Evidence map›Paper›PMID 36860861›Full record

ArticleFrontiers in immunology2023

Predictive value of

Shan Tang, Yan Zhang, Yunfei Li, Yan Zhang, Yuke Xu, Haoyuan Ding, Yue Chen, Peirong Ren, Hua Ye, Shaozhi Fu and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2023. 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
0.2field-weighted citation impact, top 46% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Delta Changes in [Biomedicines · 2025
    Article
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

11 authors at 1 institution in 1 country.

Shan TangDepartment of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Yan ZhangDepartment of Oncology, The People's Hospital of Luzhou, Luzhou, China.
Yunfei LiDepartment of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Yan ZhangDepartment of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Yuke XuDepartment of Radiology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Haoyuan DingDepartment of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Yue ChenDepartment of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Peirong RenDepartment of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Hua YeDepartment of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Shaozhi FuDepartment of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Sheng LinDepartment of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Affiliated Hospital of Southwest Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This retrospective study aimed to investigate Methods: We included 41 patients with advanced non-small cell lung cancer (NSCLC) in this study. PET/CT was performed before (SCAN-0) and one month (SCAN-1), three months (SCAN-2), and six months (SCAN-3) after treatment. Using the European Organization for Research and Treatment of Cancer 1999 criteria and PET response criteria in solid tumors, treatment responses were classified as complete metabolic response (CMR), partial metabolic response (PMR), stable metabolic disease (SMD), or progressive metabolic disease (PMD). Patients were further categorized as those with metabolic benefits (MB; SMD, PMR, and CMR) and those without MBs (NO-MB; PMD). We analyzed the prognosis and overall survival (OS) of patients with new visceral/bone lesions during treatment. Based on the findings, we generated a nomogram to predict survival. Receiver operating characteristics and calibration curves were used to evaluate the accuracy of the prediction model. Results: The mean OS based on SCANs 1, 2, and 3 was significantly higher in patients with MB and those without new visceral/bone lesions. The prediction nomogram for survival had a high area under the curve and a high predictive value based on the receiver operating characteristics and calibration curves. Conclusion:

Indexed as

Bone DiseasesCarcinoma, Non-Small-Cell LungLung NeoplasmsMetabolic DiseasesFluorodeoxyglucose F18HumansHydrolasesPositron Emission Tomography Computed TomographyProgrammed Cell Death 1 ReceptorRetrospective StudiesFluorodeoxyglucose F18HydrolasesProgrammed Cell Death 1 Receptor18F-FDG PET/CThypofractionated radiotherapyNSCLCPD-1 blockadepredictive value

Identifiers

PMID36860861
PMCPMC9969129
OpenAlexW4320496367

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.