the three countries studied. At month 12, 48% of patients achieved CCyR (42% in Australia and Canada, 60% in S. Korea), and a similar proportion of patients had CCyR at 18 months. Overall, MMR was achieved by 59% of patients at month 12, increasing to 70% at month 18. Multivariable regressions showed that receipt of previous treatment (odds ratio [OR]=1.88, 95% CI=1.08–3.25; reference [ref]: no previous treatment), and low Sokal score (OR=2.04, 95% CI=1.13–3.69; ref: intermediate) were associated with a greater likelihood of CHR at 3 months while initial dose > 400mg (OR=0.37 95% CI=0.13–1.03; ref: initial dose <= 400 mg), CCI score of 2 or higher (OR=0.23, 95% CI=0.11–0.51; ref: CCI score 0), and presence of treatment-related side effects (OR=0.41, 95% CI=0.18–0.95; ref: no side effects) predicted a lower likelihood of CHR at 3 months. High Sokal score (OR=0.39, 95% CI=0.18–0.87; ref: intermediate) was found to be associated with a lower likelihood of achieving CCyR at 12 months while the presence of treatment-related side effects (OR=1.86, 95% CI=1.04 – 3.33; ref: no side effects) was found to be associated with a higher probability of achieving CCyR at 12 months. Low Sokal score (OR=1.85, 95% CI=1.10–3.10; ref: intermediate) was the only significant prognostic indicator that was associated with a greater likelihood of MMR at 18 months while age >65 years was the only significant adverse prognostic indicator of MMR by 18 months (OR=0.42, 95% CI=0.20–0.86; ref: age 45–65). Conclusions: The favorable prognostic indicators of response among patients with chronic phase CML included previous treatment, low Sokal score, lower initial imatinib dose (< 400 mg), and no comorbidities. Better understanding of predictors of response may enable physicians to better tailor therapy to optimize patient outcomes. Disclosures: Whiteley: Pfizer Inc: Employment, Equity Ownership. Mitra:Pfizer Inc: Research Funding. Iyer:Pfizer Inc: Employment. Candrilli:Pfizer Inc: Research Funding. Kaye:Pfizer Inc: Research Funding.
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 | 0,002 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».