A phase II, open-label, randomized trial of durvalumab (D) with olaparib (O) or cediranib (C) in patients (pts) with leiomyosarcoma (LMS).
Bibliographic record
Abstract
11522 Background: The use of immune checkpoint blockade (ICB) in non-inflamed (cold) tumors is associated with limited clinical efficacy. Combination of ICB with certain molecularly targeted agents (MTA) is hypothesized to increase tumor immunogenicity by recruiting tumor infiltrating lymphocytes in cold tumors, such as LMS. Here, we present the results of LMS cohort treated on the DAPPER study (NCT03851614). Methods: LMS pts with ECOG 0-1 were randomized to either D+O (arm A), or D+C (arm B). In a 28-day cycle, D 1500mg i.v. q4w with either O 300mg bid po qd or C 20mg po qd 5d/week were administered. Overall response rates (ORR) were determined using RECISTv1.1. Evaluation of tumor kinetics (TK) was performed by calculating tumor growth rate (TGR) of target lesions on CT images at baseline and on-treatment, adjusted to account for the time difference between scans. TGR is expressed as % tumor growth/week (Ferte C et al. CCR, 2014). Additionally, paired FFPE samples (from baseline and on-treatment biopsies) were assessed using multispectral fluorescent immunohistochemistry (IHC) panel: CD3, CD8, CD20, CD68, FOXP3 and cytokeratin. Tumor areas were identified by a pathologist and immune cells were quantified using InForm image analysis software. Results: 25 metastatic LMS pts were randomized to arm A (n = 11) or B (n = 14) over 21 months. Median age was 53 years, 96% were females and 60% of pts had ≥3 lines of therapy. In 23 evaluable pts, no responses were seen, 7 pts had stable disease (SD) while 16 has progressive disease (PD). TK analysis was evaluable for 18 pts (arm A = 8, B = 10). 5/8 pts (62.5%) in arm A and 6/10 pts (60%) in arm B showed decreased TK (defined as TGRbaseline > TGRon-treatment). In 4/5 (80%) pts who had deceleration of TK in arm A, SD was maintained for ≥6 months. The reduction in TGR on treatment, compared to baseline was significant in arm A but not in arm B (measured as median % tumor growth/week of 0.5 vs 5.1, 95% CI 0.2-4.3, p = 0.035 in arm A; and 1.3 vs 2.9, 95% CI 0.2-2.7, p = 0.088 in arm B). The median PFS of arm A and B were 9 (95% CI 3-12.8) and 4 (95% CI 2.2-4.6) months respectively. There were no statistically significant differences in tumor-infiltrating immune cells when comparing baseline and on-treatment biopsies from arm A or B. In arm A, one pt with SD > 6 months had a 2.5-fold increase in CD8 (CD3+CD8+) T cells and a 7.6-fold increase in macrophages (CD68+). Conclusions: D+O or D+C resulted in stable disease in 30% of pts, mostly on arm A (D+O). TK analysis may identify pts with prolonged SD on treatment. Although a cold-to-hot immunophenotype change was not generally seen, changes in tumor infiltrating immune cell subsets were observed in one patient with prolonged stable disease. These findings support further molecular and immunophenotype characterization in LMS patients treated with D+O or D+C. Clinical trial information: NCT03851614.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".