A Phase I Study of Veliparib (ABT-888) in Combination with Low-Dose Fractionated Whole Abdominal Radiation Therapy in Patients with Advanced Solid Malignancies and Peritoneal Carcinomatosis
Bibliographic record
Abstract
PURPOSE: The combination of low-dose radiotherapy with PARP inhibition has been shown to enhance antitumor efficacy through potentiating DNA damage. We combined low-dose fractionated whole abdominal radiation (LDFWAR) with escalating doses of veliparib (ABT-888), a small-molecule PARP inhibitor, in patients with peritoneal carcinomatosis from advanced solid tumor malignancies. EXPERIMENTAL DESIGN: Patients were treated with veliparib (80-320 mg daily) for a total of 3 cycles. LDFWAR consisted of 21.6 Gy in 36 fractions, 0.6 Gy twice daily on days 1 and 5 for weeks 1-3 of each cycle. Circulating tumor cells (CTC) were collected and evaluated for γ-H2AX. Quality of life (QoL) was assessed using the EORTC-QLQ-C30 questionnaire. RESULTS: Twenty-two patients were treated. Treatment-related grade 3 and 4 toxicities included lymphopenia (68%), anemia (9%), thrombocytopenia (14%), neutropenia (4%), leukopenia (9%), ascites (4%), vomiting (4%), and dyspnea (4%). No objective responses were observed. Disease stabilization (≥24 weeks) was observed in 7 patients (33%). Median progression-free survival (mPFS) was 4.47 months and median overall survival (mOS) was 13.04 months. In the subset of 8 ovarian and fallopian cancers, mPFS was 6.77 months and mOS was 17.54 months compared with mPFS 2.71 months and mOS 13.01 months in others. Patients with ovarian and fallopian cancers had better QoL over time than those with other cancers. An increased percentage of γ-H2AX-positive CTCs was observed in a subset of patients (3/6 with >2 CTCs at baseline). CONCLUSIONS: Combined veliparib and LDFWAR is a well-tolerated regimen that resulted in prolonged disease stability for some patients with advanced solid tumors and carcinomatosis, particularly in the ovarian and fallopian cancer subpopulation.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".