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Enregistrement W2530761803 · doi:10.1182/blood.v120.21.4274.4274

Patient Preferences for Stopping Tyrosine Kinase Inhibitors in Chronic Myeloid Leukemia

2012· article· en· W2530761803 sur OpenAlexaffabout
Rachel Kyle, Alejandro Lazo‐Langner, Anargyros Xenocostas, Ian Chin‐Yee, Kang Howson‐Jan, David Sanford, Cyrus C. Hsia

Notice bibliographique

RevueBlood · 2012
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Myeloid Leukemia Treatments
Établissements canadiensVictoria HospitalLondon Health Sciences CentreWestern University
Organismes subventionnairesnon disponible
Mots-clésNilotinibMedicineDasatinibImatinibImatinib mesylateInternal medicineOncologyMyeloid leukemiaClinical trialFamily medicine

Résumé

récupéré en direct d'OpenAlex

Abstract Abstract 4274 Introduction: After the introduction of tyrosine kinase inhibitors (TKIs), chronic myeloid leukemia (CML) became the first cancer with a medical treatment that affords patients a normal lifespan. First-line treatment includes one of the three approved TKIs with regular molecular monitoring. Several reports have described individuals stopping imatinib and remaining in complete molecular response (CMR). There are currently several ongoing randomized clinical trials evaluating the safety of stopping TKI treatment in patients with a sustained CMR. In 2010 the preliminary results from the STIM (STop IMatinib) trial (Mahon, Lancet Oncology), were published. Results showed that 38% of patients had a sustained CMR after 2 years off TKI treatment and the remaining 62% who relapsed responded to restarting their previous TKI treatment. As this research will potentially influence clinical practice in the near future, we aimed to explore patient reactions, preferences and risk acceptability of stopping TKI treatment. With that in mind we conducted an interview-assisted survey of CML patients seen at a single tertiary care centre. Methods: We included CML patients with cytogenetic and molecular Ph+ chromosome confirmation currently being treated with a TKI. Patients were approached during regular follow-up appointments. A survey was conducted through structured interviews using a standard form. Patients' preferences were explored through a case-based scenario using Visual Analog Scales ranging from 0 to 100% or 5-point Likert scales ranging from “absolutely stop” (1) to “absolutely not stop” (5). A trained interviewer asked the survey questions and was able to clarify questions that were unclear to the participant. Data was analyzed using proportions for dichotomous variables and medians and interquartile ranges for continuous variables. 95% confidence intervals for the proportions were calculated using the normal approximation interval. Results: Interviews were conducted between June and August 2012 at the London Regional Cancer Program (LRCP) in London, Ontario. 38 out of 40 (95%) CML patients approached completed the survey. Mean age of participants was 51 years old and 47% were male. 37% of participants had not finished high school and another 37% had completed college/university/trade school. Participants had a diagnosis of CML for an average of 50 months prior to enrollment. The majority (21/38 participants, 55%) were taking imatinib, with 11 (29%) on nilotinib and 6 (16%) on dasatinib. 71% (95% CI ± 14%) of the participants said that taking their medications daily was “simple and easy and they were able to remember 100% of the time.” 26% reported daily side effects while 24% reported never experiencing side effects from their TKI. 79% (95% CI ± 13%) of the participants said that they have never considered stopping the drug based on the side effects that they experience. 61% of participants responded that fear of the disease going out of control keeps them taking their TKI (95% CI ± 16%), whereas 34% responded that it is their doctor's strong recommendation that motivates them (95% CI ± 15%). When asked what risk of relapse after stopping the TKI they would be willing to accept the median response was a 25% relapse rate (interquartile range 20–50). When responding to the same question after informing the participant that all patients have responded to restarting TKIs the median response increased to a 35% relapse rate (interquartile range 20–60). When given a relapse rate of 20% and a likert scale ranging from “absolutely stop” to “absolutely not stop,” the median response was “likely stop” with the 25th and 75th interquartile ranges being “absolutely stop” and “likely not stop” respectively. When the published relapse rate of 60% was given, however, the median was “likely not stop” with the 25th interquartile range at “neutral to stopping” and 75thinterquartile range at “absolutely not stop.” Discussion: This data suggests that the majority of participants perceive little difficulty with taking their TKI regularly and have never considered stopping it. Two major determinants on participant's decisions are fear of the disease going out of control and their physician's influence. Further, with the published rate of relapse after stopping TKI treatment the majority of individuals would choose to continue taking their medications for CML. Disclosures: Lazo-Langner: LeoPharma: Honoraria; Pfizer: Honoraria. Hsia:Novartis: Participant in Advisory Board Other.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,007
Version: metacan-v3-hybrid-931329e0061cStatut 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 enseignants0,003
Score d'incertitude au seuil0,011

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,007
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 savante0,0010,000
Science ouverte0,0000,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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 Opus0,022
Tête enseignante GPT0,265
Écart entre enseignants0,243 · 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 source (Gemma direct ou Codex distillé), 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

Citations3
Publié2012
Routes d'admission2
Résumé présentoui

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