Efficacy and safety of apalutamide in metastatic castration sensitive prostate cancer patients with a prior history of cardiovascular or metabolic risk factors: A post-hoc analysis of the TITAN study.
Bibliographic record
Abstract
165 Background: Patients with CV issues, such as MI, symptomatic congestive heart failure, or thromboembolic events occurring ≤6 months of randomization were excluded from the TITAN trial. However, patients with events occurring > 6 months prior or non-excluded CV conditions like IHD without MI were enrolled. Considering the demographics of prostate cancer and given prolonged ADT use may worsen existing co-morbid conditions, we conducted a post-hoc analysis to assess the efficacy and safety of apalutamide +ADT (APA) vs placebo+ADT(PBO) in patients with ≥ 1 risk factor or a history of CV or metabolic risk factors. Methods: CV and metabolic risk factors were categorized using MeDRA terminology and included CV ischemia, CV failure, CV arrhythmia, diabetes, hyperlipidemia, HT and obesity. Use of associated concomitant medications (con meds) were identified at study entry. Data from the final analysis after 44 months of median follow up were analysed for the co-primary endpoints of rPFS and OS, along with PSA90 or PSA<0.2ng/ml and TEAEs in patients with or without CV risk factors, and with con meds for these conditions. Results: In TITAN, 72% (378/524) and 69% (364/527) patients in the APA and PBO arms had a history of CV or metabolic risk factors at baseline; 68% (358/524) and 66% (347/527) were receiving con meds for these conditions. Individual risk factors were evenly matched between arms. All efficacy endpoints rPFS, OS, PSA90 and PSA<0.2ng/ml were superior in the APA group vs PBO group irrespective of CV/metabolic Risk and with con meds . Incidence of TEAEs were similar between subjects with and without CV & metabolic risk and with concomitant medications at baseline (Table). Conclusions: A large majority of patients enrolled in TITAN reflected an elderly population with a considerable CV risk profile. APA resulted in a significant improvement in both rPFS and OS and a favourable safety profile regardless of prior CV and metabolic baseline risk or with con meds at baseline for these conditions. Clinical trial information: NCT02489318 . With CV/metabolic risk factors at baseline Without CV/metabolic risk factors at baseline With CV/metabolic risk and concomitant medications at baseline APA+ADT ADT+Placebo APA+ADT ADT+Placebo APA+ADT ADT+Placebo Subgroup prevalence n(%) 378 (72.0%) 364 (69.1%) 147 (28.0%) 163 (30.9%) 358 (68.2%) 347 (65.8%) rPFS [HR (95% CI) p-value] 0.49 (0.38, 0.63) <0.0001 0.48 (0.33, 0.7) 0.0001 0.47 (0.36, 0.62) <0.0001 OS [HR (95% CI) p-value] 0.63 (0.5, 0.8) 0.0001 0.71 (0.49, 1.02) 0.0604 0.61 (0.48, 0.78) <0.0001 PSA90 or PSA<0.2ng/ml 326 (86.2%) 157 (43.1%) 121 (82.3%) 71 (43.6%) 307 (85.8%) 146 (42.1%) TEAE (all grades) 368 (97.4%) 353 (97.0%) 142 (97.3%) 157 (96.3%) 350 (97.8%) 337 (97.1%) Gr 3/4 TEAE 183 (48.4%) 165 (45.3%) 76 (52.1%) 55 (33.7%) 177 (49.4%) 161 (46.4%)
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".