Phase II Study of Single-Agent Navitoclax (ABT-263) and Biomarker Correlates in Patients with Relapsed Small Cell Lung Cancer
Bibliographic record
Abstract
PURPOSE: Bcl-2 is a critical regulator of apoptosis that is overexpressed in the majority of small cell lung cancers (SCLC). Nativoclax (ABT-263) is a potent and selective inhibitor of Bcl-2 and Bcl-x(L). The primary objectives of this phase IIa study included safety at the recommended phase II dose and preliminary, exploratory efficacy assessment in patients with recurrent and progressive SCLC after at least one prior therapy. EXPERIMENTAL DESIGN: Thirty-nine patients received navitoclax 325 mg daily, following an initial lead-in of 150 mg daily for 7 days. Study endpoints included safety and toxicity assessment, response rate, progression-free and overall survival (PFS and OS), as well as exploratory pharmacodynamic correlates. RESULTS: The most common toxicity associated with navitoclax was thrombocytopenia, which reached grade III-IV in 41% of patients. Partial response was observed in one (2.6%) patient and stable disease in 9 (23%) patients. Median PFS was 1.5 months and median OS was 3.2 months. A strong association between plasma pro-gastrin-releasing peptide (pro-GRP) level and tumor Bcl-2 copy number (R = 0.93) was confirmed. Exploratory analyses revealed baseline levels of cytokeratin 19 fragment antigen 21-1, neuron-specific enolase, pro-GRP, and circulating tumor cell number as correlates of clinical benefit. CONCLUSION: Bcl-2 targeting by navitoclax shows limited single-agent activity against advanced and recurrent SCLC. Correlative analyses suggest several putative biomarkers of clinical benefit. Preclinical models support that navitoclax may enhance sensitivity of SCLC and other solid tumors to standard cytotoxics. Future studies will focus on combination therapies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".