MO19390 (SAiL): Incidence of thromboembolic events and congestive heart failure with first-line bevacizumab (Bv)-based therapy in advanced non-small cell lung cancer (NSCLC)
Bibliographic record
Abstract
e19003 Background: MO19390 (SAiL) is a single-arm, multicenter, international trial evaluating the safety and efficacy of first-line Bv with standard chemotherapy in over 2,000 patients (pts). Methods: Key eligibility criteria were untreated locally advanced, metastatic or recurrent non-squamous NSCLC, ECOG PS 0–2, tumor not abutting major blood vessels, no uncontrolled HTN (systolic >150mmHg and/or diastolic >100mmHg) or active cardiovascular disease at baseline. Pts received Bv (7.5 or 15mg/kg) with standard chemotherapy for up to six cycles. Non-progressors proceeded to receive Bv until disease progression. The primary endpoint was safety, including the incidence of serious adverse events (SAEs) related to Bv, and the incidence of AEs of special interest. Results: Safety analyses (data cut-off July 2008) were based on 2,008 pts. Pts (%) were: male 60.1; stage IIIB/IV 19.5/80.5 (no data for 3 pts); adenocarcinoma/large cell/other 85.8/7.1/7.1; ECOG PS 0/1/2 38.1/56.1/5.8. 4.2% of pts were receiving anticoagulants at baseline. A total of 1,008 pts (50.2%) experienced at least one adverse event of special interest (all grades). Of these, 172 pts (8.6%) experienced an arterial or venous thromboembolism, which included pulmonary embolism (49 pts; 2.4%), deep vein thrombosis (40 pts; 2.0%), thrombophlebitis (26 pts; 1.3%), myocardial infarction (12 pts; 0.6%), cerebral hemorrhage (2 pts; 0.1%), cerebral ischemia (4 pts; 0.2%) and cerebrovascular accident (6 pts; 0.3%). 59 pts (2.9%) experienced congestive heart failure (CHF). Conclusions: The incidence of thromboembolic events and CHF was low in Bv-treated pts enrolled in the SAiL trial. These results, taken together with the overall safety analysis from the SAiL trial, confirm that Bv-based therapy has a well-established and manageable safety profile. Updated results will be presented. [Table: see text]
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".