Abstract PD3-10: Higher serum PD-L1 predicts for increased overall survival to lapatinib vs trastuzumab in the phase 3 CCTG MA.31 trial
Bibliographic record
Abstract
Abstract Background: In the CCTG (Canadian Clinical Trials Group) MA.31 randomized phase 3 trial, the trastuzumab-taxane combination led to longer PFS than lapatinib-taxane in HER2-positive metastatic breast cancer (MBC). We previously reported the prognostic utility of pretreatment serum PD-L1 in the trastuzumab arm of MA.31 (ASCO 2018, #1031), and here we evaluate serum PD-L1 in the lapatinib arm, and in the whole trial. Higher serum PD-L1 has been reported to be associated with reduced response to treatment with the immune checkpoint inhibitors in melanoma and lung cancer. Methods: MA.31 accrued 652 centrally and/or locally-identified HER2-positivepatients; 186 in the trastuzumab arm, and 202 in the lapatinib armhad pretreatment serum available. TheELLA immunoassay platform (ProteinSimple, San Jose, CA) was used to quantitate serum PD-L1. Step-wise forward Cox multivariate analysis was used for PFS and OS, and testing for treatment-biomarker interaction was based on the local partial-likelihood method (Liu Y, Jiang W, and Chen BE, Statistics in Medicine 34, 3516-3530, 2015). Results: In the total study population, pretreatment serum PD-L1 concentration had a median of 86.2 pg/ml, and 25% and 75% interquartiles of 64.1 and 134.3 pg/ml, respectively. In univariate analysis in the whole trial, and within both treatment arms, serum PD-L1 was not a significant biomarker for PFS. For OS, higher serum PD-L1 (as a continuous variable) was significant for shorter OS within the trastuzumab arm (HR=3.84, p=0.04), but was not associated with OS in the lapatinib arm (p=0.37). In the whole trial, in multivariate analysis for OS [15 covariates included: age, race, ECOG status, anthracyclines, other chemo, endocrine, radio, other prior adjuvant therapy, disease status, ER status, PR status, Ki67 (log transformed), CK5, EGFR, treatment arm, and serum PD-L1 (with median cut point)], serum PD-L1 remained a significant independent covariate (HR= 2.27, p= 0.001 (Table).There was significant interaction between treatment arm and continuous serum PD-L1 (Bootstrap method, p=0.0025); above 214.2 pg/ml serum PD-L1 (89% percentile), higher pretreatment serum PD-L1 was associated with a shorter OS to trastuzumab treatment, but longer OS to lapatinib treatment. Conclusions: In the CCTG MA.31 trial, serum PD-L1 was a significant predictive factor: higher pretreatment serum PD-L1 was associated with a shorter OS to trastuzumab treatment, but longer OS to lapatinib treatment. Immune evasion may decrease the effectiveness of trastuzumab therapy. Further evaluation of elevated serum PD-L1 in the advanced breast cancer setting is warranted to identify HER2-positive MBC patients who may benefit from novel immune-targeted therapies in addition to trastuzumab. Multivariate Analysis (whole trial): Significant Independent CovariatesCovariateP-ValueHRLower 95% CIHigher 95% CISerum PD-L1 (pretreatment) (>median vs Citation Format: Moku PR, Shepherd LE, Ali SM, Leitzel K, Parulekar WE, Zhu L, Virk S, Nomikos D, Aparicio S, Gelmon KA, Drabick JJ, Cream L, Halstead SE, Umstead T, Mckeone D, Maddukuri A, Polimera HV, Ali A, Poulose J, Pancholy N, Spiegel H, Nagabhairu V, Chen BE, Lipton A. Higher serum PD-L1 predicts for increased overall survival to lapatinib vs trastuzumab in the phase 3 CCTG MA.31 trial [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr PD3-10.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".