Impact of enzalutamide on patient-reported fatigue in patients with prostate cancer: data from the pivotal clinical trials
Bibliographic record
Abstract
BACKGROUND: Fatigue is a multifactorial symptom commonly reported by patients with prostate cancer as a result of disease and treatment. This study assesses the impact enzalutamide has on patient-reported fatigue ("fatigue") by using patient-reported outcomes from four pivotal, placebo-controlled trials of enzalutamide (ARCHES (NCT02677896), PROSPER (NCT02003924), PREVAIL (NCT01212991), and AFFIRM (NCT00974311)). METHODS: Fatigue was assessed in the individual studies using the Functional Assessment of Cancer Therapy-Prostate item GP1 at baseline, weeks 13 or 17, and every 12 weeks until disease progression. Longitudinal changes were assessed using mean scores and mixed-model repeated measures. RESULTS: The fatigue rates at baseline were higher in patients with later-stage disease (metastatic and/or castration-resistant prostate cancer (CRPC)) and among patients who had already received prior treatment lines; rates ranged between 58% in PROSPER (nonmetastatic CRPC) and 86% in AFFIRM (post-docetaxel metastatic CRPC). Irrespective of disease state, initiation of enzalutamide or placebo resulted in an early increase of fatigue (by weeks 13 or 17), with fatigue levels stabilizing thereafter. At last assessment, ≥55% of patients reported fatigue improvement or stabilization in all trials compared to baseline. More patients reported fatigue worsening by ≥1 or ≥2 units with enzalutamide plus androgen deprivation therapy (ADT) than with placebo plus ADT in ARCHES, PROSPER, and PREVAIL, but the between-group difference was <10% in all trials. CONCLUSIONS: The levels of fatigue were greater in mCRPC and lower in earlier states of disease. In all trials, patients reported a small increase in fatigue for the first 13-17 weeks after starting enzalutamide or placebo, with slightly greater fatigue with enzalutamide in all studies except AFFIRM, but fatigue stabilized or improved thereafter. This suggests a role for clinical management of fatigue to help patients cope early in treatment.
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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 | 0.017 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".