Patterns of Treatment and Real‐World Outcomes of Patients With Non‐small Cell Lung Cancer With <scp><i>EGFR</i></scp> Exon 20 Insertion Mutations Receiving Mobocertinib: The <scp>EXTRACT</scp> Study
Bibliographic record
Abstract
BACKGROUND: Real-world data regarding patients with non-small cell lung cancer (NSCLC) with EGFR exon 20 insertion (ex20ins) mutations receiving mobocertinib are limited. This study describes these patients' characteristics and outcomes. METHODS: A chart review was conducted across three countries (Canada, France, and Hong Kong), abstracting data from eligible patients (NCT05207423). The inclusion criteria were: ≥ 18 years old; diagnosis of stage IIIB-IV NSCLC with EGFR ex20ins between January 1, 2017 and November 30, 2021; received mobocertinib. Data on demographics, clinical parameters, treatment patterns, mobocertinib exposure, real-world outcomes, and adverse events (AEs) were collected. Results are also reported by Asian/Non-Asian races. RESULTS: Overall, 105 patients were enrolled (median [IQR] age at initial diagnosis: 64.0 years [56, 71]; women: 62.9%). The most common first-line of therapy (LoT) was chemotherapy; the most common second LoT was EGFR tyrosine kinase inhibitors. Most patients received mobocertinib during LoT two and three (74.3%); the maximum dose was 160 mg/day for 67.6% of the cohort (mean [SD] daily dose: 130.6 mg [36.68]). The median real-world progression-free survival (PFS) on mobocertinib was 4.76 months (95% CI: 3.98, 6.21). The overall response rate and disease control rate were 20.0% and 48.6%, respectively (median duration of response: 8.34 months [95% CI: 3.61, 9.49]). The median overall survival (OS) was 26.28 months (95% CI: 20.21, 36.44). Asian patients had numerically superior PFS and OS compared with non-Asian patients. Regarding safety analysis, 73 patients (69.5%) experienced any AE. The most common AE was diarrhea (any grade) (52 patients; 49.5%). CONCLUSIONS: These data illustrate the real-world effectiveness of mobocertinib.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".