Evidence map›Paper›PMID 38073679›Full record

ArticleWorld journal of clinical cases2023

Immunotherapy in SMARCB1 (INI-1)-deficient sinonasal carcinoma: Two case reports.

Lu Zhang, Ai-Xin Gao, Yu-Lu He, Ming-Jin Xu, Hai-Jun Lu

Open access · diamondAbstract readCase Reports
In one paragraph

Article in World journal of clinical cases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 22% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Lu ZhangDepartment of Oncology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China.
Ai-Xin GaoDepartment of Radiology, The Affiliated hospital of Qingdao University, Qingdao 266000, Shandong Province, China.
Yu-Lu HeDepartment of Pathology, Peking University People's Hospital, Qingdao 266003, Shandong Province, China.
Ming-Jin XuDepartment of Oncology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China.
Hai-Jun LuRadiation Oncology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China. lhj82920608@163.com.
Qingdao University · CNPeking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSMARCB1/INI-1 deficient sinonasal carcinoma (SDSC) is a rare subset of sinonasal undifferentiated carcinoma with a poor prognosis. Here, we present two case reports of SDSC patients. We also review the literature on this tumor. This is the first published report of SDSC treatment with immunotherapy. CASE SUMMARY: Here we present two patient cases of SDSC in which initial consultation and diagnosis were complicated but SDSC was ultimately diagnosed. One patient received a traditional treatment of surgery and adjuvant chemoradiotherapy, while the other patient received additional immunotherapy; the prognoses of these two patients differed. We review previous diagnostic literature reports and SDSC treatments and provide a unique perspective on this rare type of tumor.

conclusionSDSC is a rare, diagnostically challenging carcinoma with a consistently poor prognosis, early distant metastases, and frequent recurrence. Timely diagnosis and intervention are critical for treatment, for which the standard of care is surgery followed by adjuvant chemoradiotherapy, though immunotherapy may be an effective new treatment for SDSC.

Indexed as

Case reportGene deficientImmunotherapyINI-1Sinonasal carcinomaSMARCB1Surgery

Identifiers

PMID38073679
PMCPMC10698440
OpenAlexW4388701380

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.