Evidence map›Paper›PMID 35912016›Full record

ArticleJournal of Cancer2022

Clinical outcomes of Atezolizumab Therapy for Previously-Treated Advanced-Stage Non-Small Cell Lung Cancer: A Real-World Study in Taiwan.

Shang-Gin Wu, Chi-Lu Chiang, Chin-Chou Wang, Jen-Yu Hung, Te-Chun Hsia, Chih-Hsi Kuo, Jin-Yuan Shih

Abstract read
In one paragraph

Article in Journal of Cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Trial
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

7 authors.

Shang-Gin WuDepartment of Internal Medicine, National Taiwan University Hospital, National Taiwan University, Taipei, Taiwan.
Chi-Lu ChiangDepartment of Chest Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.
Chin-Chou WangDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Chang Gung Memorial Hospital-Kaohsiung Medical Center, Chang Gung University College of Medicine, Kaohsiung, Taiwan.
Jen-Yu HungDepartment of Internal Medicine, Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.
Te-Chun HsiaDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, China Medical University and China Medical University Hospital, Taichung, Taiwan.
Chih-Hsi KuoDivision of Lung Cancer and Interventional Bronchoscopy, Department of Thoracic Medicine, College of Medicine, Chang Gung Memorial Hospital, Chang Gung University, Taipei, Taiwan.
Jin-Yuan ShihDepartment of Internal Medicine, National Taiwan University Hospital, National Taiwan University, Taipei, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immune checkpoint inhibitors (ICIs) are the standard treatment for non-small-cell lung cancer (NSCLC). We assessed the clinical prognostic factors in NSCLC patients receiving atezolizumab as a second- or later-line (2L+) treatment. Data were retrospectively collected for NSCLC patients treated with atezolizumab from July 2017 to June 2019 at six medical centers in Taiwan. Clinical characteristics, treatment course and responses of patients were recorded. A total of 128 NSCLC patients received 2L+ atezolizumab, and the outcomes included a response rate of 10.2%, median progression-free survival (mPFS) of 3.5 months, and median overall survival (mOS) of 10.7 months. Eleven patients who had received osimertinib treatment before atezolizumab had a shorter mPFS (2.3

Indexed as

AtezolizumabEpidermal growth factor receptor mutationImmune checkpoint inhibitorNon-small-cell lung cancerOsimertinibTyrosine kinase inhibitor

Identifiers

PMID35912016
PMCPMC9330461

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.