Plain language summary of the development of tepotinib: a treatment for a subtype of non-small cell lung cancer called <i>MET</i> exon 14 skipping
Bibliographic record
Abstract
Plain Language SummaryWhat is this summary about? This plain language summary provides an overview of two of the main clinical studies that led to tepotinib’s approval, the phase I first-in-human study and the phase II VISION study.What is tepotinib? Tepotinib is a targeted anti-cancer treatment taken orally (by mouth). It is available in many countries for people with advanced or metastatic non-small cell lung cancer (NSCLC), where the tumor contains a genetic mutation (alteration) called ‘MET exon 14 skipping’. Tumor cells rely on this mutation to grow and survive, so targeted blocking of the effect of this mutation is an important treatment approach. MET exon 14 skipping occurs in approximately 3–4% of people with NSCLC. These people are usually of older age. This subtype of NSCLC is associated with poor outcomes. Before treatments that specifically target this MET mutation were developed, only general treatments such as chemotherapy were available for this type of cancer. Because chemotherapy attacks all rapidly dividing cells in a person’s body and is administered intravenously (through a vein), it can often cause unwanted side effects. Cancer cells grow and divide rapidly because of defects, often involving proteins called ‘tyrosine kinases’. Specific tyrosine kinase inhibitors (TKIs) were therefore developed to slow or stop cancer growth by targeting these proteins. Tepotinib is a MET TKI. This means that it blocks the activity of the MET pathway that is overactive in MET exon 14 skipping NSCLC. Doing this, may slow down cancer growth.What were the results from the clinical studies of tepotinib? In the studies summarized here, people with MET exon 14 skipping NSCLC who took tepotinib had their tumor growth stopped or their tumor shrunk for a period of time, and they mostly experienced side effects that they could tolerate. Clinical Trial Registration: NCT01014936 (tepotinib first-in-human), NCT02864992 (VISION), NCT03940703 (INSIGHT 2) (ClinicalTrials.gov)To read the full Plain Language Summary of this article, click here to view the PDF.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.181 | 0.107 |
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".