Evidence map›Paper›PMID 37118959›Full record

ArticleThe world journal of men's health2024

Nomogram Using Prostate Health Index for Predicting Prostate Cancer in the Gray Zone: Prospective, Multicenter Study.

Jae Hoon Chung, Jeong Hyun Kim, Sang Wook Lee, Hongzoo Park, Geehyun Song, Wan Song, Minyong Kang, Hyun Hwan Sung, Hwang Gyun Jeon, Byong Chang Jeong and 3 more

Open access · diamondAbstract read
In one paragraph

Article in The world journal of men's health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
2.1field-weighted citation impact, top 13% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
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  3. 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

13 authors at 2 institutions in 1 country.

Jae Hoon ChungDepartment of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-9729-3457
Jeong Hyun KimDepartment of Urology, Kangwon National University School of Medicine, Chuncheon, Korea. urodr348@kangwon.ac.kr.ORCID https://orcid.org/0000-0002-8942-0188
Sang Wook LeeDepartment of Urology, Kangwon National University School of Medicine, Chuncheon, Korea.ORCID https://orcid.org/0000-0003-0497-5916
Hongzoo ParkDepartment of Urology, Kangwon National University School of Medicine, Chuncheon, Korea.ORCID https://orcid.org/0000-0002-4953-5079
Geehyun SongDepartment of Urology, Kangwon National University School of Medicine, Chuncheon, Korea.ORCID https://orcid.org/0000-0001-7486-4520
Wan SongDepartment of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0003-0971-1805
Minyong KangDepartment of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-6966-8813
Hyun Hwan SungDepartment of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0001-9845-3742
Hwang Gyun JeonDepartment of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-5613-8389
Byong Chang JeongDepartment of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-5399-2184
Seong Il SeoDepartment of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-9792-7798
Hyun Moo LeeDepartment of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0003-3969-4540
Seong Soo JeonDepartment of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea. seongsoo.jeon@samsung.com.ORCID https://orcid.org/0000-0002-3265-6261
Samsung Medical Center · KRKangwon National University · KR

Funding

Beckman Coulter Korea IncKorea Medical Device Development Fund 202015X30National Research Foundation of Korea NRF-2020R1A2C2007662
6 · The paper itself

Abstract

purposeTo create a nomogram that can predict the probability of prostate cancer using prostate health index (PHI) and clinical parameters of patients. And the optimal cut-off value of PHI for prostate cancer was also assessed. MATERIALS AND

methodsA prospective, multi-center study was conducted. PHI was evaluated prior to biopsy in patients requiring prostate biopsy due to high prostate-specific antigen (PSA). Among screened 1,010 patients, 626 patients with clinically suspected prostate cancer with aged 40 to 85 years, and with PSA levels ranging from 2.5 to 10 ng/mL were analyzed.

resultsAmong 626 patients, 38.82% (243/626) and 22.52% (141/626) were diagnosed with prostate cancer and clinically significant prostate cancer, respectively. In the PSA 2.5 to 4 ng/mL group, the areas under the curve (AUCs) of the nomograms for overall prostate cancer and clinically significant prostate cancer were 0.796 (0.727-0.866; p<0.001), and 0.697 (0.598-0.795; p=0.001), respectively. In the PSA 4 to 10 ng/mL group, the AUCs of nomograms for overall prostate cancer and clinically significant prostate cancer were 0.812 (0.783-0.842; p<0.001), and 0.839 (0.810-0.869; p<0.001), respectively.

conclusionsEven though external validations are necessary, a nomogram using PHI might improve the prediction of prostate cancer, reducing the need for prostate biopsies.

Indexed as

DiagnosisNomogramProstate cancerRisk

Identifiers

PMID37118959
PMCPMC10782127
OpenAlexW4364856390

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.