Outcome of non-small-cell lung cancer with driven mutations treated with anti-PD-(L)1 agents: A systematic review.
Antonio GhidiniAntonio GhidiniKaren BorgonovoMaria Chiara ParatiFausto PetrelliPublished in: Tumori (2022)
Patients whose tumours harbour epidermal growth factor receptor (EGFR), and anaplastic lymphoma kinase (ALK) driver mutations can benefit most from treatment with tyrosine kinase inhibitors (TKIs). Most trials with immune checkpoint inhibitors (ICIs) included few patients whose tumour had oncogenic driver alterations. We therefore performed a meta-analysis of studies reporting the activity of ICIs in oncogene addicted NSCLC. A comprehensive search of MEDLINE, The Cochrane Library and EMBASE was conducted to identify relevant studies published up to 31 January 2021. The primary outcomes were median overall survival (OS); the secondary endpoints were progression-free survival and overall response rate (PFS and ORR). Overall, 46 studies were screened and selected for final analysis. The pooled ORR was 14.5% (95% CI 9.6-21.2%). The median pooled PFS in EGFR/ALK mutated cases was 3.9 months (95% CI 3-5.2 months). Median pooled OS was 10.7 months (95% CI 9.2-12.5 months). All registration trials in second line did not show any benefit of immunotherapy for the subgroup of patients with EGFR-mutated or ALK-rearranged tumours. The unsatisfied benefit of immunotherapy in oncogene-addicted tumours has been debated and is mainly due to the lower mutation burden of these neoplasms. Our data do not support the use of immunotherapy in the setting of oncogene actionable tumours. More data are needed to confirm or reject the benefit of the combination of TKIs with ICIs.
Keyphrases
- epidermal growth factor receptor
- advanced non small cell lung cancer
- tyrosine kinase
- small cell lung cancer
- end stage renal disease
- newly diagnosed
- free survival
- chronic kidney disease
- ejection fraction
- prognostic factors
- emergency department
- type diabetes
- transcription factor
- systematic review
- deep learning
- machine learning
- artificial intelligence
- protein kinase
- skeletal muscle