Evidence map›Paper›PMID 30255689›Full record

ArticleAsian Pacific journal of cancer prevention : APJCP2018

Clinical Presentation and Treatment Options for Clear Cell Lung Cancer: University of Cincinnati A Case Series and Literature Review of Clear Cell Lung Cancer

Ihab Eldessouki, Ola Gaber, Muhammad K Riaz, Jiang Wang, Nagla Abdel Karim

Abstract readCase Reports
In one paragraph

Article in Asian Pacific journal of cancer prevention : APJCP, 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
0.9field-weighted citation impact, top 23% 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

8 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Stenting in Non-Small Cell Lung Cancer: How Does It Affect the Outcomes?Asian Pacific journal of cancer prevention : APJCP · 2020
    Article
  7. Article
  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 at 1 institution in 1 country.

Ihab EldessoukiDepartment of Hematology- Oncology, Vontz Center for molecular studies, University of Cincinnati, OH,USA. Email: drs_olagaber@yahoo.com
Ola Gaber
Muhammad K Riaz
Jiang Wang
Nagla Abdel Karim
University of Cincinnati · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clear cell carcinomas are common finding in renal, ovarian and uterine carcinomas. However, clear cell lung cancer (CCLC), first described by Liebow and Castleman in 1963, is considered an extremely rare variant of lung tumors. The 2011 WHO classification of lung tumors considered CCLC as a rare cytologic feature of squamous cell or adenocarcinomas. It is no longer recognized as a formal subtype, albeit it can be referred to in the pathological diagnosis as “with clear cell features” even with marginal fractions of the tumor cells. Such recognition is needed since the variation in clinical features and outcome in this subset of patients. The disease has a clinically vague natural history, is characterized by slight female predominance and is often seen in the elderly. As frequently encountered with rare diseases, its clinical course and treatment options have many questions still yet to be answered. In this paper, we review both the natural history and treatment options mentioned in literature, in the light of our experience by reporting a case series of four patients diagnosed with CCLC and highlight their aspects.

Indexed as

Adenocarcinoma, Clear CellAgedCarcinoma, Non-Small-Cell LungFemaleHumansLung NeoplasmsMiddle Agedcase seriousClear celllung cancertreatment

Identifiers

PMID30255689
PMCPMC6249457
OpenAlexW2900158781

What OpenQuestion holds

Textmetadata
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.