Indirect comparison of mobocertinib and real-world therapies for pre-treated non-small cell lung cancer with EGFR exon 20 insertion mutations
Bibliographic record
Abstract
OBJECTIVES: Mobocertinib, a novel oral epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor, is available for the treatment of non-small cell lung cancer (NSCLC) with EGFR exon 20 insertion (ex20ins) mutations after platinum chemotherapy. We performed an indirect comparison of clinical trial data and real-world data (RWD) to determine the relative efficacy of mobocertinib vs. other treatments for these patients. MATERIALS AND METHODS: Data on the efficacy of mobocertinib from a phase I/II trial (NCT02716116) were compared to RWD from a retrospective study in 12 German centers using inverse probability of treatment weighting to adjust for age, sex, Eastern Cooperative Oncology Group score, smoking status, presence of brain metastasis, time from advanced diagnosis, and histology. Tumor response assessment was based on RECIST v1.1. RESULTS: The analysis included 114 patients in the mobocertinib group and 43 in the RWD group. The confirmed overall response rate (cORR) according to investigator assessment was 0% for standard treatments and 35.1% (95% confidence interval [CI], 26.4-44.6) for mobocertinib (p < 0.0001). Compared to standard regimens in the weighted population, mobocertinib prolonged overall survival (OS, median [95% CI] = 9.8 [4.3-13.7] vs. 20.2 [14.9-25.3] months; hazard ratio [HR] = 0.42 [0.25-0.69], p = 0.0035), progression-free survival (PFS, median [95% CI] = 2.6 [1.5-5.7] vs. 7.3 [5.6-8.8] months; HR = 0.28 [0.18-0.44], p < 0.0001), and time to treatment discontinuation (median [95% CI] = 2.1 [1.2-3.1] vs. 7.4 [6.4-8.5] months; HR = 0.34 [0.18-0.65], p = 0.0004). CONCLUSION: Mobocertinib was associated with an improved cORR and prolonged PFS and OS compared to standard treatments for patients with EGFR ex20ins-positive NSCLC previously treated with platinum-based chemotherapy.
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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".