Integration of immunotherapy into adjuvant therapy for resected non-small-cell lung cancer: ALCHEMIST chemo-IO (ACCIO).
Jacob M SandsSumithra J MandrekarDavid E KozonoGeoffrey R OxnardShauna L HillmanDennis A WigleRamaswamy GovindanJennifer Wilkinson CarlisleJhanelle E GrayJoseph K SalamaLuis E RaezApar GantiNathan FosterShakun MalikJeffrey BradleyKaren KellySuresh R RamalingamThomas E StinchcombePublished in: Immunotherapy (2021)
Non-small-cell lung cancer (NSCLC) causes significant mortality each year. After successful resection of disease stage IB (>4 cm) to IIIA (per AJCC 7), adjuvant platinum-based chemotherapy improves median overall survival and is the standard of care, but many patients still experience recurrence of disease. An adjuvant regimen with greater efficacy could substantially improve outcomes. Pembrolizumab, a programmed cell death-1 inhibitor, has become an important option in the treatment of metastatic NSCLC. ALCHEMIST is a clinical trial platform of the National Cancer Institute that includes biomarker analysis for resected NSCLC and supports therapeutic trials including A081801 (ACCIO), a three-arm study that will evaluate both concurrent chemotherapy plus pembrolizumab and sequential chemotherapy followed by pembrolizumab to standard of care adjuvant platinum-based chemotherapy. Clinical trial registration: NCT04267848 (ClinicalTrials.gov).
Keyphrases
- advanced non small cell lung cancer
- locally advanced
- clinical trial
- small cell lung cancer
- early stage
- squamous cell carcinoma
- healthcare
- rectal cancer
- prognostic factors
- end stage renal disease
- palliative care
- epidermal growth factor receptor
- radiation therapy
- lymph node
- ejection fraction
- newly diagnosed
- chronic kidney disease
- photodynamic therapy
- cardiovascular events
- combination therapy
- chemotherapy induced
- free survival
- brain metastases
- study protocol
- peritoneal dialysis
- open label
- coronary artery disease
- phase iii
- skeletal muscle
- risk factors
- cancer therapy
- insulin resistance
- data analysis