Patient Preferences for Stopping Tyrosine Kinase Inhibitors in Chronic Myeloid Leukemia
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".