Incidental Venous Thromboembolism in Kidney Cancer Patients: A Retrospective Case-Control Study
Bibliographic record
Abstract
Abstract Abstract 5134 Introduction: The incidence of venous thromboembolism (VTE) in kidney cancer patients has been reported at 1. 2–3. 2% with an estimated hazard ratio for death of 1. 3–3. 2. Computed Tomography (CT) scans are used frequently to stage cancer, and as the resolution of the scans increases more incidentally discovered asymptomatic VTE are being diagnosed. Currently, it is unclear if incidentally found VTE have the same effect on survival as symptomatic VTE in kidney cancer patients. Methods: We undertook a retrospective case-control analysis of all kidney cancer patients treated at our institution between January 1, 2005 and July 1, 2012. Cases with VTE were matched in a ratio of 1:2 to controls by gender, age and stage at cancer diagnosis. All charts were reviewed for comorbidities at cancer diagnosis, cancer type, stage, and treatment plan. We reviewed imaging studies to identify the location of the VTE and whether it was unsuspected – which was defined as a VTE found on a CT which was indicated for cancer staging. Results: From a cohort of 1166 primary kidney cancer patients we identified 68 (5. 8%) patients who developed a VTE. There were 30 cases of pulmonary embolism (PE), 24 lower extremity deep vein thrombosis (DVT), 5 DVT of the upper extremity and neck and 9 intra-abdominal VTE. Of these, 35% were discovered incidentally and 65% were symptomatic. Compared to matched controls, all patients with VTE did not have worsened survival (hazard ratio [HR] = 0. 87; 95% CI: 0. 54–1. 42). As demonstrated in Figure 1, symptomatic and incidentally discovered VTE were at no increased risk of death compared to controls (HR = 0. 72; 95% CI: 0. 40 – 1. 31 and HR = 1. 12; 95% CI: 0. 61 – 2. 27 respectively). Also, when looking specifically at symptomatic and incidentally discovered pulmonary embolisms, no difference in survival was detected (HR = 1. 44; 95% CI: 0. 68 – 3. 06 and HR = 0. 78; 95% CI: 0. 31 – 1. 97 respectively). Conclusions: In this analysis of kidney cancer patients we found a high rate of VTE (5. 8%) of which 35% were found incidentally on CT staging. The results from this study show that kidney cancer patients with VTE do not have worse survival outcomes than those without VTE. Moreover, the difference in survival between patients with any symptomatic VTE or PE does not differ from incidentally found VTE or PE. Disclosures: No relevant conflicts of interest to declare.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".