Evidence map›Paper›PMID 33928035›Full record

ArticleFrontiers in oncology2021

Population-Based Comparison of Different Risk Stratification Systems Among Prostate Cancer Patients.

Mu Xie, Xian-Shu Gao, Ming-Wei Ma, Xiao-Bin Gu, Hong-Zhen Li, Feng Lyu, Yun Bai, Jia-Yan Chen, Xue-Ying Ren, Ming-Zhu Liu

Abstract 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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. ZNF750: A Novel Prognostic Biomarker in Metastatic Prostate Cancer.International journal of molecular sciences · 2023
    Article
  4. Article
  5. Article
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

10 authors.

Mu XieDepartment of Radiation Oncology, Peking University First Hospital, Beijing, China.
Xian-Shu GaoDepartment of Radiation Oncology, Peking University First Hospital, Beijing, China.
Ming-Wei MaDepartment of Radiation Oncology, Peking University First Hospital, Beijing, China.
Xiao-Bin GuDepartment of Radiation Oncology, Zhengzhou University First Affiliated Hospital, Zhengzhou, China.
Hong-Zhen LiDepartment of Radiation Oncology, Peking University First Hospital, Beijing, China.
Feng LyuDepartment of Radiation Oncology, Peking University First Hospital, Beijing, China.
Yun BaiDepartment of Radiation Oncology, Peking University First Hospital, Beijing, China.
Jia-Yan ChenDepartment of Radiation Oncology, Peking University First Hospital, Beijing, China.
Xue-Ying RenDepartment of Radiation Oncology, Peking University First Hospital, Beijing, China.
Ming-Zhu LiuDepartment of Radiation Oncology, Peking University First Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIt is not known which risk stratification system has the best discrimination ability for predicting prostate cancer death.

methodsWe identified patients with non-metastatic primary prostate adenocarcinoma diagnosis between 2004 and 2015 using the Surveillance, Epidemiology, and End Results database. Patients were categorized in different risk groups using the three frequently used risk stratification systems of the National Comprehensive Cancer Network guideline (NCCN-g), American Urological Association guideline (AUA-g), and European Association of Urology guideline (EAU-g), respectively. Associations between risk classification and prostate cancer-specific mortality (PCSM) were determined using Kaplan-Meier analyses and multivariable regression with Cox proportional hazards model. Area under the receiver operating characteristics curve (AUC) analyses were used to test the discrimination ability of the three risk grouping systems.

resultsWe analyzed 310,062 patients with a median follow-up of 61 months. A total of 36,368 deaths occurred, including 6,033 prostate cancer deaths. For all the three risk stratification systems, the risk groups were significantly associated with PCSM. The AUC of the model relying on NCCN-g, AUA-g, and EAU-g risk stratification systems for PCSM at specifically 8 years were 0.818, 0.793, and 0.689 in the entire population; 0.819, 0.795, and 0.691 in Whites; 0.802, 0.777, and 0.681 in Blacks; 0.862, 0.818, and 0.714 in Asians; 0.845, 0.806, and 0.728 in Chinese patients. Regardless of the age, marital status, socioeconomic status, and treatment modality, AUC of the model relying on NCCN-g and AUA-g for PCSM was greater than that relying on EAU-g; AUC of the model relying on NCCN-g system was greater than that of the AUA-g system.

conclusionsThe NCCN-g and AUA-g risk stratification systems perform better in discriminating PCSM compared to the EAU-g system. The discrimination ability of the NCCN-g system was better than that of the AUA-g system. It is recommended to use NCCN-g to evaluate risk groups for prostate cancer patients and then provide more appropriate corresponding treatment recommendations.

Indexed as

comparisonpopulation-basedprostate cancerprostate cancer-specific mortalityrisk stratification system

Identifiers

PMID33928035
PMCPMC8076565

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