Evidence map›Paper›PMID 37916176›Full record

ArticleFrontiers in oncology2023

Case Report: Termination of unplanned pregnancy led to rapid deterioration of non-small-cell lung cancer during osimertinib treatment.

Qizhi Ma, Pei Shu, Kexun Zhou, Yongsheng Wang

Open access · goldAbstract readCase Reports
In one paragraph

Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 31% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 2 institutions in 1 country.

Qizhi MaDivision of Thoracic Tumor Multimodality Treatment, Cancer Center, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.
Pei ShuDivision of Thoracic Tumor Multimodality Treatment, Cancer Center, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.
Kexun ZhouDepartment of Medical Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China.
Yongsheng WangDivision of Thoracic Tumor Multimodality Treatment, Cancer Center, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.
State Key Laboratory of BiotherapySichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present a case of a woman with non-small-cell lung cancer (NSCLC) who experienced disease progression during treatment with the epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor (TKI) osimertinib due to an unplanned pregnancy. Given the risk of tumor progression, the patient underwent an artificial abortion. However, disease deterioration occurred shortly after termination of the pregnancy, with severe chest pain, increased dyspnea, and pleural effusion. After positive rescue measures, including emergency thoracic drainage, thoracentesis, and oxygen uptake, her symptoms improved. Considering pregnancy as an immune escape physiological process, the patient continued treatment with osimertinib, and a partial response (PR) lasting 16 months was observed. Therefore, this case highlights the importance of being vigilant about the rapid development of the tumor after delivery in pregnant patients with EGFR-mutation lung cancer and taking preventive measures to cope with various emergencies.

Indexed as

deteriorationepidermal growth factor receptornon-small-cell lung cancerpregnancytyrosine kinase inhibitor

Identifiers

PMID37916176
PMCPMC10616458
OpenAlexW4387694704

What OpenQuestion holds

Textmetadata
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.