Patterns of Venous Thromboembolism Prophylaxis during Inpatient Treatment of Acute Leukemia: Results of a North American Web-Based Survey
Bibliographic record
Abstract
Abstract On behalf of the ECOG-ACRIN Cancer Research Group Background: Venous thromboembolism (VTE) occurs in 2-12% of patients with acute leukemia (AL) despite disease and therapy-associated thrombocytopenia, and can be associated with significant morbidity and mortality. Due to limited high-quality studies, there are no evidence-based guidelines for VTE prophylaxis in this patient population. Based on our experience and the lack of consensus guidelines, we hypothesized that there would be a wide range in provider practice regarding methods of VTE prevention in patients with AL. To determine the current individual practices in North America, we devised a web-based survey of VTE prophylaxis practice among clinicians caring for patients with AL. Methods: An anonymous 19 question web-based survey, approved by the Johns Hopkins Institutional Review Board, was distributed by email to members of the ECOG-ACRIN Cancer Research Group on 10/22/14. Four reminders were sent at two-week intervals with the survey closing on 12/8/14. Results: Of the total 215 respondents, 64 were excluded for the following reasons: 52 did not directly manage medical care of AL patients, 3 referred AL patients to other centers, 5 left blank responses to all questions regarding VTE prophylaxis, 1 was a duplicate entry, and 3 described their position as support or office staff. One hundred fifty-one responses were eligible for analysis, with a response rate of 20.9% among physicians who treated leukemias. One hundred forty-seven were from the United States and 4 from Canada, representing 88 different institutions and 37 states or provinces. Overall, 47% and 45% of providers reported using pharmacologic VTE prophylaxis during induction and consolidation phases, respectively. Among the providers using pharmacologic prophylaxis, 60% designated 50,000/μL as the platelet count threshold below which they would hold prophylaxis and 26% used a platelet count of 30,000/μL. Fewer providers chose a platelet count of 20,000/μL (4%), 75,000/μL (4%), and 100,000/μL (2%). Lastly, 2% held prophylactic anticoagulation only in the setting of an active bleed and 2% reported variable thresholds. Approximately 15% of providers did not utilize any VTE prophylaxis while 36% used mechanical methods and ambulation. Among providers who did not recommend pharmacologic prophylaxis, the most commonly cited reasons were the perceived high risk of bleeding (51%), absence of data supporting use (38%), and perceived low risk of VTE (11%). Conclusions: These results demonstrate wide variation in clinician practice regarding VTE prevention in hospitalized AL patients during induction and consolidation therapy. Our findings emphasize the need to develop standardized, evidence-based guidelines in this at-risk population. VTE: venous thromboembolism, AL: acute leukemia, SC: subcutaneous, TED: thromboembolic deterrant stockings, SCD: sequential compression device Figure 1. Practice patterns of VTE prophylaxis for AL patients during induction and consolidation therapies Figure 1. Practice patterns of VTE prophylaxis for AL patients during induction and consolidation therapies Disclosures Barbarotta: Celgene, BMS, Novartis: Speakers Bureau. Prebet:CELGENE: Research Funding. Gore:Celgene: Consultancy, Honoraria, Research Funding.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".