S6-2: Patient-Reported Predictors of Early Treatment Discontinuation: NCIC JMA.27/E1Z03 Quality of Life Study of Postmenopausal Women with Primary Breast Cancer Randomized to Exemestane or Anastrozole.
Bibliographic record
Abstract
Abstract Background: Patient-reported outcomes (PRO) assess symptom burden and health-related quality of life (HRQL) more accurately than clinical report. We previously found that treatment-emergent adverse events (CTCAE V3.0) did not impact efficacy in the main NCIC MA.27 trial, although many women discontinued treatment early. The purpose of this substudy was to obtain PROs in MA.27/E1Z03 participants to evaluate treatment-related side effects and HRQL between exemestane and anastrozole and to identify predictors of treatment discontinuation. Methods: The Eastern Cooperative Oncology Group trial (E1Z03) assessed PROs in a sample of MA.27 patients (N=686; 99.3% participation rate). Participants completed the 56-item Functional Assessment of Cancer Therapy-Endocrine Symptoms (FACT-ES) pre-treatment and at months 3, 6, 12 and 24 to assess breast-cancer specific concerns, side effects of hormonal treatments and HRQL. We used 1) Wilcoxon rank sum test to compare treatment-related symptoms and HRQL between trial arms; 2) linear mixed effect models to test differences in changes of treatment-related symptoms and HRQL between trial arms; 3) linear regression to examine the effects of symptoms on HRQL and 4) adjusted Cox regression to assess predictors of treatment duration. Results: Participants included 371 women randomized to anastrozole and 315 randomized to exemestane. Demographic and disease characteristics were balanced between trial arms. Participants were a mean age of 65.6 yrs (SD=9.2), White (95.9%), ECOG PS of 0 (87.2%), stage T1 (75.5%) or T2 (22.7%), and stage N0 (73.9%) or N1 (16.3%). Prior treatments included partial mastectomy (65.7%), chemotherapy (27.8%) and radiotherapy (51.7%). Treatment-related symptoms measured by 23 items from the FACT-ES did not differ between treatment arms at months 3, 6, 12 and 24 and the timeline change of treatment-related symptoms was similar between treatment arms (p = ns). HRQL was significantly impacted by decreased libido, weight gain, feeling bloated, breast sensitivity, mood swings, irritability, join pain, nausea and bother by treatment side effects (p < 0.001). 248 participants were off-treatment by 4.1 yrs. A Cox model adjusted for other symptoms, demographic and disease characteristics indicated the hazard of discontinuing treatment early increased by 29% when the severity of being bothered by side effects at baseline increased by 1 point (HR=1.29, 95% CI:1.09−1.54). At baseline, patients with prior treatments or taking more medicines reported more bother by side effects (p < 0.001). Increased joint pain in the first 3 months after treatment was also associated with increased hazard of discontinuing treatment early (HR=1.13, 95% CI: 1.01−1.28). Conclusions: PRO assessment indicated comparable symptom burden and HRQL among postmenopausal women randomized to anastrozole or exemestane, with increasing symptom burden over time negatively affecting HRQL. Patients who 1) initiate an aromatase inhibitor (AI) with bother by side effects from prior treatment and concomitant medications and 2) experience increased joint pain during the first 3 months of AI therapy are at risk for early discontinuation of AI therapy. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr S6-2.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".