Evidence map›Paper›PMID 28138259›Full record

ReviewOncoTargets and therapy2017

Advances in antiangiogenic treatment of small-cell lung cancer.

Hongyang Lu, Zhiming Jiang

Open access · goldAbstract readReview
In one paragraph

Review in OncoTargets and therapy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.5field-weighted citation impact, top 16% 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

12 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Oncotarget · 2018
    Article
  9. Article
  10. Review
  11. Review
  12. 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

2 authors at 1 institution in 1 country.

Hongyang LuZhejiang Key Laboratory of Diagnosis & Treatment Technology on Thoracic Oncology (Lung and Esophagus); Department of Thoracic Medical Oncology, Zhejiang Cancer Hospital, Hangzhou, People's Republic of China.
Zhiming JiangDepartment of Thoracic Medical Oncology, Zhejiang Cancer Hospital, Hangzhou, People's Republic of China.
Zhejiang Cancer Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Small-cell lung cancer (SCLC), a poorly differentiated neuroendocrine malignancy, has a rapid growth rate, strong aggressiveness, early metastases, and poor prognosis. Angiogenesis greatly contributes to the metastatic process of SCLC, which has a higher vascularization compared with non-small-cell lung cancer (NSCLC). SCLC might constitute an ideal malignancy for assessing new antiangiogenic drugs and therapeutic strategies. Combining bevacizumab with paclitaxel has therapeutic benefits in chemoresistant, relapsed SCLC. The cisplatin-etoposide and bevacizumab combination, as the first-line treatment for extensive-stage SCLC, can improve progression-free survival (PFS), with an acceptable toxicity profile. Ziv-aflibercept combined with topotecan is promising for platinum-refractory SCLC. Chemotherapy combined with thalidomide cannot prolong survival. Maintenance sunitinib of 37.5 mg/day in extensive-stage SCLC patients following induction chemotherapy with platinum/etoposide improves median PFS by 1.6 months. Serum angiopoietin-2 concentrations and vascular endothelial growth factor levels correlate with poor prognosis. Bevacizumab, ziv-aflibercept, and sunitinib are worthy of further evaluation. Thalidomide, sorafenib, pomalidomide, and cediranib may not be suitable for SCLC.

Indexed as

bevacizumabsmall-cell lung cancersunitinib antiangiogenic therapy

Identifiers

PMID28138259
PMCPMC5238765
OpenAlexW2571990970

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.