Evidence map›Paper›PMID 39302433›Full record

ArticleWorld journal of urology2024

New staging criteria predicting m-tor inhibitors treatment effect of renal angiomyolipoma in tuberous sclerosis complex patients.

Wenda Wang, Dongxu Qiu, Yang Zhao, Zhan Wang, Xu Wang, Yanan Li, Yi Liu, Zhangcheng Liao, Yushi Zhang

Abstract read
PubMed Publisher
In one paragraph

Article in World journal of urology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Wenda Wang *Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 Shuaifuyuan Wangfujing, Dongcheng, Beijing, 100730, PR China.
Dongxu Qiu *Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 Shuaifuyuan Wangfujing, Dongcheng, Beijing, 100730, PR China.
Yang ZhaoDepartment of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 Shuaifuyuan Wangfujing, Dongcheng, Beijing, 100730, PR China.
Zhan WangDepartment of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 Shuaifuyuan Wangfujing, Dongcheng, Beijing, 100730, PR China.
Xu WangDepartment of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 Shuaifuyuan Wangfujing, Dongcheng, Beijing, 100730, PR China.
Yanan LiDepartment of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 Shuaifuyuan Wangfujing, Dongcheng, Beijing, 100730, PR China.
Yi LiuDepartment of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 Shuaifuyuan Wangfujing, Dongcheng, Beijing, 100730, PR China.
Zhangcheng LiaoDepartment of Urolog, Xiangya Hospital, Central South University, 410008, Changsha, China. zc.liao2020@gmail.com.
Yushi ZhangDepartment of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 Shuaifuyuan Wangfujing, Dongcheng, Beijing, 100730, PR China. beijingzhangyushi@126.com.ORCID http://orcid.org/0000-0002-8058-9702

Funding

High-level Hospital Construction Project of Guangdong Provincial People's Hospital 2022-PUMCH-A-151
6 · The paper itself

Abstract

backgroundWe aimed to launched new staging criteria to predict mTOR inhibitors treatment effect of renal angiomyolipomas (r-AMLs) in TSC patients.

methods40 TSC patients with 69 r-AMLs were divided into two groups based on the efficacy of 6-month mTOR inhibitor treatment. Epidemiological data, therapeutic response, and predictive factors of enrolled patients were collected and analyzed. Age, sex, maximum diameter, maximum cross-sectional area (CSAmax), unenhanced mean CT value, enhanced mean CT value, and added value of enhanced CT of largest r-AML at baseline were assessed as potential influencing factors. Receiver operating characteristic (ROC) curve analysis and the area under the ROC curve (AUC) was used to estimate prediction power.

resultsAfter 6 months of mTOR inhibitor treatment, the tumor reduction rates in the two groups were 55.87% and 16.44% (P < 0.001). At the start of treatment, the maximum diameters, CSAmax, added value of enhanced CT of the target lesion in two groups were 7.70 ± 0.73 cm vs. 13.18 ± 1.23 cm(P = 0.028), 57.40 ± 10.76cm2 vs. 167.29 ± 33.09cm2 (P = 0.015), and 62.32 ± 5.03HU vs. 33.06 ± 3.13HU (P = 0.009), respectively. AUCs of CSAmax, added value of enhanced CT, and combination of both were 0.8024, 0.7672, and 0.8116, respectively (P < 0.001). Cut-off values of CSAmax combined with the added value of enhanced CT were 40cm2 and 46HU. AUCs of maximum diameters, combination of maximum diameters and added value of enhanced CT were 0.7600 and 0.8100, respectively (P < 0.001), with cut-off values of 6.6 cm and 46 HU.

conclusionNew staging criteria, based on CSAmax and added value of enhanced CT, can predict the treatment efficiency of m-TOR inhibitors for r-AMLs in TSC patients. A simplified version based on maximum diameter and added value of enhanced CT of lesion has also been proposed.

Indexed as

AngiomyolipomaKidney NeoplasmsMTOR InhibitorsNeoplasm StagingTuberous SclerosisAdolescentAdultFemaleHumansMaleMiddle AgedPredictive Value of TestsRetrospective StudiesTreatment OutcomeYoung AdultMTOR InhibitorsRenal angiomyolipomaStaging criteriaTreatment efficacy predictionTuberous sclerosis complex

Identifiers

What OpenQuestion holds

Textmetadata
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.