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David S. Ettinger, MD, FACP, FCCP


Does Bias Affect Overall Survival Reporting in ALK-Positive NSCLC Treated With Alectinib Versus Ceritinib?

By: Emily Rhode
Posted: Tuesday, February 8, 2022

Greater overall survival was realized in patients with crizotinib-refractory, ALK-positive non–small cell lung cancer (NSCLC) who were treated with alectinib compared with ceritinib in both single-group trials and multicenter real-world data, according to a study published in JAMA Network Open. Vivek Subbiah, MD, of The University of Texas MD Anderson Cancer Center, Houston, and colleagues found that only substantial levels of bias invalidated these findings.

Results were robust to a range of plausible assumptions about unmeasured confounding and missing Eastern Cooperative Oncology Group (ECOG) performance status and underrecorded comorbidities in real-world data,” the researchers stated.

The study compared patients from two different single-group phase II trials of alectinib (n = 183) with real-world patients treated with alectinib (n = 81) or ceritinib (n = 91). Central nervous system metastases were present in 61.2% of patients in the single-group trials compared with 20.9% of those in the real-world data group who were treated with ceritinib.

Compared with real-world data from patients treated with ceritinib, those given alectinib achieved longer overall survival in both single-group trials (hazard ratio = 0.59) and in real-world data (hazard ratio = 0.46). Adjustments were made for 11 baseline covariates, including comorbidities, metastases, insurance status, and Asian race; the researchers found a hazard ratio of 0.60. Even with these adjustments, the overall survival for patients treated with alectinib in the single-group trials versus those in the real-world data group did not seem to differ significantly (hazard ratio = 1.19).

Although the results of this study suggest that alectinib may be associated with longer overall survival compared with ceritinib in this patient population, the investigators proposed that transparent and rigorous quantitative evaluation of uncertainty and bias should be included in nonrandomized studies to aid in decision-making.

Disclosure: For a full list of authors’ disclosures, visit

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