Thromboprophylaxis for Patients with Newly Diagnosed Vs. Recurrent Cancers: A Post-Hoc Analysis of the Avert Trial
Bibliographic record
Abstract
Background: The risk of venous thromboembolism (VTE) is increased in cancer patients, which can result in significant increases in mortality, morbidity and healthcare expenditures. The recent AVERT trial (N Engl J Med 2019 Feb 21;380(8):711-719), showed that prophylactic apixaban lowered the rate of VTE when compared to placebo in cancer patients starting chemotherapy. However, the risk-benefit ratio of primary thromboprophylaxis in patients initiating chemotherapy for recurrent disease compared to those with newly diagnosed patients who are chemotherapy naïve is unknown. Methods: This is a post-hoc analysis of the AVERT trial. The AVERT trial assessed apixaban therapy vs. placebo for prophylaxis among patients with cancer who were intermediate-to-high risk for VTE (Khorana score ≥2; the Khorana score is ranged from 0 to 6 with higher scores reflecting an increased risk of VTE) and were initiating chemotherapy. It was a randomized, placebo-controlled, double-blind clinical trial. The primary efficacy outcome was VTE and the main safety outcomes were major bleeding episodes. Secondary outcome measures included clinically relevant non-major bleeding (CRNMB). The severity of major bleeding was stratified from category 1 to 4, with category 4 being the most severe type. We performed time-to-event analysis on the primary efficacy and main safety end-points in patients with recurrent and new diagnosed cancers. The hazard ratio (HR) for the outcomes were estimated using a Cox regression model controlling for age, gender, and center. Results: A total of 574 patients were randomized in the AVERT trial. 563 were included in the modified intention-to-treat analysis. 237 and 232 patients with newly diagnosed cancer were allocated to the apixaban and placebo groups, respectively. Similarly, 51 and 43 patients with recurrent cancer were allocated to the apixaban and placebo groups, respectively. Baseline demographics and clinical characteristics are depicted in Table 1A and Table 1B. In patients with newly diagnosed cancers, the use of apixaban was associated with a significantly lower risk of VTE (HR: 0.45; 95% CI: 0.27-0.76; p = 0.002) and a higher rate of major bleeding complications (HR: 2.10; 95% CI: 1.09-4.08; p = 0.028) but not of CRNMB (HR: 1.06; 95% CI: 0.61-1.82) (Table 2A). A majority of the major bleeding complications were of category 2. In patients with recurrent cancer, apixaban was associated with a significant lower rate of VTE (HR: 0.26; 95% CI: 0.13-0.53; p < 0.001) without an associated significant increased risk of major bleeding complication (HR: 1.82; 95% CI: 0.36-9.15; p = 0.466) but with a significant increase rate of CRNMB (HR: 2.78; 95% CI: 0.58-1.34; p = 0.006) (Table 2B). Major bleeding episodes were split evenly between severity category 1 and 2. Conclusion: The risk-benefit ratio of primary thromboprophylaxis with apixaban might differ between patients with recurrent or newly diagnosed cancers. Apixaban was associated with a lower rate of VTE compared to placebo in both groups. Patients with recurrent cancer initiating chemotherapy may potentially have a more favorable risk benefit profile, as shown through the HR and the prevalence of major bleeding episodes. However, more trials are required to confirm these findings to help tailor thromboprophylaxis in this patient population. (AVERT ClinicalTrials.gov number, NCT02048865.) Disclosures Wells: BMS/Pfizer: Honoraria, Research Funding; Bayer: Honoraria; Sanofi: Honoraria; Daiichi Sankyo: Honoraria. Carrier:Leo Pharma: Honoraria, Research Funding; BMS: Honoraria, Research Funding; Servier: Honoraria; Bayer: Honoraria; Pfizer: Honoraria, Research Funding. OffLabel Disclosure: Apixaban can be used as postoperative prophylaxis of DVT/PE and for treatment of DVT/PE. This study will show whether the prophylactic effects of apixaban will be more effective when used with patients with recurrent cancer or patients with newly diagnosed cancer.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.013 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".