Evidence map›Paper›PMID 30237696›Full record

ReviewDrug design, development and therapy2018

Profile of atezolizumab in the treatment of metastatic non-small-cell lung cancer: patient selection and perspectives.

Francesco Facchinetti, Paola Bordi, Alessandro Leonetti, Sebastiano Buti, Marcello Tiseo

Abstract readReview
In one paragraph

Review in Drug design, development and therapy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
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  4. Review
  5. Article
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  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Francesco FacchinettiMedical Oncology Unit, University Hospital of Parma, Parma, Italy, francescofacchinetti2@gmail.com.
Paola BordiMedical Oncology Unit, University Hospital of Parma, Parma, Italy, francescofacchinetti2@gmail.com.
Alessandro LeonettiMedical Oncology Unit, University Hospital of Parma, Parma, Italy, francescofacchinetti2@gmail.com.
Sebastiano ButiMedical Oncology Unit, University Hospital of Parma, Parma, Italy, francescofacchinetti2@gmail.com.
Marcello TiseoMedical Oncology Unit, University Hospital of Parma, Parma, Italy, francescofacchinetti2@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Programed cell death-1/programed death ligand-1 (PD-1/PD-L1) blockade represents an affirmed reality in the treatment of advanced non-small-cell lung cancer (NSCLC) patients. Atezolizumab, an anti-PD-L1 agent, figures among the drugs that provide previously unenvisaged outcomes in the pretreated setting of metastatic NSCLC. Increasing evidence vouches for the early administration of PD-1/PD-L1 blockers in untreated patients, encompassing atezolizumab combinations with chemotherapy and the anti-angiogenic agent bevacizumab. Moreover, the development of atezolizumab allowed to derive several hints regarding clinical and immunological factors predictive of its activity and efficacy, some of them exclusive among this class of drugs. This review provides an overview of atezolizumab development throughout clinical trials toward its applicability in the routine practice, with a particular focus on patient selection based on clinical and immune-related factors.

Indexed as

Patient SelectionAntibodies, MonoclonalAntibodies, Monoclonal, HumanizedAntineoplastic AgentsCarcinoma, Non-Small-Cell LungHumansLung NeoplasmsRandomized Controlled Trials as TopicAntibodies, MonoclonalAntibodies, Monoclonal, HumanizedAntineoplastic Agentsatezolizumabatezolizumab developmentbiomarkersICBimmune checkpoint blockersnon-small cell lung cancerNSCLCPD-1PD-L1

Identifiers

PMID30237696
PMCPMC6137949

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.