Evidence map›Paper›PMID 38411691›Full record

ArticleAbdominal radiology (New York)2024

Renal cell carcinoma and venous tumor thrombus: predicting sarcomatoid dedifferentiation through preoperative IVIM-based MR imaging.

Jian Zhao, Xiaohui Ding, Shaopeng Zhou, Meifeng Wang, Cheng Peng, Xu Bai, Xiaojing Zhang, Kan Liu, Xin Ma, Xu Zhang and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in Abdominal radiology (New York), 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
0.8field-weighted citation impact, top 28% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Review
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.

Jian Zhao *Department of Radiology, First Medical Center, Chinese PLA General Hospital, No. 28, Fuxing Road, Haidian District, Beijing, 100853, People's Republic of China.
Xiaohui Ding *Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, 100853, People's Republic of China.
Shaopeng Zhou *Department of Radiology, First Medical Center, Chinese PLA General Hospital, No. 28, Fuxing Road, Haidian District, Beijing, 100853, People's Republic of China.
Meifeng WangDepartment of Radiology, Sixth Medical Center, Chinese PLA General Hospital, Beijing, 100037, People's Republic of China.
Cheng PengDepartment of Urology, Chinese PLA General Hospital, Beijing, 100853, People's Republic of China.
Xu BaiDepartment of Radiology, First Medical Center, Chinese PLA General Hospital, No. 28, Fuxing Road, Haidian District, Beijing, 100853, People's Republic of China.
Xiaojing ZhangDepartment of Radiology, First Medical Center, Chinese PLA General Hospital, No. 28, Fuxing Road, Haidian District, Beijing, 100853, People's Republic of China.
Kan LiuDepartment of Urology, Chinese PLA General Hospital, Beijing, 100853, People's Republic of China.
Xin MaDepartment of Urology, Chinese PLA General Hospital, Beijing, 100853, People's Republic of China.
Xu Zhang *Department of Urology, Chinese PLA General Hospital, Beijing, 100853, People's Republic of China.
Haiyi Wang *Department of Radiology, First Medical Center, Chinese PLA General Hospital, No. 28, Fuxing Road, Haidian District, Beijing, 100853, People's Republic of China. wanghaiyi301@outlook.com.ORCID 0000-0002-0717-1748
Chinese PLA General Hospital · CN

Funding

National Natural Science Foundation of China 81971580National Natural Science Foundation of China 82271951Natural Science Foundation of Beijing Municipality 7222167
6 · The paper itself

Abstract

purposeTo evaluate the value of preoperative intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and conventional MRI indicators in identifying sarcomatoid dedifferentiation in renal cell carcinoma (RCC) and tumor thrombus.

methodsFrom September 2016 to April 2023, consecutive patients with RCC and tumor thrombus who received routine MRI examination and IVIM-DWI before radical resection were enrolled prospectively. Kaplan-Meier method with log-rank test was used to calculate and compare the survival probability. The preoperative imaging features were analyzed. Univariate and multivariable logistic regression analyses were employed to identify independent predictors of sarcomatoid dedifferentiation. The predictive ability was evaluated by receiver operating characteristic (ROC) curves.

resultsTwenty-two patients (15.3%) of the 144 patients in the training set (median age, 58.0 years [IQR, 52.0-65.0 years]; 108 men) and 11 patients (22.4%) of the 49 patients in the test set (median age, 58.0 years [IQR, 53.0-63.0 years]; 38 men) had sarcomatoid dedifferentiated tumors. Patients with sarcomatoid-differentiated tumors had poor progress-free survival in the training set and test set (P < 0.001 and P = 0.007). f value (P = 0.011), mN stage (P = 0.007), and necrosis (P = 0.041) were independent predictors for predicting sarcomatoid dedifferentiation in the training set. The model combining conventional MRI features and f value had AUCs of 0.832 (95% CI 0.755-0.909) and 0.825 (95% CI 0.702-0.948) in predicting sarcomatoid dedifferentiation in the training set and test set.

conclusionIt is feasible to preoperatively identify sarcomatoid dedifferentiation based on IVIM-DWI and conventional MR imaging indicators.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsAgedCell DedifferentiationDiffusion Magnetic Resonance ImagingFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedPredictive Value of TestsPreoperative CareProspective StudiesVenous ThrombosisDiffusion weighted imagingIntravoxel incoherent motionMagnetic resonance imagingRenal cell carcinomaTumor thrombus

Identifiers

PMID38411691
OpenAlexW4392199256

What OpenQuestion holds

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Registered trials

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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.