Failure of the Ottawa Score to Predict the Risk of Recurrent Venous Thromboembolism in Cancer Patients: The Prospective PREDICARE Cohort Study
Bibliographic record
Abstract
INTRODUCTION: Recurrent venous thromboembolism (VTE) despite curative anticoagulation is frequent in patients with cancer. Identifying patients with a high risk of recurrence could have therapeutic implications. A prospective study was designed to validate the Ottawa risk score of recurrent VTE in cancer patients. METHODS: In a prospective multicenter observational cohort, adult cancer patients with a recent diagnosis of symptomatic or incidental lower limb deep vein thrombosis or pulmonary embolism (PE) were treated with tinzaparin for 6 months. The primary endpoint was the recurrence of symptomatic or asymptomatic VTE within the first 6 months of treatment. All clinical events were centrally reviewed and adjudicated. Time-to-event outcomes were estimated by the Kalbfleisch and Prentice method to take into account the competing risk of death. A C-statistic value of > 0.70 was needed to validate the Ottawa score. RESULTS: A total of 409 patients were included and analyzed on an intention-to-treat basis. Median age was 68 years, 60.4% of patients had PE, and VTE was symptomatic in 271 patients (66.3%). The main primary sites were lung (31.3%), lower digestive tract (14.4%), and breast (13.9%) cancers. The Ottawa score was high (≥ 1) in 58% of patients. The 6-month cumulative incidence of recurrent VTE was 7.3% (95% confidence interval [CI]: 4.9-11.1) overall, and 5.0% (95% CI: 2.3-10.8) versus 9.1% (95%CI: 6.1-13.6) in the Ottawa low versus high risk groups, respectively. The C-statistic value was 0.60 (95% CI: 0.55-0.65). CONCLUSION: In this prospective cohort of patients with cancer receiving tinzaparin for VTE, the Ottawa score failed to accurately predict recurrent VTE.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".