Evidence map›Paper›PMID 37873790›Full record

ReviewDiseases (Basel, Switzerland)2023

Comparing Efficacy of Erlotinib and Bevacizumab Combination with Erlotinib Monotherapy in Patients with Advanced Non-Small Cell Lung Cancer (NSCLC): A Systematic Review and Meta-Analysis.

Prashant Sakharkar, Sonali Kurup

Open access · goldAbstract readReview
In one paragraph

Review in Diseases (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 18% of its field
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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Review
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

2 authors at 2 institutions in 1 country.

Prashant SakharkarDepartment of Clinical and Administrative Sciences, College of Science, Health and Pharmacy, Roosevelt University, Schaumburg, IL 60173, USA.
Sonali KurupDepartment of Pharmaceutical Sciences, College of Pharmacy, Ferris State University, Big Rapids, MI 49307, USA.
Ferris State University · USRoosevelt University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objective of this systematic review and meta-analysis was to assess and contrast the efficacy and safety of combining erlotinib and bevacizumab with erlotinib alone in the treatment of patients with advanced non-small cell lung cancer (NSCLC). The authors searched databases such as PubMed, Medline, Scopus, and Cochrane Central Register of Controlled Trials for randomized control trials (RCTs) comparing erlotinib plus bevacizumab with erlotinib in NSCLC patients. The overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and adverse events (AEs) were the outcomes of interest. The pooled hazard ratio (HR) and relative risk (RR) were estimated utilizing both fixed- and random-effect models. Methodological quality of the included studies was assessed using the Cochrane Risk of Bias tool. Nine studies comprising 1698 patients with NSCLC were included in this meta-analysis, of whom 850 were treated with erlotinib plus bevacizumab, and 848 with erlotinib. The erlotinib plus bevacizumab combination significantly prolonged PFS (HR, 0.62, 95% CI: 0.56, 0.70,

Indexed as

bevacizumabEGFR-TKIepidermal growth factor receptor tyrosine kinase inhibitorerlotinibnon-small cell lung cancerNSCLCvascular endothelial growth factor receptor tyrosine kinase inhibitorVEGFR-TKI

Identifiers

PMID37873790
PMCPMC10594499
OpenAlexW4387879308

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.