Evidence map›Paper›PMID 32102135›Full record

ReviewZhongguo fei ai za zhi = Chinese journal of lung cancer2020

[Research Progress of Immunotherapy and Prognostic Markers in Small Cell Lung Cancer].

Qingyi Wang, Wenying Peng, Meilin Jiang, Lin Wu

Abstract readReview
In one paragraph

Review in Zhongguo fei ai za zhi = Chinese journal of lung cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. [Advances in Molecular Typing of Small Cell Lung Cancer].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2021
    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

4 authors.

Qingyi WangSecond Department of Thoracic Oncology, Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha 410006, China.
Wenying PengSecond Department of Thoracic Oncology, Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha 410006, China.
Meilin JiangSecond Department of Thoracic Oncology, Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha 410006, China.
Lin WuSecond Department of Thoracic Oncology, Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha 410006, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The efficacy of non-small cell lung cancer (NSCLC) has been obviously improved recent years, while the survival of small cell lung cancer (SCLC) patients remains inferior for limit treatment options. The incidence of SCLC accounts for 15% of the overall incidence of lung cancer, and it is characterized with high malignancy, rapid growth, early widespread metastasis, making it very difficult to treat. With the approval of immunotherapy for a variety of solid tumors including NSCLC, as a relatively immunogenic cancer species, relevant clinical researchs on SCLC are also underway and have made certain progress. More importantly, due to the existence of tumor heterogeneity, exploring relevant markers that can predict the efficacy of SCLC is essential for accurate therapy. This review describes the latest advances in SCLC immunotherapy and biomarkers related to the efficacy of immunotherapy.

Indexed as

Carcinoma, Non-Small-Cell LungFemaleHumansImmunotherapyLung NeoplasmsMalePrognosisSmall Cell Lung CarcinomaImmunotherapyLung neoplsmaPredictive marker

Identifiers

PMID32102135
PMCPMC7118334

What OpenQuestion holds

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LicenceCC BY
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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.