Evidence map›Paper›PMID 32779394›Full record

ArticleThoracic cancer2020

Prediction model for hyperprogressive disease in non-small cell lung cancer treated with immune checkpoint inhibitors.

Yong Jun Choi, Taehee Kim, Eun Young Kim, Sang Hoon Lee, Do Sun Kwon, Yoon Soo Chang

Abstract readCase Reports
PubMed Full text at PMC Publisher
In one paragraph

Article in Thoracic cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 3 pooled it
–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

16 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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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.

Yong Jun ChoiDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea.ORCID 0000-0002-6114-2059
Taehee KimDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea.ORCID 0000-0002-3673-7595
Eun Young KimDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea.
Sang Hoon LeeDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea.
Do Sun KwonDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea.
Yoon Soo ChangDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea.

Funding

National Research Foundation of Korea NRF-2017R1A2B4009017
6 · The paper itself

Abstract

backgroundHyperprogressive disease (HPD) is a paradoxical acceleration of tumor growth after immune checkpoint inhibitor (ICI) treatment. This study aimed to identify the risk factors and to present a predictive model for HPD in patients treated with ICIs.

methodsA total of 78 non-small cell lung cancer (NSCLC) cases, treated with at least two cycles of ICIs who underwent computed tomography (CT) for response assessment were recruited into the study from January 2016 to August 2019. HPD was defined by the following criteria: (i) time-to-treatment failure <2 months; (ii) a 50% increase in the sum of target lesion diameters; (iii) new development of at least two lesions in an already involved organ; (iv) appearance of a new organ lesion; and (v) a decrease in ECOG PS 2.

resultsOf the 78 total patients, 15 (19.2%) had HPD. The risk factors of HPD were age; primary lesion size; and metastases in the contralateral lung, pleura, liver, and bone in multivariable logistic regression (odds ratio [OR]; 0.9038, 1.6619, 28.5913, 23.8264, 14.5711, and 20.1533, respectively, all P-values < 0.05). By using these risk factors, we developed a prediction model for HPD and the area under the receiver operating characteristic curve of the model was 0.9556 (95% confidence interval [CI]: 0.9133-0.9978).

conclusionsHPD is relatively common and associated with a grave clinical outcome, requiring a careful monitoring in lung cancer patients treated with ICIs. Moreover, risk factors such as age, size of tumor and number of various metastatic lesions should be taken into consideration before ICI administration. KEY POINTS: SIGNIFICANT FINDINGS OF THE STUDY: Age, primary lesion size, and number of metastases are risk factors of HPD. HPD is strongly associated with poor prognosis. HPD during ICI use needs comprehensive monitoring. WHAT THIS STUDY ADDS: This is the first study to develop a prediction model. The area under the curve of the prediction model for HPD was 0.9556.

Indexed as

AgedCarcinoma, Non-Small-Cell LungDisease ProgressionHumansImmune Checkpoint InhibitorsLung NeoplasmsMalePrognosisImmune Checkpoint InhibitorsHyperprogressive diseaseNSCLCPD-L1 inhibitorprognosis

Identifiers

PMID32779394
PMCPMC7529559

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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.