Evidence map›Paper›PMID 33937065›Full record

ArticleFrontiers in oncology2021

A Nomogram Model to Predict Prognosis of Patients With Genitourinary Sarcoma.

Linde Li, Jiayu Liang, Turun Song, Saifu Yin, Jun Zeng, Qiang Zhong, Xiaobing Feng, Zihao Jia, Yu Fan, Xianding Wang and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

7 citing papers in PubMed, 10 citations in OpenAlex.

  1. Trial
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  5. Robot-assisted laparoscopic enucleation in the treatment of leiomyosarcoma of urinary bladder: A case report.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2023
    Article
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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 2 institutions in 1 country.

Linde LiDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Jiayu LiangDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Turun SongDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Saifu YinDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Jun ZengDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Qiang ZhongDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Xiaobing FengDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Zihao JiaDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Yu FanDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Xianding WangDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Tao LinDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Sichuan University · CNWest China Hospital of Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe aim of this study is to evaluate the significant factors influencing the overall survival (OS) and recurrence free survival (RFS) and make an attempt to develop a nomogram for predicting the prognosis of patients with genitourinary sarcoma (GS).

methodsData on adult GS from 1985 to 2010 were collected. The impact of clinical factors on OS and RFS were estimated by Kaplan-Meier (KM) analysis, and differences between groups were analyzed by the log-rank test. To establish a nomogram, all patients were randomly divided into a training set (n = 125) and a testing set (n = 63). Cox proportion hazard model was utilized to assess the prognostic effect of variables. Then, a nomogram was established to estimate 1-, 3-, and 5-year OS based on Cox regression model. Subsequently, the nomogram was validated by a training set and a validation set.

resultsA total of 188 patients were enrolled into our study. Male patients with bladder sarcoma had better OS rather than RFS when stratified by gender (P = 0.022). According to histological subtypes, patients with leiomyosarcoma (LMS) undergoing chemotherapy were associated with favorable OS (P = 0.024) and RFS (P = 0.001). Furthermore, LMS in kidney sarcoma were associated with lower recurrence rate in comparison to rhabdomyosarcoma (RMS) (P = 0.043). Margin status after surgical excision markedly influenced the OS and RFS of GS patients and negative margins presented optimal prognosis. Chemotherapy was associated with improved OS for patients without surgery (P = 0.029) and patients with positive margins (P = 0.026). Based on the multivariate analysis of the training cohort, age, gender, surgery status, histological subtype, and chemotherapy were included in our nomogram for prediction of OS. The nomogram had sufficient power with concordance index (C-index) of OS: 0.770, 95%CI: 0.760-0.772 and area under curve (AUC) of OS: 0.759, 95%CI: 0.658-0.859 in the training set and with C-index of OS: 0.741, 95%CI: 0.740-0.765, and AUC of OS: 0.744, 95%CI: 0.576-0.913 in the validation set.

conclusionsAdults GS is a group of extremely rare tumors with poor prognosis. Of all histological types, LMS is sensitive to chemotherapy. We highlighted the cardinal role of surgical resection and the importance of achieving negative margins. We identified the efficacy of chemotherapy for patients with positive margins and those without surgery as well. A nomogram is validated as an effective tool predicting short-term outcomes.

Indexed as

chemotherapygenitourinary sarcomahistologynomogramprognosissurgery

Identifiers

PMID33937065
PMCPMC8085422
OpenAlexW3155478957

What OpenQuestion holds

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LicenceCC BY
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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.