Managing lorlatinib together: An overview and practical guide for patients by ALK-positive NSCLC patients and medical experts
Bibliographic record
Abstract
Lorlatinib is an oral treatment for patients with advanced ALK-positive non-small cell lung cancer (NSCLC). Its efficacy was demonstrated in the CROWN clinical study, in which data from 5 years of follow-up demonstrated effective long-term disease control in patients with advanced ALK-positive NSCLC. While lorlatinib has a distinct side effect profile, its side effects are generally manageable. Managing side effects successfully is critical to preserving patient quality of life and promoting adherence to treatment-both of which are key to maximizing the long-term benefits of lorlatinib. The CROWN study showed that lorlatinib-associated side effects can be managed with dose adjustments, such as lowering the daily dose, without sacrificing treatment effectiveness. This guide, developed collaboratively by patients living with advanced ALK-positive NSCLC and healthcare professionals experienced with managing lorlatinib treatment, aims to help patients understand what to expect from treatment and how to take an informed, active role in their care.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".