Survival Pattern Among Venous Thromboembolism (VTE) Patients with Hematologic Malignancy in Alberta, Canada from 2003 to 2015
Bibliographic record
Abstract
Introduction: Nearly 20% of all newly identified cases of VTE is associated with cancer. Hematologic malignancies are at increased risk of developing VTE. We aimed to identify the prevalence of hematologic malignancy in VTE patients and compare the survival between VTE and non-VTE patients with or without hematologic malignancy. Methods: Using linked administrative data and a validated algorithm we identified adult VTE cases in Alberta, Canada from 2003 to 2015. We also identified patients without VTE using the same database. Subjects having ICD-10 code for hematologic malignancy and solid tumor within one year before and after the VTE index event were further identified. Cox proportional hazard regression model was applied to estimate the hazard ratio (HR) of death. The Kaplan Meier survival analysis was performed to compare survival rate among patients with different diagnosis. Results: We identified 56,907 VTE patients. Of them 37,876 (66.6%), 18,502 (32.5%) and 529 (0.9%) cases were diagnosed as deep vein thrombosis (DVT), pulmonary embolism (PE), and both DVT & PE respectively. 57.4% of the VTE patients were female. Of all VTE cases, 1647 (2.9%) patients had hematologic malignancies and 5034 (8.8%) patients had solid tumor. Of the hematologic malignancy cases 853 (51.8%) , 164 (10%), 105 (6.4%), 302(28.3%) and 223 (13.5%) had Lymphoma, leukemia, myelodysplastic syndrome (MDS), myeloproliferative neoplasm (MPN) and plasma cell dyscrasia respectively. We identified 27,664 patients without any diagnosis of VTE. Among them 586 (2.1%) and 4065 (14.7%) patients had hematologic malignancy and solid tumor, respectively. In VTE group, the hazard of death for patients with hematologic malignancy and solid tumor were 5.2 (95% CI: 4.8-5.5) and 7.5 (95% CI: 7.2-7.8) times greater than that of patients with no cancer, respectively. In the patients with no VTE, hazard of death among people with hematologic malignancy and solid tumor were 7.4 (95% CI: 6.4-8.5) and 12.4 (95% CI: 11.6-13.2) times greater than that of people with no cancer, respectively. In all hematologic malignancy and solid tumor patients, the hazard of death for patients with VTE were 1.8 (95% CI: 1.5-2.1) and 1.6 (95% CI: 1.5-1.7) times greater than that of patients with no VTE, respectively. In all patients without any cancer, those with VTE had 2.6 (95% CI: 2.4-2.7) times increased hazard of death than those without VTE. The Kaplan Meier survival analysis showed the lowest survival probability among VTE patients with solid tumor and hematologic malignancy (Log rank p<0.0001). Conclusion: Lymphoma is the most common hematologic malignancy in VTE patients. VTE patients with any type of malignancy have an increased hazard of death compared to those without VTE. Disclosures Wu: BMS-Pfizer: Honoraria; Bayer: Other: Local PI for trial ; Leo Pharma: Honoraria; BMS-Pfizer: Other: Local PI for trial ; Daiichi-Sankyo: Other: Local PI for trial ; Pfizer: Honoraria; Servier: Honoraria.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".