Development of a composite biomarker-based calculator to predict the probability of pathologic complete response (pT0) after neoadjuvant pembrolizumab (pembro) in muscle invasive bladder cancer (MIBC).
Bibliographic record
Abstract
539 Background: The PURE01 study (NCT02736266) evaluates the use of pembro before radical cystectomy (RC) in MIBC. We assessed selected individual and combined biomarkers for predicting pT0 response after pembro, and developed a tool that may be used as an aid for clinical decision-making. Methods: Patients (pts) enrolled in the PURE01 were clinical (c) stage T≤4aN0M0 MIBC. Analysis to date included a comprehensive genomic profiling (FoundationONE assay), programmed cell-death-ligand-1 (PD-L1) combined positive score assessment (CPS, Dako 22C3 antibody) and whole transcriptome (Decipher assay) and RNA-seq profiling of pre/post therapy samples. Multivariable logistic regression analyses (MVA) evaluated baseline cT-stage and biomarkers in association with pT0 response. Corresponding coefficients were used to develop a risk calculator based on the tumor mutational burden (TMB), CPS, Immune190 signature score, and cT-stage. Decision-curve analysis was performed. Results: Complete biomarker data was available for 84 pts. Increasing TMB, CPS, and Immune190 scores showed a linear positive correlation with the pT0 probability in logistic regression (p=0.02, p=0.004, p=0.02). The c-index of the risk calculator was 0.79. Decision-curve analysis found the net-benefit of the model was higher than the “treat-all” option within the clinically-meaningful threshold probabilities of achieving a pT0 of 40-60%. Within this range, adding the Immune190 score improved the model over TMB and CPS. A significant decrease in median TMB values was observed (p=0.005) in 24 matched RC, versus a non-significant change in median CPS in 38 matched RC. Molecular subtyping switching was observed in 20/31 matched cases (64.5%), most frequently to the luminal-infiltrated subtype (80%). Conclusions: The study presents the first composite biomarker-based pT0 probability calculator for optimal pt selection. Pending validation, the model may be used to recommend neoadjuvant pembro to very selected MIBC pts. The observed changes in biomarker features in post-therapy samples may have an impact on future adjuvant strategies. Clinical trial information: NCT02736266.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".