Updates on the Risk of Dalteparin Thromboprophylaxis Failure in Hospitalized Acutely Ill Medical Patients with Cancer (ARTIC STUDY)
Bibliographic record
Abstract
Abstract Background Hospitalization is a significant risk factor for venous thromboembolism (VTE) with 25% of all VTE occurring in this setting. In patients with cancer this risk may be higher due to the inherent procoagulant state malignancy-induced, -cancer therapy and its complications. Current oncology guidelines suggest that hospitalized medical patients receive venous thromboprophylaxis with unfractionated heparin or low molecular weight heparin if their hospital stay is longer than 3 days. We sought to evaluate if patients with cancer hospitalized for management of an acute medical illness are at higher risk for failing standard anticoagulation prophylaxis with dalteparin compared to historical data. Methods This is a single-centre retrospective cohort study (London, Canada). We included adult patients; with any type of active cancer admitted for at least 3 days for treatment of an acute medical reason, who received prophylaxis with dalteparin during hospital stay. Acute medical illness was: failure to thrive; fever; need for cancer treatment as an inpatient; pain control; acute respiratory illness. The main study outcome was failure of VTE prophylaxis defined as symptomatic and objectively diagnosed pulmonary embolism (PE) or deep venous thrombosis (DVT) within 3 months of the most recent hospital discharge. Results Between January 2011 and December 2013 our hospital registered 4262 admissions of patients with cancer for treatment of an acute medical illness. 875 patients (1132 admissions) fulfilled our eligibility criteria. 681 (78%) patients were classified as having a single admission. Of those, 247 had previous but excluded admissions ("pseudo-single"), which leaves 434 patients with true single admissions. In total, there were 434 (49.5%) were males, mean age was 64.3 (SD= 13.5). Primary tumor sites were hematological (n=180); genitourinary (n= 170); lung (n=158); gastrointestinal (n=128) and others (n= 289).559 (70%) patients had stage III or IV. Reasons for admission were failure to thrive (n= 232; 26.6%); fever (n= 202; 23.3%); need for cancer treatment as inpatient (n= 154; 17.7%); pain (n=126; 14.5%); respiratory distress(n= 108; 11.6%) or pain (n= 53; 6.3%). Mean hospitalization days was 14.7 (±12). VTE occurred in 78 of 875 (8.9%) patients or 78 of 1132 admission (6.9%): 36(46%) DVT, 34 (43.5%) PE and 7 PE + DVT (8.9%). 34 of 78 (43.6%) VTE occurred within the first 14 days of admission. However, the overall risk for VTE appeared to be much more significant if the patient remained hospitalized for more than 14 days [RR=3.7 (95%CI= 1.99 - 4.71; p<0.001)]. 150 (15%) patients with single admissions had a concomitant diagnosis of cancer and VTE (within 30 days of admission). A univariate analysis suggested that having had multiple admissions (OR=0.3; 95%CI=0.17- 0.54; p=0.008); being man (OR= 1.69; 95%CI: 1.03 - 2.78; p=0.039); being admitted due to respiratory distress (OR=2.6; 95%CI: 0.9 - 6.8; p=0.052) or failure to thrive (2.52; 95%CI: 1.06 - 5.9; p=0.036) were potentially significant predictors of VTE risk. However, the logistic regression confirmed that the only significant risk factor is the number of admissions (Table). When we compared our results with the pooled data from the MEDENOX, PREVENT and ARTEMIS trials we found that the incidence of VTE in the cancer patients included in the trials was the same as ours [13 of 143 patients (8.8%)] and the incidence of VTE in those without cancer was 95 of 2139 (4.5%), significantly lower compared to the cancer cohort (p=0.0004). Conclusion Our study suggests that hospitalized patients with active cancer are at high risk for VTE prophylaxis failure (8.9%) and our results are in keeping with the literature. It appears that the most important risk factor for thromboprophylaxis failure is having a first admission as a cancer patient. New VTE prophylactic strategies for this population should be investigated in future prospective studies. Table 1. Logistic Regression of potential predictors of VTE risk in hospitalized cancer patients Variable Odds Ratio 95% CI p -value Male 1.05 0.64 - 1.74 0.8270 "Pseudo-single" admission* 0.53 0.28 - 0.97 0.9182 Multiple admission* 0.29 0.16 - 0.53 0.0029 Respiratory distress 1.19 0.53 - 2.68 0.7597 Pain 1.27 0.59 - 2.71 0.5079 Failure to thrive 1.02 0.46 - 2.24 0.6820 *Reference: single admission Disclosures Louzada: janssen: Consultancy, Other: advisory board and expert opinion; pfizer: Consultancy, Other: advisory board and expert opinion; Celegene: Consultancy, Other: advisory board and expert opinion. Kovacs:Pfizer: Honoraria, Research Funding; Bayer: Honoraria, Research Funding; LEO Pharma: Honoraria; Daiichi Sankyo Pharma: 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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".