Identification and use of treatment (tx) options in patients (pts) with advanced non-small cell lung cancer (aNSCLC) after comprehensive genomic profiling (CGP): A real-world study.
Bibliographic record
Abstract
9076 Background: The number of targeted txs for NSCLC is increasing. By analyzing numerous molecular alterations, CGP may open more targeted tx options than single biomarker testing. Methods: We analyzed a database linking Flatiron Health electronic health record-based clinical and Foundation Medicine, Inc. (FMI) CGP genomic alteration (GA) data in US pts diagnosed from 1/2011 with aNSCLC, primarily from community practices, and with follow-up through 6/2018. We examined the prevalence and distribution of genomic findings, and agreement between tx received and CGP-directed tx options (approved for aNSCLC/other tumors) on the FMI report as a measure of clinical utility. The latter was evaluated in a subset of pts with sufficient tx and follow-up data after FMI testing. Results: Among 5112 FMI-tested pts (first test observed 8/2012), 49% had their FMI test before starting any line of tx, 97% had ≥ 1 GA with known/likely function (median = 5), and 85% had ≥ 1 potential tx option (52% had ≥ 1 option for aNSCLC and 33% had ≥ 1 for another tumor type only). In 1366 pts evaluable for tx agreement after FMI testing, 572 (42%) received a tx listed on the FMI report and 111 (8%) were enrolled in clinical trials. Pts with a tx option approved for aNSCLC were more likely to have a tx agreeing with an option on the FMI report (67% of 754) v pts with a tx option approved in another tumor type only (8% of 612). Among the 1366 pts, 14% had EGFR/ALK/ROS1/BRAF (EARB) tx options only. The remaining 1170 had a non-EARB tx option, either as their only option (1014; 87%), or in addition to an EARB tx option (156; 13%). The non-EARB tx options included 377 pts (32%) with a tumor mutational burden-associated tx option. In these 1170 pts, 341 (29%) had an agreeing tx besides EARB, and 100 (9%) were enrolled on trials. Conclusions: FMI CGP identified potential NSCLC-specific tx options/a clinical trial opportunity for 52% of pts with aNSCLC. Of the pts evaluated for tx agreement, almost ½ received a tx agreeing with an option on the FMI report and/or were enrolled in a clinical trial. FMI CGP adds value beyond single biomarker testing by identifying txs and trial options in a meaningful proportion of pts.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".