Kinetics and management of adverse events associated with lorlatinib after 5 years of follow-up in the CROWN study
Bibliographic record
Abstract
OBJECTIVE: With 5 years of follow-up in the phase 3 CROWN study, lorlatinib showed unprecedented improvement in progression-free survival coupled with prolonged intracranial efficacy in patients with ALK-positive metastatic non-small cell lung cancer (mNSCLC). Here, we report kinetics and mitigation practices of select adverse events (AEs) to inform therapy management strategies. DESIGN: Post hoc safety analyses from the CROWN study assessed the incidence, prevalence, time to onset, duration, management, and resolution of hyperlipidemia, edema, weight gain, central nervous system (CNS) AEs, and peripheral neuropathy in the lorlatinib group (n = 149). RESULTS: After 5 years of follow-up, no new safety signals were observed. All-cause any-grade and grade 3/4 AEs occurred in 100% and 77% of patients, respectively; AEs led to lorlatinib dose reduction in 23% of patients, dose interruption in 62%, and permanent discontinuation in 11%. The median time to onset of any-grade hyperlipidemia was 0.5 months; 71% of events were managed with lipid-lowering agents. Median time to onset of any-grade edema, weight gain, CNS AEs, and peripheral neuropathy ranged from 2 to 4 months. Most weight gain events (95%) were mitigated with lifestyle modifications. Incidence and prevalence of CNS AEs did not increase over time; 58% of events did not require medical intervention. CONCLUSIONS AND RELEVANCE: This post hoc analysis suggests that with longer lorlatinib exposure, no new safety signals emerged, and treatment discontinuation due to AEs remained low after 5 years of follow-up. Most AEs were effectively managed with dose modifications, indicating that current management strategies can be effective to mitigate toxicity. ClinicalTrials.gov NCT03052608.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".