Evidence map›Paper›PMID 38923236›Full record

ArticleCancer medicine2024

Radiomic score for lung nodules as a prognostic biomarker in locally advanced rectal cancer patients: A bi-institutional study.

Zhiyuan Zhang, Jiazhou Wang, Di Dai, Fan Xia, Yiqun Sun, Guichao Li, Juefeng Wan, Lijun Shen, Hui Zhang, Yan Wang and 3 more

Abstract readMulticenter Study
In one paragraph

Article in Cancer medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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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

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Zhiyuan ZhangDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.ORCID 0000-0003-3986-7202
Jiazhou WangDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.ORCID 0000-0002-9012-6605
Di DaiDepartment of Radiology, Nanjing Medical University Affiliated Cancer Hospital, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing, China.
Fan XiaDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Yiqun SunDepartment of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
Guichao LiDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Juefeng WanDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Lijun ShenDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Hui ZhangDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.ORCID 0000-0001-8803-2696
Yan WangDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.ORCID 0000-0001-8750-9341
Jie ZhongDepartment of Oncology, Nanjing Medical University Affiliated Cancer Hospital, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing, China.
Jun BaoDepartment of Oncology, Nanjing Medical University Affiliated Cancer Hospital, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing, China.ORCID 0000-0002-1902-995X
Zhen ZhangDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.ORCID 0000-0001-6426-5364

Funding

Beijing Xisike Clinical Oncology Research Foundation Y-Young2022-0278National Natural Science Foundation of China 82003229National Natural Science Foundation of China 82272732Shanghai Anti-Cancer Association HYXH2021096Shanghai Municipal Health Commission 20214Y0146Shanghai Science and Technology Development Foundation 21Y21900200
6 · The paper itself

Abstract

backgroundUndetermined lung nodules are common in locally advanced rectal cancer (LARC) and lack precise risk stratification. This study aimed to develop a radiomic-based score (Rad-score) to distinguish metastasis and predict overall survival (OS) in patients with LARC and lung nodules.

methodsRetrospective data from two institutions (July 10, 2006-September 24, 2015) was used to develop and validate the Rad-score for distinguishing lung nodule malignancy. The prognostic value of the Rad-score was investigated in LARC cohorts, leading to the construction and validation of a clinical and radiomic score (Cli-Rad-score) that incorporates both clinical and radiomic information for the purpose of improving personalized clinical prognosis prediction. Descriptive statistics, survival analysis, and model comparison were performed to assess the results.

resultsThe Rad-score demonstrated great performance in distinguishing malignancy, with C-index values of 0.793 [95% CI: 0.729-0.856] in the training set and 0.730 [95% CI: 0.666-0.874] in the validation set. In independent LARC cohorts, Rad-score validation achieved C-index values of 0.794 [95% CI: 0.737-0.851] and 0.747 [95% CI: 0.615-0.879]. Regarding prognostic prediction, Rad-score effectively stratified patients. Cli-Rad-score outperformed the clinicopathological information alone in risk stratification, as evidenced by significantly higher C-index values (0.735 vs. 0.695 in the internal set and 0.618 vs. 0.595 in the external set).

conclusionsCT-based radiomics could serve as a reliable and powerful tool for lung nodule malignancy distinction and prognostic prediction in LARC patients. Rad-score predicts prognosis independently. Incorporation of Cli-Rad-score significantly enhances the persionalized clinical prognostic capacity in LARC patients with lung nodules.

Indexed as

Lung NeoplasmsRectal NeoplasmsAdultAgedFemaleHumansMaleMiddle AgedPrognosisRadiomicsRetrospective StudiesTomography, X-Ray Computedlocally advanced rectal cancerlung nodulesprognostic predictionradiomics

Identifiers

PMID38923236
PMCPMC11196379

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