Atezolizumab plus Bevacizumab in Unresectable Hepatocellular Carcinoma is a research paper published in New England Journal of Medicine (2020). On theSindex it has a DataRank of 1.3. It has been cited 7,029 times.
BackgroundThe combination of atezolizumab and bevacizumab showed encouraging antitumor activity and safety in a phase 1b trial involving patients with unresectable hepatocellular carcinoma.MethodsIn a global, open-label, phase 3 trial, patients with unresectable hepatocellular carcinoma who had not previously received systemic treatment were randomly assigned in a 2:1 ratio to receive either atezolizumab plus bevacizumab or sorafenib until unacceptable toxic effects occurred or there was a loss of clinical benefit. The coprimary end points were overall survival and progression-free survival in the intention-to-treat population, as assessed at an independent review facility according to Response Evaluation Criteria in Solid Tumors, version 1.1 (RECIST 1.1).ResultsThe intention-to-treat population included 336 patients in the atezolizumab-bevacizumab group and 165 patients in the sorafenib group. At the time of the primary analysis (August 29, 2019), the hazard ratio for death with atezolizumab-bevacizumab as compared with sorafenib was 0.58 (95% confidence interval [CI], 0.42 to 0.79; PConclusionsIn patients with unresectable hepatocellular carcinoma, atezolizumab combined with bevacizumab resulted in better overall and progression-free survival outcomes than sorafenib. (Funded by F. Hoffmann-La Roche/Genentech; ClinicalTrials.gov number, NCT03434379.).
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Base Score Contribution
1.3
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.