Evidence map›Paper›PMID 38277078›Full record

ArticleJournal of cancer research and clinical oncology2024

Developing a clinical-radiomic prediction model for 3-year cancer-specific survival in lung cancer patients treated with stereotactic body radiation therapy.

Bao-Tian Huang, Ying Wang, Pei-Xian Lin

Open access · goldAbstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 2024. 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
0.8field-weighted citation impact, top 30% 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, 2 citations in OpenAlex.

  1. 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

3 authors at 2 institutions in 1 country.

Bao-Tian Huang *Department of Radiation Oncology, Cancer Hospital of Shantou University Medical College, Shantou, 515000, China. hbt830910@126.com.
Ying Wang *Department of Radiation Oncology, Cancer Hospital of Shantou University Medical College, Shantou, 515000, China.
Pei-Xian LinDepartment of Nosocomial Infection Management, The Second Affiliated Hospital of Shantou University Medical College, Shantou, 515000, China.
Shantou University · CNCancer Hospital of Shantou University Medical College · CN

Funding

Guangdong Medical Research Foundation A2015534National Natural Science Foundation of China 81602667Shantou Medical and Health Science and Technology Planning Project [2022] 88
6 · The paper itself

Abstract

purposeThe study aims to develop and validate a combined model for predicting 3-year cancer-specific survival (CSS) in lung cancer patients treated with stereotactic body radiation therapy (SBRT) by integrating clinical and radiomic parameters.

methodsClinical data and pre-treatment CT images were collected from 102 patients treated with lung SBRT. Multivariate logistic regression and the least absolute shrinkage and selection operator were used to determine the clinical and radiomic factors associated with 3-year CSS. Three prediction models were developed using clinical factors, radiomic factors, and a combination of both. The performance of the models was assessed using receiver operating characteristic curve and calibration curve. A nomogram was also created to visualize the 3-year CSS prediction.

resultsWith a 36-month follow-up, 40 patients (39.2%) died of lung cancer and 62 patients (60.8%) survived. Three clinical factors, including gender, clinical stage, and lymphocyte ratio, along with three radiomic features, were found to be independent factors correlated with 3-year CSS. The area under the curve values for the clinical, radiomic, and combined model were 0.839 (95% CI 0.735-0.914), 0.886 (95% CI 0.790-0.948), and 0.914 (95% CI 0.825-0.966) in the training cohort, and 0.757 (95% CI 0.580-0.887), 0.818 (95% CI 0.648-0.929), and 0.843 (95% CI 0.677-0.944) in the validation cohort, respectively. Additionally, the calibration curve demonstrated good calibration performance and the nomogram created from the combined model showed potential for clinical utility.

conclusionA clinical-radiomic model was developed to predict the 3-year CSS for lung cancer patients treated with SBRT.

Indexed as

Lung NeoplasmsRadiosurgeryCalibrationDeathHumansRadiomics3-year cancer-specific survivalClinical-radiomic modelLung cancerStereotactic body radiation therapy

Identifiers

PMID38277078
PMCPMC10817845
OpenAlexW4391262818

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.