Evidence map›Paper›PMID 37313822›Full record

ArticleNan fang yi ke da xue xue bao = Journal of Southern Medical University2023

[Comparison of diagnostic performance of Clear Cell Likelihood Score v1.0 and v2.0 for clear renal cell carcinoma].

Y Hao, S Gao, X Zhang, M Cui, X Ding, H Wang, D Yang, H Ye, H Wang

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Article in Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Y HaoMedical School of Chinese PLA, Beijing 100853, China.
S GaoDepartment of Radiology, Linyi Central Hospital, Linyi 276400, China.
X ZhangDepartment of Radiology, First Hospital of Shanxi Medical University, Taiyuan 030012, China.
M CuiMedical School of Chinese PLA, Beijing 100853, China.
X DingDepartment of Pathology, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China.
H WangDepartment of Radiology, Peking University First Hospital, Beijing 100035, China.
D YangDepartment of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China.
H YeDepartment of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China.
H WangDepartment of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo compare the performance of Clear Cell Likelihood Score (ccLS) v1.0 and v2.0 in diagnosing clear cell renal cell carcinoma (ccRCC) from small renal masses (SRM).

methodsWe retrospectively analyzed the clinical data and MR images of patients with pathologically confirmed solid SRM from the First Medical Center of the Chinese PLA General Hospital between January 1, 2018, and December 31, 2021, and from Beijing Friendship Hospital of Capital Medical University and Peking University First Hospital between January 1, 2019 and May 17, 2021. Six abdominal radiologists were trained for use of the ccLS algorithm and scored independently using ccLS v1.0 and ccLS v2.0. Random- effects logistic regression modeling was used to generate plot receiver operating characteristic curves (ROC) to evaluate the diagnostic performance of ccLS v1.0 and ccLS v2.0 for ccRCC, and the area under curve (AUC) of these two scoring systems were compared using the DeLong's test. Weighted Kappa test was used to evaluate the interobserver agreement of the ccLS score, and differences in the weighted Kappa coefficients was compared using the Gwet consistency coefficient.

resultsIn total, 691 patients (491 males, 200 females; mean age, 54 ± 12 years) with 700 renal masses were included in this study. The pooled accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ccLS v1.0 for diagnosing ccRCC were 77.1%, 76.8%, 77.7%, 90.2%, and 55.7%, as compared with 80.9%, 79.3%, 85.1%, 93.4%, 60.6% with ccLS v2.0, respectively. The AUC of ccLS v2.0 was significantly higher than that of ccLS v1.0 for diagnosis of ccRCC (0.897

conclusionccLS v2.0 has better performance for diagnosing ccRCC than ccLS v1.0 and can be considered for use to assist radiologists with their routine diagnostic tasks.

Indexed as

CarcinomaCarcinoma, Renal CellKidney NeoplasmsAdultAgedFemaleHumansKidneyMaleMiddle AgedRetrospective StudiesClear Cell Likelihood Scoreclear cell renal cell carcinomamulti-parameter magnetic resonance imagingsmall renal masses

Identifiers

PMID37313822
PMCPMC10267243

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