Evidence map›Paper›PMID 26557915›Full record

ArticleThoracic cancer2015

Radiofrequency ablation (RFA) for palliative treatment of painful non-small cell lung cancer (NSCLC) rib metastasis: Experience in 12 patients.

Mu Hu, Xiuyi Zhi, Jian Zhang

Open access · goldAbstract read
In one paragraph

Article in Thoracic cancer, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-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

7 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Percutaneous Image-Guided Ablation of Lung Tumors.Journal of clinical medicine · 2021
    Review
  4. Article
  5. Article
  6. Article
  7. 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

3 authors at 1 institution in 1 country.

Mu HuThoracic Surgery Department, Xuanwu Hospital Capital Medical University Beijing, China.
Xiuyi ZhiThoracic Surgery Department, Xuanwu Hospital Capital Medical University Beijing, China.
Jian ZhangThoracic Surgery Department, Xuanwu Hospital Capital Medical University Beijing, China.
Capital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPainful rib metastasis is common in non-small cell lung cancer (NSCLC). Pain is often partially or totally refractory to analgesic medications or the side effects of medication are unacceptable. We report the safety and efficacy of a new method: radiofrequency ablation (RFA) in treating painful NSCLC rib metastasis.

methodsRFA procedures were completed in 12 patients with painful rib metastasis. Patient age ranged from 66-83 years (mean 74.8 years, standard deviation (SD) = 5.3). There were four cases of squamous-carcinoma, seven adenocarcinomas, and one case of large cell carcinoma. Pain caused by neoplasm size, pain levels pre-procedure and post-procedure (as assessed using the visual analog scale, VAS), time length, and target temperature of RFA treatments were documented.

resultsRFA procedures were performed with 100% technical success. The mean pre-procedure and post-procedure pain, as measured by the VAS, was 7.9 (SD = 0.90) and 3.4 (SD = 0.99), respectively. No symptomatic complications occurred. Non-symptomatic complications included one case of pneumothorax and one case of hemoptysis.

conclusionRFA appears to be a safe, practical, and effective method for the palliative treatment of painful NSCLC chest wall metastasis.

Indexed as

Non-small cell lung cancerpainful rib metastasisradiofrequency ablation

Identifiers

PMID26557915
PMCPMC4632929
OpenAlexW2124670818

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.