Evidence map›Paper›PMID 35903379›Full record

Trial reportFrontiers in public health2022

A Web-Based Prediction Model for Cancer-Specific Survival of Elderly Patients Undergoing Surgery With Prostate Cancer: A Population-Based Study.

Zhaoxia Zhang, Chenghao Zhanghuang, Jinkui Wang, Tao Mi, Jiayan Liu, Xiaomao Tian, Liming Jin, Dawei He

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 36% 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

4 citing papers in PubMed, 3 citations in OpenAlex.

  1. 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

8 authors at 3 institutions in 1 country.

Zhaoxia ZhangDepartment of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China.
Chenghao ZhanghuangDepartment of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China.
Jinkui WangDepartment of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China.
Tao MiDepartment of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China.
Jiayan LiuDepartment of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China.
Xiaomao TianDepartment of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China.
Liming JinDepartment of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China.
Dawei HeDepartment of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China.
China International Science and Technology Cooperation · CNChongqing Medical University · CNChildren's Hospital of Chongqing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Prostate cancer (PC) is the second leading cause of cancer death in men in the United States after lung cancer in global incidence. Elderly male patients over 65 years old account for more than 60% of PC patients, and the impact of surgical treatment on the prognosis of PC patients is controversial. Moreover, there are currently no predictive models that can predict the prognosis of elderly PC patients undergoing surgical treatment. Therefore, we aimed to construct a new nomogram to predict cancer-specific survival (CSS) in elderly PC patients undergoing surgical treatment. Methods: Data for surgically treated PC patients aged 65 years and older were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression models were used to identify independent risk factors for elderly PC patients undergoing surgical treatment. A nomogram of elderly PC patients undergoing surgical treatment was developed based on the multivariate Cox regression model. The consistency index (C-index), the area under the subject operating characteristic curve (AUC), and the calibration curve were used to test the accuracy and discrimination of the predictive model. Decision curve analysis (DCA) was used to examine the potential clinical value of this model. Results: A total of 44,975 elderly PC patients undergoing surgery in 2010-2018 were randomly assigned to the training set ( Conclusions: To our knowledge, our nomogram is the first predictive model for elderly PC patients undergoing surgical treatment, filling the gap in current predictive models for this PC patient population. Our data comes from the SEER database, which is trustworthy and reliable. Moreover, our model has been internally validated in the validation set using the C-index,AUC and the and the calibration curve, showed that the model have good accuracy and reliability, which can help clinicians and patients make better clinical decision-making. Moreover, the DCA results show that our nomogram has a better potential clinical application value than the TNM staging system.

Indexed as

NomogramsProstatic NeoplasmsAgedHumansInternetMaleReproducibility of ResultsSEER ProgramUnited StatesCSSelderlynomogramprostate cancerSEERsurgery

Identifiers

PMID35903379
PMCPMC9314884
OpenAlexW4285039078

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.