Evidence map›Paper›PMID 35938033›Full record

ArticleFrontiers in genetics2022

Case Report: Pulmonary sarcomatoid carcinoma complicating TP53 mutation treated successfully with Tislelizumab combined with Anlotinib-a case report.

Yu-Feng Li, Xin-Fei Zhao, Yue Tian, Xin-Yao Xiao, Cai-Yun Yan, Hua Shen

Open access · goldAbstract readCase Reports
In one paragraph

Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.2field-weighted citation impact, top 20% 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

9 citing papers in PubMed, 8 citations in OpenAlex.

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  7. Targeted therapy for rare lung cancers: Status, challenges, and prospects.Molecular therapy : the journal of the American Society of Gene Therapy · 2023
    Review
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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

6 authors at 1 institution in 1 country.

Yu-Feng LiDepartment of Medical Oncology, The Affiliated Sir Run Run Hospital of Nanjing Medical University, Nanjing, China.
Xin-Fei ZhaoDepartment of Medical Oncology, The Affiliated Sir Run Run Hospital of Nanjing Medical University, Nanjing, China.
Yue TianDepartment of Medical Oncology, The Affiliated Sir Run Run Hospital of Nanjing Medical University, Nanjing, China.
Xin-Yao XiaoDepartment of Medical Oncology, The Affiliated Sir Run Run Hospital of Nanjing Medical University, Nanjing, China.
Cai-Yun YanDepartment of Medical Oncology, The Affiliated Sir Run Run Hospital of Nanjing Medical University, Nanjing, China.
Hua ShenDepartment of Medical Oncology, The Affiliated Sir Run Run Hospital of Nanjing Medical University, Nanjing, China.
Nanjing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pulmonary sarcomatoid carcinoma (PSC) is a rare subtype of lung malignant tumor. Conventional chemotherapy has a suboptimal effectiveness. PSC has the characteristics of rapid disease progression and poor prognosis. We herein report a 56-year-old male patient with substantial smoking history was pathologically diagnosed as PSC, cT4N0M0 IIIA stage. Peripheral blood NGS showed TP53 mutation. The patient had poor tolerance to the first-line chemotherapy regimen "albumin paclitaxel + cisplatin," but the severe anemia was significantly improved after 5 days of anti-angiogenic therapy with Anlotinib. At this time, the patient received anti-PD-1 immunotherapy with Tislelizumab. Half a month later, degree III liver injury occurred repeatedly. After excluding drug-induced liver injury, we found that HCV-RNA 3.10 × 10

Indexed as

Anlotinibcase reporthepatitis Cpulmonary sarcomatoid carcinomaTislelizumabTP53 mutation

Identifiers

PMID35938033
PMCPMC9355298
OpenAlexW4286698356

What OpenQuestion holds

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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.